Decision-relevant evaluation of climate models: A case study of chill hours in California

Science.gov (United States)

Jagannathan, K. A.; Jones, A. D.; Kerr, A. C.

2017-12-01

The past decade has seen a proliferation of different climate datasets with over 60 climate models currently in use. Comparative evaluation and validation of models can assist practitioners chose the most appropriate models for adaptation planning. However, such assessments are usually conducted for `climate metrics' such as seasonal temperature, while sectoral decisions are often based on `decision-relevant outcome metrics' such as growing degree days or chill hours. Since climate models predict different metrics with varying skill, the goal of this research is to conduct a bottom-up evaluation of model skill for `outcome-based' metrics. Using chill hours (number of hours in winter months where temperature is lesser than 45 deg F) in Fresno, CA as a case, we assess how well different GCMs predict the historical mean and slope of chill hours, and whether and to what extent projections differ based on model selection. We then compare our results with other climate-based evaluations of the region, to identify similarities and differences. For the model skill evaluation, historically observed chill hours were compared with simulations from 27 GCMs (and multiple ensembles). Model skill scores were generated based on a statistical hypothesis test of the comparative assessment. Future projections from RCP 8.5 runs were evaluated, and a simple bias correction was also conducted. Our analysis indicates that model skill in predicting chill hour slope is dependent on its skill in predicting mean chill hours, which results from the non-linear nature of the chill metric. However, there was no clear relationship between the models that performed well for the chill hour metric and those that performed well in other temperature-based evaluations (such winter minimum temperature or diurnal temperature range). Further, contrary to conclusions from other studies, we also found that the multi-model mean or large ensemble mean results may not always be most appropriate for this

A new fit-for-purpose model testing framework: Decision Crash Tests

Science.gov (United States)

Tolson, Bryan; Craig, James

2016-04-01

Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building

Issues in Developing a Normative Descriptive Model for Dyadic Decision Making

Science.gov (United States)

Serfaty, D.; Kleinman, D. L.

1984-01-01

Most research in modelling human information processing and decision making has been devoted to the case of the single human operator. In the present effort, concepts from the fields of organizational behavior, engineering psychology, team theory and mathematical modelling are merged in an attempt to consider first the case of two cooperating decisionmakers (the Dyad) in a multi-task environment. Rooted in the well-known Dynamic Decision Model (DDM), the normative descriptive approach brings basic cognitive and psychophysical characteristics inherent to human behavior into a team theoretic analytic framework. An experimental paradigm, involving teams in dynamic decision making tasks, is designed to produce the data with which to build the theoretical model.

A case study of optimization in the decision process: Siting groundwater monitoring wells

International Nuclear Information System (INIS)

Cardwell, H.; Huff, D.; Douthitt, J.; Sale, M.

1993-12-01

Optimization is one of the tools available to assist decision makers in balancing multiple objectives and concerns. In a case study of the siting decision for groundwater monitoring wells, we look at the influence of the optimization models on the decisions made by the responsible groundwater specialist. This paper presents a multi-objective integer programming model for determining the location of monitoring wells associated with a groundwater pump-and-treat remediation. After presenting the initial optimization results, we analyze the actual decision and revise the model to incorporate elements of the problem that were later identified as important in the decision-making process. The results of a revised model are compared to the actual siting plans, the recommendations from the initial optimization runs, and the initial monitoring network proposed by the decision maker

An ontology-driven, case-based clinical decision support model for removable partial denture design

Science.gov (United States)

Chen, Qingxiao; Wu, Ji; Li, Shusen; Lyu, Peijun; Wang, Yong; Li, Miao

2016-06-01

We present the initial work toward developing a clinical decision support model for specific design of removable partial dentures (RPDs) in dentistry. We developed an ontological paradigm to represent knowledge of a patient’s oral conditions and denture component parts. During the case-based reasoning process, a cosine similarity algorithm was applied to calculate similarity values between input patients and standard ontology cases. A group of designs from the most similar cases were output as the final results. To evaluate this model, the output designs of RPDs for 104 randomly selected patients were compared with those selected by professionals. An area under the curve of the receiver operating characteristic (AUC-ROC) was created by plotting true-positive rates against the false-positive rate at various threshold settings. The precision at position 5 of the retrieved cases was 0.67 and at the top of the curve it was 0.96, both of which are very high. The mean average of precision (MAP) was 0.61 and the normalized discounted cumulative gain (NDCG) was 0.74 both of which confirmed the efficient performance of our model. All the metrics demonstrated the efficiency of our model. This methodology merits further research development to match clinical applications for designing RPDs. This paper is organized as follows. After the introduction and description of the basis for the paper, the evaluation and results are presented in Section 2. Section 3 provides a discussion of the methodology and results. Section 4 describes the details of the ontology, similarity algorithm, and application.

P.C. disposal decisions: a banking industry case study

Science.gov (United States)

Shah, Sejal P.; Sarkis, Joseph

2002-02-01

The service industry and the manufacturing industry are interlinked in a supply chain situation. Part of the effectiveness of some manufacturing industry environmental performance based on remanufacturing and recycling is dependent on service industry decisions. In the information technology arena, personal computers (PCs) are the hard equipment of the service industry. The end-of-life decisions made by the service industry, and in this case the banking industry will have implications for the amount of systems within the waste or reverse logistics stream for manufacturers. Looking at some of the issues (and presenting a model for evaluation) related to decision making concerning end-of-life disposition for PCs is something this paper investigates. The analytical hierarchy process (AHP) is applied in this circumstance. The development of the model, its application, and results, provide the basis for much of the discussion in this paper.

Effectiveness of a Case-Based Computer Program on Students' Ethical Decision Making.

Science.gov (United States)

Park, Eun-Jun; Park, Mihyun

2015-11-01

The aim of this study was to test the effectiveness of a case-based computer program, using an integrative ethical decision-making model, on the ethical decision-making competency of nursing students in South Korea. This study used a pre- and posttest comparison design. Students in the intervention group used a computer program for case analysis assignments, whereas students in the standard group used a traditional paper assignment for case analysis. The findings showed that using the case-based computer program as a complementary tool for the ethics courses offered at the university enhanced students' ethical preparedness and satisfaction with the course. On the basis of the findings, it is recommended that nurse educators use a case-based computer program as a complementary self-study tool in ethics courses to supplement student learning without an increase in course hours, particularly in terms of analyzing ethics cases with dilemma scenarios and exercising ethical decision making. Copyright 2015, SLACK Incorporated.

Rule-based decision making model

International Nuclear Information System (INIS)

Sirola, Miki

1998-01-01

A rule-based decision making model is designed in G2 environment. A theoretical and methodological frame for the model is composed and motivated. The rule-based decision making model is based on object-oriented modelling, knowledge engineering and decision theory. The idea of safety objective tree is utilized. Advanced rule-based methodologies are applied. A general decision making model 'decision element' is constructed. The strategy planning of the decision element is based on e.g. value theory and utility theory. A hypothetical process model is built to give input data for the decision element. The basic principle of the object model in decision making is division in tasks. Probability models are used in characterizing component availabilities. Bayes' theorem is used to recalculate the probability figures when new information is got. The model includes simple learning features to save the solution path. A decision analytic interpretation is given to the decision making process. (author)

Application Of Decision Tree Approach To Student Selection Model- A Case Study

Science.gov (United States)

Harwati; Sudiya, Amby

2016-01-01

The main purpose of the institution is to provide quality education to the students and to improve the quality of managerial decisions. One of the ways to improve the quality of students is to arrange the selection of new students with a more selective. This research takes the case in the selection of new students at Islamic University of Indonesia, Yogyakarta, Indonesia. One of the university's selection is through filtering administrative selection based on the records of prospective students at the high school without paper testing. Currently, that kind of selection does not yet has a standard model and criteria. Selection is only done by comparing candidate application file, so the subjectivity of assessment is very possible to happen because of the lack standard criteria that can differentiate the quality of students from one another. By applying data mining techniques classification, can be built a model selection for new students which includes criteria to certain standards such as the area of origin, the status of the school, the average value and so on. These criteria are determined by using rules that appear based on the classification of the academic achievement (GPA) of the students in previous years who entered the university through the same way. The decision tree method with C4.5 algorithm is used here. The results show that students are given priority for admission is that meet the following criteria: came from the island of Java, public school, majoring in science, an average value above 75, and have at least one achievement during their study in high school.

Multiple attribute decision making model and application to food safety risk evaluation.

Science.gov (United States)

Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng

2017-01-01

Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Application fields for the new Object Management Group (OMG) Standards Case Management Model and Notation (CMMN) and Decision Management Notation (DMN) in the perioperative field.

Science.gov (United States)

Wiemuth, M; Junger, D; Leitritz, M A; Neumann, J; Neumuth, T; Burgert, O

2017-08-01

Medical processes can be modeled using different methods and notations. Currently used modeling systems like Business Process Model and Notation (BPMN) are not capable of describing the highly flexible and variable medical processes in sufficient detail. We combined two modeling systems, Business Process Management (BPM) and Adaptive Case Management (ACM), to be able to model non-deterministic medical processes. We used the new Standards Case Management Model and Notation (CMMN) and Decision Management Notation (DMN). First, we explain how CMMN, DMN and BPMN could be used to model non-deterministic medical processes. We applied this methodology to model 79 cataract operations provided by University Hospital Leipzig, Germany, and four cataract operations provided by University Eye Hospital Tuebingen, Germany. Our model consists of 85 tasks and about 20 decisions in BPMN. We were able to expand the system with more complex situations that might appear during an intervention. An effective modeling of the cataract intervention is possible using the combination of BPM and ACM. The combination gives the possibility to depict complex processes with complex decisions. This combination allows a significant advantage for modeling perioperative processes.

Understanding the Impact of Business Cases on IT Investment Decisions

DEFF Research Database (Denmark)

Berghout, Egon; Tan, Chee-Wee

2013-01-01

This study synthesizes the extant literature to derive an integrative developmental framework for IT business cases that can be applied to diagnose the feasibility of technological investments. We then construct a theoretical model that postulates the impact of IT business case elements on the in......This study synthesizes the extant literature to derive an integrative developmental framework for IT business cases that can be applied to diagnose the feasibility of technological investments. We then construct a theoretical model that postulates the impact of IT business case elements...... on the initial cost estimates of technological investments. Subsequently, our theoretical model is subjected to empirical validation through content analysis of IT business cases developed for municipal e-government projects. Findings indicate that the richness of the richness of business cases translates...... to more initial costs being identified in technological investments, thereby conserving resources for the organization through informed investment decisions....

A public health decision support system model using reasoning methods.

Science.gov (United States)

Mera, Maritza; González, Carolina; Blobel, Bernd

2015-01-01

Public health programs must be based on the real health needs of the population. However, the design of efficient and effective public health programs is subject to availability of information that can allow users to identify, at the right time, the health issues that require special attention. The objective of this paper is to propose a case-based reasoning model for the support of decision-making in public health. The model integrates a decision-making process and case-based reasoning, reusing past experiences for promptly identifying new population health priorities. A prototype implementation of the model was performed, deploying the case-based reasoning framework jColibri. The proposed model contributes to solve problems found today when designing public health programs in Colombia. Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.

A novel sustainable decision making model for municipal solid waste management

International Nuclear Information System (INIS)

Hung, M.-L.; Ma Hwongwen; Yang, W.-F.

2007-01-01

This paper reviews several models developed to support decision making in municipal solid waste management (MSWM). The concepts underlying sustainable MSWM models can be divided into two categories: one incorporates social factors into decision making methods, and the other includes public participation in the decision-making process. The public is only apprised or takes part in discussion, and has little effect on decision making in most research efforts. Few studies have considered public participation in the decision-making process, and the methods have sought to strike a compromise between concerned criteria, not between stakeholders. However, the source of the conflict arises from the stakeholders' complex web of value. Such conflict affects the feasibility of implementing any decision. The purpose of this study is to develop a sustainable decision making model for MSWM to overcome these shortcomings. The proposed model combines multicriteria decision making (MCDM) and a consensus analysis model (CAM). The CAM is built up to aid in decision-making when MCDM methods are utilized and, subsequently, a novel sustainable decision making model for MSWM is developed. The main feature of CAM is the assessment of the degree of consensus between stakeholders for particular alternatives. A case study for food waste management in Taiwan is presented to demonstrate the practicality of this model

Multiple attribute decision making model and application to food safety risk evaluation.

Directory of Open Access Journals (Sweden)

Lihua Ma

Full Text Available Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Decision Making Model for Business Process Outsourcing of Enterprise Content Management

Directory of Open Access Journals (Sweden)

Zhuojun Yi

2013-03-01

Full Text Available Business process outsourcing (BPO in enterprise content management (ECM is a growing though immature market. BPO in ECM focuses on pursuing market transactions in the process of managing all types of content being used in organizations. However, inadequate sourcing decisions lead to organizational sensitive content exposure, high transaction cost, poor outsourcer performance, low flexibility. ECM BPO in general is rarely discussed in the literature and no discussion was found on decision making strategies in ECM BPO. In this paper, we present a decision making model for ECM BPO that will fill the literature gap and guide industry practitioners with ECM sourcing decision making strategies. Our proposed decision making model includes two parts. Part one is an ECM functional framework that shows what functionality component or functionality combinations can be outsourced. Part two is a decision making model that provides guidance for decision making in ECM BPO. We apply the model in two case studies, and the results indicate that the model can guide the sourcing decision making process for organizations, and determine the factors when considering sourcing alternatives in ECM.

An Intuitionistic Fuzzy Stochastic Decision-Making Method Based on Case-Based Reasoning and Prospect Theory

Directory of Open Access Journals (Sweden)

Peng Li

2017-01-01

Full Text Available According to the case-based reasoning method and prospect theory, this paper mainly focuses on finding a way to obtain decision-makers’ preferences and the criterion weights for stochastic multicriteria decision-making problems and classify alternatives. Firstly, we construct a new score function for an intuitionistic fuzzy number (IFN considering the decision-making environment. Then, we aggregate the decision-making information in different natural states according to the prospect theory and test decision-making matrices. A mathematical programming model based on a case-based reasoning method is presented to obtain the criterion weights. Moreover, in the original decision-making problem, we integrate all the intuitionistic fuzzy decision-making matrices into an expectation matrix using the expected utility theory and classify or rank the alternatives by the case-based reasoning method. Finally, two illustrative examples are provided to illustrate the implementation process and applicability of the developed method.

Fuzziness and fuzzy modelling in Bulgaria's energy policy decision-making dilemma

International Nuclear Information System (INIS)

Wang Xingquan

2006-01-01

The decision complexity resulting from imprecision in decision variables and parameters, a major difficulty for conventional decision analysis methods, can be relevantly analysed and modelled by fuzzy logic. Bulgaria's nuclear policy decision-making process implicates such complexity of imprecise nature: stakeholders, criteria, measurement, etc. Given the suitable applicability of fuzzy logic in this case, this article tries to offer a concrete fuzzy paradigm including delimitation of decision space, quantification of imprecise variables, and, of course, parameterisation. (author)

A heuristic forecasting model for stock decision

OpenAIRE

Zhang, D.; Jiang, Q.; Li, X.

2005-01-01

This paper describes a heuristic forecasting model based on neural networks for stock decision-making. Some heuristic strategies are presented for enhancing the learning capability of neural networks and obtaining better trading performance. The China Shanghai Composite Index is used as case study. The forecasting model can forecast the buying and selling signs according to the result of neural network prediction. Results are compared with a benchmark buy-and-hold strategy. ...

A design process for using normative models in shared decision making: a case study in the context of prenatal testing.

Science.gov (United States)

Rapaport, Sivan; Leshno, Moshe; Fink, Lior

2014-12-01

Shared decision making (SDM) encourages the patient to play a more active role in the process of medical consultation and its primary objective is to find the best treatment for a specific patient. Recent findings, however, show that patient preferences cannot be easily or accurately judged on the basis of communicative exchange during routine office visits, even for patients who seek to expand their role in medical decision making (MDM). The objective of this study is to improve the quality of patient-physician communication by developing a novel design process for SDM and then demonstrating, through a case study, the applicability of this process in enabling the use of a normative model for a specific medical situation. Our design process goes through the following stages: definition of medical situation and decision problem, development/identification of normative model, adaptation of normative model, empirical analysis and development of decision support systems (DSS) tools that facilitate the SDM process in the specific medical situation. This study demonstrates the applicability of the process through the implementation of the general normative theory of MDM under uncertainty for the medical-financial dilemma of choosing a physician to perform amniocentesis. The use of normative models in SDM raises several issues, such as the goal of the normative model, the relation between the goals of prediction and recommendation, and the general question of whether it is valid to use a normative model for people who do not behave according to the model's assumptions. © 2012 John Wiley & Sons Ltd.

Ethics and rationality in information-enriched decisions: A model for technical communication

Science.gov (United States)

Dressel, S. B.; Carlson, P.; Killingsworth, M. J.

1993-12-01

In a technological culture, information has a crucial impact upon decisions, but exactly how information plays into decisions is not always clear. Decisions that are effective, efficient, and ethical must be rational. That is, we must be able to determine and present good reasons for our actions. The topic in this paper is how information relates to good reasons and thereby affects the best decisions. A brief sketch of a model for decision-making, is presented which offers a synthesis of theoretical approaches to argument and to information analysis. Then the model is applied to a brief hypothetical case. The main purpose is to put the model before an interested audience in hopes of stimulating discussion and further research.

Theoretical Background for the Decision-Making Process Modelling under Controlled Intervention Conditions

OpenAIRE

Bakanauskienė Irena; Baronienė Laura

2017-01-01

This article is intended to theoretically justify the decision-making process model for the cases, when active participation of investing entities in controlling the activities of an organisation and their results is noticeable. Based on scientific literature analysis, a concept of controlled conditions is formulated, and using a rational approach to the decision-making process, a model of the 11-steps decision-making process under controlled intervention is presented. Also, there have been u...

Searching for solutions to mitigate greenhouse gas emissions by agricultural policy decisions--Application of system dynamics modeling for the case of Latvia.

Science.gov (United States)

Dace, Elina; Muizniece, Indra; Blumberga, Andra; Kaczala, Fabio

2015-09-15

European Union (EU) Member States have agreed to limit their greenhouse gas (GHG) emissions from sectors not covered by the EU Emissions Trading Scheme (non-ETS). That includes also emissions from agricultural sector. Although the Intergovernmental Panel on Climate Change (IPCC) has established a methodology for assessment of GHG emissions from agriculture, the forecasting options are limited, especially when policies and their interaction with the agricultural system are tested. Therefore, an advanced tool, a system dynamics model, was developed that enables assessment of effects various decisions and measures have on agricultural GHG emissions. The model is based on the IPCC guidelines and includes the main elements of an agricultural system, i.e. land management, livestock farming, soil fertilization and crop production, as well as feedback mechanisms between the elements. The case of Latvia is selected for simulations, as agriculture generates 22% of the total anthropogenic GHG emissions in the country. The results demonstrate that there are very limited options for GHG mitigation in the agricultural sector. Thereby, reaching the non-ETS GHG emission targets will be very challenging for Latvia, as the level of agricultural GHG emissions will be exceeded considerably above the target levels. Thus, other non-ETS sectors will have to reduce their emissions drastically to "neutralize" the agricultural sector's emissions for reaching the EU's common ambition to move towards low-carbon economy. The developed model may serve as a decision support tool for impact assessment of various measures and decisions on the agricultural system's GHG emissions. Although the model is applied to the case of Latvia, the elements and structure of the model developed are similar to agricultural systems in many countries. By changing numeric values of certain parameters, the model can be applied to analyze decisions and measures in other countries. Copyright © 2015 Elsevier B.V. All

Clinical decision-making by midwives: managing case complexity.

Science.gov (United States)

Cioffi, J; Markham, R

1997-02-01

In making clinical judgements, it is argued that midwives use 'shortcuts' or heuristics based on estimated probabilities to simplify the decision-making task. Midwives (n = 30) were given simulated patient assessment situations of high and low complexity and were required to think aloud. Analysis of verbal protocols showed that subjective probability judgements (heuristics) were used more frequently in the high than low complexity case and predominated in the last quarter of the assessment period for the high complexity case. 'Representativeness' was identified more frequently in the high than in the low case, but was the dominant heuristic in both. Reports completed after each simulation suggest that heuristics based on memory for particular conditions affect decisions. It is concluded that midwives use heuristics, derived mainly from their clinical experiences, in an attempt to save cognitive effort and to facilitate reasonably accurate decisions in the decision-making process.

Modelling farmer decision-making: The case of the Dutch pork sector

NARCIS (Netherlands)

Ambrosius, F.H.W.; Hofstede, G.J.; Bock, B.B.; Bokkers, E.A.M.; Beulens, A.J.M.

2015-01-01

Purpose – The purpose of this paper is to develop a framework that models farmers’ strategic decision making, taking into account that farmers adapt to institutional changes, given the social structure in which they are embedded. Design/methodology/approach – First, a theoretical framework was

A decision model to allocate protective safety barriers and mitigate domino effects

International Nuclear Information System (INIS)

Janssens, Jochen; Talarico, Luca; Reniers, Genserik; Sörensen, Kenneth

2015-01-01

In this paper, we present a model to support decision-makers about where to locate safety barriers and mitigate the consequences of an accident triggering domino effects. Based on the features of an industrial area that may be affected by domino accidents, and knowing the characteristics of the safety barriers that can be installed to stall the fire propagation between installations, the decision model can help practitioners in their decision-making. The model can be effectively used to decide how to allocate a limited budget in terms of safety barriers. The goal is to maximize the time-to-failure of a chemical installation ensuring a worst case scenario approach. The model is mathematically stated and a flexible and effective solution approach, based on metaheuristics, is developed and tested on an illustrative case study representing a tank storage area of a chemical company. We show that a myopic optimization approach, which does not take into account knock-on effects possibly triggered by an accident, can lead to a distribution of safety barriers that are not effective in mitigating the consequences of a domino accident. Moreover, the optimal allocation of safety barriers, when domino effects are considered, may depend on the so-called cardinality of the domino effects. - Highlights: • A model to allocate safety barriers and mitigate domino effects is proposed. • The goal is to maximize the escalation time of the worst case scenario. • The model provides useful recommendations for decision makers. • A fast metaheuristic approach is proposed to solve such a complex problem. • Numerical simulations on a realistic case study are shown

Risk Decision Making Based on Decision-theoretic Rough Set: A Three-way View Decision Model

OpenAIRE

Huaxiong Li; Xianzhong Zhou

2011-01-01

Rough set theory has witnessed great success in data mining and knowledge discovery, which provides a good support for decision making on a certain data. However, a practical decision problem always shows diversity under the same circumstance according to different personality of the decision makers. A simplex decision model can not provide a full description on such diverse decisions. In this article, a review of Pawlak rough set models and probabilistic rough set models is presented, and a ...

Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

International Nuclear Information System (INIS)

Ben Rabah, N; Saddem, R; Carre-Menetrier, V; Ben Hmida, F; Tagina, M

2017-01-01

Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach. (paper)

Modelling decision-making by pilots

Science.gov (United States)

Patrick, Nicholas J. M.

1993-01-01

Our scientific goal is to understand the process of human decision-making. Specifically, a model of human decision-making in piloting modern commercial aircraft which prescribes optimal behavior, and against which we can measure human sub-optimality is sought. This model should help us understand such diverse aspects of piloting as strategic decision-making, and the implicit decisions involved in attention allocation. Our engineering goal is to provide design specifications for (1) better computer-based decision-aids, and (2) better training programs for the human pilot (or human decision-maker, DM).

Ethical decision making within the bureaucratic context: a case study.

Science.gov (United States)

Desai, Kathryn

2003-01-01

Balancing the polarized notions of quality and quantity of service and care is a challenge for the 21st century health and social service system. The expectation of transparent decision making at both the policy and the practice level of case management has forced practitioners to seek guidance in ethical decision making. Case management, as a system, has potential to lead this new practice approach by incorporating the principles of ethical decision making in planning and coordinating care. A recent case study of ethical decision making within the bureaucratic context offers some insight and learning and may help inform future practice.

Case Studies of Decision-Making in Organizations: Purchase Decisions in Business Firms.

Science.gov (United States)

Patchen, Martin; And Others

Conducted during 1966-67, these 33 case studies were expected to provide insights into various aspects of organizational decision making (especially the ways in which influence is exerted and perceived in specific decisions). Eleven firms, all having headquarters and at least one plant or division in the Chicago area, were chosen from a directory…

Decision-Making Theories and Models: A Discussion of Rational and Psychological Decision-Making Theories and Models: The Search for a Cultural-Ethical Decision-Making Model

OpenAIRE

Oliveira, Arnaldo

2007-01-01

This paper examines rational and psychological decision-making models. Descriptive and normative methodologies such as attribution theory, schema theory, prospect theory, ambiguity model, game theory, and expected utility theory are discussed. The definition of culture is reviewed, and the relationship between culture and decision making is also highlighted as many organizations use a cultural-ethical decision-making model.

Mathematical modelling with case studies using Maple and Matlab

CERN Document Server

Barnes, B

2014-01-01

Introduction to Mathematical ModelingMathematical models An overview of the book Some modeling approaches Modeling for decision makingCompartmental Models Introduction Exponential decay and radioactivity Case study: detecting art forgeries Case study: Pacific rats colonize New Zealand Lake pollution models Case study: Lake Burley Griffin Drug assimilation into the blood Case study: dull, dizzy, or dead? Cascades of compartments First-order linear DEs Equilibrium points and stability Case study: money, money, money makes the world go aroundModels of Single PopulationsExponential growth Density-

Measuring and modeling behavioral decision dynamics in collective evacuation.

Directory of Open Access Journals (Sweden)

Jean M Carlson

Full Text Available Identifying and quantifying factors influencing human decision making remains an outstanding challenge, impacting the performance and predictability of social and technological systems. In many cases, system failures are traced to human factors including congestion, overload, miscommunication, and delays. Here we report results of a behavioral network science experiment, targeting decision making in a natural disaster. In a controlled laboratory setting, our results quantify several key factors influencing individual evacuation decision making in a controlled laboratory setting. The experiment includes tensions between broadcast and peer-to-peer information, and contrasts the effects of temporal urgency associated with the imminence of the disaster and the effects of limited shelter capacity for evacuees. Based on empirical measurements of the cumulative rate of evacuations as a function of the instantaneous disaster likelihood, we develop a quantitative model for decision making that captures remarkably well the main features of observed collective behavior across many different scenarios. Moreover, this model captures the sensitivity of individual- and population-level decision behaviors to external pressures, and systematic deviations from the model provide meaningful estimates of variability in the collective response. Identification of robust methods for quantifying human decisions in the face of risk has implications for policy in disasters and other threat scenarios, specifically the development and testing of robust strategies for training and control of evacuations that account for human behavior and network topologies.

The attentional drift-diffusion model extends to simple purchasing decisions

Directory of Open Access Journals (Sweden)

Ian eKrajbich

2012-06-01

Full Text Available How do we make simple purchasing decisions (e.g., whether or not to buy a product ata given price? Previous work has shown that the Attentional-Drift-Diffusion-Model (aDDMcan provide accurate descriptions of the psychometric data for binary and trinary value-based choices, and of how the choice process is guided by visual attention. However, the computational processes used to make purchasing decisions are unknown. Here we extend the aDDM to the case of purchasing decisions, and test it using an eye-tracking experiment. We find that the model provides a quantitatively accurate description of the relationship between choice, reaction time, and visual fixations using parameters that are very similar to those that best fit the previous data. The only critical difference is that the choice biases induced by the fixations are about half as big in purchasing decisions as in binary choices.This suggests that the brain uses similar computational processes in these varied decision situations.

Searching for solutions to mitigate greenhouse gas emissions by agricultural policy decisions — Application of system dynamics modeling for the case of Latvia

International Nuclear Information System (INIS)

Dace, Elina; Muizniece, Indra; Blumberga, Andra; Kaczala, Fabio

2015-01-01

European Union (EU) Member States have agreed to limit their greenhouse gas (GHG) emissions from sectors not covered by the EU Emissions Trading Scheme (non-ETS). That includes also emissions from agricultural sector. Although the Intergovernmental Panel on Climate Change (IPCC) has established a methodology for assessment of GHG emissions from agriculture, the forecasting options are limited, especially when policies and their interaction with the agricultural system are tested. Therefore, an advanced tool, a system dynamics model, was developed that enables assessment of effects various decisions and measures have on agricultural GHG emissions. The model is based on the IPCC guidelines and includes the main elements of an agricultural system, i.e. land management, livestock farming, soil fertilization and crop production, as well as feedback mechanisms between the elements. The case of Latvia is selected for simulations, as agriculture generates 22% of the total anthropogenic GHG emissions in the country. The results demonstrate that there are very limited options for GHG mitigation in the agricultural sector. Thereby, reaching the non-ETS GHG emission targets will be very challenging for Latvia, as the level of agricultural GHG emissions will be exceeded considerably above the target levels. Thus, other non-ETS sectors will have to reduce their emissions drastically to “neutralize” the agricultural sector's emissions for reaching the EU's common ambition to move towards low-carbon economy. The developed model may serve as a decision support tool for impact assessment of various measures and decisions on the agricultural system's GHG emissions. Although the model is applied to the case of Latvia, the elements and structure of the model developed are similar to agricultural systems in many countries. By changing numeric values of certain parameters, the model can be applied to analyze decisions and measures in other countries. - Highlights: �

Searching for solutions to mitigate greenhouse gas emissions by agricultural policy decisions — Application of system dynamics modeling for the case of Latvia

Energy Technology Data Exchange (ETDEWEB)

Dace, Elina, E-mail: elina.dace@rtu.lv [Institute of Energy Systems and Environment, Riga Technical University, Azenes 12/1, Riga LV1048 (Latvia); Muizniece, Indra; Blumberga, Andra [Institute of Energy Systems and Environment, Riga Technical University, Azenes 12/1, Riga LV1048 (Latvia); Kaczala, Fabio [Department of Biology and Environmental Science, Faculty of Health & Life Sciences, Linnaeus University, SE-39182 Kalmar (Sweden)

2015-09-15

European Union (EU) Member States have agreed to limit their greenhouse gas (GHG) emissions from sectors not covered by the EU Emissions Trading Scheme (non-ETS). That includes also emissions from agricultural sector. Although the Intergovernmental Panel on Climate Change (IPCC) has established a methodology for assessment of GHG emissions from agriculture, the forecasting options are limited, especially when policies and their interaction with the agricultural system are tested. Therefore, an advanced tool, a system dynamics model, was developed that enables assessment of effects various decisions and measures have on agricultural GHG emissions. The model is based on the IPCC guidelines and includes the main elements of an agricultural system, i.e. land management, livestock farming, soil fertilization and crop production, as well as feedback mechanisms between the elements. The case of Latvia is selected for simulations, as agriculture generates 22% of the total anthropogenic GHG emissions in the country. The results demonstrate that there are very limited options for GHG mitigation in the agricultural sector. Thereby, reaching the non-ETS GHG emission targets will be very challenging for Latvia, as the level of agricultural GHG emissions will be exceeded considerably above the target levels. Thus, other non-ETS sectors will have to reduce their emissions drastically to “neutralize” the agricultural sector's emissions for reaching the EU's common ambition to move towards low-carbon economy. The developed model may serve as a decision support tool for impact assessment of various measures and decisions on the agricultural system's GHG emissions. Although the model is applied to the case of Latvia, the elements and structure of the model developed are similar to agricultural systems in many countries. By changing numeric values of certain parameters, the model can be applied to analyze decisions and measures in other countries. - Highlights: �

A Mining Algorithm for Extracting Decision Process Data Models

Directory of Open Access Journals (Sweden)

Cristina-Claudia DOLEAN

2011-01-01

Full Text Available The paper introduces an algorithm that mines logs of user interaction with simulation software. It outputs a model that explicitly shows the data perspective of the decision process, namely the Decision Data Model (DDM. In the first part of the paper we focus on how the DDM is extracted by our mining algorithm. We introduce it as pseudo-code and, then, provide explanations and examples of how it actually works. In the second part of the paper, we use a series of small case studies to prove the robustness of the mining algorithm and how it deals with the most common patterns we found in real logs.

Application of a Resilience Framework to Military Installations: A Methodology for Energy Resilience Business Case Decisions

Science.gov (United States)

2016-09-01

align to a disruption or an associated downtime impacting mission performance. Reliability metrics and models were also used throughout the study to...Military Installations: A Methodology for Energy Resilience Business Case Decisions N. Judson A.L. Pina E.V. Dydek S.B. Van Broekhoven A.S...Methodology for Energy Resilience Business Case Decisions N. Judson A.L. Pina E.V. Dydek S.B. Van Broekhoven Group 73 A.S. Castillo TBD

Does decision documentation help junior designers rationalize their decisions? A comparative multiple-case study

OpenAIRE

Heesch, U. van; Avgeriou, P.; Tang, A.

2013-01-01

Software architecture design is challenging, especially for junior software designers. Lacking practice and experience, junior designers need process support in order to make rational architecture decisions. In this paper, we present the results of a comparative multiple-case study conducted to find out if decision viewpoints from van Heesch et al. (2012, in press) can provide such a support. The case study was conducted with four teams of software engineering students working in industrial s...

Estimating the impact of enterprise resource planning project management decisions on post-implementation maintenance costs: a case study using simulation modelling

Science.gov (United States)

Fryling, Meg

2010-11-01

Organisations often make implementation decisions with little consideration for the maintenance phase of an enterprise resource planning (ERP) system, resulting in significant recurring maintenance costs. Poor cost estimations are likely related to the lack of an appropriate framework for enterprise-wide pre-packaged software maintenance, which requires an ongoing relationship with the software vendor (Markus, M.L., Tanis, C., and Fenema, P.C., 2000. Multisite ERP implementation. CACM, 43 (4), 42-46). The end result is that critical project decisions are made with little empirical data, resulting in substantial long-term cost impacts. The product of this research is a formal dynamic simulation model that enables theory testing, scenario exploration and policy analysis. The simulation model ERPMAINT1 was developed by combining and extending existing frameworks in several research domains, and by incorporating quantitative and qualitative case study data. The ERPMAINT1 model evaluates tradeoffs between different ERP project management decisions and their impact on post-implementation total cost of ownership (TCO). Through model simulations a variety of dynamic insights were revealed that could assist ERP project managers. Major findings from the simulation show that upfront investments in mentoring and system exposure translate to long-term cost savings. The findings also indicate that in addition to customisations, add-ons have a significant impact on TCO.

Consensual decision-making model based on game theory for LNG processes

International Nuclear Information System (INIS)

Castillo, Luis; Dorao, Carlos A.

2012-01-01

Highlights: ► A Decision Making (DM) approach for LNG projects based on game theory is presented. ► DM framework was tested with two different cases, using analytical models and a simple LNG process. ► The problems were solved by using a Genetic Algorithm (GA) binary coding and Nash-GA. ► Integrated models from the design and optimization of the process could result in more realistic outcome. ► The major challenge in such a framework is related to the uncertainties in the market models. - Abstract: Decision-Making (DM) in LNG projects is a quite complex process due to the number of actors, approval phases, large investments and capital return in the long time. Furthermore, due to the very high investment of a LNG project, a detailed and efficient DM process is required in order to minimize risks. In this work a Decision-Making (DM) approach for LNG projects is presented. The approach is based on a consensus algorithm to address the consensus output over a common value using cost functions within a framework based on game theory. The DM framework was tested with two different cases. The first case was used for evaluating the performance of the framework with analytical models, while the second case corresponds to a simple LNG process. The problems were solved by using a Genetic Algorithm (GA) binary coding and Nash-GA. The results of the DM framework in the LNG project indicate that considering an integrated DM model and including the markets role from the design and optimization of the process more realistic outcome could be obtained. However, the major challenge in such a framework is related to the uncertainties in the market models.

A Common Decision of Compartmental Models on the Base of Laplace Transform and Retain Function Concept

International Nuclear Information System (INIS)

Dimitrov, L.; Tzvetkova, A.; Nikolov, A.

1997-01-01

The compartmental models have a variety of applications in the analysis of the transport of radioactive and non-radioactive material in complex systems as atmosphere, hydrosphere, food chains, human body. The analysis of the biokinetic behaviour of the radioactive material into a human body gives a possibility for correct assessment of the dose from internal irradiation. Skrable has given a decision of non-cyclic linear compartmental models in case of a single intake of material in the compartments as an initial condition. The main purpose of our article is to write down a procedure for analysis of a general compartmental model in case of continuous intake of material into the compartments. This procedure is related to retain function concept and had developed on the base of Laplace transform. On the base on the proposed procedure a non-cyclic linear compartmental model decisions are given in case of both a single and a continuous intake. The Laplace images of cyclic and circular linear compartmental model decisions and their originals in some cases are given too. (author)

Salience Theory of Judicial Decisions

OpenAIRE

Pedro Bordalo; Nicola Gennaioli; Andrei Shleifer

2015-01-01

We present a model of judicial decision making in which the judge overweights the salient facts of the case. The context of the judicial decision, which is comparative by nature, shapes which aspects of the case stand out and draw the judge’s attention. By focusing judicial attention on such salient aspects of the case, legally irrelevant information can affect judicial decisions. Our model accounts for a range of recent experimental evidence that bears on the psychology of judicial decisions...

Optimising Transport Decision Making using Customised Decision Models and Decision Conferences

DEFF Research Database (Denmark)

Barfod, Michael Bruhn

The subject of this Ph.D. thesis entitled “Optimising Transport Decision Making using Customised Decision Models and Decision Conferences” is multi-criteria decision analysis (MCDA) and decision support in the context of transport infrastructure assessments. Despite the fact that large amounts...... is concerned with the insufficiency of conventional cost-benefit analysis (CBA), and proposes the use of MCDA as a supplementing tool in order to also capture impacts of a more strategic character in the appraisals and hence make more use of the often large efforts put in the preliminary examinations. MCDA...... and rail to bike transport projects. Two major concerns have been to propose an examination process that can be used in situations where complex decision problems need to be addressed by experts as well as non-experts in decision making, and to identify appropriate assessment techniques to be used...

The attentional drift-diffusion model extends to simple purchasing decisions.

Science.gov (United States)

Krajbich, Ian; Lu, Dingchao; Camerer, Colin; Rangel, Antonio

2012-01-01

How do we make simple purchasing decisions (e.g., whether or not to buy a product at a given price)? Previous work has shown that the attentional drift-diffusion model (aDDM) can provide accurate quantitative descriptions of the psychometric data for binary and trinary value-based choices, and of how the choice process is guided by visual attention. Here we extend the aDDM to the case of purchasing decisions, and test it using an eye-tracking experiment. We find that the model also provides a reasonably accurate quantitative description of the relationship between choice, reaction time, and visual fixations using parameters that are very similar to those that best fit the previous data. The only critical difference is that the choice biases induced by the fixations are about half as big in purchasing decisions as in binary choices. This suggests that a similar computational process is used to make binary choices, trinary choices, and simple purchasing decisions.

A Case-Based Learning Model in Orthodontics.

Science.gov (United States)

Engel, Francoise E.; Hendricson, William D.

1994-01-01

A case-based, student-centered instructional model designed to mimic orthodontic problem solving and decision making in dental general practice is described. Small groups of students analyze case data, then record and discuss their diagnoses and treatments. Students and instructors rated the seminars positively, and students reported improved…

The effect of modelling expert knowledge and uncertainty on multicriteria decision making: a river management case study

NARCIS (Netherlands)

Janssen, Judith; Krol, Martinus S.; Schielen, Ralph Mathias Johannes; Hoekstra, Arjen Ysbert

2010-01-01

To support decision making on complex environmental issues, models are often used to explore the potential impacts of different management alternatives on the environmental system. We explored how different model outcomes affect decision making. Two topics have our particular interest, namely (1)

Decision making under risk in the case of nuclear power system development

International Nuclear Information System (INIS)

Pavelescu, M.; Szakats, A.; Ursu, I.

1981-01-01

The theory of risk preference as applied to decision making in the case of a nuclear power system consisting of PHWRs and PWRs integrated with LMFBRs, is examined. An econometric model of the system offers the cost price of annual energy generated by the system at the end of a given time interval for every possible state of any of nine development alternatives. Optimal development alternatives of the nuclear system in three cases: risk-preference, risk-indifference and risk-aversion are obtained and the solution in the last case is discussed in detail. (U.K.)

Validating the predictions of case-based decision theory

OpenAIRE

Radoc, Benjamin

2015-01-01

Real-life decision-makers typically do not know all possible outcomes arising from alternative courses of action. Instead, when people face a problem, they may rely on the recollection of their past personal experience: the situation, the action taken, and the accompanying consequence. In addition, the applicability of a past experience in decision-making may depend on how similar the current problem is to situations encountered previously. Case-based decision theory (CBDT), proposed by Itzha...

The decision of out-of-home placement in residential care after parental neglect: Empirically testing a psychosocial model.

Science.gov (United States)

Rodrigues, Leonor; Calheiros, Manuela; Pereira, Cícero

2015-11-01

Out-of-home placement decisions in residential care are complex, ambiguous and full of uncertainty, especially in cases of parental neglect. Literature on this topic is so far unable to understand and demonstrate the source of errors involved in those decisions and still fails to focus on professional's decision making process. Therefore, this work intends to test a socio-psychological model of decision-making that is a more integrated, dualistic and ecological version of the Theory of Planned Behavior's model. It describes the process through which the decision maker takes into account personal, contextual and social factors of the Decision-Making Ecology in the definition of his/her decision threshold. One hundred and ninety-five professionals from different Children and Youth Protection Units, throughout the Portuguese territory, participated in this online study. After reading a vignette of a (psychological and physical) neglect case toward a one-year-old child, participants were presented with a group of questions that measured worker's assessment of risk, intention, attitude, subjective norm, behavior control and beliefs toward residential care placement decision, as well as worker's behavior experience, emotions and family/child-related-values involved in that decision. A set of structural equation modeling analyses have proven the good fit of the proposed model. The intention to propose a residential care placement decision was determined by cognitive, social, affective, value-laden and experience variables and the perceived risk. Altogether our model explained 61% of professional's decision toward a parental neglect case. The theoretical and practical implications of these results are discussed, namely the importance of raising awareness about the existence of these biased psychosocial determinants. Copyright © 2015 Elsevier Ltd. All rights reserved.

Decision-making in palliative care: a reflective case study.

Science.gov (United States)

Birchall, Melissa

2005-01-01

Critical examination of the processes by which we as nurses judge and reach clinical decisions is important. It facilitates the maintenance and refinement of good standards of nursing care and the pinpointing of areas where improvement is needed. In turn this potentially could support broader validation of nurse expertise and contribute to emancipation of the nursing profession. As pure theory, clinical decision-making may appear abstract and alien to nurses struggling in 'the swampy lowlands' (Schon 1983) of the realities of practice. This paper explores some of the key concepts in decision-making theory by introducing, then integrating, them in a reflective case study. The case study, which examines a 'snapshot' of the patient and practitioner's journey, interwoven with theory surrounding clinical decision-making, may aid understanding and utility of concepts and theories in practice.

A Costing Analysis for Decision Making Grid Model in Failure-Based Maintenance

Directory of Open Access Journals (Sweden)

Burhanuddin M. A.

2011-01-01

Full Text Available Background. In current economic downturn, industries have to set good control on production cost, to maintain their profit margin. Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid model is used to identify strategies for maintenance decision. However, the model has limitation as it consider two factors only, that is, downtime and frequency of failures. We consider third factor, cost, in this study for failure-based maintenance. The objective of this paper is to introduce the formulae to estimate maintenance cost. Methods. Fish bone analysis conducted with Ishikawa model and Decision Making Grid methods are used in this study to reveal some underlying risk factors that delay failure-based maintenance. The goal of the study is to estimate the risk factor that is, repair cost to fit in the Decision Making Grid model. Decision Making grid model consider two variables, frequency of failure and downtime in the analysis. This paper introduces third variable, repair cost for Decision Making Grid model. This approaches give better result to categorize the machines, reduce cost, and boost the earning for the manufacturing plant. Results. We collected data from one of the food processing factories in Malaysia. From our empirical result, Machine C, Machine D, Machine F, and Machine I must be in the Decision Making Grid model even though their frequency of failures and downtime are less than Machine B and Machine N, based on the costing analysis. The case study and experimental results show that the cost analysis in Decision Making Grid model gives more promising strategies in failure-based maintenance. Conclusions. The improvement of Decision Making Grid model for decision analysis with costing analysis is our contribution in this paper for

Ethical case deliberation and decision making.

Science.gov (United States)

Gracia, Diego

2003-01-01

During the last thirty years different methods have been proposed in order to manage and resolve ethical quandaries, specially in the clinical setting. Some of these methodologies are based on the principles of Decision-making theory. Others looked to other philosophical traditions, like Principlism, Hermeneutics, Narrativism, Casuistry, Pragmatism, etc. This paper defends the view that deliberation is the cornerstone of any adequate methodology. This is due to the fact that moral decisions must take into account not only principles and ideas, but also emotions, values and beliefs. Deliberation is the process in which everyone concerned by the decision is considered a valid moral agent, obliged to give reasons for their own points of view, and to listen to the reasons of others. The goal of this process is not the reaching of a consensus but the enrichment of one's own point of view with that of the others, increasing in this way the maturity of one's own decision, in order to make it more wise or prudent. In many cases the members of a group of deliberation will differ in the final solution of the case, but the confrontation of their reasons will modify the perception of the problem of everyone. This is the profit of the process. Our moral decisions cannot be completely rational, due to the fact that they are influenced by feelings, values, beliefs, etc., but they must be reasonable, that is, wise and prudent. Deliberation is the main procedure to reach this goal. It obliges us to take others into account, respecting their different beliefs and values and prompting them to give reasons for their own points of view. This method has been traditional in Western clinical medicine all over its history, and it should be also the main procedure for clinical ethics.

Comparative Analysis of Investment Decision Models

Directory of Open Access Journals (Sweden)

Ieva Kekytė

2017-06-01

Full Text Available Rapid development of financial markets resulted new challenges for both investors and investment issues. This increased demand for innovative, modern investment and portfolio management decisions adequate for market conditions. Financial market receives special attention, creating new models, includes financial risk management and investment decision support systems.Researchers recognize the need to deal with financial problems using models consistent with the reality and based on sophisticated quantitative analysis technique. Thus, role mathematical modeling in finance becomes important. This article deals with various investments decision-making models, which include forecasting, optimization, stochatic processes, artificial intelligence, etc., and become useful tools for investment decisions.

Modeling Human Elements of Decision-Making

Science.gov (United States)

2002-06-01

include factors such as personality, emotion , and level of expertise, which vary from individual to individual. The process of decision - making during... rational choice theories such as utility theory, to more descriptive psychological models that focus more on the process of decision - making ...descriptive nature, they provide a more realistic representation of human decision - making than the rationally based models. However these models do

Making optimal investment decisions for energy service companies under uncertainty: A case study

International Nuclear Information System (INIS)

Deng, Qianli; Jiang, Xianglin; Zhang, Limao; Cui, Qingbin

2015-01-01

Varied initial energy efficiency investments would result in different annual energy savings achievements. In order to balance the savings revenue and the potential capital loss through EPC (Energy Performance Contracting), a cost-effective investment decision is needed when selecting energy efficiency technologies. In this research, an approach is developed for the ESCO (Energy Service Company) to evaluate the potential energy savings profit, and thus make the optimal investment decisions. The energy savings revenue under uncertainties, which are derived from energy efficiency performance variation and energy price fluctuation, are first modeled as stochastic processes. Then, the derived energy savings profit is shared by the owner and the ESCO according to the contract specification. A simulation-based model is thus built to maximize the owner's profit, and at the same time, satisfy the ESCO's expected rate of return. In order to demonstrate the applicability of the proposed approach, the University of Maryland campus case is also presented. The proposed method could not only help the ESCO determine the optimal energy efficiency investments, but also assist the owner's decision in the bidding selection. - Highlights: • An optimization model is built for determining energy efficiency investment for ESCO. • Evolution of the energy savings revenue is modeled as a stochastic process. • Simulation is adopted to calculate investment balancing the owner and the ESCO's profit. • A campus case is presented to demonstrate applicability of the proposed approach

Research on the decision-making model of land-use spatial optimization

Science.gov (United States)

He, Jianhua; Yu, Yan; Liu, Yanfang; Liang, Fei; Cai, Yuqiu

2009-10-01

Using the optimization result of landscape pattern and land use structure optimization as constraints of CA simulation results, a decision-making model of land use spatial optimization is established coupled the landscape pattern model with cellular automata to realize the land use quantitative and spatial optimization simultaneously. And Huangpi district is taken as a case study to verify the rationality of the model.

A System Dynamics Model for Integrated Decision Making ...

Science.gov (United States)

EPA’s Sustainable and Healthy Communities Research Program (SHC) is conducting transdisciplinary research to inform and empower decision-makers. EPA tools and approaches are being developed to enable communities to effectively weigh and integrate human health, socioeconomic, environmental, and ecological factors into their decisions to promote community sustainability. To help achieve this goal, EPA researchers have developed systems approaches to account for the linkages among resources, assets, and outcomes managed by a community. System dynamics (SD) is a member of the family of systems approaches and provides a framework for dynamic modeling that can assist with assessing and understanding complex issues across multiple dimensions. To test the utility of such tools when applied to a real-world situation, the EPA has developed a prototype SD model for community sustainability using the proposed Durham-Orange Light Rail Project (D-O LRP) as a case study.The EPA D-O LRP SD modeling team chose the proposed D-O LRP to demonstrate that an integrated modeling approach could represent the multitude of related cross-sectoral decisions that would be made and the cascading impacts that could result from a light rail transit system connecting Durham and Chapel Hill, NC. In keeping with the SHC vision described above, the proposal for the light rail is a starting point solution for the more intractable problems of population growth, unsustainable land use, environmenta

Modeling decision making as a support tool for policy making on renewable energy development

International Nuclear Information System (INIS)

Cannemi, Marco; García-Melón, Mónica; Aragonés-Beltrán, Pablo; Gómez-Navarro, Tomás

2014-01-01

This paper presents the findings of a study on decision making models for the analysis of capital-risk investors’ preferences on biomass power plants projects. The aim of the work is to improve the support tools for policy makers in the field of renewable energy development. Analytic Network Process (ANP) helps to better understand capital-risk investors preferences towards different kinds of biomass fueled power plants. The results of the research allow public administration to better foresee the investors’ reaction to the incentive system, or to modify the incentive system to better drive investors’ decisions. Changing the incentive system is seen as major risk by investors. Therefore, public administration must design better and longer-term incentive systems, forecasting market reactions. For that, two scenarios have been designed, one showing a typical decision making process and another proposing an improved decision making scenario. A case study conducted in Italy has revealed that ANP allows understanding how capital-risk investors interpret the situation and make decisions when investing on biomass power plants; the differences between the interests of public administrations’s and promoters’, how decision making could be influenced by adding new decision criteria, and which case would be ranked best according to the decision models. - Highlights: • We applied ANP to the investors’ preferences on biomass power plants projects. • The aim is to improve the advising tools for renewable energy policy making. • A case study has been carried out with the help of two experts. • We designed two scenarios: decision making as it is and how could it be improved. • Results prove ANP is a fruitful tool enhancing participation and transparency

Simulation Models of Human Decision-Making Processes

Directory of Open Access Journals (Sweden)

Nina RIZUN

2014-10-01

Full Text Available The main purpose of the paper is presentation of the new concept of human decision-making process modeling via using the analogy with Automatic Control Theory. From the author's point of view this concept allows to develop and improve the theory of decision-making in terms of the study and classification of specificity of the human intellectual processes in different conditions. It was proved that the main distinguishing feature between the Heuristic / Intuitive and Rational Decision-Making Models is the presence of so-called phenomenon of "enrichment" of the input information with human propensity, hobbies, tendencies, expectations, axioms and judgments, presumptions or bias and their justification. In order to obtain additional knowledge about the basic intellectual processes as well as the possibility of modeling the decision results in various parameters characterizing the decision-maker, the complex of the simulation models was developed. These models are based on the assumptions that:  basic intellectual processes of the Rational Decision-Making Model can be adequately simulated and identified by the transient processes of the proportional-integral-derivative controller; basic intellectual processes of the Bounded Rationality and Intuitive Models can be adequately simulated and identified by the transient processes of the nonlinear elements.The taxonomy of the most typical automatic control theory elements and their compliance with certain decision-making models with a point of view of decision-making process specificity and decision-maker behavior during a certain time of professional activity was obtained.

MODELLING OF DECISION MAKING OF UNMANNED AERIAL VEHICLE'S OPERATOR IN EMERGENCY SITUATIONS

Directory of Open Access Journals (Sweden)

Volodymyr Kharchenko

2017-03-01

Full Text Available Purpose: lack of recommendation action algorithm of UAV operator in emergency situations; decomposition of the process of decision making (DM by UAV’s Operator in emergency situations; development of the structure of distributed decision support system (DDSS for remotely piloted aircraft; development of a database of local decision support system (DSS operators Remotely Piloted Aircraft Systems (RPAS; working-out of models DM by UAV’s Operator. Methods: Algoritm of actions of UAV operator by Wald criterion, Laplace criterion, Hurwitz criterion. Results: The program "UAV_AS" that gives to UAV operator recommendations on how to act in case of emergency. Discussion: The article deals with the problem of Unmanned Aerial Vehicles (UAV flights for decision of different tasks in emergency situation. Based on statistical data it was analyzing the types of emergencies for unmanned aircraft. Defined sequence of actions UAV operator and in case of emergencies.

Towards Measures to Establish the Relevance of Climate Model Output for Decision Support

Science.gov (United States)

Clarke, L.; Smith, L. A.

2007-12-01

How exactly can decision-support and policy making benefit from the use of multiple climate model experiments in terms of coping with the uncertainties on climate change projections? Climate modelling faces challenges beyond those of weather forecasting or even seasonal forecasting, as with climate we are now (and will probably always be) required to extrapolate to regimes in which we have no relevant forecast-verification archive. This suggests a very different approach from traditional methods of mixing models and skill based weighting to gain profitable probabilistic information when a large forecast-verification archive is in hand. In the case of climate, it may prove more rational to search for agreement between our models (in distribution), the aim being to determine the space and timescales on which, given our current understanding, the details of the simulation models are unimportant. This suggestion and others from Smith (2002, Proc. National Acad. Sci. USA 4 (99): 2487-2492) are interpreted in the light of recent advances. Climate models are large nonlinear dynamical systems which insightfully but imperfectly reflect the evolving weather patterns of the Earth. Their use in policy making and decision support assumes both that they contain sufficient information regarding reality to inform the decision, and that this information can be effectively communicated to the decision makers. There is nothing unique about climate modeling and these constraints, they apply in all cases where scientific modeling is applied to real-word actions (other than, perhaps, the action of improving our models). Starting with the issue of communication, figures from the 2007 IPCC Summary for Policy Makers will be constructively criticized from the perspective of decision makers, specifically those of the energy sector and the insurance/reinsurance sector. More information on basic questions of reliability and robustness would be of significant value when determining how heavily

Multidimensional Balanced Efficiency Decision Model

Directory of Open Access Journals (Sweden)

Antonella Petrillo

2015-10-01

Full Text Available In this paper a multicriteria methodological approach, based on Balanced Scorecard (BSC and Analytic Network Process (ANP, is proposed to evaluate competitiveness performance in luxury sector. A set of specific key performance indicators (KPIs have been proposed. The contribution of our paper is to present the integration of two methodologies, BSC – a multiple perspective framework for performance assessment – and ANP – a decision-making tool to prioritize multiple performance perspectives and indicators and to generate a unified metric that incorporates diversified issues for conducting supply chain improvements. The BSC/ANP model is used to prioritize all performances within a luxury industry. A real case study is presented.

Decision model on the demographic profile for tuberculosis control using fuzzy logic

Directory of Open Access Journals (Sweden)

Laisa Ribeiro de Sá

2015-06-01

Full Text Available This study aimed to describe the relationship between demographic factors and the involvement of tuberculosis by applying a decision support model based on fuzzy logic to classify the regions as priority and non-priority in the city of João Pessoa, state of Paraíba (PB. As data source, we used the Notifiable Diseases Information System between 2009 and 2011. We chose the descriptive analysis, relative risk (RR, spatial distribution and fuzzy logic. The total of 1,245 cases remained in the study, accounting for 37.02% of cases in 2009. High and low risk clusters were identified, and the RR was higher among men (8.47, with 12 clusters, and among those uneducated (11.65, with 13 clusters. To demonstrate the functionality of the model was elected the year with highest number of cases, and the municipality district with highest population. The methodology identified priority areas, guiding managers to make decisions that respect the local particularities.

Revisiting the generation and interpretation of climate models experiments for adaptation decision-making (Invited)

Science.gov (United States)

Ranger, N.; Millner, A.; Niehoerster, F.

2010-12-01

Traditionally, climate change risk assessments have taken a roughly four-stage linear ‘chain’ of moving from socioeconomic projections, to climate projections, to primary impacts and then finally onto economic and social impact assessment. Adaptation decisions are then made on the basis of these outputs. The escalation of uncertainty through this chain is well known; resulting in an ‘explosion’ of uncertainties in the final risk and adaptation assessment. The space of plausible future risk scenarios is growing ever wider with the application of new techniques which aim to explore uncertainty ever more deeply; such as those used in the recent ‘probabilistic’ UK Climate Projections 2009, and the stochastic integrated assessment models, for example PAGE2002. This explosion of uncertainty can make decision-making problematic, particularly given that the uncertainty information communicated can not be treated as strictly probabilistic and therefore, is not an easy fit with standard decision-making under uncertainty approaches. Additional problems can arise from the fact that the uncertainty estimated for different components of the ‘chain’ is rarely directly comparable or combinable. Here, we explore the challenges and limitations of using current projections for adaptation decision-making. We report the findings of a recent report completed for the UK Adaptation Sub-Committee on approaches to deal with these challenges and make robust adaptation decisions today. To illustrate these approaches, we take a number of illustrative case studies, including a case of adaptation to hurricane risk on the US Gulf Coast. This is a particularly interesting case as it involves urgent adaptation of long-lived infrastructure but requires interpreting highly uncertain climate change science and modelling; i.e. projections of Atlantic basin hurricane activity. An approach we outline is reversing the linear chain of assessments to put the economics and decision

Markov Decision Process Measurement Model.

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LaMar, Michelle M

2018-03-01

Within-task actions can provide additional information on student competencies but are challenging to model. This paper explores the potential of using a cognitive model for decision making, the Markov decision process, to provide a mapping between within-task actions and latent traits of interest. Psychometric properties of the model are explored, and simulation studies report on parameter recovery within the context of a simple strategy game. The model is then applied to empirical data from an educational game. Estimates from the model are found to correlate more strongly with posttest results than a partial-credit IRT model based on outcome data alone.

The role of decision analytic modeling in the health economic assessment of spinal intervention.

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Edwards, Natalie C; Skelly, Andrea C; Ziewacz, John E; Cahill, Kevin; McGirt, Matthew J

2014-10-15

Narrative review. To review the common tenets, strengths, and weaknesses of decision modeling for health economic assessment and to review the use of decision modeling in the spine literature to date. For the majority of spinal interventions, well-designed prospective, randomized, pragmatic cost-effectiveness studies that address the specific decision-in-need are lacking. Decision analytic modeling allows for the estimation of cost-effectiveness based on data available to date. Given the rising demands for proven value in spine care, the use of decision analytic modeling is rapidly increasing by clinicians and policy makers. This narrative review discusses the general components of decision analytic models, how decision analytic models are populated and the trade-offs entailed, makes recommendations for how users of spine intervention decision models might go about appraising the models, and presents an overview of published spine economic models. A proper, integrated, clinical, and economic critical appraisal is necessary in the evaluation of the strength of evidence provided by a modeling evaluation. As is the case with clinical research, all options for collecting health economic or value data are not without their limitations and flaws. There is substantial heterogeneity across the 20 spine intervention health economic modeling studies summarized with respect to study design, models used, reporting, and general quality. There is sparse evidence for populating spine intervention models. Results mostly showed that interventions were cost-effective based on $100,000/quality-adjusted life-year threshold. Spine care providers, as partners with their health economic colleagues, have unique clinical expertise and perspectives that are critical to interpret the strengths and weaknesses of health economic models. Health economic models must be critically appraised for both clinical validity and economic quality before altering health care policy, payment strategies, or

Comprehensive decision tree models in bioinformatics.

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Gregor Stiglic

Full Text Available PURPOSE: Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. METHODS: This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. RESULTS: The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. CONCLUSIONS: The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets

Comprehensive decision tree models in bioinformatics.

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Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

2012-01-01

Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly

A spiral model of musical decision-making.

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Bangert, Daniel; Schubert, Emery; Fabian, Dorottya

2014-01-01

This paper describes a model of how musicians make decisions about performing notated music. The model builds on psychological theories of decision-making and was developed from empirical studies of Western art music performance that aimed to identify intuitive and deliberate processes of decision-making, a distinction consistent with dual-process theories of cognition. The model proposes that the proportion of intuitive (Type 1) and deliberate (Type 2) decision-making processes changes with increasing expertise and conceptualizes this change as movement along a continually narrowing upward spiral where the primary axis signifies principal decision-making type and the vertical axis marks level of expertise. The model is intended to have implications for the development of expertise as described in two main phases. The first is movement from a primarily intuitive approach in the early stages of learning toward greater deliberation as analytical techniques are applied during practice. The second phase occurs as deliberate decisions gradually become automatic (procedural), increasing the role of intuitive processes. As a performer examines more issues or reconsiders decisions, the spiral motion toward the deliberate side and back to the intuitive is repeated indefinitely. With increasing expertise, the spiral tightens to signify greater control over decision type selection. The model draws on existing theories, particularly Evans' (2011) Intervention Model of dual-process theories, Cognitive Continuum Theory Hammond et al. (1987), Hammond (2007), Baylor's (2001) U-shaped model for the development of intuition by level of expertise. By theorizing how musical decision-making operates over time and with increasing expertise, this model could be used as a framework for future research in music performance studies and performance science more generally.

A spiral model of musical decision-making

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Daniel eBangert

2014-04-01

Full Text Available This paper describes a model of how musicians make decisions about performing notated music. The model builds on psychological theories of decision-making and was developed from empirical studies of Western art music performance that aimed to identify intuitive and deliberate processes of decision-making, a distinction consistent with dual-process theories of cognition. The model proposes that the proportion of intuitive (Type 1 and deliberate (Type 2 decision-making processes changes with increasing expertise and conceptualises this change as movement along a continually narrowing upward spiral where the primary axis signifies principal decision-making type and the vertical axis marks level of expertise. The model is intended to have implications for the development of expertise as described in two main phases. The first is movement from a primarily intuitive approach in the early stages of learning towards greater deliberation as analytical techniques are applied during practice. The second phase occurs as deliberate decisions gradually become automatic (procedural, increasing the role of intuitive processes. As a performer examines more issues or reconsiders decisions, the spiral motion towards the deliberate side and back to the intuitive is repeated indefinitely. With increasing expertise, the spiral tightens to signify greater control over decision type selection. The model draws on existing theories, particularly Evans’ (2011 Intervention Model of dual-process theories, Cognitive Continuum Theory (Hammond et al., 1987; Hammond, 2007, and Baylor’s (2001 U-shaped model for the development of intuition by level of expertise. By theorising how musical decision-making operates over time and with increasing expertise, this model could be used as a framework for future research in music performance studies and performance science more generally.

An approach for assessing human decision reliability

International Nuclear Information System (INIS)

Pyy, P.

2000-01-01

This paper presents a method to study human reliability in decision situations related to nuclear power plant disturbances. Decisions often play a significant role in handling of emergency situations. The method may be applied to probabilistic safety assessments (PSAs) in cases where decision making is an important dimension of an accident sequence. Such situations are frequent e.g. in accident management. In this paper, a modelling approach for decision reliability studies is first proposed. Then, a case study with two decision situations with relatively different characteristics is presented. Qualitative and quantitative findings of the study are discussed. In very simple decision cases with time pressure, time reliability correlation proved out to be a feasible reliability modelling method. In all other decision situations, more advanced probabilistic decision models have to be used. Finally, decision probability assessment by using simulator run results and expert judgement is presented

Gender Difference or Indifference? Detective Decision Making in Sexual Assault Cases

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Alderden, Megan A.; Ullman, Sarah E.

2012-01-01

Prior research examining sexual assault case decision making has failed to account for the demographic characteristics of the criminal justice practitioners charged with making case decisions. Inclusion of such information is important because it provides researchers with a greater understanding of how criminal justice practitioners' own gender,…

A preference aggregation model and application in AHP-group decision making

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Yang, Taiyi; Yang, De; Chao, Xiangrui

2018-04-01

Group decision making process integrate individual preferences to obtain the group preference by applying aggregation rules and preference relations. The two most useful approaches, the aggregation of individual judgements and the aggregation of individual priorities, traditionally are employed in the Analytic Hierarchy Process to deal with group decision making problems. In both cases, it is assumed that the group preference is approximate weighted mathematical expectation of individual judgements and individual priorities. We propose new preference aggregation methods using optimization models in order to obtain group preference which is close to all individual priorities. Some illustrative examples are finally examined to demonstrate proposed models for application.

A decision model for the risk management of hazardous processes

International Nuclear Information System (INIS)

Holmberg, J.E.

1997-03-01

A decision model for risk management of hazardous processes as an optimisation problem of a point process is formulated in the study. In the approach, the decisions made by the management are divided into three categories: (1) planned process lifetime, (2) selection of the design and, (3) operational decisions. These three controlling methods play quite different roles in the practical risk management, which is also reflected in our approach. The optimisation of the process lifetime is related to the licensing problem of the process. It provides a boundary condition for a feasible utility function that is used as the actual objective function, i.e., maximizing the process lifetime utility. By design modifications, the management can affect the inherent accident hazard rate of the process. This is usually a discrete optimisation task. The study particularly concentrates upon the optimisation of the operational strategies given a certain design and licensing time. This is done by a dynamic risk model (marked point process model) representing the stochastic process of events observable or unobservable to the decision maker. An optimal long term control variable guiding the selection of operational alternatives in short term problems is studied. The optimisation problem is solved by the stochastic quasi-gradient procedure. The approach is illustrated by a case study. (23 refs.)

How Participatory Should Environmental Governance Be? Testing the Applicability of the Vroom-Yetton-Jago Model in Public Environmental Decision-Making

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Lührs, Nikolas; Jager, Nicolas W.; Challies, Edward; Newig, Jens

2018-02-01

Public participation is potentially useful to improve public environmental decision-making and management processes. In corporate management, the Vroom-Yetton-Jago normative decision-making model has served as a tool to help managers choose appropriate degrees of subordinate participation for effective decision-making given varying decision-making contexts. But does the model recommend participatory mechanisms that would actually benefit environmental management? This study empirically tests the improved Vroom-Jago version of the model in the public environmental decision-making context. To this end, the key variables of the Vroom-Jago model are operationalized and adapted to a public environmental governance context. The model is tested using data from a meta-analysis of 241 published cases of public environmental decision-making, yielding three main sets of findings: (1) The Vroom-Jago model proves limited in its applicability to public environmental governance due to limited variance in its recommendations. We show that adjustments to key model equations make it more likely to produce meaningful recommendations. (2) We find that in most of the studied cases, public environmental managers (implicitly) employ levels of participation close to those that would have been recommended by the model. (3) An ANOVA revealed that such cases, which conform to model recommendations, generally perform better on stakeholder acceptance and environmental standards of outputs than those that diverge from the model. Public environmental management thus benefits from carefully selected and context-sensitive modes of participation.

A communication model of shared decision making: accounting for cancer treatment decisions.

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Siminoff, Laura A; Step, Mary M

2005-07-01

The authors present a communication model of shared decision making (CMSDM) that explicitly identifies the communication process as the vehicle for decision making in cancer treatment. In this view, decision making is necessarily a sociocommunicative process whereby people enter into a relationship, exchange information, establish preferences, and choose a course of action. The model derives from contemporary notions of behavioral decision making and ethical conceptions of the doctor-patient relationship. This article briefly reviews the theoretical approaches to decision making, notes deficiencies, and embeds a more socially based process into the dynamics of the physician-patient relationship, focusing on cancer treatment decisions. In the CMSDM, decisions depend on (a) antecedent factors that have potential to influence communication, (b) jointly constructed communication climate, and (c) treatment preferences established by the physician and the patient.

Case law and administrative decisions

International Nuclear Information System (INIS)

Anon.

2005-01-01

About the case law we find four parts, one concerns France and the judgement of the council of state on an application for annulment of the decree of 10 january 2003 authorizing Cogema to modify a major nuclear installation, a second one is in relation with the Usa through the ruling in relation to the sale of uranium enrichment services in the united States, decision concerning the Yucca mountain repository, Indiana michigan power company v. United States, natural resources defense council, snake river alliance, confederated tribes and bands of the Yakama indian Nation, Shoshone Bannock Tribes v. Abraham. For the third part devoted to European union it is question of the judgement of the European Court of justice in European union v. UK, the fourth part concerns administrative decisions with the early shutdown of Barsebaeck-2 in Sweden. (N.C.)

Simple Prediction of Type 2 Diabetes Mellitus via Decision Tree Modeling

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Mehrab Sayadi

2017-06-01

Full Text Available Background: Type 2 Diabetes Mellitus (T2DM is one of the most important risk factors in cardiovascular disorders considered as a common clinical and public health problem. Early diagnosis can reduce the burden of the disease. Decision tree, as an advanced data mining method, can be used as a reliable tool to predict T2DM. Objectives: This study aimed to present a simple model for predicting T2DM using decision tree modeling. Materials and Methods: This analytical model-based study used a part of the cohort data obtained from a database in Healthy Heart House of Shiraz, Iran. The data included routine information, such as age, gender, Body Mass Index (BMI, family history of diabetes, and systolic and diastolic blood pressure, which were obtained from the individuals referred for gathering baseline data in Shiraz cohort study from 2014 to 2015. Diabetes diagnosis was used as binary datum. Decision tree technique and J48 algorithm were applied using the WEKA software (version 3.7.5, New Zealand. Additionally, Receiver Operator Characteristic (ROC curve and Area Under Curve (AUC were used for checking the goodness of fit. Results: The age of the 11302 cases obtained after data preparation ranged from 18 to 89 years with the mean age of 48.1 ± 11.4 years. Additionally, 51.1% of the cases were male. In the tree structure, blood pressure and age were placed where most information was gained. In our model, however, gender was not important and was placed on the final branch of the tree. Total precision and AUC were 87% and 89%, respectively. This indicated that the model had good accuracy for distinguishing patients from normal individuals. Conclusions: The results showed that T2DM could be predicted via decision tree model without laboratory tests. Thus, this model can be used in pre-clinical and public health screening programs.

Interactive use of simulation models for collaborative knowledge construction: the case of flood policy decision-making

NARCIS (Netherlands)

Leskens, Anne

2015-01-01

There is an increasing use of interactive flood simulation models in work sessions with practitioners, which is supposed to be more effective than feeding static model results from conventional simulation models into the decision-making process. These interactive simulation models rely on fast and

Integrated micro-economic modelling and multi-criteria methodology to support public decision-making: the case of liquid bio-fuels in France

International Nuclear Information System (INIS)

Rozakis, S.; Sourie, J.-C.; Vanderpooten, D.

2001-01-01

Decision making to determine government support policy for agro-energy industry can be assisted by mathematical programming and Multiple Criteria procedures. In this case study, tax credit policy in the French bio-fuel industry producing ethanol and esters is determined. Micro-economic models simulate the agricultural sector and the bio-fuel industry through multi-level mixed integer linear programming. Aggregate supply of energy crops at the national level is estimated using a staircase model of 450 individual farm sub-models specialising in arable cropping. The government acts as a leader, since bio-fuel chains depend on subsidies. The model provides rational responses of the industry, taking into account of the energy crops' supply, to any public policy scheme (unitary tax exemptions for bio-fuels subject to budgetary constraints) as well as the performance of each response regarding total greenhouse gases emissions (GHG), budgetary expenditure and agents' surpluses. Budgetary, environmental and social concerns will affect policy decisions, and a multi-criteria optimisation module projects the decision maker aims at the closest feasible compromise solutions. When public expenditure is the first priority, the best compromise solution corresponds to tax exemptions of about 2 FF l -1 [FF: French Franc (1Euro equivalent to 6.559FF)] for ester and 3FF l -1 for ethanol (current tax exemptions amount at 2.30FF l -1 for ester and 3.30FF l -1 for ethanol). On the other hand, a priority on the reduction of GHG emissions requires an increase of ester volume produced at the expense of ethanol production (2.30 FF l -1 for both ester and ethanol chains proposed by the model). (Author)

Decision-making for supplying energy projects: A four-dimensional model

International Nuclear Information System (INIS)

Smith Stegen, Karen; Palovic, Martin

2014-01-01

Highlights: • Extant pipeline evaluation models offer insufficient supplier analysis tools. • We offer a four-dimensional decision-making tool to augment extant models. • Model employs four filters to help decision makers eliminate unsuitable suppliers. • Aids in prioritization of best courses of action for overcoming obstacles. • Case study of Nabucco pipeline shows Azerbaijan would have been best supply option. - Abstract: Importing states and regions employ myriad strategies to enhance energy security, from stockpiling to diversification to efficiency programs. As has occurred in recent years, importers can seek diversification by initiating pipeline and liquefied natural gas projects, meaning they may also have to select suppliers. However, most extant pipeline evaluation models erroneously assume suppliers are known and thus neglect supplier selection. We propose a decision-making tool to augment these older models: a systematic and replicable four-dimensional model to help policymakers and managers identify suitable suppliers and prioritize the best courses of action for overcoming obstacles. The first three dimensions—timeframe, supply availability and infrastructure constraints—filter out unsuitable suppliers. The fourth dimension then assesses the political, geopolitical and commercial stability of the remaining candidates. To demonstrate the model in practice, we assess the original Nabucco pipeline proposal, which was designed to transport gas from the Caspian and Middle East regions to Europe

"Best Case/Worst Case": Qualitative Evaluation of a Novel Communication Tool for Difficult in-the-Moment Surgical Decisions.

Science.gov (United States)

Kruser, Jacqueline M; Nabozny, Michael J; Steffens, Nicole M; Brasel, Karen J; Campbell, Toby C; Gaines, Martha E; Schwarze, Margaret L

2015-09-01

To evaluate a communication tool called "Best Case/Worst Case" (BC/WC) based on an established conceptual model of shared decision-making. Focus group study. Older adults (four focus groups) and surgeons (two focus groups) using modified questions from the Decision Aid Acceptability Scale and the Decisional Conflict Scale to evaluate and revise the communication tool. Individuals aged 60 and older recruited from senior centers (n = 37) and surgeons from academic and private practices in Wisconsin (n = 17). Qualitative content analysis was used to explore themes and concepts that focus group respondents identified. Seniors and surgeons praised the tool for the unambiguous illustration of multiple treatment options and the clarity gained from presentation of an array of treatment outcomes. Participants noted that the tool provides an opportunity for in-the-moment, preference-based deliberation about options and a platform for further discussion with other clinicians and loved ones. Older adults worried that the format of the tool was not universally accessible for people with different educational backgrounds, and surgeons had concerns that the tool was vulnerable to physicians' subjective biases. The BC/WC tool is a novel decision support intervention that may help facilitate difficult decision-making for older adults and their physicians when considering invasive, acute medical treatments such as surgery. © 2015, Copyright the Authors Journal compilation © 2015, The American Geriatrics Society.

Model of Decision Making through Consensus in Ranking Case

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Tarigan, Gim; Darnius, Open

2018-01-01

The basic problem to determine ranking consensus is a problem to combine some rankings those are decided by two or more Decision Maker (DM) into ranking consensus. DM is frequently asked to present their preferences over a group of objects in terms of ranks, for example to determine a new project, new product, a candidate in a election, and so on. The problem in ranking can be classified into two major categories; namely, cardinal and ordinal rankings. The objective of the study is to obtin the ranking consensus by appying some algorithms and methods. The algorithms and methods used in this study were partial algorithm, optimal ranking consensus, BAK (Borde-Kendal)Model. A method proposed as an alternative in ranking conssensus is a Weighted Distance Forward-Backward (WDFB) method, which gave a little difference i ranking consensus result compare to the result oethe example solved by Cook, et.al (2005).

Intelligent Decision Support in Proportional–Stop-Loss Reinsurance Using Multiple Attribute Decision-Making (MADM

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Shirley Jie Xuan Wang

2017-11-01

Full Text Available This article addresses the possibility of incorporating intelligent decision support systems into reinsurance decision-making. This involves the insurance company and the reinsurance company, and is negotiated through reinsurance intermediaries. The article proposes a decision flow to model the reinsurance design and selection process. This article focuses on adopting more than one optimality criteria under a more generic combinational design of commonly used reinsurance products, i.e., proportional reinsurance and stop-loss reinsurance. In terms of methodology, the significant contribution of the study the incorporation of the well-established decision analysis tool multiple-attribute decision-making (MADM into the modelling of reinsurance selection. To illustrate the feasibility of incorporating intelligent decision supporting systems in the reinsurance market, the study includes a numerical case study using the simulation software @Risk in modeling insurance claims, as well as programming in MATLAB to realize MADM. A list of managerial implications could be drawn from the case study results. Most importantly, when choosing the most appropriate type of reinsurance, insurance companies should base their decisions on multiple measurements instead of single-criteria decision-making models so that their decisions may be more robust.

Parental decision-making on utilisation of out-of-home respite in children's palliative care: findings of qualitative case study research - a proposed new model.

Science.gov (United States)

Ling, J; Payne, S; Connaire, K; McCarron, M

2016-01-01

Respite in children's palliative care aims to provide a break for family's from the routine of caring. Parental decision-making regarding the utilisation of out-of-home respite is dependent on many interlinking factors including the child's age, diagnosis, geographical location and the family's capacity to meet their child's care needs. A proposed model for out-of-home respite has been developed based on the findings of qualitative case study research. Utilising multiple, longitudinal, qualitative case study design, the respite needs and experiences of parents caring for a child with a life-limiting condition were explored. Multiple, in-depth interviews were undertaken with the parents identified by a hospital-based children's palliative care team. Data were analysed using thematic analysis. Each individual case consists of a whole study. Cross-case comparison was also conducted. Nine families were recruited and followed for two years. A total of 19 in-depth interviews were conducted with mothers and fathers (one or both) caring for a child with a life-limiting condition in Ireland. Each family reported vastly different needs and experiences of respite from their own unique perspective. Cross-case comparison showed that for all parents utilising respite care, regardless of their child's age and condition, home was the location of choice. Many interlinking factors influencing these decisions included: past experience of in-patient care, and trust and confidence in care providers. Issues were raised regarding the impact of care provision in the home on family life, siblings and the concept of home. Respite is an essential element of children's palliative care. Utilisation of out-of-home respite is heavily dependent on a number of interlinked and intertwined factors. The proposed model of care offers an opportunity to identify how these decisions are made and may ultimately assist in identifying the elements of responsive and family-focused respite that are important

The Role of Integrated Modelling and Assessment for Decision-Making: Lessons from Water Allocation Issues in Australia

Science.gov (United States)

Jakeman, A. J.; Guillaume, J. H. A.; El Sawah, S.; Hamilton, S.

2014-12-01

Integrated modelling and assessment (IMA) is best regarded as a process that can support environmental decision-making when issues are strongly contested and uncertainties pervasive. To be most useful, the process must be multi-dimensional and phased. Principally, it must be tailored to the problem context to encompass diverse issues of concern, management settings and stakeholders. This in turn requires the integration of multiple processes and components of natural and human systems and their corresponding spatial and temporal scales. Modellers therefore need to be able to integrate multiple disciplines, methods, models, tools and data, and many sources and types of uncertainty. These dimensions are incorporated into iteration between the various phases of the IMA process, including scoping, problem framing and formulation, assessing options and communicating findings. Two case studies in Australia are employed to share the lessons of how integration can be achieved in these IMA phases using a mix of stakeholder participation processes and modelling tools. One case study aims to improve the relevance of modelling by incorporating stakeholder's views of irrigated viticulture and water management decision making. It used a novel methodology with the acronym ICTAM, consisting of Interviews to elicit mental models, Cognitive maps to represent and analyse individual and group mental models, Time-sequence diagrams to chronologically structure the decision making process, an All-encompassing conceptual model, and computational Models of stakeholder decision making. The second case uses a hydro-economic river network model to examine basin-wide impacts of water allocation cuts and adoption of farm innovations. The knowledge exchange approach used in each case was designed to integrate data and knowledge bearing in mind the contextual dimensions of the problem at hand, and the specific contributions that environmental modelling was thought to be able to make.

Assessing electronic health record systems in emergency departments: Using a decision analytic Bayesian model.

Science.gov (United States)

Ben-Assuli, Ofir; Leshno, Moshe

2016-09-01

In the last decade, health providers have implemented information systems to improve accuracy in medical diagnosis and decision-making. This article evaluates the impact of an electronic health record on emergency department physicians' diagnosis and admission decisions. A decision analytic approach using a decision tree was constructed to model the admission decision process to assess the added value of medical information retrieved from the electronic health record. Using a Bayesian statistical model, this method was evaluated on two coronary artery disease scenarios. The results show that the cases of coronary artery disease were better diagnosed when the electronic health record was consulted and led to more informed admission decisions. Furthermore, the value of medical information required for a specific admission decision in emergency departments could be quantified. The findings support the notion that physicians and patient healthcare can benefit from implementing electronic health record systems in emergency departments. © The Author(s) 2015.

Nuclear weapons decision-making; an application of organization theory to the mini-nuke case

International Nuclear Information System (INIS)

Kangas, J.L.

1985-01-01

This dissertation addresses the problem of constructing and developing normative theory responsive to the need for improving the quality of decision-making in the nuclear weapons policy-making. Against the background of a critical evaluation of various paradigms in the literature (systems analysis and opposed-systems designed, the bureaucratic politics model, and the cybernetic theory of decision) an attempt is made to design an alternative analytic framework based on the writings of numerous organization theorists such as Herbert Simon and Kenneth Arrow. The framework is applied to the case of mini-nukes, i.e., proposals in the mid-1970s to develop and deploy tens of thousands of very low-yield (sub-kiloton), miniaturized fission weapons in NATO. Heuristic case study identifies the type of study undertaken in the dissertation in contrast to the more familiar paradigmatic studies identified, for example, with the Harvard Weapons Project. Application of the analytic framework developed in the dissertation of the mini-nuke case resulted in an empirical understanding of why decision making concerning tactical nuclear weapons has been such a complex task and why force modernization issues in particular have been so controversial and lacking in policy resolution

Introduction to Modeling of Buying Decisions

Directory of Open Access Journals (Sweden)

O. Gruenwald

2011-01-01

Full Text Available Buying decision models of customers to adjust the competitiveness of organizations have been a challenge for marketing disciplines for several generations. This topic has been explored by researchers and academics in past years, and quite an extensive theoretical base exists with a number of approaches for dealing with this challenge.This paper presents some approaches for creating a customer decision model, and provides experimental results from an electronic investigation intended to build the Kano Model; to prove an ability to understand the modeling principle; and to find out the interpretation of the examined demand in a specific market segment involving students of a technical university. The last section of the paper contains a brief introduction to Choice-Based Modeling with Choice-Based Conjoint Analysis (CBC, which was tailored for modeling purchasing decisions.

Case law and administrative decisions

International Nuclear Information System (INIS)

2003-01-01

Some extracts of case law: ruling of the Supreme Administrative Court on the decision to shut units 3 and 4 of Kozloduy nuclear power plant (Bulgaria), judgement of the County Court of Cherbourg concerning the import of spent fuel to La Hague (France), judgement of the Nagoya High Court on the invalidity of the licence to establish the Monju reactor, judgement of the Mito District Court issuing penalties in respect of the Tokai-Mura accident, the Principle of justification: the application of the Principle to the Manufacture of MOX fuel in the UK, Ruling of the US Court of International trade in relation to the sale of uranium enrichment services in the United States, Commission v Council Accession of the Community to the Convention on nuclear safety, government decision not to appeal court ruling on the continued operation of the Borssele nuclear power plant. (N.C.)

A decision rule based on goal programming and one-stage models for uncertain multi-criteria mixed decision making and games against nature

Directory of Open Access Journals (Sweden)

Helena Gaspars-Wieloch

2017-01-01

Full Text Available This paper is concerned with games against nature and multi-criteria decision making under uncertainty along with scenario planning. We focus on decision problems where a deterministic evaluation of criteria is not possible. The procedure we propose is based on weighted goal programming and may be applied when seeking a mixed strategy. A mixed strategy allows the decision maker to select and perform a weighted combination of several accessible alternatives. The new method takes into consideration the decision maker’s preference structure (importance of particular goals and nature (pessimistic, moderate or optimistic attitude towards a given problem. It is designed for one-shot decisions made under uncertainty with unknown probabilities (frequencies, i.e. for decision making under complete uncertainty or decision making under strategic uncertainty. The procedure refers to one-stage models, i.e. models considering combinations of scenarios and criteria (scenario-criterion pairs as distinct meta-attributes, which means that the novel approach can be used in the case of totally independent payoff matrices for particular targets. The algorithm does not require any information about frequencies, which is especially desirable for new decision problems. It can be successfully applied by passive decision makers, as only criteria weights and the coefficient of optimism have to be declared.

Multi-Criteria Decision Making For Determining A Simple Model of Supplier Selection

Science.gov (United States)

Harwati

2017-06-01

Supplier selection is a decision with many criteria. Supplier selection model usually involves more than five main criteria and more than 10 sub-criteria. In fact many model includes more than 20 criteria. Too many criteria involved in supplier selection models sometimes make it difficult to apply in many companies. This research focuses on designing supplier selection that easy and simple to be applied in the company. Analytical Hierarchy Process (AHP) is used to weighting criteria. The analysis results there are four criteria that are easy and simple can be used to select suppliers: Price (weight 0.4) shipment (weight 0.3), quality (weight 0.2) and services (weight 0.1). A real case simulation shows that simple model provides the same decision with a more complex model.

The two-model problem in rational decision making

NARCIS (Netherlands)

Boumans, Marcel

2011-01-01

A model of a decision problem frames that problem in three dimensions: sample space, target probability and information structure. Each specific model imposes a specific rational decision. As a result, different models may impose different, even contradictory, rational decisions, creating choice

A dynamic dual process model of risky decision making.

Science.gov (United States)

Diederich, Adele; Trueblood, Jennifer S

2018-03-01

Many phenomena in judgment and decision making are often attributed to the interaction of 2 systems of reasoning. Although these so-called dual process theories can explain many types of behavior, they are rarely formalized as mathematical or computational models. Rather, dual process models are typically verbal theories, which are difficult to conclusively evaluate or test. In the cases in which formal (i.e., mathematical) dual process models have been proposed, they have not been quantitatively fit to experimental data and are often silent when it comes to the timing of the 2 systems. In the current article, we present a dynamic dual process model framework of risky decision making that provides an account of the timing and interaction of the 2 systems and can explain both choice and response-time data. We outline several predictions of the model, including how changes in the timing of the 2 systems as well as time pressure can influence behavior. The framework also allows us to explore different assumptions about how preferences are constructed by the 2 systems as well as the dynamic interaction of the 2 systems. In particular, we examine 3 different possible functional forms of the 2 systems and 2 possible ways the systems can interact (simultaneously or serially). We compare these dual process models with 2 single process models using risky decision making data from Guo, Trueblood, and Diederich (2017). Using this data, we find that 1 of the dual process models significantly outperforms the other models in accounting for both choices and response times. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Decision models in explorative and exploitative innovation projects: a case study

NARCIS (Netherlands)

Wolbers, Michiel; Hofman, Erwin; Halman, Johannes I.M.

2013-01-01

Innovation processes are seen as collections of decisions that are made in the context of a single innovation project. Those decisions determine the course and the final success of an innovation project. There is, however, a lack of literature on how decisions are made in innovation projects. In

A system dynamics model of clinical decision thresholds for the detection of developmental-behavioral disorders

Directory of Open Access Journals (Sweden)

R. Christopher Sheldrick

2016-11-01

Full Text Available Abstract Background Clinical decision-making has been conceptualized as a sequence of two separate processes: assessment of patients’ functioning and application of a decision threshold to determine whether the evidence is sufficient to justify a given decision. A range of factors, including use of evidence-based screening instruments, has the potential to influence either or both processes. However, implementation studies seldom specify or assess the mechanism by which screening is hypothesized to influence clinical decision-making, thus limiting their ability to address unexpected findings regarding clinicians’ behavior. Building on prior theory and empirical evidence, we created a system dynamics (SD model of how physicians’ clinical decisions are influenced by their assessments of patients and by factors that may influence decision thresholds, such as knowledge of past patient outcomes. Using developmental-behavioral disorders as a case example, we then explore how referral decisions may be influenced by changes in context. Specifically, we compare predictions from the SD model to published implementation trials of evidence-based screening to understand physicians’ management of positive screening results and changes in referral rates. We also conduct virtual experiments regarding the influence of a variety of interventions that may influence physicians’ thresholds, including improved access to co-located mental health care and improved feedback systems regarding patient outcomes. Results Results of the SD model were consistent with recent implementation trials. For example, the SD model suggests that if screening improves physicians’ accuracy of assessment without also influencing decision thresholds, then a significant proportion of children with positive screens will not be referred and the effect of screening implementation on referral rates will be modest—results that are consistent with a large proportion of published

Expectation Violation in Political Decision Making: A Psychological Case Study

Directory of Open Access Journals (Sweden)

Michael Öllinger

2017-10-01

Full Text Available Since the early Gestaltists there has been a strong interest in the question of how problem solvers get stuck in a mental impasse. A key idea is that the repeated activation of a successful strategy from the past results in a mental set (‘Einstellung’ which determines and constrains the option space to solve a problem. We propose that this phenomenon, which mostly was tested by fairly restricted experiments in the lab, could also be applied to more complex problem constellations and naturalistic decision making. We aim at scrutinizing and reconstructing how a mental set determines the misinterpretation of facts in the field of political decision making and leads in consequence to wrong expectations and an ill-defined problem representation. We will exemplify this psychological mechanism considering a historical example, namely the unexpected stabilization of the Franco regime at the end of World War II and its survival thereafter. A specific focus will be drawn to the significant observation that erroneous expectations were taken as the basis for decisions. This is congruent with the notion that in case of discrepancy between preconceived notions and new information, the former prevails over the new findings. Based on these findings, we suggest a theoretical model for expectation violation in political decision making and develop novel approaches for cognitive empirical research on the mechanisms of expectation violation and its maintenance in political decision making processes.

A neural model of decision making

OpenAIRE

Larsen, Torben

2008-01-01

Background: A descriptive neuroeconomic model is aimed for relativity of the concept of economic man to empirical science.Method: A 4-level client-server-integrator model integrating the brain models of McLean and Luria is the general framework for the model of empirical findings.Results: Decision making relies on integration across brain levels of emotional intelligence (LU) and logico-matematico intelligence (RIA), respectively. The integrated decision making formula approaching zero by bot...

Integrated micro-economic modelling and multi-criteria methodology to support public decision-making: the case of liquid bio-fuels in France

Energy Technology Data Exchange (ETDEWEB)

Rozakis, S.; Sourie, J.-C. [Institut National de la Recherche Agronomique, Economie et Sociologie Rurales, Thiveral-Grignon, 78 (France); Vanderpooten, D. [Universite Paris-Dauphine, LAMSADE, Paris, 75 (France)

2001-07-01

Decision making to determine government support policy for agro-energy industry can be assisted by mathematical programming and Multiple Criteria procedures. In this case study, tax credit policy in the French bio-fuel industry producing ethanol and esters is determined. Micro-economic models simulate the agricultural sector and the bio-fuel industry through multi-level mixed integer linear programming. Aggregate supply of energy crops at the national level is estimated using a staircase model of 450 individual farm sub-models specialising in arable cropping. The government acts as a leader, since bio-fuel chains depend on subsidies. The model provides rational responses of the industry, taking into account of the energy crops' supply, to any public policy scheme (unitary tax exemptions for bio-fuels subject to budgetary constraints) as well as the performance of each response regarding total greenhouse gases emissions (GHG), budgetary expenditure and agents' surpluses. Budgetary, environmental and social concerns will affect policy decisions, and a multi-criteria optimisation module projects the decision maker aims at the closest feasible compromise solutions. When public expenditure is the first priority, the best compromise solution corresponds to tax exemptions of about 2 FF l{sup -1} [FF: French Franc (1Euro equivalent to 6.559FF)] for ester and 3FF l{sup -1} for ethanol (current tax exemptions amount at 2.30FF l{sup -1} for ester and 3.30FF l{sup -1} for ethanol). On the other hand, a priority on the reduction of GHG emissions requires an increase of ester volume produced at the expense of ethanol production (2.30 FF l{sup -1} for both ester and ethanol chains proposed by the model). (Author)

Modeling Common-Sense Decisions

Science.gov (United States)

Zak, Michail

This paper presents a methodology for efficient synthesis of dynamical model simulating a common-sense decision making process. The approach is based upon the extension of the physics' First Principles that includes behavior of living systems. The new architecture consists of motor dynamics simulating actual behavior of the object, and mental dynamics representing evolution of the corresponding knowledge-base and incorporating it in the form of information flows into the motor dynamics. The autonomy of the decision making process is achieved by a feedback from mental to motor dynamics. This feedback replaces unavailable external information by an internal knowledgebase stored in the mental model in the form of probability distributions.

A judgment and decision-making model for plant behavior.

Science.gov (United States)

Karban, Richard; Orrock, John L

2018-06-12

Recently plant biologists have documented that plants, like animals, engage in many activities that can be considered as behaviors, although plant biologists currently lack a conceptual framework to understand these processes. Borrowing the well-established framework developed by psychologists, we propose that plant behaviors can be constructively modeled by identifying four distinct components: 1) a cue or stimulus that provides information, 2) a judgment whereby the plant perceives and processes this informative cue, 3) a decision whereby the plant chooses among several options based on their relative costs and benefits, and 4) action. Judgment for plants can be determined empirically by monitoring signaling associated with electrical, calcium, or hormonal fluxes. Decision-making can be evaluated empirically by monitoring gene expression or differential allocation of resources. We provide examples of the utility of this judgment and decision-making framework by considering cases in which plants either successfully or unsuccessfully induced resistance against attacking herbivores. Separating judgment from decision-making suggests new analytical paradigms (i.e., Bayesian methods for judgment and economic utility models for decision-making). Following this framework, we propose an experimental approach to plant behavior that explicitly manipulates the stimuli provided to plants, uses plants that vary in sensory abilities, and examines how environmental context affects plant responses. The concepts and approaches that follow from the judgment and decision-making framework can shape how we study and understand plant-herbivore interactions, biological invasions, plant responses to climate change, and the susceptibility of plants to evolutionary traps. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Interactive modelling with stakeholders in two cases in flood management

Science.gov (United States)

Leskens, Johannes; Brugnach, Marcela

2013-04-01

New policies on flood management called Multi-Level Safety (MLS), demand for an integral and collaborative approach. The goal of MLS is to minimize flood risks by a coherent package of protection measures, crisis management and flood resilience measures. To achieve this, various stakeholders, such as water boards, municipalities and provinces, have to collaborate in composing these measures. Besides the many advances this integral and collaborative approach gives, the decision-making environment becomes also more complex. Participants have to consider more criteria than they used to do and have to take a wide network of participants into account, all with specific perspectives, cultures and preferences. In response, sophisticated models are developed to support decision-makers in grasping this complexity. These models provide predictions of flood events and offer the opportunity to test the effectiveness of various measures under different criteria. Recent model advances in computation speed and model flexibility allow stakeholders to directly interact with a hydrological hydraulic model during meetings. Besides a better understanding of the decision content, these interactive models are supposed to support the incorporation of stakeholder knowledge in modelling and to support mutual understanding of different perspectives of stakeholders To explore the support of interactive modelling in integral and collaborate policies, such as MLS, we tested a prototype of an interactive flood model (3Di) with respect to a conventional model (Sobek) in two cases. The two cases included the designing of flood protection measures in Amsterdam and a flood event exercise in Delft. These case studies yielded two main results. First, we observed that in the exploration phase of a decision-making process, stakeholders participated actively in interactive modelling sessions. This increased the technical understanding of complex problems and the insight in the effectiveness of various

LANL Institutional Decision Support By Process Modeling and Analysis Group (AET-2)

Energy Technology Data Exchange (ETDEWEB)

Booth, Steven Richard [Los Alamos National Laboratory

2016-04-04

AET-2 has expertise in process modeling, economics, business case analysis, risk assessment, Lean/Six Sigma tools, and decision analysis to provide timely decision support to LANS leading to continuous improvement. This capability is critical during the current tight budgetary environment as LANS pushes to identify potential areas of cost savings and efficiencies. An important arena is business systems and operations, where processes can impact most or all laboratory employees. Lab-wide efforts are needed to identify and eliminate inefficiencies to accomplish Director McMillan’s charge of “doing more with less.” LANS faces many critical and potentially expensive choices that require sound decision support to ensure success. AET-2 is available to provide this analysis support to expedite the decisions at hand.

Improved TOPSIS decision model for NPP emergencies

International Nuclear Information System (INIS)

Zhang Jin; Liu Feng; Huang Lian

2011-01-01

In this paper,an improved decision model is developed for its use as a tool to respond to emergencies at nuclear power plants. Given the complexity of multi-attribute emergency decision-making on nuclear accident, the improved TOPSIS method is used to build a decision-making model that integrates subjective weight and objective weight of each evaluation index. A comparison between the results of this new model and two traditional methods of fuzzy hierarchy analysis method and weighted analysis method demonstrates that the improved TOPSIS model has a better evaluation effect. (authors)

Decision-based model development for nuclear material theft, smuggling, and illicit use

International Nuclear Information System (INIS)

Scott, B.

2002-01-01

Full text: Nuclear material is vulnerable to a range of theft, sabotage, smuggling and illicit use scenarios. These scenarios are dependent on the choices of individuals and organizations involved in these activities. These choices, in turn; are dependent on the perceived payoff vectors of the involved players. These payoff vectors can include monetary gain, ability to avoid detection, penalties for detection, difficulty of accomplishment, resource constraints, infrastructure support, etc. Threat scenarios can be developed from these individual choices, and the set of worst-case threat scenarios can be compiled into a threat definition. The implementation of physical protection controls is dependent on the developed threat scenarios. The analysis of the composition of the postulated threat can be based on the analysis of the postulated decisions of the individuals and organizations involved on theft, smuggling, and illicit use. This paper proposes a model to systematically analyze the significant decision points that an individual or organization addresses as result of its goals. The model's dependence on assumptions is discussed. Using these assumptions, a model is developed that assigns probabilities to a set of decisions performed by the individuals involved in theft/smuggling. The individual and organisation's decisions are based on the perceived cost/benefit of the decisions and the resource constraints. Methods for functionally obtaining decision probabilities from perceived cost/benefit are proposed. The treatment of high-consequence/low-probability events is discussed in terms of analysis of precursor events, and the use of sensitivity analysis is discussed. An example of a simplified model for nuclear material theft, smuggling, and illicit use is presented, and the results of this simplified model are evaluated. By attempting to model the potential distribution of nuclear material theft/smuggling events, this model increases the analytical tools available

[Decision modeling for economic evaluation of health technologies].

Science.gov (United States)

de Soárez, Patrícia Coelho; Soares, Marta Oliveira; Novaes, Hillegonda Maria Dutilh

2014-10-01

Most economic evaluations that participate in decision-making processes for incorporation and financing of technologies of health systems use decision models to assess the costs and benefits of the compared strategies. Despite the large number of economic evaluations conducted in Brazil, there is a pressing need to conduct an in-depth methodological study of the types of decision models and their applicability in our setting. The objective of this literature review is to contribute to the knowledge and use of decision models in the national context of economic evaluations of health technologies. This article presents general definitions about models and concerns with their use; it describes the main models: decision trees, Markov chains, micro-simulation, simulation of discrete and dynamic events; it discusses the elements involved in the choice of model; and exemplifies the models addressed in national economic evaluation studies of diagnostic and therapeutic preventive technologies and health programs.

Behavioural modelling of irrigation decision making under water scarcity

Science.gov (United States)

Foster, T.; Brozovic, N.; Butler, A. P.

2013-12-01

Providing effective policy solutions to aquifer depletion caused by abstraction for irrigation is a key challenge for socio-hydrology. However, most crop production functions used in hydrological models do not capture the intraseasonal nature of irrigation planning, or the importance of well yield in land and water use decisions. Here we develop a method for determining stochastic intraseasonal water use that is based on observed farmer behaviour but is also theoretically consistent with dynamically optimal decision making. We use the model to (i) analyse the joint land and water use decision by farmers; (ii) to assess changes in behaviour and production risk in response to water scarcity; and (iii) to understand the limits of applicability of current methods in policy design. We develop a biophysical model of water-limited crop yield building on the AquaCrop model. The model is calibrated and applied to case studies of irrigated corn production in Nebraska and Texas. We run the model iteratively, using long-term climate records, to define two formulations of the crop-water production function: (i) the aggregate relationship between total seasonal irrigation and yield (typical of current approaches); and (ii) the stochastic response of yield and total seasonal irrigation to the choice of an intraseasonal soil moisture target and irrigated area. Irrigated area (the extensive margin decision) and per-area irrigation intensity (the intensive margin decision) are then calculated for different seasonal water restrictions (corresponding to regulatory policies) and well yield constraints on intraseasonal abstraction rates (corresponding to aquifer system limits). Profit- and utility-maximising decisions are determined assuming risk neutrality and varying degrees of risk aversion, respectively. Our results demonstrate that the formulation of the production function has a significant impact on the response to water scarcity. For low well yields, which are the major concern

A new fuzzy MCDA framework for make-or-buy decisions: A case study of aerospace industry

Directory of Open Access Journals (Sweden)

Mohsen Cheshmberah

2011-07-01

Full Text Available One of the primary managerial decisions for manufacturing units is to find out which activity must be outsourced. A good outsourcing decision is normally involved with different criteria such as opportunity costs, cost saving, etc. In this paper, we present a multi criteria decision-making method to find a suitable solution for outsourcing activities called preference ranking organization method for enrichment evaluations (PROMETHEE. The proposed model of this paper uses fuzzy numbers to determine the relative importance of different criteria and it is implemented for a real-world case study of aerospace industry.

Leadership of risk decision making in a complex, technology organization: The deliberative decision making model

Science.gov (United States)

Flaming, Susan C.

2007-12-01

The continuing saga of satellite technology development is as much a story of successful risk management as of innovative engineering. How do program leaders on complex, technology projects manage high stakes risks that threaten business success and satellite performance? This grounded theory study of risk decision making portrays decision leadership practices at one communication satellite company. Integrated product team (IPT) leaders of multi-million dollar programs were interviewed and observed to develop an extensive description of the leadership skills required to navigate organizational influences and drive challenging risk decisions to closure. Based on the study's findings the researcher proposes a new decision making model, Deliberative Decision Making, to describe the program leaders' cognitive and organizational leadership practices. This Deliberative Model extends the insights of prominent decision making models including the rational (or classical) and the naturalistic and qualifies claims made by bounded rationality theory. The Deliberative Model describes how leaders proactively engage resources to play a variety of decision leadership roles. The Model incorporates six distinct types of leadership decision activities, undertaken in varying sequence based on the challenges posed by specific risks. Novel features of the Deliberative Decision Model include: an inventory of leadership methods for managing task challenges, potential stakeholder bias and debates; four types of leadership meta-decisions that guide decision processes, and aligned organizational culture. Both supporting and constraining organizational influences were observed as leaders managed major risks, requiring active leadership on the most difficult decisions. Although the company's engineering culture emphasized the importance of data-based decisions, the uncertainties intrinsic to satellite risks required expert engineering judgment to be exercised throughout. An investigation into

Early decision-analytic modeling - a case study on vascular closure devices.

Science.gov (United States)

Brandes, Alina; Sinner, Moritz F; Kääb, Stefan; Rogowski, Wolf H

2015-10-27

As economic considerations become more important in healthcare reimbursement, decisions about the further development of medical innovations need to take into account not only medical need and potential clinical effectiveness, but also cost-effectiveness. Already early in the innovation process economic evaluations can support decisions on development in specific indications or patient groups by anticipating future reimbursement and implementation decisions. One potential concept for early assessment is value-based pricing. The objective is to assess the feasibility of value-based pricing and product design for a hypothetical vascular closure device in the pre-clinical stage which aims at decreasing bleeding events. A deterministic decision-analytic model was developed to estimate the cost-effectiveness of established vascular closure devices from the perspective of the Statutory Health Insurance system. To identify early benchmarks for pricing and product design, three strategies of determining the product's value are explored: 1) savings from complications avoided by the new device; 2) valuation of the avoided complications based on an assumed willingness-to-pay-threshold (the efficiency frontier approach); 3) value associated with modifying the care pathways within which the device would be applied. Use of established vascular closure devices is dominated by manual compression. The hypothetical vascular closure device reduces overall complication rates at higher costs than manual compression. Maximum cost savings of only about €4 per catheterization could be realized by applying the hypothetical device. Extrapolation of an efficiency frontier is only possible for one subgroup where vascular closure devices are not a dominated strategy. Modifying care in terms of same-day discharge of patients treated with vascular closure devices could result in cost savings of €400-600 per catheterization. It was partially feasible to calculate value-based prices for the

Decision Support Model for Mosque Renovation and Rehabilitation (Case Study: Ten Mosques in Jakarta Barat, Indonesia)

Science.gov (United States)

Utama, D. N.; Triana, Y. S.; Iqbal, M. M.; Iksal, M.; Fikri, I.; Dharmawan, T.

2018-03-01

Mosque, for Muslim, is not only a place for daily worshipping, however as a center of culture as well. It is an important and valuable building to be well managed. For a responsible department or institution (such as Religion or Plan Department in Indonesia), to practically manage a lot of mosques is not simple task to handle. The challenge is in relation to data number and characteristic problems tackled. Specifically for renovating and rehabilitating the damaged mosques, a decision to determine the first damaged mosque priority to be renovated and rehabilitated is problematic. Through two types of optimization method, simulated-annealing and hill-climbing, a decision support model for mosque renovation and rehabilitation was systematically constructed. The method fuzzy-logic was also operated to establish the priority of eleven selected parameters. The constructed model is able to simulate an efficiency comparison between two optimization methods used and suggest the most objective decision coming from 196 generated alternatives.

Service Level Decision-making in Rural Physiotherapy: Development of Conceptual Models.

Science.gov (United States)

Adams, Robyn; Jones, Anne; Lefmann, Sophie; Sheppard, Lorraine

2016-06-01

Understanding decision-making about health service provision is increasingly important in an environment of increasing demand and constrained resources. Multiple factors are likely to influence decisions about which services will be provided, yet workforce is the most noted factor in the rural physiotherapy literature. This paper draws together results obtained from exploration of service level decision-making (SLDM) to propose 'conceptual' models of rural physiotherapy SLDM. A prioritized qualitative approach enabled exploration of participant perspectives about rural physiotherapy decision-making. Stakeholder perspectives were obtained through surveys and in-depth interviews. Interviews were transcribed verbatim and reviewed by participants. Participant confidentiality was maintained by coding both participants and sites. A system theory-case study heuristic provided a framework for exploration across sites within the investigation area: a large area of one Australian state with a mix of regional, rural and remote communities. Thirty-nine surveys were received from participants in 11 communities. Nineteen in-depth interviews were conducted with physiotherapists and key decision-makers. Results reveal the complexity of factors influencing rural physiotherapy service provision and the value of a systems approach when exploring decision-making about rural physiotherapy service provision. Six key features were identified that formed the rural physiotherapy SLDM system: capacity and capability; contextual influences; layered decision-making; access issues; value and beliefs; and tensions and conflict. Rural physiotherapy SLDM is not a one-dimensional process but results from the complex interaction of clusters of systems issues. Decision-making about physiotherapy service provision is influenced by both internal and external factors. Similarities in influencing factors and the iterative nature of decision-making emerged, which enabled linking physiotherapy SLDM with

Decision support for life extension of technical systems through virtual age modelling

International Nuclear Information System (INIS)

Pérez Ramírez, Pedro A.; Utne, Ingrid Bouwer

2013-01-01

This article presents a virtual age model for decision support regarding life extension of ageing repairable systems. The aim of the model is to evaluate different life extension decision alternatives and their impact on the future performance of the system. The model can be applied to systems operated continuously (e.g., process systems) and systems operated on demand (e.g., safety systems). Deterioration and efficiency of imperfect maintenance is assessed when there is limited or no degradation data, and only failure and maintenance data is available. Systems that are in operation can be studied, meaning that the systems may be degraded. The current degradation is represented by a “current virtual age”, which is calculated from recorded maintenance data. The model parameters are estimated with the maximum likelihood method. A case study illustrates the application of the model for life extension of two fire water pumps in an oil and gas facility. The performance of the pump system is assessed with respect to number of failures, safety unavailability and costs during the life extension period. -- Highlights: ► Life extension assessment of technical systems using virtual age model is proposed. ► A virtual age model is generalised for systems in stand-by and continuous operation. ► The concept of current virtual age describes technical condition of the system. ► Different decision alternatives for life extension can be easily analysed. ► The decision process is improved even when only scarce failure data is available

Examining Preservice Teachers' Decision Behaviors and Individual Differences in Three Online Case-Based Approaches

Science.gov (United States)

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

This study compared the impact of three types of case-based methods (case-based reasoning, worked example, and faded worked example) on preservice teachers' (n = 71) interaction with decision tasks and whether decision related measures (task difficulty, mental effort, decision making performance) were associated with the differences in student…

Developing GIS based decision-making tools in case of radiological contamination of agricultural soil

International Nuclear Information System (INIS)

Kepka, Pavel; Brom, Jakub; Prochazka, Jan; Vincikova, Hana; Pecharova, Emilie

2010-01-01

A set of supporting tools to help take remedial decisions in case of radiological contamination of agricultural produce is being developed within the EURANOS project. The tools are created in the ArcGIS environment in the Python programming language. So far, a simple model to estimate biomass in the contaminated area has been set up. This module will make it possible to estimate additional parameters, such as activity per kg or amount of waste created, which are useful when taking decision regarding premature crops harvesting. Areas where no remedial action is required can be also identified, of course

Modeling and Analyzing Operational Decision-Making Synchronization of C2 Organization in Complex Environment

Directory of Open Access Journals (Sweden)

Zou Zhigang

2013-01-01

Full Text Available In order to improve capability of operational decision-making synchronization (ODMS in command and control (C2 organization, the paper puts forward that ODMS is the negotiation process of situation cognition with three phases about “situation cognition, situation interaction and decision-making synchronization” in complex environment, and then the model and strategies of ODMS are given in quantity. Firstly, measure indexes of three steps above are given in the paper based on the time consumed in negotiation, and three patterns are proposed for negotiating timely in high quality during situation interaction. Secondly, the ODMS model with two stages in continuous changing situation is put forward in the paper, and ODMS strategies are analyzed within environment influence and time restriction. Thirdly, simulation cases are given to validate the process of ODMS under different continuous changing situations the results of this model are better than the other previous models to fulfill the actual restrictions, and the process of ODMS can be adjusted more reasonable for improving the capability of ODMS. Then we discuss the case and summarize the influence factors of ODMS in the C2 organization as organization structure, shared information resources, negotiation patterns, and allocation of decision rights.

Dacfood: a knowledge-based system for decision support in case of radiological contamination of foodstuffs

International Nuclear Information System (INIS)

Diaz, A.; Despres, A.; Soulatges, D.

1991-01-01

In case of radiological contamination of foodstuffs, the introduction of a countermeasure has to be justified by balancing its advantages and drawbacks, as recommended by ICRP. Also, to provide authorities with information about the decision context, it has been decided to develop a Decision Support System (DSS). A knowledge-based approach is used for the DSS. Indeed, it allows: . better modelling thanks to, for instance, object oriented programming and rules, . ability to introduce more knowledge thanks to an easier consistency and validity control of the knowledge base, . handling of uncertainties (incomplete, uncertain or evolving knowledge). The present state of the system is presented. DACFOOD is a decision aiding system for contamined foodstuffs, based on a knowledge-based approach. A demonstration model has been developed in a post-Chernobyl CEC research program. It evaluates the sanitary situation, the alternative actions through costs and sanitary effects, and gives information on the decisional background

Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications

Directory of Open Access Journals (Sweden)

Kao-Yi Shen

2018-05-01

Full Text Available With the surging complexity of real-world problems in important domains such as sustainability, there is a need to leverage advanced modern computational methods or intelligent techniques to support decisions or policy-making. In this Special Issue, 15 selected and formally peer-reviewed papers contribute their novelty and findings, by applying various advanced decision methods or computational techniques to resolve different sustainability problems. Despite the innovations of the proposed models, most of the selected papers involve domain expert’s opinions and knowledge with in-depth discussions. These case studies enrich the practical contributions of this Special Issue.

Combining Bayesian Networks and Agent Based Modeling to develop a decision-support model in Vietnam

Science.gov (United States)

Nong, Bao Anh; Ertsen, Maurits; Schoups, Gerrit

2016-04-01

Complexity and uncertainty in natural resources management have been focus themes in recent years. Within these debates, with the aim to define an approach feasible for water management practice, we are developing an integrated conceptual modeling framework for simulating decision-making processes of citizens, in our case in the Day river area, Vietnam. The model combines Bayesian Networks (BNs) and Agent-Based Modeling (ABM). BNs are able to combine both qualitative data from consultants / experts / stakeholders, and quantitative data from observations on different phenomena or outcomes from other models. Further strengths of BNs are that the relationship between variables in the system is presented in a graphical interface, and that components of uncertainty are explicitly related to their probabilistic dependencies. A disadvantage is that BNs cannot easily identify the feedback of agents in the system once changes appear. Hence, ABM was adopted to represent the reaction among stakeholders under changes. The modeling framework is developed as an attempt to gain better understanding about citizen's behavior and factors influencing their decisions in order to reduce uncertainty in the implementation of water management policy.

Dual processing model of medical decision-making

Science.gov (United States)

2012-01-01

Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. Methods We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. Results We show that physician’s beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker’s threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. Conclusions We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical

Dual processing model of medical decision-making.

Science.gov (United States)

Djulbegovic, Benjamin; Hozo, Iztok; Beckstead, Jason; Tsalatsanis, Athanasios; Pauker, Stephen G

2012-09-03

Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. We show that physician's beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker's threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical decision-making field, which is still to the

Decisions at hand: a decision support system on handhelds.

Science.gov (United States)

Zupan, B; Porenta, A; Vidmar, G; Aoki, N; Bratko, I; Beck, J R

2001-01-01

One of the applications of clinical information systems is decision support. Although the advantages of utilizing such aids have never been theoretically disputed, they have been rarely used in practice. The factor that probably often limits the utility of clinical decision support systems is the need for computing power at the very site of decision making--at the place where the patient is interviewed, in discussion rooms, etc. The paper reports on a possible solution to this problem. A decision-support shell LogReg is presented, which runs on a handheld computer. A general schema for handheld-based decision support is also proposed, where decision models are developed on personal computers/workstations, encoded in XML and then transferred to handhelds, where the models are used within a decision support shell. A use case where LogReg has been applied to clinical outcome prediction in crush injury is presented.

Child Protection Decision Making: A Factorial Analysis Using Case Vignettes

Science.gov (United States)

Stokes, Jacqueline; Schmidt, Glen

2012-01-01

This study explored decision making by child protection social workers in the province of British Columbia, Canada. A factorial survey method was used in which case vignettes were constructed by randomly assigning a number of key characteristics associated with decision making in child protection. Child protection social workers (n = 118) assessed…

Modular Architecture for Integrated Model-Based Decision Support.

Science.gov (United States)

Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen

2018-01-01

Model-based decision support systems promise to be a valuable addition to oncological treatments and the implementation of personalized therapies. For the integration and sharing of decision models, the involved systems must be able to communicate with each other. In this paper, we propose a modularized architecture of dedicated systems for the integration of probabilistic decision models into existing hospital environments. These systems interconnect via web services and provide model sharing and processing capabilities for clinical information systems. Along the lines of IHE integration profiles from other disciplines and the meaningful reuse of routinely recorded patient data, our approach aims for the seamless integration of decision models into hospital infrastructure and the physicians' daily work.

The Judge’s Progressive Decisions in Civil Law Cases (An Analysis on “the Case of Mango Tree”

Directory of Open Access Journals (Sweden)

Suwito

2015-04-01

Full Text Available The idea of a progressive law arbitrate by placing the concept of law as an instrument in achieving social goals. This idea also emphasizes the discovery of the laws in each judge’s decision as an attempt to explore the values that live in the community. This progressive legal thought has been applied in several decisions of judges in Indonesia. One is in the civil case, known as “The Case of Mango Tree” which occurred in the jurisdiction of the Jayapura District Court. The aim in this study was intended to examine the normative juridical one court decision in a civil case based progressive law. The method used is a normative approach to the court decision as a primary legal materials. The results showed that there is a judicial consideration of progressive law judge based on the decision of the court, where the judge has successfully completed the legal issues, including complicated and abstract categories. The conclusion of this cases shows that every legal issue can be resolved without having to override the rules by sticking fast to the rules to achieve a sense of justice, expediency and the rule of law as a hallmark of progressive laws.

Integrating decision management with UML modeling concepts and tools

DEFF Research Database (Denmark)

Könemann, Patrick

2009-01-01

, but also for guiding the user by proposing subsequent decisions. In model-based software development, many decisions directly affect the structural and behavioral models used to describe and develop a software system and its architecture. However, the decisions are typically not connected to these models...... of formerly disconnected tools could improve tool usability as well as decision maker productivity....

A diffusion decision model analysis of evidence variability in the lexical decision task.

Science.gov (United States)

Tillman, Gabriel; Osth, Adam F; van Ravenzwaaij, Don; Heathcote, Andrew

2017-12-01

The lexical-decision task is among the most commonly used paradigms in psycholinguistics. In both the signal-detection theory and Diffusion Decision Model (DDM; Ratcliff, Gomez, & McKoon, Psychological Review, 111, 159-182, 2004) frameworks, lexical-decisions are based on a continuous source of word-likeness evidence for both words and non-words. The Retrieving Effectively from Memory model of Lexical-Decision (REM-LD; Wagenmakers et al., Cognitive Psychology, 48(3), 332-367, 2004) provides a comprehensive explanation of lexical-decision data and makes the prediction that word-likeness evidence is more variable for words than non-words and that higher frequency words are more variable than lower frequency words. To test these predictions, we analyzed five lexical-decision data sets with the DDM. For all data sets, drift-rate variability changed across word frequency and non-word conditions. For the most part, REM-LD's predictions about the ordering of evidence variability across stimuli in the lexical-decision task were confirmed.

Disability Case Review of Administrative Law Judge Hearing Decisions

Data.gov (United States)

Social Security Administration — The Disability Case Review is a post-effectuation quality review of administrative law judge (ALJ) disability hearing decisions. This dataset includes results from...

Human-centric decision-making models for social sciences

CERN Document Server

Pedrycz, Witold

2014-01-01

The volume delivers a wealth of effective methods to deal with various types of uncertainty inherently existing in human-centric decision problems. It elaborates on  comprehensive decision frameworks to handle different decision scenarios, which help use effectively the explicit and tacit knowledge and intuition, model perceptions and preferences in a more human-oriented style. The book presents original approaches and delivers new results on fundamentals and applications related to human-centered decision making approaches to business, economics and social systems. Individual chapters cover multi-criteria (multiattribute) decision making, decision making with prospect theory, decision making with incomplete probabilistic information, granular models of decision making and decision making realized with the use of non-additive measures. New emerging decision theories being presented as along with a wide spectrum of ongoing research make the book valuable to all interested in the field of advanced decision-mak...

MARKET EVALUATION MODEL: TOOL FORBUSINESS DECISIONS

OpenAIRE

Porlles Loarte, José; Yenque Dedios, Julio; Lavado Soto, Aurelio

2014-01-01

In the present work the concepts of potential market and global market are analyzed as the basis for strategic decisions of market with long term perspectives, when the implantation of a business in certain geographic area is evaluated. On this conceptual frame, the methodological tool is proposed to evaluate a commercial decision, for which it is taken as reference the case from the brewing industry in Peru, considering that this industry faces in the region entrepreneurial reorderings withi...

Case-based ethics instruction: the influence of contextual and individual factors in case content on ethical decision-making.

Science.gov (United States)

Bagdasarov, Zhanna; Thiel, Chase E; Johnson, James F; Connelly, Shane; Harkrider, Lauren N; Devenport, Lynn D; Mumford, Michael D

2013-09-01

Cases have been employed across multiple disciplines, including ethics education, as effective pedagogical tools. However, the benefit of case-based learning in the ethics domain varies across cases, suggesting that not all cases are equal in terms of pedagogical value. Indeed, case content appears to influence the extent to which cases promote learning and transfer. Consistent with this argument, the current study explored the influences of contextual and personal factors embedded in case content on ethical decision-making. Cases were manipulated to include a clear description of the social context and the goals of the characters involved. Results indicated that social context, specifically the description of an autonomy-supportive environment, facilitated execution of sense making processes and resulted in greater decision ethicality. Implications for designing optimal cases and case-based training programs are discussed.

Arational heuristic model of economic decision making

OpenAIRE

Grandori, Anna

2010-01-01

The article discuss the limits of both the rational actor and the behavioral paradigms in explaining and guiding innovative decision making and outlines a model of economic decision making that in the course of being 'heuristic' (research and discovery oriented) is also 'rational' (in the broad sense of following correct reasoning and scientific methods, non 'biasing'). The model specifies a set of 'rational heuristics' for innovative decision making, for the various sub-processes of problem ...

Abstraction of an Affective-Cognitive Decision Making Model Based on Simulated Behaviour and Perception Chains

Science.gov (United States)

Sharpanskykh, Alexei; Treur, Jan

Employing rich internal agent models of actors in large-scale socio-technical systems often results in scalability issues. The problem addressed in this paper is how to improve computational properties of a complex internal agent model, while preserving its behavioral properties. The problem is addressed for the case of an existing affective-cognitive decision making model instantiated for an emergency scenario. For this internal decision model an abstracted behavioral agent model is obtained, which ensures a substantial increase of the computational efficiency at the cost of approximately 1% behavioural error. The abstraction technique used can be applied to a wide range of internal agent models with loops, for example, involving mutual affective-cognitive interactions.

Ethical Decision Making

DEFF Research Database (Denmark)

Lauesen, Linne Marie

2012-01-01

of the interaction between a corporation and its stakeholders. Methodology/approach: This paper offers a theoretical 'Organic Stakeholder Model' based on decision making theory, risk assessment and adaption to a rapidly changing world combined with appropriate stakeholder theory for ethical purposes in decision...... applicable): The Model is based on case studies, but the limited scope of the length of the paper did not leave room to show the empirical evidence, but only the theoretical study. Originality / value of a paper: The model offers a new way of combining risk management with ethical decision-making processes...... by the inclusion of multiple stakeholders. The conceptualization of the model enhances business ethics in decision making by managing and balancing stakeholder concerns with the same concerns as the traditional risk management models does – for the sake of the wider social responsibilities of the businesses...

Handbook of Marketing Decision Models

NARCIS (Netherlands)

B. Wierenga (Berend)

2008-01-01

textabstractThis book presents the state of the art in marketing decision models, dealing with new modeling areas such as customer relationship management, customer value and online marketing, but also describes recent developments in other areas. In the category of marketing mix models, the latest

Subjective Expected Utility: A Model of Decision-Making.

Science.gov (United States)

Fischoff, Baruch; And Others

1981-01-01

Outlines a model of decision making known to researchers in the field of behavioral decision theory (BDT) as subjective expected utility (SEU). The descriptive and predictive validity of the SEU model, probability and values assessment using SEU, and decision contexts are examined, and a 54-item reference list is provided. (JL)

Does decision documentation help junior designers rationalize their decisions? A comparative multiple-case study

NARCIS (Netherlands)

Heesch, U. van; Avgeriou, P.; Tang, A.

Software architecture design is challenging, especially for junior software designers. Lacking practice and experience, junior designers need process support in order to make rational architecture decisions. In this paper, we present the results of a comparative multiple-case study conducted to find

Channels of social influence for decision making in restaurants: A case study

Directory of Open Access Journals (Sweden)

M. Romero-Charneco

2018-05-01

Full Text Available Consumers use the Internet to obtain information on tourism products and services. When evaluating the alternatives, they are faced with a large volume of information that makes their purchasing decision difficult. In this context, the generalized use of mobile instant messaging (MIM has led to the implementation of chatbots in these channels, to help to plan the purchase. This research explores restaurant selection through a WhatsApp mobile instant messaging (MIM chatbot. A study is made of the channels consulted by travellers on Web 2.0 as well as the search models and restaurant selection processes, and a case study is presented. The results allow the diagnosis of the main criteria of user behaviour in this type of conversational interface in the decision-making process related to gastronomic consumption.

A diffusion decision model analysis of evidence variability in the lexical decision task

NARCIS (Netherlands)

Tillman, Gabriel; Osth, Adam F.; van Ravenzwaaij, Don; Heathcote, Andrew

2017-01-01

The lexical-decision task is among the most commonly used paradigms in psycholinguistics. In both the signal-detection theory and Diffusion Decision Model (DDM; Ratcliff, Gomez, & McKoon, Psychological Review, 111, 159–182, 2004) frameworks, lexical-decisions are based on a continuous source of

Evidence accumulation in decision making: unifying the "take the best" and the "rational" models.

Science.gov (United States)

Lee, Michael D; Cummins, Tarrant D R

2004-04-01

An evidence accumulation model of forced-choice decision making is proposed to unify the fast and frugal take the best (TTB) model and the alternative rational (RAT) model with which it is usually contrasted. The basic idea is to treat the TTB model as a sequential-sampling process that terminates as soon as any evidence in favor of a decision is found and the rational approach as a sequential-sampling process that terminates only when all available information has been assessed. The unified TTB and RAT models were tested in an experiment in which participants learned to make correct judgments for a set of real-world stimuli on the basis of feedback, and were then asked to make additional judgments without feedback for cases in which the TTB and the rational models made different predictions. The results show that, in both experiments, there was strong intraparticipant consistency in the use of either the TTB or the rational model but large interparticipant differences in which model was used. The unified model is shown to be able to capture the differences in decision making across participants in an interpretable way and is preferred by the minimum description length model selection criterion.

Dual processing model of medical decision-making

Directory of Open Access Journals (Sweden)

Djulbegovic Benjamin

2012-09-01

Full Text Available Abstract Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I and/or an analytical, deliberative (system II processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. Methods We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. Results We show that physician’s beliefs about whether to treat at higher (lower probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker’s threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. Conclusions We have developed the first dual processing model of medical decision-making that has potential to

Perspective on safety case to support a possible site recommendation decision

International Nuclear Information System (INIS)

Gil, A.V.; Gamble, R.P.

2002-01-01

The mission of the US Department of Energy (DOE) is to provide the basis for a national decision regarding the development of a geological repository for spent nuclear fuel and high-level radioactive waste at the Yucca Mountain site in Nevada. There are a number of steps in the decision process defined by US law that must be completed prior to development of a repository at this site. The DOE's focus is currently on the first two steps in this process: characterization of the site to support a determination by the DOE on whether the site is suitable for a geologic repository and a decision by the Secretary of Energy (the Secretary) on whether to recommend to the President that the site be approved for a repository. To enhance the confidence of multiple audiences in the basis for these actions, and to provide a basis for subsequent action by the President and the US Congress, information supporting the decision process must include the elements of a safety case consistent with the statutory and regulatory framework for these decisions. The idea of a safety case is to broaden the basis for confidence by decision-makers and the public in conclusions about safety. A safety case should cite multiple lines of evidence, or reasoning, beyond the results of a safety assessment to support the demonstration of safety, which includes compliance with applicable safety criteria. The multiple lines of evidence should show the basis for confidence in safety. To be most effective, such evidence requires information not directly used in the safety assessment. (author)

Cognitive processes, models and metaphors in decision research

Directory of Open Access Journals (Sweden)

Ben Newell

2008-03-01

Full Text Available Decision research in psychology has traditionally been influenced by the extit{homo oeconomicus} metaphor with its emphasis on normative models and deviations from the predictions of those models. In contrast, the principal metaphor of cognitive psychology conceptualizes humans as `information processors', employing processes of perception, memory, categorization, problem solving and so on. Many of the processes described in cognitive theories are similar to those involved in decision making, and thus increasing cross-fertilization between the two areas is an important endeavour. A wide range of models and metaphors has been proposed to explain and describe `information processing' and many models have been applied to decision making in ingenious ways. This special issue encourages cross-fertilization between cognitive psychology and decision research by providing an overview of current perspectives in one area that continues to highlight the benefits of the synergistic approach: cognitive modeling of multi-attribute decision making. In this introduction we discuss aspects of the cognitive system that need to be considered when modeling multi-attribute decision making (e.g., automatic versus controlled processing, learning and memory constraints, metacognition and illustrate how such aspects are incorporated into the approaches proposed by contributors to the special issue. We end by discussing the challenges posed by the contrasting and sometimes incompatible assumptions of the models and metaphors.

Models of sequential decision making in consumer lending

OpenAIRE

Kanshukan Rajaratnam; Peter A. Beling; George A. Overstreet

2016-01-01

Abstract In this paper, we introduce models of sequential decision making in consumer lending. From the definition of adverse selection in static lending models, we show that homogenous borrowers take-up offers at different instances of time when faced with a sequence of loan offers. We postulate that bounded rationality and diverse decision heuristics used by consumers drive the decisions they make about credit offers. Under that postulate, we show how observation of early decisions in a seq...

Multi-objective decision-making model based on CBM for an aircraft fleet

Science.gov (United States)

Luo, Bin; Lin, Lin

2018-04-01

Modern production management patterns, in which multi-unit (e.g., a fleet of aircrafts) are managed in a holistic manner, have brought new challenges for multi-unit maintenance decision making. To schedule a good maintenance plan, not only does the individual machine maintenance have to be considered, but also the maintenance of the other individuals have to be taken into account. Since most condition-based maintenance researches for aircraft focused on solely reducing maintenance cost or maximizing the availability of single aircraft, as well as considering that seldom researches concentrated on both the two objectives: minimizing cost and maximizing the availability of a fleet (total number of available aircraft in fleet), a multi-objective decision-making model based on condition-based maintenance concentrated both on the above two objectives is established. Furthermore, in consideration of the decision maker may prefer providing the final optimal result in the form of discrete intervals instead of a set of points (non-dominated solutions) in real decision-making problem, a novel multi-objective optimization method based on support vector regression is proposed to solve the above multi-objective decision-making model. Finally, a case study regarding a fleet is conducted, with the results proving that the approach efficiently generates outcomes that meet the schedule requirements.

Making the case for evidence-based design in healthcare: a descriptive case study of organizational decision making.

Science.gov (United States)

Shoemaker, Lorie K; Kazley, Abby Swanson; White, Andrea

2010-01-01

The aim of this study was to describe the organizational decision-making process used in the selection of evidence-based design (EBD) concepts, the criteria used to make these decisions, and the extent to which leadership style may have influenced the decision-making process. Five research questions were formulated to frame the direction of this study, including: (1) How did healthcare leaders learn of innovations in design? (2) How did healthcare leaders make decisions in the selection of healthcare design concepts? (3) What criteria did healthcare leaders use in the decision-making process? (4) How did healthcare leaders consider input from the staff in design decisions? and (5) To what extent did the leadership style of administrators affect the outcomes of the decision-making process? Current issues affecting healthcare in the community led the principal investigator's organization to undertake an ambitious facilities expansion project. As part of its planning process, the organization learned of EBD principles that seemingly had a positive impact on patient care and safety and staff working conditions. Although promising, a paucity of empirical research addressed the cost/benefit of incorporating many EBD concepts into one hospital setting, and there was no research that articulated the organizational decision-making process used by healthcare administrators when considering the use of EBD in expansion projects. A mixed-method, descriptive, qualitative, single-case study and quantitative design were used to address the five research questions. The Systems Research Organizing Model provided the theoretical framework. A variety of data collection methods was used, including interviews of key respondents, the review of documentary evidence, and the Multifactor Leadership Questionnaire. A participatory process was used throughout the design decision phases, involving staff at all levels of the organization. The Internet and architects facilitated learning about

Model For Marketing Strategy Decision Based On Multicriteria Decicion Making: A Case Study In Batik Madura Industry

Science.gov (United States)

Anna, I. D.; Cahyadi, I.; Yakin, A.

2018-01-01

Selection of marketing strategy is a prominent competitive advantage for small and medium enterprises business development. The selection process is is a multiple criteria decision-making problem, which includes evaluation of various attributes or criteria in a process of strategy formulation. The objective of this paper is to develop a model for the selection of a marketing strategy in Batik Madura industry. The current study proposes an integrated approach based on analytic network process (ANP) and technique for order preference by similarity to ideal solution (TOPSIS) to determine the best strategy for Batik Madura marketing problems. Based on the results of group decision-making technique, this study selected fourteen criteria, including consistency, cost, trend following, customer loyalty, business volume, uniqueness manpower, customer numbers, promotion, branding, bussiness network, outlet location, credibility and the inovation as Batik Madura marketing strategy evaluation criteria. A survey questionnaire developed from literature review was distributed to a sample frame of Batik Madura SMEs in Pamekasan. In the decision procedure step, expert evaluators were asked to establish the decision matrix by comparing the marketing strategy alternatives under each of the individual criteria. Then, considerations obtained from ANP and TOPSIS methods were applied to build the specific criteria constraints and range of the launch strategy in the model. The model in this study demonstrates that, under current business situation, Straight-focus marketing strategy is the best marketing strategy for Batik Madura SMEs in Pamekasan.

Emergent collective decision-making: Control, model and behavior

Science.gov (United States)

Shen, Tian

In this dissertation we study emergent collective decision-making in social groups with time-varying interactions and heterogeneously informed individuals. First we analyze a nonlinear dynamical systems model motivated by animal collective motion with heterogeneously informed subpopulations, to examine the role of uninformed individuals. We find through formal analysis that adding uninformed individuals in a group increases the likelihood of a collective decision. Secondly, we propose a model for human shared decision-making with continuous-time feedback and where individuals have little information about the true preferences of other group members. We study model equilibria using bifurcation analysis to understand how the model predicts decisions based on the critical threshold parameters that represent an individual's tradeoff between social and environmental influences. Thirdly, we analyze continuous-time data of pairs of human subjects performing an experimental shared tracking task using our second proposed model in order to understand transient behavior and the decision-making process. We fit the model to data and show that it reproduces a wide range of human behaviors surprisingly well, suggesting that the model may have captured the mechanisms of observed behaviors. Finally, we study human behavior from a game-theoretic perspective by modeling the aforementioned tracking task as a repeated game with incomplete information. We show that the majority of the players are able to converge to playing Nash equilibrium strategies. We then suggest with simulations that the mean field evolution of strategies in the population resemble replicator dynamics, indicating that the individual strategies may be myopic. Decisions form the basis of control and problems involving deciding collectively between alternatives are ubiquitous in nature and in engineering. Understanding how multi-agent systems make decisions among alternatives also provides insight for designing

Reviewing model application to support animal health decision making.

Science.gov (United States)

Singer, Alexander; Salman, Mo; Thulke, Hans-Hermann

2011-04-01

Animal health is of societal importance as it affects human welfare, and anthropogenic interests shape decision making to assure animal health. Scientific advice to support decision making is manifold. Modelling, as one piece of the scientific toolbox, is appreciated for its ability to describe and structure data, to give insight in complex processes and to predict future outcome. In this paper we study the application of scientific modelling to support practical animal health decisions. We reviewed the 35 animal health related scientific opinions adopted by the Animal Health and Animal Welfare Panel of the European Food Safety Authority (EFSA). Thirteen of these documents were based on the application of models. The review took two viewpoints, the decision maker's need and the modeller's approach. In the reviewed material three types of modelling questions were addressed by four specific model types. The correspondence between tasks and models underpinned the importance of the modelling question in triggering the modelling approach. End point quantifications were the dominating request from decision makers, implying that prediction of risk is a major need. However, due to knowledge gaps corresponding modelling studies often shed away from providing exact numbers. Instead, comparative scenario analyses were performed, furthering the understanding of the decision problem and effects of alternative management options. In conclusion, the most adequate scientific support for decision making - including available modelling capacity - might be expected if the required advice is clearly stated. Copyright © 2011 Elsevier B.V. All rights reserved.

A decision support model for reducing electric energy consumption in elementary school facilities

International Nuclear Information System (INIS)

Hong, Taehoon; Koo, Choongwan; Jeong, Kwangbok

2012-01-01

Highlights: ► Decision support model is developed to reduce CO 2 emission in elementary schools. ► The model can select the school to be the most effective in energy savings. ► Decision tree improved the prediction accuracy by 1.83–3.88%. ► Using the model, decision-maker can save the electric-energy consumption by 16.58%. ► The model can make the educational-facility improvement program more effective. -- Abstract: The South Korean government has been actively promoting an educational-facility improvement program as part of its energy-saving efforts. This research seeks to develop a decision support model for selecting the facility expected to be effective in generating energy savings and making the facility improvement program more effective. In this research, project characteristics and electric-energy consumption data for the year 2009 were collected from 6282 elementary schools located in seven metropolitan cities in South Korea. In this research, the following were carried out: (i) a group of educational facilities was established based on electric-energy consumption, using a decision tree; (ii) a number of similar projects were retrieved from the same group of facilities, using case-based reasoning; and (iii) the accuracy of prediction was improved, using the combination of genetic algorithms, the artificial neural network, and multiple regression analysis. The results of this research can be useful for the following purposes: (i) preliminary research on the systematic and continuous management of educational facilities’ electric-energy consumption; (ii) basic research on electric-energy consumption prediction based on the project characteristics; and (iii) practical research for selecting an optimum facility that can more effectively apply an educational-facility improvement program as a decision support model.

The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks

OpenAIRE

Ratcliff, Roger; McKoon, Gail

2008-01-01

The diffusion decision model allows detailed explanations of behavior in two-choice discrimination tasks. In this article, the model is reviewed to show how it translates behavioral data—accuracy, mean response times, and response time distributions—into components of cognitive processing. Three experiments are used to illustrate experimental manipulations of three components: stimulus difficulty affects the quality of information on which a decision is based; instructions emphasizing either ...

Seven business models for decision management

NARCIS (Netherlands)

dr. Martijn Zoet; Eline de Haan; Koen Smit

2016-01-01

Research, advisory companies, consultants and system integrators all predict that a lot of money will be earned with decision management (business rules, algorithms and analytics). But how can you actually make money with decision management or in other words: Which business models are exactly

A generic methodology for developing fuzzy decision models

NARCIS (Netherlands)

Bosma, R.H.; Berg, van den J.; Kaymak, Uzay; Udo, H.M.J.; Verreth, J.A.J.

2012-01-01

An important paradigm in decision-making models is utility-maximization where most models do not include actors’ motives. Fuzzy set theory on the other hand offers a method to simulate human decision-making. However, the literature describing expert-driven fuzzy logic models, rarely gives precise

A hierarchical Markov decision process modeling feeding and marketing decisions of growing pigs

DEFF Research Database (Denmark)

Pourmoayed, Reza; Nielsen, Lars Relund; Kristensen, Anders Ringgaard

2016-01-01

Feeding is the most important cost in the production of growing pigs and has a direct impact on the marketing decisions, growth and the final quality of the meat. In this paper, we address the sequential decision problem of when to change the feed-mix within a finisher pig pen and when to pick pigs...... for marketing. We formulate a hierarchical Markov decision process with three levels representing the decision process. The model considers decisions related to feeding and marketing and finds the optimal decision given the current state of the pen. The state of the system is based on information from on...

Dissolving decision making? : Models and their roles in decision-making processes and policy at large

NARCIS (Netherlands)

Zeiss, Ragna; van Egmond, S.

2014-01-01

This article studies the roles three science-based models play in Dutch policy and decision making processes. Key is the interaction between model construction and environment. Their political and scientific environments form contexts that shape the roles of models in policy decision making.

Evolution of quantum-like modeling in decision making processes

Energy Technology Data Exchange (ETDEWEB)

Khrennikova, Polina [School of Management, University of Leicester, University Road Leicester LE1 7RH (United Kingdom)

2012-12-18

The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schroedinger equation to describe the evolution of people's mental states. A shortcoming of Schroedinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.

Evolution of quantum-like modeling in decision making processes

Science.gov (United States)

Khrennikova, Polina

2012-12-01

The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schrödinger equation to describe the evolution of people's mental states. A shortcoming of Schrödinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.

Evolution of quantum-like modeling in decision making processes

International Nuclear Information System (INIS)

Khrennikova, Polina

2012-01-01

The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schrödinger equation to describe the evolution of people's mental states. A shortcoming of Schrödinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.

Comparing the Applicability of Commonly Used Hydrological Ecosystem Services Models for Integrated Decision-Support

Directory of Open Access Journals (Sweden)

Anna Lüke

2018-01-01

Full Text Available Different simulation models are used in science and practice in order to incorporate hydrological ecosystem services in decision-making processes. This contribution compares three simulation models, the Soil and Water Assessment Tool, a traditional hydrological model and two ecosystem services models, the Integrated Valuation of Ecosystem Services and Trade-offs model and the Resource Investment Optimization System model. The three models are compared on a theoretical and conceptual basis as well in a comparative case study application. The application of the models to a study area in Nicaragua reveals that a practical benefit to apply these models for different questions in decision-making generally exists. However, modelling of hydrological ecosystem services is associated with a high application effort and requires input data that may not always be available. The degree of detail in temporal and spatial variability in ecosystem service provision is higher when using the Soil and Water Assessment Tool compared to the two ecosystem service models. In contrast, the ecosystem service models have lower requirements on input data and process knowledge. A relationship between service provision and beneficiaries is readily produced and can be visualized as a model output. The visualization is especially useful for a practical decision-making context.

Multi-level decision making models, methods and applications

CERN Document Server

Zhang, Guangquan; Gao, Ya

2015-01-01

This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.  

A Representation for Gaining Insight into Clinical Decision Models

Science.gov (United States)

Jimison, Holly B.

1988-01-01

For many medical domains uncertainty and patient preferences are important components of decision making. Decision theory is useful as a representation for such medical models in computer decision aids, but the methodology has typically had poor performance in the areas of explanation and user interface. The additional representation of probabilities and utilities as random variables serves to provide a framework for graphical and text insight into complicated decision models. The approach allows for efficient customization of a generic model that describes the general patient population of interest to a patient- specific model. Monte Carlo simulation is used to calculate the expected value of information and sensitivity for each model variable, thus providing a metric for deciding what to emphasize in the graphics and text summary. The computer-generated explanation includes variables that are sensitive with respect to the decision or that deviate significantly from what is typically observed. These techniques serve to keep the assessment and explanation of the patient's decision model concise, allowing the user to focus on the most important aspects for that patient.

Integrating a Decision Management Tool with UML Modeling Tools

DEFF Research Database (Denmark)

Könemann, Patrick

by proposing potential subsequent design issues. In model-based software development, many decisions directly affect the structural and behavioral models used to describe and develop a software system and its architecture. However, these decisions are typically not connected to the models created during...... integration of formerly disconnected tools improves tool usability as well as decision maker productivity....

Generative Agents for Player Decision Modeling in Games

DEFF Research Database (Denmark)

Holmgård, Christoffer; Liapis, Antonios; Togelius, Julian

2014-01-01

This paper presents a method for modeling player decision making through the use of agents as AI-driven personas. The paper argues that artificial agents, as generative player models, have properties that allow them to be used as psyhometrically valid, abstract simulations of a human player......’s internal decision making processes. Such agents can then be used to interpret human decision making, as personas and playtesting tools in the game design process, as baselines for adapting agents to mimic classes of human players, or as believable, human-like opponents. This argument is explored...... in a crowdsourced decision making experiment, in which the decisions of human players are recorded in a small-scale dungeon themed puzzle game. Human decisions are compared to the decisions of a number of a priori defined “archetypical” agent-personas, and the humans are characterized by their likeness...

Joint perceptual decision-making: A case study in explanatory pluralism

DEFF Research Database (Denmark)

Abney, Drew; Dale, Rick; Yoshimi, Jeffrey

2014-01-01

and spatial scales, using appropriate methodological tools. Explanatory pluralism has been often described abstractly, but has rarely been applied to concrete cases. We present a case study of explanatory pluralism. We discuss three separate ways of studying the same phenomenon: a perceptual decision- making...... task (Bahrami et al., 2010), where pairs of subjects share information to jointly individuate an oddball stimulus among a set of distractors. Each approach analyzed the same corpus but targeted different units of analysis at different levels of description: decision-making at the behavioral level......, confidence sharing at the linguistic level, and acoustic energy at the physical level. We discuss the utility of explanatory pluralism for describing this complex, multiscale phenomenon, show ways in which this case study sheds new light on the concept of pluralism, and highlight good practices to critically...

Pharmaceutical expenditure forecast model to support health policy decision making.

Science.gov (United States)

Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

2014-01-01

With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project 'European Union (EU) Pharmaceutical expenditure forecast' - http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). A model was built to assess policy scenarios' impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate, and distribution. Reducing, even slightly, the prices of

Conflict of interest in Health Technology Assessment decisions: case law in France and impact on reimbursement decisions.

Science.gov (United States)

Frybourg, Sandrine; Remuzat, Cécile; Kornfeld, Åsa; Toumi, Mondher

2015-01-01

The slow reaction of French authorities to the so-called Mediator® saga in 2009 in France led to investigations that questioned the way conflicts of interest are reported. France implemented the Loi Bertrand ('Bertrand Law') in May 2013, known as the 'French Sunshine Act', with the aim of specifying the scope of disclosure obligations. This policy research reviewed the Loi Bertrand and reported case law from the French Council of State (COS) related to conflicts of interest in French Health technology assessment (HTA) opinion. The Loi Bertrand requires the publication of most of the agreements concluded between health-care professionals and companies and covers a vast range of health products. Commercial sales agreements of goods and services concluded between manufacturers and health-care professionals are a strong exception to this disclosure obligation. Six cases examined by the COS were analyzed, most of them related to the publication of guidelines or the removal of products from the list of reimbursed drugs and devices. These cases have been reviewed, as well as the impact of the ruling on reimbursement decisions. Four cases led to suspension or invalidation of decisions based on the Haute Autorité de Santé (HAS) recommendations due to conflicts of interest. In the two other cases, the HAS provided post hoc declarations of interest when required by the COS, and the COS considered the conflicts of interest as irrelevant for the decision. It appears that the COS based its decisions on two main criteria: the acknowledgement of negative conflicts of interest (a link with competitors) and the absence of declarations of conflicts of interest, which have to be presented when required by legal authorities irrespective of when they were completed (even posterior to the HAS opinion). However, the number of cases that have been decided against the HAS remains very limited with respect to the volume of assessments performed yearly. The strengthening of the regulation

Climate change decision-making: Model & parameter uncertainties explored

Energy Technology Data Exchange (ETDEWEB)

Dowlatabadi, H.; Kandlikar, M.; Linville, C.

1995-12-31

A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to inform decision makers about the likely outcome of policy initiatives, and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.1. This model includes representation of the processes of demographics, economic activity, emissions, atmospheric chemistry, climate and sea level change and impacts from these changes and policies for emissions mitigation, and adaptation to change. The model has over 800 objects of which about one half are used to represent uncertainty. In this paper we show, that when considering parameter uncertainties, the relative contribution of climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. When considering model structure uncertainties we find that the choice of policy is often dominated by model structure choice, rather than parameter uncertainties.

Modeling Adversaries in Counterterrorism Decisions Using Prospect Theory.

Science.gov (United States)

Merrick, Jason R W; Leclerc, Philip

2016-04-01

Counterterrorism decisions have been an intense area of research in recent years. Both decision analysis and game theory have been used to model such decisions, and more recently approaches have been developed that combine the techniques of the two disciplines. However, each of these approaches assumes that the attacker is maximizing its utility. Experimental research shows that human beings do not make decisions by maximizing expected utility without aid, but instead deviate in specific ways such as loss aversion or likelihood insensitivity. In this article, we modify existing methods for counterterrorism decisions. We keep expected utility as the defender's paradigm to seek for the rational decision, but we use prospect theory to solve for the attacker's decision to descriptively model the attacker's loss aversion and likelihood insensitivity. We study the effects of this approach in a critical decision, whether to screen containers entering the United States for radioactive materials. We find that the defender's optimal decision is sensitive to the attacker's levels of loss aversion and likelihood insensitivity, meaning that understanding such descriptive decision effects is important in making such decisions. © 2014 Society for Risk Analysis.

Economic decision-models for climate adaptation: a survey; Ekonomiska verktyg som beslutsstoed i klimatanpassningsarbetet: en metodoeversikt

Energy Technology Data Exchange (ETDEWEB)

Kaagebro, Elin; Vredin Johansson, Maria

2008-05-15

Several of the adaptations to the climate change we are about to experience will occur successively and voluntarily in response to the climate change experienced. In many cases these adaptations will work perfectly but, for investments and activities with relatively long life-times (say more than 25 years) and for investments and activities that are sensitive to climate extremes, climate change requires increased planning and foresight. In these situations economic decision models can aid the decision-makers through providing well-founded bases for the decisions, as well as tools for prioritizations. In this report we describe the most common economic decision-models: cost-benefit analysis (CBA), cost-effectiveness analysis (CEA) and multi-criteria analysis (MCA). The descriptions will form a foundation for the continuing work on generating tools that can be useful for local decision-makers in their pursuit of coping with climate change within the Climatools programme

Decision Making under Uncertainty: A Neural Model based on Partially Observable Markov Decision Processes

Directory of Open Access Journals (Sweden)

Rajesh P N Rao

2010-11-01

Full Text Available A fundamental problem faced by animals is learning to select actions based on noisy sensory information and incomplete knowledge of the world. It has been suggested that the brain engages in Bayesian inference during perception but how such probabilistic representations are used to select actions has remained unclear. Here we propose a neural model of action selection and decision making based on the theory of partially observable Markov decision processes (POMDPs. Actions are selected based not on a single optimal estimate of state but on the posterior distribution over states (the belief state. We show how such a model provides a unified framework for explaining experimental results in decision making that involve both information gathering and overt actions. The model utilizes temporal difference (TD learning for maximizing expected reward. The resulting neural architecture posits an active role for the neocortex in belief computation while ascribing a role to the basal ganglia in belief representation, value computation, and action selection. When applied to the random dots motion discrimination task, model neurons representing belief exhibit responses similar to those of LIP neurons in primate neocortex. The appropriate threshold for switching from information gathering to overt actions emerges naturally during reward maximization. Additionally, the time course of reward prediction error in the model shares similarities with dopaminergic responses in the basal ganglia during the random dots task. For tasks with a deadline, the model learns a decision making strategy that changes with elapsed time, predicting a collapsing decision threshold consistent with some experimental studies. The model provides a new framework for understanding neural decision making and suggests an important role for interactions between the neocortex and the basal ganglia in learning the mapping between probabilistic sensory representations and actions that maximize

Pre-planned versus unplanned decision making in the case of environmental decontamination

International Nuclear Information System (INIS)

Paschoa, A.S.; Tranjan Filho, A.

2000-01-01

Until a few years ago it was not usual to pre-plan realistic countermeasures directly related to a radiological emergency or a nuclear accident (RENA), mostly because the probability of occurrence of such events was considered to be too low for real concern. The Three Mile Island, Chernobyl and Goiania accidents, however, changed long accepted views of the decision making community throughout the world. Today, meetings are being held just to discuss how one can go about making decisions to face the problems that may occur in a number of RENAs. The present work will examine several well established scientifically based radiological criteria to be used in decision making processes concerning either radioactive decontamination following a severe RENA, or decommissioning procedures. Such criteria can certainly be used to select pre-planned countermeasures, but can also be helpful as guidance to decision makers when facing a choice of untested and unplanned options. Selected advantages and disadvantages of each criterion based option will be presented and briefly discussed, as, for example, the amount of radioactive waste produced vis-B-vis the risk (concentration or projected dose) level adopted in the decontamination procedures. In addition, non-scientific aspects will be brought into the discussion, because their social, economical, and political implications cannot be ignored by responsible decision makers. Uncertainties associated with both non-scientific aspects and scientifically based environmental and dosimetric models will also be examined for specific cases. (author)

Safety assessment of dangerous goods transport enterprise based on the relative entropy aggregation in group decision making model.

Science.gov (United States)

Wu, Jun; Li, Chengbing; Huo, Yueying

2014-01-01

Safety of dangerous goods transport is directly related to the operation safety of dangerous goods transport enterprise. Aiming at the problem of the high accident rate and large harm in dangerous goods logistics transportation, this paper took the group decision making problem based on integration and coordination thought into a multiagent multiobjective group decision making problem; a secondary decision model was established and applied to the safety assessment of dangerous goods transport enterprise. First of all, we used dynamic multivalue background and entropy theory building the first level multiobjective decision model. Secondly, experts were to empower according to the principle of clustering analysis, and combining with the relative entropy theory to establish a secondary rally optimization model based on relative entropy in group decision making, and discuss the solution of the model. Then, after investigation and analysis, we establish the dangerous goods transport enterprise safety evaluation index system. Finally, case analysis to five dangerous goods transport enterprises in the Inner Mongolia Autonomous Region validates the feasibility and effectiveness of this model for dangerous goods transport enterprise recognition, which provides vital decision making basis for recognizing the dangerous goods transport enterprises.

Make or buy decision model with multi-stage manufacturing process and supplier imperfect quality

Science.gov (United States)

Pratama, Mega Aria; Rosyidi, Cucuk Nur

2017-11-01

This research develops an make or buy decision model considering supplier imperfect quality. This model can be used to help companies make the right decision in case of make or buy component with the best quality and the least cost in multistage manufacturing process. The imperfect quality is one of the cost component that must be minimizing in this model. Component with imperfect quality, not necessarily defective. It still can be rework and used for assembly. This research also provide a numerical example and sensitivity analysis to show how the model work. We use simulation and help by crystal ball to solve the numerical problem. The sensitivity analysis result show that percentage of imperfect generally not affect to the model significantly, and the model is not sensitive to changes in these parameters. This is because the imperfect cost are smaller than overall total cost components.

Modeling as a Decision-Making Process

Science.gov (United States)

Bleiler-Baxter, Sarah K.; Stephens, D. Christopher; Baxter, Wesley A.; Barlow, Angela T.

2017-01-01

The goal in this article is to support teachers in better understanding what it means to model with mathematics by focusing on three key decision-making processes: Simplification, Relationship Mapping, and Situation Analysis. The authors use the Theme Park task to help teachers develop a vision of how students engage in these three decision-making…

Implementation of Data Mining to Analyze Drug Cases Using C4.5 Decision Tree

Science.gov (United States)

Wahyuni, Sri

2018-03-01

Data mining was the process of finding useful information from a large set of databases. One of the existing techniques in data mining was classification. The method used was decision tree method and algorithm used was C4.5 algorithm. The decision tree method was a method that transformed a very large fact into a decision tree which was presenting the rules. Decision tree method was useful for exploring data, as well as finding a hidden relationship between a number of potential input variables with a target variable. The decision tree of the C4.5 algorithm was constructed with several stages including the selection of attributes as roots, created a branch for each value and divided the case into the branch. These stages would be repeated for each branch until all the cases on the branch had the same class. From the solution of the decision tree there would be some rules of a case. In this case the researcher classified the data of prisoners at Labuhan Deli prison to know the factors of detainees committing criminal acts of drugs. By applying this C4.5 algorithm, then the knowledge was obtained as information to minimize the criminal acts of drugs. From the findings of the research, it was found that the most influential factor of the detainee committed the criminal act of drugs was from the address variable.

Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial.

Science.gov (United States)

Krijkamp, Eline M; Alarid-Escudero, Fernando; Enns, Eva A; Jalal, Hawre J; Hunink, M G Myriam; Pechlivanoglou, Petros

2018-04-01

Microsimulation models are becoming increasingly common in the field of decision modeling for health. Because microsimulation models are computationally more demanding than traditional Markov cohort models, the use of computer programming languages in their development has become more common. R is a programming language that has gained recognition within the field of decision modeling. It has the capacity to perform microsimulation models more efficiently than software commonly used for decision modeling, incorporate statistical analyses within decision models, and produce more transparent models and reproducible results. However, no clear guidance for the implementation of microsimulation models in R exists. In this tutorial, we provide a step-by-step guide to build microsimulation models in R and illustrate the use of this guide on a simple, but transferable, hypothetical decision problem. We guide the reader through the necessary steps and provide generic R code that is flexible and can be adapted for other models. We also show how this code can be extended to address more complex model structures and provide an efficient microsimulation approach that relies on vectorization solutions.

29 CFR 1614.303 - Petitions to the EEOC from MSPB decisions on mixed case appeals and complaints.

Science.gov (United States)

2010-07-01

... 29 Labor 4 2010-07-01 2010-07-01 false Petitions to the EEOC from MSPB decisions on mixed case... Petitions to the EEOC from MSPB decisions on mixed case appeals and complaints. (a) Who may file. Individuals who have received a final decision from the MSPB on a mixed case appeal or on the appeal of a...

Integrating Design Decision Management with Model-based Software Development

DEFF Research Database (Denmark)

Könemann, Patrick

Design decisions are continuously made during the development of software systems and are important artifacts for design documentation. Dedicated decision management systems are often used to capture such design knowledge. Most such systems are, however, separated from the design artifacts...... of the system. In model-based software development, where design models are used to develop a software system, outcomes of many design decisions have big impact on design models. The realization of design decisions is often manual and tedious work on design models. Moreover, keeping design models consistent......, or by ignoring the causes. This substitutes manual reviews to some extent. The concepts, implemented in a tool, have been validated with design patterns, refactorings, and domain level tests that comprise a replay of a real project. This proves the applicability of the solution to realistic examples...

Use of travel cost models in planning: A case study

Science.gov (United States)

Allan Marsinko; William T. Zawacki; J. Michael Bowker

2002-01-01

This article examines the use of the travel cost, method in tourism-related decision making in the area of nonconsumptive wildlife-associated recreation. A travel cost model of nonconsumptive wildlife-associated recreation, developed by Zawacki, Maninko, and Bowker, is used as a case study for this analysis. The travel cost model estimates the demand for the activity...

Regulatory decision making by decision analyses

International Nuclear Information System (INIS)

Holmberg, J.; Pulkkinen, U.

1993-11-01

The Technical Research Centre of Finland (VTT) has studied with the Finnish Centre for Radiation and Nuclear Safety (STUK) the applicability of decision analytic approach to the treatment of nuclear safety related problems at the regulatory body. The role of probabilistic safety assessment (PSA) in decision making has also been discussed. In the study, inspectors from STUK exercised with a decision analytic approach by reoperationalizing two occurred and solved problems. The research scientist from VTT acted as systems analysts guiding the analysis process. The first case was related to a common cause failure phenomenon in solenoid valves controlling pneumatic valves important to safety of the plant. The problem of the regulatory body was to judge whether to allow continued operation or to require more detailed inspections and in which time chedule the inspections should be done. The latter problem was to evaluate design changes of external electrical grid connections after a fire incident had revealed weakness in the separation of electrical system. In both cases, the decision analysis was carried out several sessions in which decision makers, technical experts as well as experts of decision analysis participated. A multi-attribute value function was applied as a decision model so that attributes had to be defined to quantify the levels of achievements of the objectives. The attributes included both indicators related to the level of operational safety of the plant such as core damage frequency given by PSA, and indicators related to the safety culture, i.e., how well the chosen option fits on the regulatory policy. (24 refs., 6 figs., 9 tabs.)

Death Penalty Decisions: Instruction Comprehension, Attitudes, and Decision Mediators.

Science.gov (United States)

Patry, Marc W; Penrod, Steven D

2013-01-01

A primary goal of this research was to empirically evaluate a set of assumptions, advanced in the Supreme Court's ruling in Buchanan v. Angelone (1998), about jury comprehension of death penalty instructions. Further, this research examined the use of evidence in capital punishment decision making by exploring underlying mediating factors upon which death penalty decisions may be based. Manipulated variables included the type of instructions and several variations of evidence. Study 1 was a paper and pencil study of 245 undergraduate mock jurors. The experimental design was an incomplete 4×2×2×2×2 factorial model resulting in 56 possible conditions. Manipulations included four different types of instructions, presence of a list of case-specific mitigators to accompany the instructions, and three variations in the case facts: age of the defendant, bad prior record, and defendant history of emotional abuse. Study 2 was a fully-crossed 2×2×2×2×2 experiment with four deliberating mock juries per cell. Manipulations included jury instructions (original or revised), presence of a list of case-specific mitigators, defendant history of emotional abuse, bad prior record, and heinousness of the crime. The sample of 735 jury-eligible participants included 130 individuals who identified themselves as students. Participants watched one of 32 stimulus videotapes based on a replication of a capital sentencing hearing. The present findings support previous research showing low comprehension of capital penalty instructions. Further, we found that higher instruction comprehension was associated with higher likelihood of issuing life sentence decisions. The importance of instruction comprehension is emphasized in a social cognitive model of jury decision making at the sentencing phase of capital cases.

Reducing suboptimal employee decisions can build the business case for employee benefits.

Science.gov (United States)

Goldsmith, Christopher; Cyboran, Steven F

2013-01-01

Suboptimal employee decisions are prevalent in employee benefit plans. Poor decisions have significant consequences for employees and employers. Improving participant decisions produces beneficial outcomes such as lower labor costs, higher productivity and better workforce management. The business case for employee benefits can be strengthened by applying lessons learned from the field of behavioral economics to employee benefit plan design and to workforce communication. This article explains the types of behavioral biases that influence suboptimal decisions and explores how enlightened employee benefit plan choice architecture and vivid behavioral messaging contribute to human and better organizational outcomes.

A decision-making model for engineering designers

DEFF Research Database (Denmark)

Ahmed, S.; Hansen, Claus Thorp

2002-01-01

This paper describes research that combines the generic decision-making model of Hansen, together with design strategies employed by experienced engineering designers. The relationship between the six decision-making sub-activities and the eight design strategies are examined. By combining...

Constructing Perceptions of Climate Change: a case study of regional political decision makers

Science.gov (United States)

Bray, D.

2012-12-01

This case study of climate change communications assesses the salient means of communication and the message adopted by regional political decision makers on the German Baltic coast. Realizing that cultural factors and local values (and not simply knowledge) are significant influences in explaining attitudes towards climate change, this analysis draws from the records of regional weather, from scientists with a specific focus on the region, from the political decision makers for that region, and the media message reaching the decision makers, ensuring all elements of the analysis are drawn from the same socioeconomic, geophysical, political and cultural context. This is important as the social dynamics surrounding the trust in science is of critical importance and, as such, all elements of the case study are specifically contained within a common context. If the utility of climate change knowledge is to prompt well conceived adaptation/mitigation strategies then the political decision process, or at least the perceptions shaping it, can best be understood by locating it within the world view of the decision makers involved in the production process. Using the results of two survey questionnaires, one of regional climate scientists and one of regional political decision makers, ten years of local weather records, and a summary of the message from mass media circulation, the discord in perceptions of regional climate change are quantitatively explored. The conclusions drawn from the analysis include, compared to the scientific assessment: The decision makers' perceptions of recent past differ from actual observations. The decision makers' perceptions of the future differ from scientific assessments. The decision makers tend to over estimate the magnitude of regional climate change and its impacts. The decision makers tend to over estimate the sense of immediacy for adaptation measures. The conclusions drawn suggest that in the regional political realm, it is often a

Solid Waste Management Holistic Decision Modeling

OpenAIRE

World Bank

2008-01-01

This study provides support to the Bank's ability to conduct client dialogue on solid waste management technology selection, and will contribute to client decision-making. The goal of the study was to fully explore the use of the United States Environmental Protection Agency and the Research Triangle Institute (EPA/RTI) holistic decision model to study alternative solid waste systems in a ...

FUZZY DECISION MAKING MODEL FOR BYZANTINE AGREEMENT

Directory of Open Access Journals (Sweden)

S. MURUGAN

2014-04-01

Full Text Available Byzantine fault tolerance is of high importance in the distributed computing environment where malicious attacks and software errors are common. A Byzantine process sends arbitrary messages to every other process. An effective fuzzy decision making approach is proposed to eliminate the Byzantine behaviour of the services in the distributed environment. It is proposed to derive a fuzzy decision set in which the alternatives are ranked with grade of membership and based on that an appropriate decision can be arrived on the messages sent by the different services. A balanced decision is to be taken from the messages received across the services. To accomplish this, Hurwicz criterion is used to balance the optimistic and pessimistic views of the decision makers on different services. Grades of membership for the services are assessed using the non-functional Quality of Service parameters and have been estimated using fuzzy entropy measure which logically ranks the participant services. This approach for decision making is tested by varying the number of processes, varying the number of faulty services, varying the message values sent to different services and considering the variation in the views of the decision makers about the services. The experimental result shows that the decision reached is an enhanced one and in case of conflict, the proposed approach provides a concrete result, whereas decision taken using the Lamport’s algorithm is an arbitrary one.

Economic modelling for life extension decision making

International Nuclear Information System (INIS)

Farber, M.A.; Harrison, D.L.; Carlson, D.D.

1987-01-01

This paper presents a methodology for the economic and financial analysis of nuclear plant life extension under uncertainty and demonstrates its use in a case analysis. While the economic and financial evaluation of life extension does not require new analytical tools, such studies should be based on the following three premises. First, the methodology should examine effects at the level of the company or utility system, because the most important economic implications of life extension relate to the altered generation system expansion plan. Second, it should focus on the implications of uncertainty in order to understand the factors that most affect life extension benefits and identify risk management efforts. Third, the methodology should address multiple objectives, at a minimum, both economic and financial objectives. An analysis of the role of life extension for Virginia Power's generating system was performed using the MIDAS model, developed by the Electric Power Research Institute. MIDAS is particularly well suited to this type of study because of its decision analysis framework. The model incorporates modules for load analysis, capacity expansion, production costing, financial analysis, and rates. The decision tree structure facilitates the multiple-scenario analysis of uncertainty. The model's output includes many economic and financial measures, including capital expenditures, fuel and purchases power costs, revenue requirements, average rates, external financing requirements, and coverage ratio. Based on findings for Virginia Power's Surry 1 plant, nuclear plant life extension has economic benefits for a utility's customers and financial benefits for the utility's investors. These benefits depend on a number of economic, technical and regulatory factors. The economic analysis presented in this paper identifies many of the key factors and issues relevant to life extension planning

Pattern-based Automatic Translation of Structured Power System Data to Functional Models for Decision Support Applications

DEFF Research Database (Denmark)

Heussen, Kai; Weckesser, Johannes Tilman Gabriel; Kullmann, Daniel

2013-01-01

Improved information and insight for decision support in operations and design are central promises of a smart grid. Well-structured information about the composition of power systems is increasingly becoming available in the domain, e.g. due to standard information models (e.g. CIM or IEC61850......) or otherwise structured databases. More measurements and data do not automatically improve decisions, but there is an opportunity to capitalize on this information for decision support. With suitable reasoning strategies data can be contextualized and decision-relevant events can be promoted and identified....... This paper presents an approach to link available structured power system data directly to a functional representation suitable for diagnostic reasoning. The translation method is applied to test cases also illustrating decision support....

Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making

Directory of Open Access Journals (Sweden)

Gwenan M. Knight

2016-01-01

Full Text Available The dominant approach to decision-making in public health policy for infectious diseases relies heavily on expert opinion, which often applies empirical evidence to policy questions in a manner that is neither systematic nor transparent. Although systematic reviews are frequently commissioned to inform specific components of policy (such as efficacy, the same process is rarely applied to the full decision-making process. Mathematical models provide a mechanism through which empirical evidence can be methodically and transparently integrated to address such questions. However, such models are often considered difficult to interpret. In addition, models provide estimates that need to be iteratively re-evaluated as new data or considerations arise. Using the case study of a novel diagnostic for tuberculosis, a framework for improved collaboration between public health decision-makers and mathematical modellers that could lead to more transparent and evidence-driven policy decisions for infectious diseases in the future is proposed. The framework proposes that policymakers should establish long-term collaborations with modellers to address key questions, and that modellers should strive to provide clear explanations of the uncertainty of model structure and outputs. Doing so will improve the applicability of models and clarify their limitations when used to inform real-world public health policy decisions.

Decision tree based knowledge acquisition and failure diagnosis using a PWR loop vibration model

International Nuclear Information System (INIS)

Bauernfeind, V.; Ding, Y.

1993-01-01

An analytical vibration model of the primary system of a 1300 MW PWR was used for simulating mechanical faults. Deviations in the calculated power density spectra and coherence functions are determined and classified. The decision tree technique is then used for a personal computer supported knowledge presentation and for optimizing the logical relationships between the simulated faults and the observed symptoms. The optimized decision tree forms the knowledge base and can be used to diagnose known cases as well as to include new data into the knowledge base if new faults occur. (author)

Dual processing model of medical decision-making

OpenAIRE

Djulbegovic, Benjamin; Hozo, Iztok; Beckstead, Jason; Tsalatsanis, Athanasios; Pauker, Stephen G

2012-01-01

Abstract Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administe...

Pharmaceutical expenditure forecast model to support health policy decision making

Science.gov (United States)

Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

2014-01-01

Background and objective With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project ‘European Union (EU) Pharmaceutical expenditure forecast’ – http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). Methods A model was built to assess policy scenarios’ impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). Results Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. Conclusions Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate

A methodology for eliciting, representing, and analysing stakeholder knowledge for decision making on complex socio-ecological systems: from cognitive maps to agent-based models.

Science.gov (United States)

Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J

2015-03-15

This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Signal Detection Model of Compound Decision Tasks

Science.gov (United States)

2006-12-01

strict isolation (for many examples of such models see Egan, 1975; Macmillan & Creelman , 1991). The result has been twofold: A rich corpus of decision...Macmillan & Creelman , 1991). It is important to point out that SDT models are primarily decision models. They specify the rules and procedures for how...Broadbent, 1958; Macmillan & Creelman , 1991; Nolte & Jaarsma, 1967; Swensson & Judy, 1981; Tanner & Norman, 1954). To better understand how these two

Decision-Based Design Integrating Consumer Preferences into Engineering Design

CERN Document Server

Chen, Wei; Wassenaar, Henk Jan

2013-01-01

Building upon the fundamental principles of decision theory, Decision-Based Design: Integrating Consumer Preferences into Engineering Design presents an analytical approach to enterprise-driven Decision-Based Design (DBD) as a rigorous framework for decision making in engineering design.  Once the related fundamentals of decision theory, economic analysis, and econometrics modelling are established, the remaining chapters describe the entire process, the associated analytical techniques, and the design case studies for integrating consumer preference modeling into the enterprise-driven DBD framework. Methods for identifying key attributes, optimal design of human appraisal experiments, data collection, data analysis, and demand model estimation are presented and illustrated using engineering design case studies. The scope of the chapters also provides: •A rigorous framework of integrating the interests from both producer and consumers in engineering design, •Analytical techniques of consumer choice model...

5 CFR 2430.12 - Administrative Law Judge's decision; contents; service; transfer of case to the Authority...

Science.gov (United States)

2010-01-01

... Administrative Law Judge's decision and of the order transferring the case to the Board shall be complete upon... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Administrative Law Judge's decision; contents; service; transfer of case to the Authority; contents of record in case. 2430.12 Section 2430.12...

Functional Freedom: A Psychological Model of Freedom in Decision-Making.

Science.gov (United States)

Lau, Stephan; Hiemisch, Anette

2017-07-05

The freedom of a decision is not yet sufficiently described as a psychological variable. We present a model of functional decision freedom that aims to fill that role. The model conceptualizes functional freedom as a capacity of people that varies depending on certain conditions of a decision episode. It denotes an inner capability to consciously shape complex decisions according to one's own values and needs. Functional freedom depends on three compensatory dimensions: it is greatest when the decision-maker is highly rational, when the structure of the decision is highly underdetermined, and when the decision process is strongly based on conscious thought and reflection. We outline possible research questions, argue for psychological benefits of functional decision freedom, and explicate the model's implications on current knowledge and research. In conclusion, we show that functional freedom is a scientific variable, permitting an additional psychological foothold in research on freedom, and that is compatible with a deterministic worldview.

Bayesian risk-based decision method for model validation under uncertainty

International Nuclear Information System (INIS)

Jiang Xiaomo; Mahadevan, Sankaran

2007-01-01

This paper develops a decision-making methodology for computational model validation, considering the risk of using the current model, data support for the current model, and cost of acquiring new information to improve the model. A Bayesian decision theory-based method is developed for this purpose, using a likelihood ratio as the validation metric for model assessment. An expected risk or cost function is defined as a function of the decision costs, and the likelihood and prior of each hypothesis. The risk is minimized through correctly assigning experimental data to two decision regions based on the comparison of the likelihood ratio with a decision threshold. A Bayesian validation metric is derived based on the risk minimization criterion. Two types of validation tests are considered: pass/fail tests and system response value measurement tests. The methodology is illustrated for the validation of reliability prediction models in a tension bar and an engine blade subjected to high cycle fatigue. The proposed method can effectively integrate optimal experimental design into model validation to simultaneously reduce the cost and improve the accuracy of reliability model assessment

Models and theories of prescribing decisions: A review and suggested a new model.

Science.gov (United States)

Murshid, Mohsen Ali; Mohaidin, Zurina

2017-01-01

To date, research on the prescribing decisions of physician lacks sound theoretical foundations. In fact, drug prescribing by doctors is a complex phenomenon influenced by various factors. Most of the existing studies in the area of drug prescription explain the process of decision-making by physicians via the exploratory approach rather than theoretical. Therefore, this review is an attempt to suggest a value conceptual model that explains the theoretical linkages existing between marketing efforts, patient and pharmacist and physician decision to prescribe the drugs. The paper follows an inclusive review approach and applies the previous theoretical models of prescribing behaviour to identify the relational factors. More specifically, the report identifies and uses several valuable perspectives such as the 'persuasion theory - elaboration likelihood model', the stimuli-response marketing model', the 'agency theory', the theory of planned behaviour,' and 'social power theory,' in developing an innovative conceptual paradigm. Based on the combination of existing methods and previous models, this paper suggests a new conceptual model of the physician decision-making process. This unique model has the potential for use in further research.

Implementing interactive decision support: A case for combining cyberinfrastructure, data fusion, and social process to mobilize scientific knowledge in sustainability problems

Science.gov (United States)

Pierce, S. A.

2014-12-01

Geosciences are becoming increasingly data intensive, particularly in relation to sustainability problems, which are multi-dimensional, weakly structured and characterized by high levels of uncertainty. In the case of complex resource management problems, the challenge is to extract meaningful information from data and make sense of it. Simultaneously, scientific knowledge alone is insufficient to change practice. Creating tools, and group decision support processes for end users to interact with data are key challenges to transforming science-based information into actionable knowledge. The ENCOMPASS project began as a multi-year case study in the Atacama Desert of Chile to design and implement a knowledge transfer model for energy-water-mining conflicts in the region. ENCOMPASS combines the use of cyberinfrastructure (CI), automated data collection, interactive interfaces for dynamic decision support, and participatory modelling to support social learning. A pilot version of the ENCOMPASS CI uses open source systems and serves as a structure to integrate and store multiple forms of data and knowledge, such as DEM, meteorological, water quality, geomicrobiological, energy demand, and groundwater models. In the case study, informatics and data fusion needs related to scientific uncertainty around deep groundwater flowpaths and energy-water connections. Users may upload data from field sites with handheld devices or desktops. Once uploaded, data assets are accessible for a variety of uses. To address multi-attributed decision problems in the Atacama region a standalone application with touch-enabled interfaces was created to improve real-time interactions with datasets by groups. The tool was used to merge datasets from the ENCOMPASS CI to support exploration among alternatives and build shared understanding among stakeholders. To date, the project has increased technical capacity among stakeholders, resulted in the creation of both for-profit and non

Research on investment decisions model of trans-regional transmission network based on the theory of NPV

Science.gov (United States)

Zai, Wenjiao; Wang, Bo; Liu, Jichun; Shi, Haobo; Zeng, Pingliang

2018-02-01

The investment decision model of trans-regional transmission network in the context of Global Energy Internet was studied in this paper. The key factors affecting the trans-regional transmission network investment income: the income tax rate, the loan interest rate, the expected return on investment of the investment subject, the per capita GDP and so on were considered in the transmission network investment income model. First, according to the principle of system dynamics, the causality diagram of key factors was constructed. Then, the dynamic model of transmission investment decision was established. A case study of the power transmission network between China and Mongolia, through the simulation of the system dynamic model, the influence of the above key factors on the investment returns was analyzed, and the feasibility and effectiveness of the model was proved.

Support System Model for Value based Group Decision on Roof System Selection

Directory of Open Access Journals (Sweden)

Christiono Utomo

2011-02-01

Full Text Available A group decision support system is required on a value-based decision because there are different concern caused by differing preferences, experiences, and background. It is to enable each decision-maker to evaluate and rank the solution alternatives before engaging into negotiation with other decision-makers. Stakeholder of multi-criteria decision making problems usually evaluates the alternative solution from different perspective, making it possible to have a dominant solution among the alternatives. Each stakeholder needs to identify the goals that can be optimized and those that can be compromised in order to reach an agreement with other stakeholders. This paper presents group decision model involving three decision-makers on the selection of suitable system for a building’s roof. The objective of the research is to find an agreement options model and coalition algorithms for multi person decision with two main preferences of value which are function and cost. The methodology combines value analysis method using Function Analysis System Technique (FAST; Life Cycle Cost analysis, group decision analysis method based on Analytical Hierarchy Process (AHP in a satisfying options, and Game theory-based agent system to develop agreement option and coalition formation for the support system. The support system bridges theoretical gap between automated design in construction domain and automated negotiation in information technology domain by providing a structured methodology which can lead to systematic support system and automated negotiation. It will contribute to value management body of knowledge as an advanced method for creativity and analysis phase, since the practice of this knowledge is teamwork based. In the case of roof system selection, it reveals the start of the first negotiation round. Some of the solutions are not an option because no individual stakeholder or coalition of stakeholders desires to select it. The result indicates

The power of science economic research and European decision-making : the case of energy and environment policies

CERN Document Server

Rossetti di Valdalbero, Domenico

2010-01-01

This book highlights the interaction between science and politics and between research in economics and European Union policy-making. It focuses on the use of Quantitative tools, Top-down and Bottom-up models in up-stream European decision-making process through five EU policy case studies: energy taxation, climate change, energy efficiency, renewable energy, and internalisation of external costs.

Identifying the decision to be supported: a review of papers from environmental modelling and software

Science.gov (United States)

Sojda, Richard S.; Chen, Serena H.; El Sawah, Sondoss; Guillaume, Joseph H.A.; Jakeman, A.J.; Lautenbach, Sven; McIntosh, Brian S.; Rizzoli, A.E.; Seppelt, Ralf; Struss, Peter; Voinov, Alexey; Volk, Martin

2012-01-01

Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for

Exploring a Laboratory Model of Pharmacogenetics as Applied to Clinical Decision Making

Directory of Open Access Journals (Sweden)

David F. Kisor

2013-01-01

Full Text Available Objective: To evaluate a pilot of a laboratory model for relating pharmacogenetics to clinical decision making. Case Study: This pilot was undertaken and evaluated to help determine if a pharmacogenetics laboratory should be included in the core Doctor of Pharmacy curriculum. The placement of the laboratory exercise in the curriculum was determined by identifying the point in the curriculum where the students had been introduced to the chemistry of deoxyribonucleic acid (DNA as well as instructed on the chemistry of genetic variation. The laboratory included cytochrome P450 2C19 genotyping relative to the *2 variant. Twenty-four students served as the pilot group. Students provided buccal swabs as the source of DNA. Students stabilized the samples and were then provided instructions related to sample preparation, polymerase chain reaction, and gel electrophoresis. The results were reported as images of gels. Students used a reference gel image to compare their results to. Students then applied a dosing algorithm to make a "clinical decision" relative to clopidogrel use. Students were offered a post laboratory survey regarding attitudes toward the laboratory. Twenty-four students completed the laboratory with genotyping results being provided for 22 students (91.7%. Sixteen students were wild-type (*1/*1, while six students were heterozygous (*1/*2. Twenty-three students (96% completed the post laboratory survey. All 23 agreed (6, 26.1% or strongly agreed (17, 73.9% that the laboratory "had relevance and value in the pharmacy curriculum" Conclusion: The post pilot study survey exploring a laboratory model for pharmacogenetics related to clinical decision making indicated that such a laboratory would be viewed positively by students. This model may be adopted by colleges to expand pharmacogenetics education.   Type: Case Study

Uncertainty, causality and decision: The case of social risks and nuclear risk in particular

International Nuclear Information System (INIS)

Lahidji, R.

2012-01-01

Probability and causality are two indispensable tools for addressing situations of social risk. Causal relations are the foundation for building risk assessment models and identifying risk prevention, mitigation and compensation measures. Probability enables us to quantify risk assessments and to calibrate intervention measures. It therefore seems not only natural, but also necessary to make the role of causality and probability explicit in the definition of decision problems in situations of social risk. Such is the aim of this thesis.By reviewing the terminology of risk and the logic of public interventions in various fields of social risk, we gain a better understanding of the notion and of the issues that one faces when trying to model it. We further elaborate our analysis in the case of nuclear safety, examining in detail how methods and policies have been developed in this field and how they have evolved through time. This leads to a number of observations concerning risk and safety assessments.Generalising the concept of intervention in a Bayesian network allows us to develop a variety of causal Bayesian networks adapted to our needs. In this framework, we propose a definition of risk which seems to be relevant for a broad range of issues. We then offer simple applications of our model to specific aspects of the Fukushima accident and other nuclear safety problems. In addition to specific lessons, the analysis leads to the conclusion that a systematic approach for identifying uncertainties is needed in this area. When applied to decision theory, our tool evolves into a dynamic decision model in which acts cause consequences and are causally interconnected. The model provides a causal interpretation of Savage's conceptual framework, solves some of its paradoxes and clarifies certain aspects. It leads us to considering uncertainty with regard to a problem's causal structure as the source of ambiguity in decision-making, an interpretation which corresponds to a

Nurses' decision-making process in cases of physical restraint in acute elderly care: a qualitative study.

Science.gov (United States)

Goethals, S; Dierckx de Casterlé, B; Gastmans, C

2013-05-01

The increasing vulnerability of patients in acute elderly care requires constant critical reflection in ethically charged situations such as when employing physical restraint. Qualitative evidence concerning nurses' decision making in cases of physical restraint is limited and fragmented. A thorough understanding of nurses' decision-making process could be useful to understand how nurses reason and make decisions in ethically laden situations. The aims of this study were to explore and describe nurses' decision-making process in cases of physical restraint. We used a qualitative interview design inspired by the Grounded Theory approach. Data analysis was guided by the Qualitative Analysis Guide of Leuven. Twelve hospitals geographically spread throughout the five provinces of Flanders, Belgium. Twenty-one acute geriatric nurses interviewed between October 2009 and April 2011 were purposively and theoretically selected, with the aim of including nurses having a variety of characteristics and experiences concerning decisions on using physical restraint. In cases of physical restraint in acute elderly care, nurses' decision making was never experienced as a fixed decision but rather as a series of decisions. Decision making was mostly reasoned upon and based on rational arguments; however, decisions were also made routinely and intuitively. Some nurses felt very certain about their decisions, while others experienced feelings of uncertainty regarding their decisions. Nurses' decision making is an independent process that requires nurses to obtain a good picture of the patient, to be constantly observant, and to assess and reassess the patient's situation. Coming to thoughtful and individualized decisions requires major commitment and constant critical reflection. Copyright © 2012 Elsevier Ltd. All rights reserved.

29 CFR 102.45 - Administrative law judge's decision; contents; service; transfer of case to the Board; contents...

Science.gov (United States)

2010-07-01

... and Transfer of Case to the Board § 102.45 Administrative law judge's decision; contents; service... administrative law judge's decision and of the order transferring the case to the Board shall be complete upon... 29 Labor 2 2010-07-01 2010-07-01 false Administrative law judge's decision; contents; service...

29 CFR 102.153 - Administrative law judge's decision; contents; service; transfer of case to the Board; contents...

Science.gov (United States)

2010-07-01

... Expenses § 102.153 Administrative law judge's decision; contents; service; transfer of case to the Board... administrative law judge's decision and of the order transferring the case to the Board shall be complete upon... 29 Labor 2 2010-07-01 2010-07-01 false Administrative law judge's decision; contents; service...

A decision model for selecting sustainable drinking water supply and greywater reuse systems for developing communities with a case study in Cimahi, Indonesia.

Science.gov (United States)

Henriques, Justin J; Louis, Garrick E

2011-01-01

Capacity Factor Analysis is a decision support system for selection of appropriate technologies for municipal sanitation services in developing communities. Developing communities are those that lack the capability to provide adequate access to one or more essential services, such as water and sanitation, to their residents. This research developed two elements of Capacity Factor Analysis: a capacity factor based classification for technologies using requirements analysis, and a matching policy for choosing technology options. First, requirements analysis is used to develop a ranking for drinking water supply and greywater reuse technologies. Second, using the Capacity Factor Analysis approach, a matching policy is developed to guide decision makers in selecting the appropriate drinking water supply or greywater reuse technology option for their community. Finally, a scenario-based informal hypothesis test is developed to assist in qualitative model validation through case study. Capacity Factor Analysis is then applied in Cimahi Indonesia as a form of validation. The completed Capacity Factor Analysis model will allow developing communities to select drinking water supply and greywater reuse systems that are safe, affordable, able to be built and managed by the community using local resources, and are amenable to expansion as the community's management capacity increases. Copyright © 2010 Elsevier Ltd. All rights reserved.

Joint perceptual decision-making: A case study in explanatory pluralism

Directory of Open Access Journals (Sweden)

Drew Hamilton Abney

2014-04-01

Full Text Available Traditionally different approaches to the study of cognition have been viewed as competing explanatory frameworks. An alternative view, explanatory pluralism, regards different approaches to the study of cognition as complementary ways of studying the same phenomenon, at specific temporal and spatial scales, using appropriate methodological tools. Explanatory pluralism has been often described abstractly, but has rarely been applied to concrete cases. We present a case study of explanatory pluralism. We discuss three separate ways of studying the same phenomenon: a perceptual decision- making task (Bahrami et al., 2010, where pairs of subjects share information to jointly individuate an oddball stimulus among a set of distractors. Each approach analyzed the same corpus but targeted different units of analysis at different levels of description: decision-making at the behavioral level, confidence sharing at the linguistic level, and acoustic energy at the physical level. We discuss the utility of explanatory pluralism for describing this complex, multiscale phenomenon, show ways in which this case study sheds new light on the concept of pluralism, and highlight good practices to critically assess and complement approaches.

A decision model for planetary missions

Science.gov (United States)

Hazelrigg, G. A., Jr.; Brigadier, W. L.

1976-01-01

Many techniques developed for the solution of problems in economics and operations research are directly applicable to problems involving engineering trade-offs. This paper investigates the use of utility theory for decision making in planetary exploration space missions. A decision model is derived that accounts for the objectives of the mission - science - the cost of flying the mission and the risk of mission failure. A simulation methodology for obtaining the probability distribution of science value and costs as a function spacecraft and mission design is presented and an example application of the decision methodology is given for various potential alternatives in a comet Encke mission.

Decision optimization of case-based computer-aided decision systems using genetic algorithms with application to mammography

International Nuclear Information System (INIS)

Mazurowski, Maciej A; Habas, Piotr A; Zurada, Jacek M; Tourassi, Georgia D

2008-01-01

This paper presents an optimization framework for improving case-based computer-aided decision (CB-CAD) systems. The underlying hypothesis of the study is that each example in the knowledge database of a medical decision support system has different importance in the decision making process. A new decision algorithm incorporating an importance weight for each example is proposed to account for these differences. The search for the best set of importance weights is defined as an optimization problem and a genetic algorithm is employed to solve it. The optimization process is tailored to maximize the system's performance according to clinically relevant evaluation criteria. The study was performed using a CAD system developed for the classification of regions of interests (ROIs) in mammograms as depicting masses or normal tissue. The system was constructed and evaluated using a dataset of ROIs extracted from the Digital Database for Screening Mammography (DDSM). Experimental results show that, according to receiver operator characteristic (ROC) analysis, the proposed method significantly improves the overall performance of the CAD system as well as its average specificity for high breast mass detection rates

CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

Science.gov (United States)

Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

2015-01-01

The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratiodecisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

Stock Selection for Portfolios Using Expected Utility-Entropy Decision Model

Directory of Open Access Journals (Sweden)

Jiping Yang

2017-09-01

Full Text Available Yang and Qiu proposed and then recently improved an expected utility-entropy (EU-E measure of risk and decision model. When segregation holds, Luce et al. derived an expected utility term, plus a constant multiplies the Shannon entropy as the representation of risky choices, further demonstrating the reasonability of the EU-E decision model. In this paper, we apply the EU-E decision model to selecting the set of stocks to be included in the portfolios. We first select 7 and 10 stocks from the 30 component stocks of Dow Jones Industrial Average index, and then derive and compare the efficient portfolios in the mean-variance framework. The conclusions imply that efficient portfolios composed of 7(10 stocks selected using the EU-E model with intermediate intervals of the tradeoff coefficients are more efficient than that composed of the sets of stocks selected using the expected utility model. Furthermore, the efficient portfolio of 7(10 stocks selected by the EU-E decision model have almost the same efficient frontier as that of the sample of all stocks. This suggests the necessity of incorporating both the expected utility and Shannon entropy together when taking risky decisions, further demonstrating the importance of Shannon entropy as the measure of uncertainty, as well as the applicability of the EU-E model as a decision-making model.

Effluent trading in river systems through stochastic decision-making process: a case study.

Science.gov (United States)

Zolfagharipoor, Mohammad Amin; Ahmadi, Azadeh

2017-09-01

The objective of this paper is to provide an efficient framework for effluent trading in river systems. The proposed framework consists of two pessimistic and optimistic decision-making models to increase the executability of river water quality trading programs. The models used for this purpose are (1) stochastic fallback bargaining (SFB) to reach an agreement among wastewater dischargers and (2) stochastic multi-criteria decision-making (SMCDM) to determine the optimal treatment strategy. The Monte-Carlo simulation method is used to incorporate the uncertainty into analysis. This uncertainty arises from stochastic nature and the errors in the calculation of wastewater treatment costs. The results of river water quality simulation model are used as the inputs of models. The proposed models are used in a case study on the Zarjoub River in northern Iran to determine the best solution for the pollution load allocation. The best treatment alternatives selected by each model are imported, as the initial pollution discharge permits, into an optimization model developed for trading of pollution discharge permits among pollutant sources. The results show that the SFB-based water pollution trading approach reduces the costs by US$ 14,834 while providing a relative consensus among pollutant sources. Meanwhile, the SMCDM-based water pollution trading approach reduces the costs by US$ 218,852, but it is less acceptable by pollutant sources. Therefore, it appears that giving due attention to stability, or in other words acceptability of pollution trading programs for all pollutant sources, is an essential element of their success.

Photovoltaics in agriculture: A case study on decision making of farmers

International Nuclear Information System (INIS)

Brudermann, Thomas; Reinsberger, Kathrin; Orthofer, Anita; Kislinger, Martin; Posch, Alfred

2013-01-01

This paper aims to identify the success factors, incentives, barriers and challenges in the adoption process of photovoltaics (PV) in the agricultural sector, with particular focus placed on decision making of individual farmers and network effects. We investigated a successful case of an Austrian farmers' association that set up a community power plant concept and a society for facilitating PV adoption among farmers. We found that PV adoption decisions are driven by economic and environmental considerations and that while ethical considerations are relatively strong among farmers, they cannot be used as predictors in the decision making process. Results furthermore suggest that while adoption of PV increases belief in technological progress as a solution to environmental problems, it may simultaneously lead to a weakening in the belief that underlying lifestyle changes are necessary. Our conclusions address crucial aspects of PV adoption in agriculture, and implications for policy measures related to respective community initiatives. - Highlights: • Study on successful community PV adoption case in agriculture. • Bottom-up emergence of institutional agreements as reaction to public subsidies. • Economic and environmental considerations guide decision making of farmers. • PV adoption might change perception of environmental problems. • Policy measures required to cope with potential added-value of private initiatives

Making decision process knowledge explicit using the product data model

NARCIS (Netherlands)

Petrusel, R.; Vanderfeesten, I.T.P.; Dolean, Cristina; Mican, D.

2011-01-01

In this paper, we present a new knowledge acquisition and formalization method: the decision mining approach. Basically, we aim to produce a model of the workflow of mental actions performed by decision makers during the decision process. We show that through the use of a Product Data Model (PDM) we

Munich case, some decisions make great stories: Business Model innovation by means of Social Media

OpenAIRE

Rodríguez Donaire, Silvia; Olivé Tomàs, Antoni

2012-01-01

The main objective of this article is to identify how Social Media influences the way the business is managed and/or innovated. To evaluate this Business Model Innovation we have conducted a case study that assesses how strategic choices made by managers, due to the implementation of Social Media, influences Business Model Innovation. The contribution of this article throughout the company’s history, Munich case, allows us to see how Munich’s Business Model has been innovated, and how Social ...

Real-Time Decision Making and Aggressive Behavior in Youth: A Heuristic Model of Response Evaluation and Decision (RED).

Science.gov (United States)

Fontaine, Reid Griffith; Dodge, Kenneth A

2006-11-01

Considerable scientific and intervention attention has been paid to judgment and decision-making systems associated with aggressive behavior in youth. However, most empirical studies have investigated social-cognitive correlates of stable child and adolescent aggressiveness, and less is known about real-time decision making to engage in aggressive behavior. A model of real-time decision making must incorporate both impulsive actions and rational thought. The present paper advances a process model (response evaluation and decision; RED) of real-time behavioral judgments and decision making in aggressive youths with mathematic representations that may be used to quantify response strength. These components are a heuristic to describe decision making, though it is doubtful that individuals always mentally complete these steps. RED represents an organization of social-cognitive operations believed to be active during the response decision step of social information processing. The model posits that RED processes can be circumvented through impulsive responding. This article provides a description and integration of thoughtful, rational decision making and nonrational impulsivity in aggressive behavioral interactions.

Identification of reverse logistics decision types from mathematical models

Directory of Open Access Journals (Sweden)

Pascual Cortés Pellicer

2018-04-01

Full Text Available Purpose: The increase in social awareness, politics and environmental regulation, the scarcity of raw materials and the desired “green” image, are some of the reasons that lead companies to decide for implement processes of Reverse Logistics (RL. At the time when incorporate new RL processes as key business processes, new and important decisions need to be made. Identification and knowledge of these decisions, including the information available and the implications for the company or supply chain, will be fundamental for decision-makers to achieve the best results. In the present work, the main types of RL decisions are identified. Design/methodology/approach: This paper is based on the analysis of mathematical models designed as tools to aid decision making in the field of RL. Once the types of interest work to be analyzed are defined, those studies that really deal about the object of study are searched and analyzed. The decision variables that are taken at work are identified and grouped according to the type of decision and, finally, are showed the main types of decisions used in mathematical models developed in the field of RL.     Findings: The principal conclusion of the research is that the most commonly addressed decisions with mathematical models in the field of RL are those related to the network’s configuration, followed by tactical/operative decisions such as the selections of product’s treatments to realize and the policy of returns or prices, among other decisions. Originality/value: The identification of the main decisions types of the reverse logistics will allow the managers of these processes to know and understand them better, while offer an integrated vision of them, favoring the achievement of better results.

Empirical Descriptions of Criminal Sentencing Decision-Making

Directory of Open Access Journals (Sweden)

Rasmus H. Wandall

2014-05-01

Full Text Available The article addresses the widespread use of statistical causal modelling to describe criminal sentencing decision-making empirically in Scandinavia. The article describes the characteristics of this model, and on this basis discusses three aspects of sentencing decision-making that the model does not capture: 1 the role of law and legal structures in sentencing, 2 the processes of constructing law and facts as they occur in the processes of handling criminal cases, and 3 reflecting newer organisational changes to sentencing decision-making. The article argues for a stronger empirically based design of sentencing models and for a more balanced use of different social scientific methodologies and models of sentencing decision-making.

Data acquisition in modeling using neural networks and decision trees

Directory of Open Access Journals (Sweden)

R. Sika

2011-04-01

Full Text Available The paper presents a comparison of selected models from area of artificial neural networks and decision trees in relation with actualconditions of foundry processes. The work contains short descriptions of used algorithms, their destination and method of data preparation,which is a domain of work of Data Mining systems. First part concerns data acquisition realized in selected iron foundry, indicating problems to solve in aspect of casting process modeling. Second part is a comparison of selected algorithms: a decision tree and artificial neural network, that is CART (Classification And Regression Trees and BP (Backpropagation in MLP (Multilayer Perceptron networks algorithms.Aim of the paper is to show an aspect of selecting data for modeling, cleaning it and reducing, for example due to too strong correlationbetween some of recorded process parameters. Also, it has been shown what results can be obtained using two different approaches:first when modeling using available commercial software, for example Statistica, second when modeling step by step using Excel spreadsheetbasing on the same algorithm, like BP-MLP. Discrepancy of results obtained from these two approaches originates from a priorimade assumptions. Mentioned earlier Statistica universal software package, when used without awareness of relations of technologicalparameters, i.e. without user having experience in foundry and without scheduling ranks of particular parameters basing on acquisition, can not give credible basis to predict the quality of the castings. Also, a decisive influence of data acquisition method has been clearly indicated, the acquisition should be conducted according to repetitive measurement and control procedures. This paper is based on about 250 records of actual data, for one assortment for 6 month period, where only 12 data sets were complete (including two that were used for validation of neural network and useful for creating a model. It is definitely too

Multiobjective Optimization of Aircraft Maintenance in Thailand Using Goal Programming: A Decision-Support Model

Directory of Open Access Journals (Sweden)

Yuttapong Pleumpirom

2012-01-01

Full Text Available The purpose of this paper is to develop the multiobjective optimization model in order to evaluate suppliers for aircraft maintenance tasks, using goal programming. The authors have developed a two-step process. The model will firstly be used as a decision-support tool for managing demand, by using aircraft and flight schedules to evaluate and generate aircraft-maintenance requirements, including spare-part lists. Secondly, they develop a multiobjective optimization model by minimizing cost, minimizing lead time, and maximizing the quality under various constraints in the model. Finally, the model is implemented in the actual airline's case.

Case analysis online: a strategic management case model for the health industry.

Science.gov (United States)

Walsh, Anne; Bearden, Eithne

2004-01-01

Despite the plethora of methods and tools available to support strategic management, the challenge for health executives in the next century will relate to their ability to access and interpret data from multiple and intricate communication networks. Integrated digital networks and satellite systems will expand the scope and ease of sharing information between business divisions, and networked systems will facilitate the use of virtual case discussions across universities. While the internet is frequently used to support clinical decisions in the healthcare industry, few executives rely upon the internetfor strategic analysis. Although electronic technologies can easily synthesize data from multiple information channels, research as well as technical issues may deter their application in strategic analysis. As digital models transform access to information, online models may become increasingly relevant in designing strategic solutions. While there are various pedagogical models available to support the strategic management process, this framework was designed to enhance strategic analysis through the application of technology and electronic research. A strategic analysis framework, which incorporated internet research and case analysis in a strategic managementcourse, is described alongwith design and application issues that emerged during the case analysis process.

The Limitations of Applying Rational Decision-Making Models

African Journals Online (AJOL)

decision-making models as applied to child spacing and more. specificaDy to the use .... also assumes that the individual operates as a rational decision- making organism in ..... work involves: Motivation; Counselling; Distribution ofIEC mate-.

Predicting Lung Radiotherapy-Induced Pneumonitis Using a Model Combining Parametric Lyman Probit With Nonparametric Decision Trees

International Nuclear Information System (INIS)

Das, Shiva K.; Zhou Sumin; Zhang, Junan; Yin, F.-F.; Dewhirst, Mark W.; Marks, Lawrence B.

2007-01-01

Purpose: To develop and test a model to predict for lung radiation-induced Grade 2+ pneumonitis. Methods and Materials: The model was built from a database of 234 lung cancer patients treated with radiotherapy (RT), of whom 43 were diagnosed with pneumonitis. The model augmented the predictive capability of the parametric dose-based Lyman normal tissue complication probability (LNTCP) metric by combining it with weighted nonparametric decision trees that use dose and nondose inputs. The decision trees were sequentially added to the model using a 'boosting' process that enhances the accuracy of prediction. The model's predictive capability was estimated by 10-fold cross-validation. To facilitate dissemination, the cross-validation result was used to extract a simplified approximation to the complicated model architecture created by boosting. Application of the simplified model is demonstrated in two example cases. Results: The area under the model receiver operating characteristics curve for cross-validation was 0.72, a significant improvement over the LNTCP area of 0.63 (p = 0.005). The simplified model used the following variables to output a measure of injury: LNTCP, gender, histologic type, chemotherapy schedule, and treatment schedule. For a given patient RT plan, injury prediction was highest for the combination of pre-RT chemotherapy, once-daily treatment, female gender and lowest for the combination of no pre-RT chemotherapy and nonsquamous cell histologic type. Application of the simplified model to the example cases revealed that injury prediction for a given treatment plan can range from very low to very high, depending on the settings of the nondose variables. Conclusions: Radiation pneumonitis prediction was significantly enhanced by decision trees that added the influence of nondose factors to the LNTCP formulation

Strategic decisions in transport: a case study for a naval base selection in Brazil

Directory of Open Access Journals (Sweden)

Amaury Caruzzo

2016-04-01

Full Text Available A decision on a military strategic environment, such as the selection of a new naval base, is a complex process and involves various criteria. In this context, few studies are available on the problems of military-naval transport decisions. Therefore, the aim of this paper is to present a maritime transport case study using a multi-methodology framework in a process of strategic decision making in logistics. Through a review of the literature, normative documents from the Brazilian armed forces, and interviews with military officers, criteria and preferences were identified and a hierarchical structure was constructed for a case study in the Brazilian Navy–the location of the second Fleet Headquarters. The results indicated that São Marcos Bay, in Maranhão State, was the best location among the alternatives. The multi-criteria approach was shown to be a valuable tool in assisting the decision making process and to understand the trade-offs between strategic and operational criteria in a transport decision.

Reliability analysis framework for computer-assisted medical decision systems

International Nuclear Information System (INIS)

Habas, Piotr A.; Zurada, Jacek M.; Elmaghraby, Adel S.; Tourassi, Georgia D.

2007-01-01

We present a technique that enhances computer-assisted decision (CAD) systems with the ability to assess the reliability of each individual decision they make. Reliability assessment is achieved by measuring the accuracy of a CAD system with known cases similar to the one in question. The proposed technique analyzes the feature space neighborhood of the query case to dynamically select an input-dependent set of known cases relevant to the query. This set is used to assess the local (query-specific) accuracy of the CAD system. The estimated local accuracy is utilized as a reliability measure of the CAD response to the query case. The underlying hypothesis of the study is that CAD decisions with higher reliability are more accurate. The above hypothesis was tested using a mammographic database of 1337 regions of interest (ROIs) with biopsy-proven ground truth (681 with masses, 656 with normal parenchyma). Three types of decision models, (i) a back-propagation neural network (BPNN), (ii) a generalized regression neural network (GRNN), and (iii) a support vector machine (SVM), were developed to detect masses based on eight morphological features automatically extracted from each ROI. The performance of all decision models was evaluated using the Receiver Operating Characteristic (ROC) analysis. The study showed that the proposed reliability measure is a strong predictor of the CAD system's case-specific accuracy. Specifically, the ROC area index for CAD predictions with high reliability was significantly better than for those with low reliability values. This result was consistent across all decision models investigated in the study. The proposed case-specific reliability analysis technique could be used to alert the CAD user when an opinion that is unlikely to be reliable is offered. The technique can be easily deployed in the clinical environment because it is applicable with a wide range of classifiers regardless of their structure and it requires neither additional

The International Decision Support Initiative Reference Case for Economic Evaluation: An Aid to Thought.

Science.gov (United States)

Wilkinson, Thomas; Sculpher, Mark J; Claxton, Karl; Revill, Paul; Briggs, Andrew; Cairns, John A; Teerawattananon, Yot; Asfaw, Elias; Lopert, Ruth; Culyer, Anthony J; Walker, Damian G

2016-12-01

Policymakers in high-, low-, and middle-income countries alike face challenging choices about resource allocation in health. Economic evaluation can be useful in providing decision makers with the best evidence of the anticipated benefits of new investments, as well as their expected opportunity costs-the benefits forgone of the options not chosen. To guide the decisions of health systems effectively, it is important that the methods of economic evaluation are founded on clear principles, are applied systematically, and are appropriate to the decision problems they seek to inform. The Bill and Melinda Gates Foundation, a major funder of economic evaluations of health technologies in low- and middle-income countries (LMICs), commissioned a "reference case" through the International Decision Support Initiative (iDSI) to guide future evaluations, and improve both the consistency and usefulness to decision makers. The iDSI Reference Case draws on previous insights from the World Health Organization, the US Panel on Cost-Effectiveness in Health Care, and the UK National Institute for Health and Care Excellence. Comprising 11 key principles, each accompanied by methodological specifications and reporting standards, the iDSI Reference Case also serves as a means of identifying priorities for methods research, and can be used as a framework for capacity building and technical assistance in LMICs. The iDSI Reference Case is an aid to thought, not a substitute for it, and should not be followed slavishly without regard to context, culture, or history. This article presents the iDSI Reference Case and discusses the rationale, approach, components, and application in LMICs. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Confronting evidence: individualised care and the case for shared decision-making.

LENUS (Irish Health Repository)

Ryan, P

2014-11-01

In many clinical scenarios there exists more than one clinically appropriate intervention strategy. When these involve subjective trade-offs between potential benefits and harms, patients\\' preferences should inform decision-making. Shared decision-making is a collaborative process, where clinician and patient reconcile the best available evidence with respect for patients\\' individualized care preferences. In practice, clinicians may be poorly equipped to participate in this process. Shared decision-making is applicable to many conditions including stable coronary artery disease, end-of-life care, and numerous small decisions in chronic disease management. There is evidence of more clinically appropriate care patterns, improved patient understanding and sense of empowerment. Many trials reported a 20% reduction in major surgery in favour of conservative treatment, although demand tends to increase for some interventions. The generalizability of international evidence to Ireland is unclear. Considering the potential benefits, there is a case for implementing and evaluating shared decision-making pilot projects in Ireland.

Narrative medicine and decision-making capacity.

Science.gov (United States)

Mahr, Greg

2015-06-01

The author proposes a new model for the assessment of decision-making capacity based on the principles of narrative medicine. The narrative method proposed by the author addresses the hidden power realtionships implicit in the current model of capacity assessment. Sample cases are reviewed using the traditional model in comparison with the narrative model. Narrative medicine provides an effective model for the assessment of decision-making capacity. Deficiencies in the traditional model capacity assessment can be effectively addressed using narrative strategies. © 2015 John Wiley & Sons, Ltd.

The case for repeatable analysis with energy economy optimization models

International Nuclear Information System (INIS)

DeCarolis, Joseph F.; Hunter, Kevin; Sreepathi, Sarat

2012-01-01

Energy economy optimization (EEO) models employ formal search techniques to explore the future decision space over several decades in order to deliver policy-relevant insights. EEO models are a critical tool for decision-makers who must make near-term decisions with long-term effects in the face of large future uncertainties. While the number of model-based analyses proliferates, insufficient attention is paid to transparency in model development and application. Given the complex, data-intensive nature of EEO models and the general lack of access to source code and data, many of the assumptions underlying model-based analysis are hidden from external observers. This paper discusses the simplifications and subjective judgments involved in the model building process, which cannot be fully articulated in journal papers, reports, or model documentation. In addition, we argue that for all practical purposes, EEO model-based insights cannot be validated through comparison to real world outcomes. As a result, modelers are left without credible metrics to assess a model's ability to deliver reliable insight. We assert that EEO models should be discoverable through interrogation of publicly available source code and data. In addition, third parties should be able to run a specific model instance in order to independently verify published results. Yet a review of twelve EEO models suggests that in most cases, replication of model results is currently impossible. We provide several recommendations to help develop and sustain a software framework for repeatable model analysis.

Optimal Decision-making Model of Integrated Water Resources Management - A Case of Hsinchu Water Resources Management

Science.gov (United States)

Wang, S. Y.; Ho, C. C.; Chang, L. C.

2017-12-01

The public use water in Hsinchu are mainly supplied from Baoshan Reservoir, Second Baoshan Reservoir, Yongheshan Reservoir and Longen Weir. However, the increasing water demand, caused by development of the Hsinchu Science and Industrial Park, results in supply stable water getting more difficult. For stabilize water supply in Hsinchu, the study applies long-term and short-term plans to fulfill the water shortage. Developing an efficient methodology to define a cost-effective action portfolio is an important task. Hence, the study develops a novel decision model, the Stochastic Programming with Recourse Decision Model (SPRDM), to estimate a cost-effective action portfolio. The first-stage of SPRDM determine the long-term action portfolio and the portfolio accompany recourse information (the probability for water shortage event). The second-stage of SPRDM optimize the cost-effective action portfolio in response to the recourse information. In order to consider the uncertainty of reservoir sediment and demand growth, the study set 9 scenarios comprise optimistic, most likely, and pessimistic reservoir sediment and demand growth. The results show the optimal action portfolio consist of FengTain Lake and Panlon Weir, Hsinchu Desalination Plant, Domestic and Industrial Water long-term plans, and Emergency Backup Well, Irrigation Water Transference, Preliminary Water Rationing, Advanced Water Rationing and Water Transport from Other Districts short-term plans. The minimum expected cost of optimal action portfolio is NT$1.1002 billion. The results can be used as a reference for decision making because the results have considered the uncertainty of varied hydrology, reservoir sediment, and water demand growth.

Optimal policy for value-based decision-making.

Science.gov (United States)

Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

2016-08-18

For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down.

Elements for the Design of a Decision-making Information System for activities related to genetically modified organisms: Contributions from a case study

International Nuclear Information System (INIS)

Benavides Molineros, Julia; Aguirre Ramirez, Nestor

2012-01-01

In Colombia, decisions related to genetically modified organisms (GMOs) must be supported by assessment of the risk to biodiversity, human health and agricultural production. Based on this assessment, authorities can make decisions involving authorization or denial of the requested activities. The rationality of the decision-making process is very well established with respect to human health, particularly toxicity and allergenicity, but that is not the case for biodiversity issues. One of the biggest problems in this area is the lack of definition of a decision-making methodology, which leads to decisions made in an intuitive and non-systematic manner. Authorities in the field have recognized the need for a decision-making information system to help solve this situation. A proposal for the basic structure of a decision-making information system oriented to authorities involved in the process is presented. The proposal was developed based on a review of the main existing methodologies for GMO risk assessment and on a case study of the gene flow from GMOs to wild relatives. The structure is presented as a broad entity-relationship model from which the detailed design of the system can be developed. The proposal emphasizes the documentation of the decision protocols and the rationality of use of the information inputs.

Discrete Event Simulation for Decision Modeling in Health Care: Lessons from Abdominal Aortic Aneurysm Screening

Science.gov (United States)

Jones, Edmund; Masconi, Katya L.; Sweeting, Michael J.; Thompson, Simon G.; Powell, Janet T.

2018-01-01

Markov models are often used to evaluate the cost-effectiveness of new healthcare interventions but they are sometimes not flexible enough to allow accurate modeling or investigation of alternative scenarios and policies. A Markov model previously demonstrated that a one-off invitation to screening for abdominal aortic aneurysm (AAA) for men aged 65 y in the UK and subsequent follow-up of identified AAAs was likely to be highly cost-effective at thresholds commonly adopted in the UK (£20,000 to £30,000 per quality adjusted life-year). However, new evidence has emerged and the decision problem has evolved to include exploration of the circumstances under which AAA screening may be cost-effective, which the Markov model is not easily able to address. A new model to handle this more complex decision problem was needed, and the case of AAA screening thus provides an illustration of the relative merits of Markov models and discrete event simulation (DES) models. An individual-level DES model was built using the R programming language to reflect possible events and pathways of individuals invited to screening v. those not invited. The model was validated against key events and cost-effectiveness, as observed in a large, randomized trial. Different screening protocol scenarios were investigated to demonstrate the flexibility of the DES. The case of AAA screening highlights the benefits of DES, particularly in the context of screening studies.

A Dynamic Bayesian Model for Characterizing Cross-Neuronal Interactions During Decision-Making.

Science.gov (United States)

Zhou, Bo; Moorman, David E; Behseta, Sam; Ombao, Hernando; Shahbaba, Babak

2016-01-01

The goal of this paper is to develop a novel statistical model for studying cross-neuronal spike train interactions during decision making. For an individual to successfully complete the task of decision-making, a number of temporally-organized events must occur: stimuli must be detected, potential outcomes must be evaluated, behaviors must be executed or inhibited, and outcomes (such as reward or no-reward) must be experienced. Due to the complexity of this process, it is likely the case that decision-making is encoded by the temporally-precise interactions between large populations of neurons. Most existing statistical models, however, are inadequate for analyzing such a phenomenon because they provide only an aggregated measure of interactions over time. To address this considerable limitation, we propose a dynamic Bayesian model which captures the time-varying nature of neuronal activity (such as the time-varying strength of the interactions between neurons). The proposed method yielded results that reveal new insight into the dynamic nature of population coding in the prefrontal cortex during decision making. In our analysis, we note that while some neurons in the prefrontal cortex do not synchronize their firing activity until the presence of a reward, a different set of neurons synchronize their activity shortly after stimulus onset. These differentially synchronizing sub-populations of neurons suggests a continuum of population representation of the reward-seeking task. Secondly, our analyses also suggest that the degree of synchronization differs between the rewarded and non-rewarded conditions. Moreover, the proposed model is scalable to handle data on many simultaneously-recorded neurons and is applicable to analyzing other types of multivariate time series data with latent structure. Supplementary materials (including computer codes) for our paper are available online.

Provincial prenatal record revision: a multiple case study of evidence-based decision-making at the population-policy level

Directory of Open Access Journals (Sweden)

Olson Joanne

2008-12-01

Full Text Available Abstract Background There is a significant gap in the knowledge translation literature related to how research evidence actually contributes to health care decision-making. Decisions around what care to provide at the population (rather than individual level are particularly complex, involving considerations such as feasibility, cost, and population needs in addition to scientific evidence. One example of decision-making at this "population-policy" level involves what screening questions and intervention guides to include on standardized provincial prenatal records. As mandatory medical reporting forms, prenatal records are potentially powerful vehicles for promoting population-wide evidence-based care. However, the extent to which Canadian prenatal records reflect best-practice recommendations for the assessment of well-known risk factors such as maternal smoking and alcohol consumption varies markedly across Canadian provinces and territories. The goal of this study is to better understand the interaction of contextual factors and research evidence on decision-making at the population-policy level, by examining the processes by which provincial prenatal records are reviewed and revised. Methods Guided by Dobrow et al.'s (2004 conceptual model for context-based evidence-based decision-making, this study will use a multiple case study design with embedded units of analysis to examine contextual factors influencing the prenatal record revision process in different Canadian provinces and territories. Data will be collected using multiple methods to construct detailed case descriptions for each province/territory. Using qualitative data analysis techniques, decision-making processes involving prenatal record content specifically related to maternal smoking and alcohol use will be compared both within and across each case, to identify key contextual factors influencing the uptake and application of research evidence by prenatal record review

A procurement decision model for a video rental store — A case study

African Journals Online (AJOL)

eral; hence the video rental store owner (the decision maker) is required to procure new ... process by presenting a point of departure from which procurement decisions may be made. .... M = number of titles available for purchase,. Qi.

Relevance of a Managerial Decision-Model to Educational Administration.

Science.gov (United States)

Lundin, Edward.; Welty, Gordon

The rational model of classical economic theory assumes that the decision maker has complete information on alternatives and consequences, and that he chooses the alternative that maximizes expected utility. This model does not allow for constraints placed on the decision maker resulting from lack of information, organizational pressures,…

Operational readiness decisions at nuclear power plants. Which factors influence the decisions?

International Nuclear Information System (INIS)

Kecklund, Lena; Petterson, Sara

2007-11-01

The purpose of this project has been to propose a model for how operational readiness decisions are made and to identify important factors influencing these decisions. The project has also studied the support from the management system for decision making, and made a comparison to how decisions are made in practice. This is mainly an explorative study, but it also deals with relevant research and theories about decision making. The project consists of several parts. The first part is composed of descriptions of important notations and terms, and a summary of relevant research about decision making and its relation to the management system. The project proposes a model for the decision making process. The second part consists of analyses of reports from SKI about operational readiness decisions. The last part is a case study at a nuclear power plant. The case study describes the support from work method theories at the nuclear power plant to the decision maker. Decision makers with different roles in the safety management system were interviewed to give a description of the decision making process and of factors influencing the decisions made in practice. The case study also consists of an analysis of decisions in some real events at the nuclear power plant, as well as of making interviews in connection with these. To sum up, this report presents a model for the decision process and describes the work method theories that support the different parts in the process, how the different parts are applied in practice and circumstances that influence the decision process. The results of the project give an understanding for decision making in operational readiness decisions and the factors that influence the decision. The results are meant to be used as a basis for further studies in other nuclear power plants. The results indicate that the decision process is facilitated if there are clear criteria and work methods, if the work methods are well established and if the

Modeling Common-Sense Decisions in Artificial Intelligence

Science.gov (United States)

Zak, Michail

2010-01-01

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation

The Decision Module Working Paper

Science.gov (United States)

1973-12-01

and goal change has received very little attention In the litera- ture on the analysis of choice situations. It has generally been the case that the...Decision Making: Approach and Prototype" (197:0, done In context of the Mesarovlc - Pestel World Model Projet’ The Issues dealing with «-he cho ce...Nelson, Winder, and Schuette (1973) on evolutionary economic growth models. The discussion of the two components of the decision module that follows

The Vroom and Yetton Normative Leadership Model Applied to Public School Case Examples.

Science.gov (United States)

Sample, John

This paper seeks to familiarize school administrators with the Vroom and Yetton Normative Leadership model by presenting its essential components and providing original case studies for its application to school settings. The five decision-making methods of the Vroom and Yetton model, including two "autocratic," two…

Applying Case-Based Reasoning in Supporting Strategy Decisions

OpenAIRE

S. M. Seyedhosseini; A. Makui; M. Ghadami

2011-01-01

Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, ...

Conflict within the Turkish foreign policy decision making mechanism:

OpenAIRE

Oğuz, Mustafa; Oguz, Mustafa

2005-01-01

This thesis presents an analysis of Turkish foreign policy decision making in a theoretical model and argues that Turkish foreign policy is a product of negotiation and compromises among various foreign policy making actors. Theoretical foundation is built on decision units framework advanced by Margaret G. Herman. It applies this framework to two cases and four decision occasions to investigate who made foreign policy decisions and how this influenced foreign policy of Turkey. The first case...

On the impact of optimisation models in maintenance decision making: the state of the art

International Nuclear Information System (INIS)

Dekker, Rommert; Scarf, Philip A.

1998-01-01

In this paper we discuss the state of the art in applications of maintenance optimisation models. After giving a short introduction to the area, we consider several ways in which models may be used to optimise maintenance, such as case studies, operational and strategic decision support systems, and give examples of each of them. Next we discuss several areas where the models have been applied successfully. These include civil structure and aeroplane maintenance. From a comparative point of view, we discuss future prospects

Translational Models of Gambling-Related Decision-Making.

Science.gov (United States)

Winstanley, Catharine A; Clark, Luke

Gambling is a harmless, recreational pastime that is ubiquitous across cultures. However, for some, gambling becomes a maladaptive and compulsive, and this syndrome is conceptualized as a behavioural addiction. Laboratory models that capture the key cognitive processes involved in gambling behaviour, and that can be translated across species, have the potential to make an important contribution to both decision neuroscience and the study of addictive disorders. The Iowa gambling task has been widely used to assess human decision-making under uncertainty, and this paradigm can be successfully modelled in rodents. Similar neurobiological processes underpin choice behaviour in humans and rats, and thus, a preference for the disadvantageous "high-risk, high-reward" options may reflect meaningful vulnerability for mental health problems. However, the choice behaviour operationalized by these tasks does not necessarily approximate the vulnerability to gambling disorder (GD) per se. We consider a number of psychological challenges that apply to modelling gambling in a translational way, and evaluate the success of the existing models. Heterogeneity in the structure of gambling games, as well as in the motivations of individuals with GD, is highlighted. The potential issues with extrapolating too directly from established animal models of drug dependency are discussed, as are the inherent difficulties in validating animal models of GD in the absence of any approved treatments for GD. Further advances in modelling the cognitive biases endemic in human decision-making, which appear to be exacerbated in GD, may be a promising line of research.

Modeling Feedbacks Between Individual Human Decisions and Hydrology Using Interconnected Physical and Social Models

Science.gov (United States)

Murphy, J.; Lammers, R. B.; Proussevitch, A. A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Alessa, L.; Kliskey, A. D.

2014-12-01

The global hydrological cycle intersects with human decision making at multiple scales, from dams and irrigation works to the taps in individuals' homes. Residential water consumers are commonly encouraged to conserve; these messages are heard against a background of individual values and conceptions about water quality, uses, and availability. The degree to which these values impact the larger-hydrological dynamics, the way that changes in those values have impacts on the hydrological cycle through time, and the feedbacks by which water availability and quality in turn shape those values, are not well explored. To investigate this domain we employ a global-scale water balance model (WBM) coupled with a social-science-grounded agent-based model (ABM). The integration of a hydrological model with an agent-based model allows us to explore driving factors in the dynamics in coupled human-natural systems. From the perspective of the physical hydrologist, the ABM offers a richer means of incorporating the human decisions that drive the hydrological system; from the view of the social scientist, a physically-based hydrological model allows the decisions of the agents to play out against constraints faithful to the real world. We apply the interconnected models to a study of Tucson, Arizona, USA, and its role in the larger Colorado River system. Our core concept is Technology-Induced Environmental Distancing (TIED), which posits that layers of technology can insulate consumers from direct knowledge of a resource. In Tucson, multiple infrastructure and institutional layers have arguably increased the conceptual distance between individuals and their water supply, offering a test case of the TIED framework. Our coupled simulation allows us to show how the larger system transforms a resource with high temporal and spatial variability into a consumer constant, and the effects of this transformation on the regional system. We use this to explore how pricing, messaging, and

Human Errors in Decision Making

OpenAIRE

Mohamad, Shahriari; Aliandrina, Dessy; Feng, Yan

2005-01-01

The aim of this paper was to identify human errors in decision making process. The study was focused on a research question such as: what could be the human error as a potential of decision failure in evaluation of the alternatives in the process of decision making. Two case studies were selected from the literature and analyzed to find the human errors contribute to decision fail. Then the analysis of human errors was linked with mental models in evaluation of alternative step. The results o...

Improving rural electricity system planning: An agent-based model for stakeholder engagement and decision making

International Nuclear Information System (INIS)

Alfaro, Jose F.; Miller, Shelie; Johnson, Jeremiah X.; Riolo, Rick R.

2017-01-01

Energy planners in regions with low rates of electrification face complex and high-risk challenges in selecting appropriate generating technologies and grid centralization. To better inform such processes, we present an Agent-Based Model (ABM) that facilitates engagement with stakeholders. This approach evaluates long-term plans using the cost of delivered electricity, resource mix, jobs and economic stimulus created within communities, and decentralized generation mix of the system, with results provided in a spatially-resolved format. This approach complements existing electricity planning methods (e.g., Integrated Resource Planning) by offering novel evaluation criteria based on typical stakeholder preferences. We demonstrate the utility of this approach with a case study based on a “blank-slate” scenario, which begins without generation or transmission infrastructure, for the long-term rural renewable energy plans of Liberia, West Africa. We consider five electrification strategies: prioritizing larger populations, deploying large resources, creating jobs, providing economic stimulus, and step-wise cost minimization. Through the case study we demonstrate how this approach can be used to engage stakeholders, supplement more established energy planning tools, and illustrate the effects of stakeholder decisions and preferences on the performance of the system. - Highlights: • An Agent Based Model, BABSTER, for electrification planning is presented. • BABSTER provides a highly engaging spatially resolved interface. • Allows flexible investigation of decision strategies with real-world incentives. • We show that decision strategies directly impact centralization and resource choice. • It is illustrated through the case study of Liberia, West Africa.

Use of multi-criteria decision analysis in public bidding processes: a case study

Directory of Open Access Journals (Sweden)

André Andrade Longaray

2014-02-01

Full Text Available Institutions of Higher Education in Brazil (IFES play an important role in the country’s social and scientific development. Focused mainly on teaching, research and extension activities, the IFES are backed by support foundations aimed to the management of financial, human and material resources. Characterized as public bodies, the support foundations are governed by Law no 8.666/93 in what concerns the procurement of goods and services. Therefore, the present study is aimed to develop a model to assist the managers of such foundations in the selection of suppliers to participate in bidding processes that use invitation for bids. Therefore, we conducted a case study in one of the 55 foundations that support Brazilian federal universities. The intervention tool used was the Analytic Hierarchy Process (AHP. Firstly, we established the hierarchy of criteria for problem-solving. Then, a paired comparison was made between criteria for the same level. Subsequently, the consistency analysis of comparison matrices was verified. Finally, the relative priorities of each criterion were obtained and the objective function of the model was constructed. The model was tested through the assessment of the performance of three potential suppliers of IT equipment, and the result was legitimized by decision makers who found the instrument a valid tool to aid in making decisions on supplier selection for the foundation.

Intuitionistic preference modeling and interactive decision making

CERN Document Server

Xu, Zeshui

2014-01-01

This book offers an in-depth and comprehensive introduction to the priority methods of intuitionistic preference relations, the consistency and consensus improving procedures for intuitionistic preference relations, the approaches to group decision making based on intuitionistic preference relations, the approaches and models for interactive decision making with intuitionistic fuzzy information, and the extended results in interval-valued intuitionistic fuzzy environments.

A methodological model to assist in the optimization and risk management of mining investment decisions

International Nuclear Information System (INIS)

Botin, Jose A; Guzman, Ronald R; Smith, Martin L

2011-01-01

Identifying, quantifying, and minimizing technical risks associated with investment decisions is a key challenge for mineral industry decision makers and investors. However, risk analysis in most bankable mine feasibility studies are based on the stochastic modeling of project N et Present Value (NPV)which, in most cases, fails to provide decision makers with a truly comprehensive analysis of risks associated with technical and management uncertainty and, as a result, are of little use for risk management and project optimization. This paper presents a value-chain risk management approach where project risk is evaluated for each step of the project life cycle, from exploration to mine closure, and risk management is performed as a part of a stepwise value-added optimization process.

Modelling a flows in supply chain with analytical models: Case of a chemical industry

Science.gov (United States)

Benhida, Khalid; Azougagh, Yassine; Elfezazi, Said

2016-02-01

This study is interested on the modelling of the logistics flows in a supply chain composed on a production sites and a logistics platform. The contribution of this research is to develop an analytical model (integrated linear programming model), based on a case study of a real company operating in the phosphate field, considering a various constraints in this supply chain to resolve the planning problems for a better decision-making. The objectives of this model is to determine and define the optimal quantities of different products to route, to and from the various entities in the supply chain studied.

Beyond pain: modeling decision-making deficits in chronic pain

Science.gov (United States)

Hess, Leonardo Emanuel; Haimovici, Ariel; Muñoz, Miguel Angel; Montoya, Pedro

2014-01-01

Risky decision-making seems to be markedly disrupted in patients with chronic pain, probably due to the high cost that impose pain and negative mood on executive control functions. Patients’ behavioral performance on decision-making tasks such as the Iowa Gambling Task (IGT) is characterized by selecting cards more frequently from disadvantageous than from advantageous decks, and by switching often between competing responses in comparison with healthy controls (HCs). In the present study, we developed a simple heuristic model to simulate individuals’ choice behavior by varying the level of decision randomness and the importance given to gains and losses. The findings revealed that the model was able to differentiate the behavioral performance of patients with chronic pain and HCs at the group, as well as at the individual level. The best fit of the model in patients with chronic pain was yielded when decisions were not based on previous choices and when gains were considered more relevant than losses. By contrast, the best account of the available data in HCs was obtained when decisions were based on previous experiences and losses loomed larger than gains. In conclusion, our model seems to provide useful information to measure each individual participant extensively, and to deal with the data on a participant-by-participant basis. PMID:25136301

Beyond pain: modeling decision-making deficits in chronic pain.

Science.gov (United States)

Hess, Leonardo Emanuel; Haimovici, Ariel; Muñoz, Miguel Angel; Montoya, Pedro

2014-01-01

Risky decision-making seems to be markedly disrupted in patients with chronic pain, probably due to the high cost that impose pain and negative mood on executive control functions. Patients' behavioral performance on decision-making tasks such as the Iowa Gambling Task (IGT) is characterized by selecting cards more frequently from disadvantageous than from advantageous decks, and by switching often between competing responses in comparison with healthy controls (HCs). In the present study, we developed a simple heuristic model to simulate individuals' choice behavior by varying the level of decision randomness and the importance given to gains and losses. The findings revealed that the model was able to differentiate the behavioral performance of patients with chronic pain and HCs at the group, as well as at the individual level. The best fit of the model in patients with chronic pain was yielded when decisions were not based on previous choices and when gains were considered more relevant than losses. By contrast, the best account of the available data in HCs was obtained when decisions were based on previous experiences and losses loomed larger than gains. In conclusion, our model seems to provide useful information to measure each individual participant extensively, and to deal with the data on a participant-by-participant basis.

Models and theories of prescribing decisions: A review and suggested a new model

Science.gov (United States)

Mohaidin, Zurina

2017-01-01

To date, research on the prescribing decisions of physician lacks sound theoretical foundations. In fact, drug prescribing by doctors is a complex phenomenon influenced by various factors. Most of the existing studies in the area of drug prescription explain the process of decision-making by physicians via the exploratory approach rather than theoretical. Therefore, this review is an attempt to suggest a value conceptual model that explains the theoretical linkages existing between marketing efforts, patient and pharmacist and physician decision to prescribe the drugs. The paper follows an inclusive review approach and applies the previous theoretical models of prescribing behaviour to identify the relational factors. More specifically, the report identifies and uses several valuable perspectives such as the ‘persuasion theory - elaboration likelihood model’, the stimuli–response marketing model’, the ‘agency theory’, the theory of planned behaviour,’ and ‘social power theory,’ in developing an innovative conceptual paradigm. Based on the combination of existing methods and previous models, this paper suggests a new conceptual model of the physician decision-making process. This unique model has the potential for use in further research. PMID:28690701

Models and theories of prescribing decisions: A review and suggested a new model

Directory of Open Access Journals (Sweden)

Ali Murshid M

2017-06-01

Full Text Available To date, research on the prescribing decisions of physician lacks sound theoretical foundations. In fact, drug prescribing by doctors is a complex phenomenon influenced by various factors. Most of the existing studies in the area of drug prescription explain the process of decision-making by physicians via the exploratory approach rather than theoretical. Therefore, this review is an attempt to suggest a value conceptual model that explains the theoretical linkages existing between marketing efforts, patient and pharmacist and physician decision to prescribe the drugs. The paper follows an inclusive review approach and applies the previous theoretical models of prescribing behaviour to identify the relational factors. More specifically, the report identifies and uses several valuable perspectives such as the ‘persuasion theory - elaboration likelihood model’, the stimuli–response marketing model’, the ‘agency theory’, the theory of planned behaviour,’ and ‘social power theory,’ in developing an innovative conceptual paradigm. Based on the combination of existing methods and previous models, this paper suggests a new conceptual model of the physician decision-making process. This unique model has the potential for use in further research.

Functional Freedom: A Psychological Model of Freedom in Decision-Making

Science.gov (United States)

Lau, Stephan; Hiemisch, Anette

2017-01-01

The freedom of a decision is not yet sufficiently described as a psychological variable. We present a model of functional decision freedom that aims to fill that role. The model conceptualizes functional freedom as a capacity of people that varies depending on certain conditions of a decision episode. It denotes an inner capability to consciously shape complex decisions according to one’s own values and needs. Functional freedom depends on three compensatory dimensions: it is greatest when the decision-maker is highly rational, when the structure of the decision is highly underdetermined, and when the decision process is strongly based on conscious thought and reflection. We outline possible research questions, argue for psychological benefits of functional decision freedom, and explicate the model’s implications on current knowledge and research. In conclusion, we show that functional freedom is a scientific variable, permitting an additional psychological foothold in research on freedom, and that is compatible with a deterministic worldview. PMID:28678165

Examining Preservice Teachers' Classroom Management Decisions in Three Case-Based Teaching Approaches

Science.gov (United States)

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

This study was aimed at comparing the impact of three types of case-based approaches (worked example, faded work example, and case-based reasoning) on preservice teachers' decision making and reasoning skills related to realistic classroom management situations. Participants in this study received a short-term implementation of one of these three…

Independence and interdependence in collective decision making: an agent-based model of nest-site choice by honeybee swarms

Science.gov (United States)

List, Christian; Elsholtz, Christian; Seeley, Thomas D.

2008-01-01

Condorcet's jury theorem shows that when the members of a group have noisy but independent information about what is best for the group as a whole, majority decisions tend to outperform dictatorial ones. When voting is supplemented by communication, however, the resulting interdependencies between decision makers can strengthen or undermine this effect: they can facilitate information pooling, but also amplify errors. We consider an intriguing non-human case of independent information pooling combined with communication: the case of nest-site choice by honeybee (Apis mellifera) swarms. It is empirically well documented that when there are different nest sites that vary in quality, the bees usually choose the best one. We develop a new agent-based model of the bees' decision process and show that its remarkable reliability stems from a particular interplay of independence and interdependence between the bees. PMID:19073474

The interrogation decision-making model: A general theoretical framework for confessions.

Science.gov (United States)

Yang, Yueran; Guyll, Max; Madon, Stephanie

2017-02-01

This article presents a new model of confessions referred to as the interrogation decision-making model . This model provides a theoretical umbrella with which to understand and analyze suspects' decisions to deny or confess guilt in the context of a custodial interrogation. The model draws upon expected utility theory to propose a mathematical account of the psychological mechanisms that not only underlie suspects' decisions to deny or confess guilt at any specific point during an interrogation, but also how confession decisions can change over time. Findings from the extant literature pertaining to confessions are considered to demonstrate how the model offers a comprehensive and integrative framework for organizing a range of effects within a limited set of model parameters. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Introductie Decision Model and Notation (DMN) : Deel 3

NARCIS (Netherlands)

dr. Martijn Zoet; Koen Smit

2017-01-01

Sinds september 2015 is de ‘business rule management wereld’ / ‘decision management wereld’ weer een standaard rijker: The Decision Model and Notation (DMN). De Object Management Group (OMG) heeft deze nieuwe standaard uitgebracht met als doel een standaardtaal te creëren om 1) requirements voor

A Hybrid Multiple Criteria Decision Making Model for Supplier Selection

Directory of Open Access Journals (Sweden)

Chung-Min Wu

2013-01-01

Full Text Available The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP is then used to obtain their weights. To avoid calculation and additional pairwise comparisons of ANP, a technique for order preference by similarity to ideal solution (TOPSIS is used to rank the alternatives. The use of a combination of the fuzzy Delphi method, ANP, and TOPSIS, proposing an MCDM model for supplier selection, and applying these to a real case are the unique features of this study.

Exploring predictors of scientific performance with decision tree analysis: The case of research excellence in early career mathematics

Energy Technology Data Exchange (ETDEWEB)

Lindahl, J.

2016-07-01

The purpose of this study was (1) to introduce the exploratory method of decision tree analysis as a complementary alternative to current confirmatory methods used in scientometric prediction studies of research performance; and (2) as an illustrative case, to explore predictors of future research excellence at the individual level among 493 early career mathematicians in the sub-field of number theory between 1999 and 2010. A conceptual introduction to decision tree analysis is provided including an overview of the main steps of the tree-building algorithm and the statistical method of cross-validation used to evaluate the performance of decision tree models. A decision tree analysis of 493 mathematicians was conducted to find useful predictors and important relationships between variables in the context of predicting research excellence. The results suggest that the number of prestige journal publications and a topically diverse output are important predictors of future research excellence. Researchers with no prestige journal publications are very unlikely to produce excellent research. Limitations of decision three analysis are discussed. (Author)

Computer models for economic and silvicultural decisions

Science.gov (United States)

Rosalie J. Ingram

1989-01-01

Computer systems can help simplify decisionmaking to manage forest ecosystems. We now have computer models to help make forest management decisions by predicting changes associated with a particular management action. Models also help you evaluate alternatives. To be effective, the computer models must be reliable and appropriate for your situation.

Decision making in Brazil and emerging technologies: the case of 18F-FDG

International Nuclear Information System (INIS)

Sousa, Willy Hoppe de

2013-01-01

The article recalls the history of the development of Fluor FDG in Brazil. Important facts that impacted this development and how this technology evolved considering a time span of more then ten years, starting from 1996 is presented in this paper. Five decisions, taken between 2004 and 2005, were selected and analyzed from the perspective of knowledge that a key decision maker has developed around the main elements of a decision - problem, objectives, alternatives, consequences, risks approach and linked decisions. Contextual aspects that influenced these decisions, such as the evolution of the technology efficiency, installation of new equipment in hospitals and the consequences associated with these decisions, such as daily production capacity, distance service and numbers of attended clients are part of this study. In conclusion, this case shows that experienced decision makers can make quality decisions when they are equipped with the appropriate information, align the relevant decisions taken over time, know how to use the right tactics at the right time and with all participants in decision making. Experienced decision makers identify opportunities where there seems to be problems, review the current strategies and visualize new strategies, prepare themselves adequately to deal with the uncertainties. (author)

Using decision tree induction systems for modeling space-time behavior

NARCIS (Netherlands)

Arentze, T.A.; Hofman, F.; Mourik, van H.; Timmermans, H.J.P.; Wets, G.

2000-01-01

Discrete choice models are commonly used to predict individuals' activity and travel choices either separately or simultaneously in activity scheduling models. This paper investigates the possibilities of decision tree induction systems as an alternative approach. The ability of decision frees to

20 CFR 416.1484 - Appeals Council review of administrative law judge decision in a case remanded by a Federal court.

Science.gov (United States)

2010-04-01

... § 416.1484 Appeals Council review of administrative law judge decision in a case remanded by a Federal... proceedings leading to the final decision in your case or subsequently considered by the administrative law... reversing the decision of the administrative law judge, or it will remand the case to an administrative law...

[Mathematical models of decision making and learning].

Science.gov (United States)

Ito, Makoto; Doya, Kenji

2008-07-01

Computational models of reinforcement learning have recently been applied to analysis of brain imaging and neural recording data to identity neural correlates of specific processes of decision making, such as valuation of action candidates and parameters of value learning. However, for such model-based analysis paradigms, selecting an appropriate model is crucial. In this study we analyze the process of choice learning in rats using stochastic rewards. We show that "Q-learning," which is a standard reinforcement learning algorithm, does not adequately reflect the features of choice behaviors. Thus, we propose a generalized reinforcement learning (GRL) algorithm that incorporates the negative reward effect of reward loss and forgetting of values of actions not chosen. Using the Bayesian estimation method for time-varying parameters, we demonstrated that the GRL algorithm can predict an animal's choice behaviors as efficiently as the best Markov model. The results suggest the usefulness of the GRL for the model-based analysis of neural processes involved in decision making.

Introductie Decision Model and Notation (DMN) : Deel 1

NARCIS (Netherlands)

dr. Martijn Zoet; Koen Smit

2017-01-01

Sinds september 2015 is de ‘business rule management wereld’ / ‘decision management wereld’ weer een standaard rijker: The Decision Model and Notation (DMN). De Object Management Group (OMG) heeft deze nieuwe standaard uitgebracht met als doel een standaard taal te creëren om 1) requirements voor

Introductie Decision Model and Notation (DMN) : Deel 2

NARCIS (Netherlands)

dr. Martijn Zoet; Koen Smit

2017-01-01

Sinds september 2015 is de ‘business rule management wereld’ / ‘decision management wereld’ weer een standaard rijker: The Decision Model and Notation (DMN). De Object Management Group (OMG) heeft deze nieuwe standaard uitgebracht met als doel een standaard taal te creëren om 1) requirements voor

Decision support for choice optimal power generation projects: Fuzzy comprehensive evaluation model based on the electricity market

International Nuclear Information System (INIS)

Liang Zhihong; Yang Kun; Sun Yaowei; Yuan Jiahai; Zhang Hongwei; Zhang Zhizheng

2006-01-01

In 2002, China began to inspire restructuring of the electric power sector to improve its performance. Especially, with the rapid increase of electricity demand in China, there is a need for non-utility generation investment that cannot be met by government finance alone. However, a first prerequisite is that regulators and decision-makers (DMs) should carefully consider how to balance the need to attract private investment against the policy objectives of minimizing monopoly power and fostering competitive markets. So in the interim term of electricity market, a decentralized decision-making process should eventually replace the centralized generation capacity expansion planning. In this paper, firstly, on the basis of the current situation, a model for evaluating generation projects by comprehensive utilization of fuzzy appraisal and analytic hierarchy process (AHP) is developed. Secondly, a case study of generation project evaluation in China is presented to illustrate the effectiveness of the model in selecting optimal generation projects and attracting private investors. In the case study, with considerations of attracting adequate private investment and promoting energy conservation in China, five most promising policy instruments selected as evaluation factors include project duration, project costs, predicted on-grid price level, environmental protection, enterprise credit grading and performance. Finally, a comprehensive framework that enables the DM to have better concentration and to make more sound decisions by combining the model proposed with modern computer science is designed

Quantitative Decision Making Model for Carbon Reduction in Road Construction Projects Using Green Technologies

Directory of Open Access Journals (Sweden)

Woosik Jang

2015-08-01

Full Text Available Numerous countries have established policies for reducing greenhouse gas emissions and have suggested goals pertaining to these reductions. To reach the target reduction amounts, studies on the reduction of carbon emissions have been conducted with regard to all stages and processes in construction projects. According to a study on carbon emissions, the carbon emissions generated during the construction stage of road projects account for approximately 76 to 86% of the total carbon emissions, far exceeding the other stages, such as maintenance or demolition. Therefore, this study aims to develop a quantitative decision making model that supports the application of green technologies (GTs to reduce carbon emissions during the construction stage of road construction projects. First, the authors selected environmental soundness, economic feasibility and constructability as the key assessment indices for evaluating 20 GTs. Second, a fuzzy set/qualitative comparative analysis (FS/QCA was used to establish an objective decision-making model for the assessment of both the quantitative and qualitative characteristics of the key indices. To support the developed model, an expert survey was performed to assess the applicability of each GT from a practical perspective, which was verified with a case study using two additional GTs. The proposed model is expected to support practitioners in the application of suitable GTs to road projects and reduce carbon emissions, resulting in better decision making during road construction projects.

Uncertainty and sensitivity analysis of flood risk management decisions based on stationary and nonstationary model choices

Directory of Open Access Journals (Sweden)

Rehan Balqis M.

2016-01-01

Full Text Available Current practice in flood frequency analysis assumes that the stochastic properties of extreme floods follow that of stationary conditions. As human intervention and anthropogenic climate change influences in hydrometeorological variables are becoming evident in some places, there have been suggestions that nonstationary statistics would be better to represent the stochastic properties of the extreme floods. The probabilistic estimation of non-stationary models, however, is surrounded with uncertainty related to scarcity of observations and modelling complexities hence the difficulty to project the future condition. In the face of uncertain future and the subjectivity of model choices, this study attempts to demonstrate the practical implications of applying a nonstationary model and compares it with a stationary model in flood risk assessment. A fully integrated framework to simulate decision makers’ behaviour in flood frequency analysis is thereby developed. The framework is applied to hypothetical flood risk management decisions and the outcomes are compared with those of known underlying future conditions. Uncertainty of the economic performance of the risk-based decisions is assessed through Monte Carlo simulations. Sensitivity of the results is also tested by varying the possible magnitude of future changes. The application provides quantitative and qualitative comparative results that satisfy a preliminary analysis of whether the nonstationary model complexity should be applied to improve the economic performance of decisions. Results obtained from the case study shows that the relative differences of competing models for all considered possible future changes are small, suggesting that stationary assumptions are preferred to a shift to nonstationary statistics for practical application of flood risk management. Nevertheless, nonstationary assumption should also be considered during a planning stage in addition to stationary assumption

Beyond pain: modeling decision-making deficits in chronic pain

Directory of Open Access Journals (Sweden)

Leonardo Emanuel Hess

2014-08-01

Full Text Available Risky decision-making seems to be markedly disrupted in patients with chronic pain, probably due to the high cost that impose pain and negative mood on executive control functions. Patients’ behavioral performance on decision-making tasks such as the Iowa Gambling Task (IGT is characterized by selecting cards more frequently from disadvantageous than from advantageous decks, and by switching often between competing responses in comparison with healthy controls. In the present study, we developed a simple heuristic model to simulate individuals’ choice behavior by varying the level of decision randomness and the importance given to gains and losses. The findings revealed that the model was able to differentiate the behavioral performance of patients with chronic pain and healthy controls at the group, as well as at the individual level. The best fit of the model in patients with chronic pain was yielded when decisions were not based on previous choices and when gains were considered more relevant than losses. By contrast, the best account of the available data in healthy controls was obtained when decisions were based on previous experiences and losses loomed larger than gains. In conclusion, our model seems to provide useful information to measure each individual participant extensively, and to deal with the data on a participant-by-participant basis.

Gossip Management at Universities Using Big Data Warehouse Model Integrated with a Decision Support System

Directory of Open Access Journals (Sweden)

Pelin Vardarlier

2016-01-01

Full Text Available Big Data has recently been used for many purposes like medicine, marketing and sports. It has helped improve management decisions. However, for almost each case a unique data warehouse should be built to benefit from the merits of data mining and Big Data. Hence, each time we start from scratch to form and build a Big Data Warehouse. In this study, we propose a Big Data Warehouse and a model for universities to be used for information management, to be more specific gossip management. The overall model is a decision support system that may help university administraitons when they are making decisions and also provide them with information or gossips being circulated among students and staff. In the model, unsupervised machine learning algorithms have been employed. A prototype of the proposed system has also been presented in the study. User generated data has been collected from students in order to learn gossips and students’ problems related to school, classes, staff and instructors. The findings and results of the pilot study suggest that social media messages among students may give important clues for the happenings at school and this information may be used for management purposes.The model may be developed and implemented by not only universities but also some other organisations.

Models of Affective Decision Making: How Do Feelings Predict Choice?

Science.gov (United States)

Charpentier, Caroline J; De Neve, Jan-Emmanuel; Li, Xinyi; Roiser, Jonathan P; Sharot, Tali

2016-06-01

Intuitively, how you feel about potential outcomes will determine your decisions. Indeed, an implicit assumption in one of the most influential theories in psychology, prospect theory, is that feelings govern choice. Surprisingly, however, very little is known about the rules by which feelings are transformed into decisions. Here, we specified a computational model that used feelings to predict choices. We found that this model predicted choice better than existing value-based models, showing a unique contribution of feelings to decisions, over and above value. Similar to the value function in prospect theory, our feeling function showed diminished sensitivity to outcomes as value increased. However, loss aversion in choice was explained by an asymmetry in how feelings about losses and gains were weighted when making a decision, not by an asymmetry in the feelings themselves. The results provide new insights into how feelings are utilized to reach a decision. © The Author(s) 2016.

Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

Science.gov (United States)

Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

Embedding a State Space Model Into a Markov Decision Process

DEFF Research Database (Denmark)

Nielsen, Lars Relund; Jørgensen, Erik; Højsgaard, Søren

2011-01-01

In agriculture Markov decision processes (MDPs) with finite state and action space are often used to model sequential decision making over time. For instance, states in the process represent possible levels of traits of the animal and transition probabilities are based on biological models...

Decision making under uncertainty in viticulture: a case study of Port wine

Directory of Open Access Journals (Sweden)

Ana Paula Lopes

2013-06-01

Full Text Available In decision making under uncertainty individual decision makers (winegrowers must choose one of a set number of decision alternatives with ample information about their outcomes but, most of the times, have not enough knowledge or data about the probabilities of the several states of nature. This paper focuses on the classical Maximax, Maximin, Minimax Regret and Realism criteria. The different approaches are analyzed and compared in a case study of Port wine production and selling. The computational involvedness and efficacy of the criterion are also presented. The paper finishes with the results of all observed criteria and alternatives in the circumstances of uncertainty.

Critical infrastructure protection decision support system decision model : overview and quick-start user's guide.

Energy Technology Data Exchange (ETDEWEB)

Samsa, M.; Van Kuiken, J.; Jusko, M.; Decision and Information Sciences

2008-12-01

The Critical Infrastructure Protection Decision Support System Decision Model (CIPDSS-DM) is a useful tool for comparing the effectiveness of alternative risk-mitigation strategies on the basis of CIPDSS consequence scenarios. The model is designed to assist analysts and policy makers in evaluating and selecting the most effective risk-mitigation strategies, as affected by the importance assigned to various impact measures and the likelihood of an incident. A typical CIPDSS-DM decision map plots the relative preference of alternative risk-mitigation options versus the annual probability of an undesired incident occurring once during the protective life of the investment, assumed to be 20 years. The model also enables other types of comparisons, including a decision map that isolates a selected impact variable and displays the relative preference for the options of interest--parameterized on the basis of the contribution of the isolated variable to total impact, as well as the likelihood of the incident. Satisfaction/regret analysis further assists the analyst or policy maker in evaluating the confidence with which one option can be selected over another.

Perceptual decision neurosciences: a model-based review

NARCIS (Netherlands)

Mulder, M.J.; van Maanen, L.; Forstmann, B.U.

2014-01-01

In this review we summarize findings published over the past 10 years focusing on the neural correlates of perceptual decision-making. Importantly, this review highlights only studies that employ a model-based approach, i.e., they use quantitative cognitive models in combination with neuroscientific

IMPORTANCE OF DIFFERENT MODELS IN DECISION MAKING, EXPLAINING THE STRATEGIC BEHAVIOR IN ORGANIZATIONS

Directory of Open Access Journals (Sweden)

Cristiano de Oliveira Maciel

2006-11-01

Full Text Available This study is about the different models of decision process analyzing the organizational strategy. The article presents the strategy according to a cognitive approach. The discussion about that approach has three models of decision process: rational actor model, organizational behavior, and political model. These models, respectively, present some improvement in the decision making results, search for a good decision facing the cognitive restrictions of the administrator, and lots of talks for making a decision. According to the emphasis of each model, the possibilities for analyzing the strategy are presented. The article also shows that it is necessary to take into account the three different ways of analysis. That statement is justified once the analysis as well as the decision making become more complex, mainly those which are more important for the organizations.

Multicriteria decision group model for the selection of suppliers

Directory of Open Access Journals (Sweden)

Luciana Hazin Alencar

2008-08-01

Full Text Available Several authors have been studying group decision making over the years, which indicates how relevant it is. This paper presents a multicriteria group decision model based on ELECTRE IV and VIP Analysis methods, to those cases where there is great divergence among the decision makers. This model includes two stages. In the first, the ELECTRE IV method is applied and a collective criteria ranking is obtained. In the second, using criteria ranking, VIP Analysis is applied and the alternatives are selected. To illustrate the model, a numerical application in the context of the selection of suppliers in project management is used. The suppliers that form part of the project team have a crucial role in project management. They are involved in a network of connected activities that can jeopardize the success of the project, if they are not undertaken in an appropriate way. The question tackled is how to select service suppliers for a project on behalf of an enterprise that assists the multiple objectives of the decision-makers.Vários autores têm estudado decisão em grupo nos últimos anos, o que indica a relevância do assunto. Esse artigo apresenta um modelo multicritério de decisão em grupo baseado nos métodos ELECTRE IV e VIP Analysis, adequado aos casos em que se tem uma grande divergência entre os decisores. Esse modelo é composto por dois estágios. No primeiro, o método ELECTRE IV é aplicado e uma ordenação dos critérios é obtida. No próximo estágio, com a ordenação dos critérios, o método VIP Analysis é aplicado e as alternativas são selecionadas. Para ilustrar o modelo, uma aplicação numérica no contexto da seleção de fornecedores em projetos é realizada. Os fornecedores que fazem parte da equipe do projeto têm um papel fundamental no gerenciamento de projetos. Eles estão envolvidos em uma rede de atividades conectadas que, caso não sejam executadas de forma apropriada, podem colocar em risco o sucesso do

Decision support models for solid waste management: Review and game-theoretic approaches

International Nuclear Information System (INIS)

Karmperis, Athanasios C.; Aravossis, Konstantinos; Tatsiopoulos, Ilias P.; Sotirchos, Anastasios

2013-01-01

Highlights: ► The mainly used decision support frameworks for solid waste management are reviewed. ► The LCA, CBA and MCDM models are presented and their strengths, weaknesses, similarities and possible combinations are analyzed. ► The game-theoretic approach in a solid waste management context is presented. ► The waste management bargaining game is introduced as a specific decision support framework. ► Cooperative and non-cooperative game-theoretic approaches to decision support for solid waste management are discussed. - Abstract: This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decision support frameworks, which are the life-cycle assessment, the cost–benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed

Decision support models for solid waste management: Review and game-theoretic approaches

Energy Technology Data Exchange (ETDEWEB)

Karmperis, Athanasios C., E-mail: athkarmp@mail.ntua.gr [Sector of Industrial Management and Operational Research, School of Mechanical Engineering, National Technical University of Athens, Iroon Polytechniou 9, 15780 Athens (Greece); Army Corps of Engineers, Hellenic Army General Staff, Ministry of Defence (Greece); Aravossis, Konstantinos; Tatsiopoulos, Ilias P.; Sotirchos, Anastasios [Sector of Industrial Management and Operational Research, School of Mechanical Engineering, National Technical University of Athens, Iroon Polytechniou 9, 15780 Athens (Greece)

2013-05-15

Highlights: ► The mainly used decision support frameworks for solid waste management are reviewed. ► The LCA, CBA and MCDM models are presented and their strengths, weaknesses, similarities and possible combinations are analyzed. ► The game-theoretic approach in a solid waste management context is presented. ► The waste management bargaining game is introduced as a specific decision support framework. ► Cooperative and non-cooperative game-theoretic approaches to decision support for solid waste management are discussed. - Abstract: This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decision support frameworks, which are the life-cycle assessment, the cost–benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed.

Problem-Oriented Corporate Knowledge Base Models on the Case-Based Reasoning Approach Basis

Science.gov (United States)

Gluhih, I. N.; Akhmadulin, R. K.

2017-07-01

One of the urgent directions of efficiency enhancement of production processes and enterprises activities management is creation and use of corporate knowledge bases. The article suggests a concept of problem-oriented corporate knowledge bases (PO CKB), in which knowledge is arranged around possible problem situations and represents a tool for making and implementing decisions in such situations. For knowledge representation in PO CKB a case-based reasoning approach is encouraged to use. Under this approach, the content of a case as a knowledge base component has been defined; based on the situation tree a PO CKB knowledge model has been developed, in which the knowledge about typical situations as well as specific examples of situations and solutions have been represented. A generalized problem-oriented corporate knowledge base structural chart and possible modes of its operation have been suggested. The obtained models allow creating and using corporate knowledge bases for support of decision making and implementing, training, staff skill upgrading and analysis of the decisions taken. The universal interpretation of terms “situation” and “solution” adopted in the work allows using the suggested models to develop problem-oriented corporate knowledge bases in different subject domains. It has been suggested to use the developed models for making corporate knowledge bases of the enterprises that operate engineer systems and networks at large production facilities.

Consumer's Online Shopping Influence Factors and Decision-Making Model

Science.gov (United States)

Yan, Xiangbin; Dai, Shiliang

Previous research on online consumer behavior has mostly been confined to the perceived risk which is used to explain those barriers for purchasing online. However, perceived benefit is another important factor which influences consumers’ decision when shopping online. As a result, an integrated consumer online shopping decision-making model is developed which contains three elements—Consumer, Product, and Web Site. This model proposed relative factors which influence the consumers’ intention during the online shopping progress, and divided them into two different dimensions—mentally level and material level. We tested those factors with surveys, from both online volunteers and offline paper surveys with more than 200 samples. With the help of SEM, the experimental results show that the proposed model and method can be used to analyze consumer’s online shopping decision-making process effectively.

Decision process regarding nuclear generation: the Brazilian case

International Nuclear Information System (INIS)

Metri, Paulo

2009-01-01

Countries face a constant need to expand their electricity generation capacities. Electricity sources in a country and the respective generation technologies have different technical, economic, environmental, social and political characteristics. The evaluation criteria of the generating sources and their technologies must not be restricted to the supply of the increased demand at the lowest cost. Compliance with other public policies must be considered in the decision process of the expansion, for instance, maximize local acquisition and minimize foreign fuel purchase. Countries have different energy resources, as well as different levels of technology and development in their industrial parks. Brazil has many mineral reserves, besides the hydraulic potential, for supporting the expansion. The decision process in this sector, which includes nuclear energy as a sub-sector, requires analyzing and evaluating various information and data. In this stage, a quantitative model providing a first approach for the decision may be applied. The new institutional structure adopted in the sector during the 1990s and 2000s brought about new conditions into an already complex decision process. In such context of methodology complexity, political aspects gain relevance, becoming of increased importance. The political environment is described and the players are identified. One conclusion and a few recommendations are provided. (author)

Structural Model Error and Decision Relevancy

Science.gov (United States)

Goldsby, M.; Lusk, G.

2017-12-01

The extent to which climate models can underwrite specific climate policies has long been a contentious issue. Skeptics frequently deny that climate models are trustworthy in an attempt to undermine climate action, whereas policy makers often desire information that exceeds the capabilities of extant models. While not skeptics, a group of mathematicians and philosophers [Frigg et al. (2014)] recently argued that even tiny differences between the structure of a complex dynamical model and its target system can lead to dramatic predictive errors, possibly resulting in disastrous consequences when policy decisions are based upon those predictions. They call this result the Hawkmoth effect (HME), and seemingly use it to rebuke rightwing proposals to forgo mitigation in favor of adaptation. However, a vigorous debate has emerged between Frigg et al. on one side and another philosopher-mathematician pair [Winsberg and Goodwin (2016)] on the other. On one hand, Frigg et al. argue that their result shifts the burden to climate scientists to demonstrate that their models do not fall prey to the HME. On the other hand, Winsberg and Goodwin suggest that arguments like those asserted by Frigg et al. can be, if taken seriously, "dangerous": they fail to consider the variety of purposes for which models can be used, and thus too hastily undermine large swaths of climate science. They put the burden back on Frigg et al. to show their result has any effect on climate science. This paper seeks to attenuate this debate by establishing an irenic middle position; we find that there is more agreement between sides than it first seems. We distinguish a `decision standard' from a `burden of proof', which helps clarify the contributions to the debate from both sides. In making this distinction, we argue that scientists bear the burden of assessing the consequences of HME, but that the standard Frigg et al. adopt for decision relevancy is too strict.

Social influence and perceptual decision making: a diffusion model analysis.

Science.gov (United States)

Germar, Markus; Schlemmer, Alexander; Krug, Kristine; Voss, Andreas; Mojzisch, Andreas

2014-02-01

Classic studies on social influence used simple perceptual decision-making tasks to examine how the opinions of others change individuals' judgments. Since then, one of the most fundamental questions in social psychology has been whether social influence can alter basic perceptual processes. To address this issue, we used a diffusion model analysis. Diffusion models provide a stochastic approach for separating the cognitive processes underlying speeded binary decisions. Following this approach, our study is the first to disentangle whether social influence on decision making is due to altering the uptake of available sensory information or due to shifting the decision criteria. In two experiments, we found consistent evidence for the idea that social influence alters the uptake of available sensory evidence. By contrast, participants did not adjust their decision criteria.

Risk-based systems analysis for emerging technologies: Applications of a technology risk assessment model to public decision making

International Nuclear Information System (INIS)

Quadrel, M.J.; Fowler, K.M.; Cameron, R.; Treat, R.J.; McCormack, W.D.; Cruse, J.

1995-01-01

The risk-based systems analysis model was designed to establish funding priorities among competing technologies for tank waste remediation. The model addresses a gap in the Department of Energy's (DOE's) ''toolkit'' for establishing funding priorities among emerging technologies by providing disciplined risk and cost assessments of candidate technologies within the context of a complete remediation system. The model is comprised of a risk and cost assessment and a decision interface. The former assesses the potential reductions in risk and cost offered by new technology relative to the baseline risk and cost of an entire system. The latter places this critical information in context of other values articulated by decision makers and stakeholders in the DOE system. The risk assessment portion of the model is demonstrated for two candidate technologies for tank waste retrieval (arm-based mechanical retrieval -- the ''long reach arm'') and subsurface barriers (close-coupled chemical barriers). Relative changes from the base case in cost and risk are presented for these two technologies to illustrate how the model works. The model and associated software build on previous work performed for DOE's Office of Technology Development and the former Underground Storage Tank Integrated Demonstration, and complement a decision making tool presented at Waste Management 1994 for integrating technical judgements and non-technical (stakeholder) values when making technology funding decisions

Decision support models for natural gas dispatch

Energy Technology Data Exchange (ETDEWEB)

Chin, L. (Bentley College, Waltham, MA (United States)); Vollmann, T.E. (International Inst. for Management Development, Lausanne (Switzerland))

A decision support model is presented which will give utilities the support tools to manage the purchasing of natural gas supplies in the most cost effective manner without reducing winter safety stocks to below minimum levels. In Business As Usual (BAU) purchasing quantities vary with the daily forecasts. With Material Requirements Planning (MRP) and Linear Programming (LP), two types of factors are used: seasonal weather and decision rule. Under current practices, BAU simulation uses the least expensive gas source first, then adding successively more expensive sources. Material Requirements Planning is a production planning technique which uses a parent item master production schedule to determine time phased requirements for component points. Where the MPS is the aggregate gas demand forecasts for the contract year. This satisfies daily demand with least expensive gas and uses more expensive when necessary with automatic computation of available-to-promise (ATP) gas a dispacher knows daily when extra gas supplies may be ATP. Linear Programming is a mathematical algorithm used to determine optimal allocations of scarce resources to achieve a desired result. The LP model determines optimal daily gas purchase decisions with respect to supply cost minimization. Using these models, it appears possible to raise gross income margins 6 to 10% with minimal additions of customers and no new gas supply.

Decision support models for natural gas dispatch

International Nuclear Information System (INIS)

Chin, L.; Vollmann, T.E.

1992-01-01

A decision support model is presented which will give utilities the support tools to manage the purchasing of natural gas supplies in the most cost effective manner without reducing winter safety stocks to below minimum levels. In Business As Usual (BAU) purchasing quantities vary with the daily forecasts. With Material Requirements Planning (MRP) and Linear Programming (LP), two types of factors are used: seasonal weather and decision rule. Under current practices, BAU simulation uses the least expensive gas source first, then adding successively more expensive sources. Material Requirements Planning is a production planning technique which uses a parent item master production schedule to determine time phased requirements for component points. Where the MPS is the aggregate gas demand forecasts for the contract year. This satisfies daily demand with least expensive gas and uses more expensive when necessary with automatic computation of available-to-promise (ATP) gas a dispacher knows daily when extra gas supplies may be ATP. Linear Programming is a mathematical algorithm used to determine optimal allocations of scarce resources to achieve a desired result. The LP model determines optimal daily gas purchase decisions with respect to supply cost minimization. Using these models, it appears possible to raise gross income margins 6 to 10% with minimal additions of customers and no new gas supply

Intelligent Model Management in a Forest Ecosystem Management Decision Support System

Science.gov (United States)

Donald Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mark Twery; H. Michael Rauscher; Peter Knopp; Scott Thomasma; Mayukh Dass; Hajime Uchiyama

2002-01-01

Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard...

Non-thermal transitions in a model inspired by moral decisions

International Nuclear Information System (INIS)

Alamino, Roberto C

2016-01-01

This work introduces a model in which agents of a network act upon one another according to three different kinds of moral decisions. These decisions are based on an increasing level of sophistication in the empathy capacity of the agent, a hierarchy which we name Piaget ’ s ladder . The decision strategy of the agents is non-rational, in the sense they are arbitrarily fixed, and the model presents quenched disorder given by the distribution of its defining parameters. An analytical solution for this model is obtained in the large system limit as well as a leading order correction for finite-size systems which shows that typical realisations of the model develop a phase structure with both continuous and discontinuous non-thermal transitions. (paper)

Hierarchical decision modeling essays in honor of Dundar F. Kocaoglu

CERN Document Server

2016-01-01

This volume, developed in honor of Dr. Dundar F. Kocaoglu, aims to demonstrate the applications of the Hierarchical Decision Model (HDM) in different sectors and its capacity in decision analysis. It is comprised of essays from noted scholars, academics and researchers of engineering and technology management around the world. This book is organized into four parts: Technology Assessment, Strategic Planning, National Technology Planning and Decision Making Tools. Dr. Dundar F. Kocaoglu is one of the pioneers of multiple decision models using hierarchies, and creator of the HDM in decision analysis. HDM is a mission-oriented method for evaluation and/or selection among alternatives. A wide range of alternatives can be considered, including but not limited to, different technologies, projects, markets, jobs, products, cities to live in, houses to buy, apartments to rent, and schools to attend. Dr. Kocaoglu’s approach has been adopted for decision problems in many industrial sectors, including electronics rese...

Expanding business-to-business customer relationships : modeling the customer's upgrade decision

NARCIS (Netherlands)

Bolton, R.; Lemon, K.N.; Verhoef, P.C.

This article develops a model of a business customer's decision to upgrade service contracts conditional on the decision to renew the contract. It proposes that the firm's upgrade decision is influenced by (1) decision-maker perceptions of the relationship with the supplier, (2) contract-level

Building a maintenance policy through a multi-criterion decision-making model

Science.gov (United States)

Faghihinia, Elahe; Mollaverdi, Naser

2012-08-01

A major competitive advantage of production and service systems is establishing a proper maintenance policy. Therefore, maintenance managers should make maintenance decisions that best fit their systems. Multi-criterion decision-making methods can take into account a number of aspects associated with the competitiveness factors of a system. This paper presents a multi-criterion decision-aided maintenance model with three criteria that have more influence on decision making: reliability, maintenance cost, and maintenance downtime. The Bayesian approach has been applied to confront maintenance failure data shortage. Therefore, the model seeks to make the best compromise between these three criteria and establish replacement intervals using Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II), integrating the Bayesian approach with regard to the preference of the decision maker to the problem. Finally, using a numerical application, the model has been illustrated, and for a visual realization and an illustrative sensitivity analysis, PROMETHEE GAIA (the visual interactive module) has been used. Use of PROMETHEE II and PROMETHEE GAIA has been made with Decision Lab software. A sensitivity analysis has been made to verify the robustness of certain parameters of the model.

Decision and Inhibitory Trees for Decision Tables with Many-Valued Decisions

KAUST Repository

Azad, Mohammad

2018-06-06

Decision trees are one of the most commonly used tools in decision analysis, knowledge representation, machine learning, etc., for its simplicity and interpretability. We consider an extension of dynamic programming approach to process the whole set of decision trees for the given decision table which was previously only attainable by brute-force algorithms. We study decision tables with many-valued decisions (each row may contain multiple decisions) because they are more reasonable models of data in many cases. To address this problem in a broad sense, we consider not only decision trees but also inhibitory trees where terminal nodes are labeled with “̸= decision”. Inhibitory trees can sometimes describe more knowledge from datasets than decision trees. As for cost functions, we consider depth or average depth to minimize time complexity of trees, and the number of nodes or the number of the terminal, or nonterminal nodes to minimize the space complexity of trees. We investigate the multi-stage optimization of trees relative to some cost functions, and also the possibility to describe the whole set of strictly optimal trees. Furthermore, we study the bi-criteria optimization cost vs. cost and cost vs. uncertainty for decision trees, and cost vs. cost and cost vs. completeness for inhibitory trees. The most interesting application of the developed technique is the creation of multi-pruning and restricted multi-pruning approaches which are useful for knowledge representation and prediction. The experimental results show that decision trees constructed by these approaches can often outperform the decision trees constructed by the CART algorithm. Another application includes the comparison of 12 greedy heuristics for single- and bi-criteria optimization (cost vs. cost) of trees. We also study the three approaches (decision tables with many-valued decisions, decision tables with most common decisions, and decision tables with generalized decisions) to handle

The decision book fifty models for strategic thinking

CERN Document Server

Krogerus, Mikael

2011-01-01

Most of us face the same questions every day: What do I want? And how can I get it? How can I live more happily and work more efficiently? A worldwide bestseller, The Decision Book distils into a single volume the fifty best decision-making models used on MBA courses and elsewhere that will help you tackle these important questions - from the well known (the Eisenhower matrix for time management) to the less familiar but equally useful (the Swiss Cheese model). It will even show you how to remember everything you will have learned by the end of it. Stylish and compact, this little black book is a powerful asset. Whether you need to plot a presentation, assess someone's business idea or get to know yourself better, this unique guide will help you simplify any problem and take steps towards the right decision.

Is all sexual harassment viewed the same? Mock juror decisions in same- and cross-gender cases.

Science.gov (United States)

Wayne, J H; Riordan, C M; Thomas, K M

2001-04-01

Given recent court decisions, there is a need to investigate less common forms of sexual harassment, including women harassing men and same-gender harassment. The present study was a 2 (harasser gender) x 2 (target gender) x 2 (participant gender) factorial design in which 408 mock jurors made decisions in a hostile work environment case. Women harassing men were more likely to be found guilty than were men harassing women, and harassers in same-gender cases were more likely to be found guilty and were perceived more negatively than harassers in cross-gender cases. Participant gender differences were found in cross-gender, but not same-gender, conditions. Results suggest that the gender composition of the harasser and target may be an extralegal factor influencing managerial and juror decision making.

A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making

Directory of Open Access Journals (Sweden)

Sabine Prezenski

2017-08-01

Full Text Available Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying

A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making.

Science.gov (United States)

Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

2017-01-01

Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from

Managing health care decisions and improvement through simulation modeling.

Science.gov (United States)

Forsberg, Helena Hvitfeldt; Aronsson, Håkan; Keller, Christina; Lindblad, Staffan

2011-01-01

Simulation modeling is a way to test changes in a computerized environment to give ideas for improvements before implementation. This article reviews research literature on simulation modeling as support for health care decision making. The aim is to investigate the experience and potential value of such decision support and quality of articles retrieved. A literature search was conducted, and the selection criteria yielded 59 articles derived from diverse applications and methods. Most met the stated research-quality criteria. This review identified how simulation can facilitate decision making and that it may induce learning. Furthermore, simulation offers immediate feedback about proposed changes, allows analysis of scenarios, and promotes communication on building a shared system view and understanding of how a complex system works. However, only 14 of the 59 articles reported on implementation experiences, including how decision making was supported. On the basis of these articles, we proposed steps essential for the success of simulation projects, not just in the computer, but also in clinical reality. We also presented a novel concept combining simulation modeling with the established plan-do-study-act cycle for improvement. Future scientific inquiries concerning implementation, impact, and the value for health care management are needed to realize the full potential of simulation modeling.

A Decision Support Model and Tool to Assist Financial Decision-Making in Universities

Science.gov (United States)

Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive

2015-01-01

In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…

A generic methodology for developing fuzzy decision models

NARCIS (Netherlands)

Bosma, R.; Berg, van den J.; Kaymak, U.; Udo, H.; Verreth, J.

2012-01-01

An important paradigm in decision-making models is utility-maximization where most models do not include actors’ motives. Fuzzy set theory on the other hand offers a method to simulate human decisionmaking. However, the literature describing expert-driven fuzzy logic models, rarely gives precise

A decision-making framework to model environmental flow requirements in oasis areas using Bayesian networks

Science.gov (United States)

Xue, Jie; Gui, Dongwei; Zhao, Ying; Lei, Jiaqiang; Zeng, Fanjiang; Feng, Xinlong; Mao, Donglei; Shareef, Muhammad

2016-09-01

The competition for water resources between agricultural and natural oasis ecosystems has become an increasingly serious problem in oasis areas worldwide. Recently, the intensive extension of oasis farmland has led to excessive exploitation of water discharge, and consequently has resulted in a lack of water supply in natural oasis. To coordinate the conflicts, this paper provides a decision-making framework for modeling environmental flows in oasis areas using Bayesian networks (BNs). Three components are included in the framework: (1) assessment of agricultural economic loss due to meeting environmental flow requirements; (2) decision-making analysis using BNs; and (3) environmental flow decision-making under different water management scenarios. The decision-making criterion is determined based on intersection point analysis between the probability of large-level total agro-economic loss and the ratio of total to maximum agro-economic output by satisfying environmental flows. An application in the Qira oasis area of the Tarim Basin, Northwest China indicates that BNs can model environmental flow decision-making associated with agricultural economic loss effectively, as a powerful tool to coordinate water-use conflicts. In the case study, the environmental flow requirement is determined as 50.24%, 49.71% and 48.73% of the natural river flow in wet, normal and dry years, respectively. Without further agricultural economic loss, 1.93%, 0.66% and 0.43% of more river discharge can be allocated to eco-environmental water demands under the combined strategy in wet, normal and dry years, respectively. This work provides a valuable reference for environmental flow decision-making in any oasis area worldwide.

A decision-making model based on a spiking neural circuit and synaptic plasticity.

Science.gov (United States)

Wei, Hui; Bu, Yijie; Dai, Dawei

2017-10-01

To adapt to the environment and survive, most animals can control their behaviors by making decisions. The process of decision-making and responding according to cues in the environment is stable, sustainable, and learnable. Understanding how behaviors are regulated by neural circuits and the encoding and decoding mechanisms from stimuli to responses are important goals in neuroscience. From results observed in Drosophila experiments, the underlying decision-making process is discussed, and a neural circuit that implements a two-choice decision-making model is proposed to explain and reproduce the observations. Compared with previous two-choice decision making models, our model uses synaptic plasticity to explain changes in decision output given the same environment. Moreover, biological meanings of parameters of our decision-making model are discussed. In this paper, we explain at the micro-level (i.e., neurons and synapses) how observable decision-making behavior at the macro-level is acquired and achieved.

Learning to maximize reward rate: a model based on semi-Markov decision processes.

Science.gov (United States)

Khodadadi, Arash; Fakhari, Pegah; Busemeyer, Jerome R

2014-01-01

WHEN ANIMALS HAVE TO MAKE A NUMBER OF DECISIONS DURING A LIMITED TIME INTERVAL, THEY FACE A FUNDAMENTAL PROBLEM: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will remain for other decisions. In the framework of sequential sampling models, the question is how animals learn to set their decision threshold such that the total expected outcome achieved during a limited time is maximized. The aim of this paper is to provide a theoretical framework for answering this question. To this end, we consider an experimental design in which each trial can come from one of the several possible "conditions." A condition specifies the difficulty of the trial, the reward, the penalty and so on. We show that to maximize the expected reward during a limited time, the subject should set a separate value of decision threshold for each condition. We propose a model of learning the optimal value of decision thresholds based on the theory of semi-Markov decision processes (SMDP). In our model, the experimental environment is modeled as an SMDP with each "condition" being a "state" and the value of decision thresholds being the "actions" taken in those states. The problem of finding the optimal decision thresholds then is cast as the stochastic optimal control problem of taking actions in each state in the corresponding SMDP such that the average reward rate is maximized. Our model utilizes a biologically plausible learning algorithm to solve this problem. The simulation results show that at the beginning of learning the model choses high values of decision threshold which lead to sub-optimal performance. With experience, however, the model learns to lower the value of decision thresholds till finally it finds the optimal values.

Expected Utility and Entropy-Based Decision-Making Model for Large Consumers in the Smart Grid

Directory of Open Access Journals (Sweden)

Bingtuan Gao

2015-09-01

Full Text Available In the smart grid, large consumers can procure electricity energy from various power sources to meet their load demands. To maximize its profit, each large consumer needs to decide their energy procurement strategy under risks such as price fluctuations from the spot market and power quality issues. In this paper, an electric energy procurement decision-making model is studied for large consumers who can obtain their electric energy from the spot market, generation companies under bilateral contracts, the options market and self-production facilities in the smart grid. Considering the effect of unqualified electric energy, the profit model of large consumers is formulated. In order to measure the risks from the price fluctuations and power quality, the expected utility and entropy is employed. Consequently, the expected utility and entropy decision-making model is presented, which helps large consumers to minimize their expected profit of electricity procurement while properly limiting the volatility of this cost. Finally, a case study verifies the feasibility and effectiveness of the proposed model.

Using the ACT-R architecture to specify 39 quantitative process models of decision making

Directory of Open Access Journals (Sweden)

Julian N. Marewski

2011-08-01

Full Text Available Hypotheses about decision processes are often formulated qualitatively and remain silent about the interplay of decision, memorial, and other cognitive processes. At the same time, existing decision models are specified at varying levels of detail, making it difficult to compare them. We provide a methodological primer on how detailed cognitive architectures such as ACT-R allow remedying these problems. To make our point, we address a controversy, namely, whether noncompensatory or compensatory processes better describe how people make decisions from the accessibility of memories. We specify 39 models of accessibility-based decision processes in ACT-R, including the noncompensatory recognition heuristic and various other popular noncompensatory and compensatory decision models. Additionally, to illustrate how such models can be tested, we conduct a model comparison, fitting the models to one experiment and letting them generalize to another. Behavioral data are best accounted for by race models. These race models embody the noncompensatory recognition heuristic and compensatory models as a race between competing processes, dissolving the dichotomy between existing decision models.

A Plastic Cortico-Striatal Circuit Model of Adaptation in Perceptual Decision

Directory of Open Access Journals (Sweden)

Pao-Yueh eHsiao

2013-12-01

Full Text Available The ability to optimize decisions and adapt them to changing environments is a crucial brain function that increase survivability. Although much has been learned about the neuronal activity in various brain regions that are associated with decision making, and about how the nervous systems may learn to achieve optimization, the underlying neuronal mechanisms of how the nervous systems optimize decision strategies with preference given to speed or accuracy, and how the systems adapt to changes in the environment, remain unclear. Based on extensive empirical observations, we addressed the question by extending a previously described cortico-basal ganglia circuit model of perceptual decisions with the inclusion of a dynamic dopamine (DA system that modulates spike-timing dependent plasticity. We found that, once an optimal model setting that maximized the reward rate was selected, the same setting automatically optimized decisions across different task environments through dynamic balancing between the facilitating and depressing components of the DA dynamics. Interestingly, other model parameters were also optimal if we considered the reward rate that was weighted by the subject’s preferences for speed or accuracy. Specifically, the circuit model favored speed if we increased the phasic DA response to the reward prediction error, whereas the model favored accuracy if we reduced the tonic DA activity or the phasic DA responses to the estimated reward probability. The proposed model provides insight into the roles of different components of DA responses in decision adaptation and optimization in a changing environment.

Decision and Inhibitory Rule Optimization for Decision Tables with Many-valued Decisions

KAUST Repository

Alsolami, Fawaz

2016-04-25

‘If-then’ rule sets are one of the most expressive and human-readable knowledge representations. This thesis deals with optimization and analysis of decision and inhibitory rules for decision tables with many-valued decisions. The most important areas of applications are knowledge extraction and representation. The benefit of considering inhibitory rules is connected with the fact that in some situations they can describe more knowledge than the decision ones. Decision tables with many-valued decisions arise in combinatorial optimization, computational geometry, fault diagnosis, and especially under the processing of data sets. In this thesis, various examples of real-life problems are considered which help to understand the motivation of the investigation. We extend relatively simple results obtained earlier for decision rules over decision tables with many-valued decisions to the case of inhibitory rules. The behavior of Shannon functions (which characterize complexity of rule systems) is studied for finite and infinite information systems, for global and local approaches, and for decision and inhibitory rules. The extensions of dynamic programming for the study of decision rules over decision tables with single-valued decisions are generalized to the case of decision tables with many-valued decisions. These results are also extended to the case of inhibitory rules. As a result, we have algorithms (i) for multi-stage optimization of rules relative to such criteria as length or coverage, (ii) for counting the number of optimal rules, (iii) for construction of Pareto optimal points for bi-criteria optimization problems, (iv) for construction of graphs describing relationships between two cost functions, and (v) for construction of graphs describing relationships between cost and accuracy of rules. The applications of created tools include comparison (based on information about Pareto optimal points) of greedy heuristics for bi-criteria optimization of rules

[Clinical decision making: Fostering critical thinking in the nursing diagnostic process through case studies].

Science.gov (United States)

Müller-Staub, Maria; Stuker-Studer, Ursula

2006-10-01

Case studies, based on actual patients' situations, provide a method of clinical decision making to foster critical thinking in nurses. This paper describes the method and process of group case studies applied in continuous education settings. This method bases on Balints' case supervision and was further developed and combined with the nursing diagnostic process. A case study contains different phases: Pre-phase, selection phase, case delineation and case work. The case provider narratively tells the situation of a patient. This allows the group to analyze and cluster signs and symptoms, to state nursing diagnoses and to derive nursing interventions. Results of the case study are validated by applying the theoretical background and critical appraisal of the case provider. Learning effects of the case studies were evaluated by means of qualitative questionnaires and analyzed according to Mayring. Findings revealed the following categories: a) Patients' problems are perceived in a patient centred way, accurate nursing diagnoses are stated and effective nursing interventions implemented. b) Professional nursing tasks are more purposefully perceived and named more precise. c) Professional nursing relationship, communication and respectful behaviour with patients were perceived in differentiated ways. The theoretical framework is described in the paper "Clinical decision making and critical thinking in the nursing diagnostic process". (Müller-Staub, 2006).

Does Core Task Matter for Decision-Making? A Comparative Case Study on Whether Differences in Job Characteristics Affect Discretionary Street-Level Decision-Making

DEFF Research Database (Denmark)

Jensen, Didde Cramer

2017-01-01

This article sets out to test the hypothesis that differences in fundamental job characteristics (service vs. regulation) affect discretionary street-level decision-making. The hypothesis was tested by examining whether systematic variation could be found in the moral assessments on which street......-level bureaucrats performing different types of core tasks base their decisions. The issue was addressed in a comparative case study comprising three institutions, which differ systematically as far as variables of tasks are concerned. Findings showed that differences in core tasks do affect discretionary decision...

What's on a decision makers mind? - Identifying barriers in information flows between actors in integrated water management using mental model mapping. Poster.

NARCIS (Netherlands)

Kolkman, Rien; van Os, A.G.; Geurts, Petrus A.T.M.; van der Veen, A.

2004-01-01

This research studies the relation between mental models and the decision process outcome, in the specific case of the Zwolle storm surge barrier. Differences in mental models between stakeholders will result in different lines of argumentation leading to different solution alternatives. The final

THE MAKING OF DECISION MAKING

Directory of Open Access Journals (Sweden)

Leonardo Yuji Tamura

2016-04-01

Full Text Available Quantum Electronics was a Brazilian startup in the 1990's that was acquired by an American equity fund in 2012. They are currently the largest manufacturer of vehicle tracking and infotainment systems. The company was founded by three college friends, who are currently executives at the company: Camilo Santos, Pedro Barbosa and Luana Correa. Edward Hutter was sent by the equity fund to take over the company’s finances, but is having trouble making organizational decisions with his colleagues. As a consultant, I was called to help them improve their decision making process and project prioritization. I adapted and deployed our firm's methodology, but, in the end, its adequacy is shown to be very much in question. The author of this case study intends to explore how actual organizational decisions rely on different decision models and their assumptions, .as well as demonstrate that a decision model is neither absolutely good nor bad as its quality is context dependent.

A Fuzzy Max–Min Decision Bi-Level Fuzzy Programming Model for Water Resources Optimization Allocation under Uncertainty

Directory of Open Access Journals (Sweden)

Chongfeng Ren

2018-04-01

Full Text Available Water competing conflict among water competing sectors from different levels should be taken under consideration during the optimization allocation of water resources. Furthermore, uncertainties are inevitable in the optimization allocation of water resources. In order to deal with the above problems, this study developed a fuzzy max–min decision bi-level fuzzy programming model. The developed model was then applied to a case study in Wuwei, Gansu Province, China. In this study, the net benefit and yield were regarded as the upper-level and lower-level objectives, respectively. Optimal water resource plans were obtained under different possibility levels of fuzzy parameters, which could deal with water competing conflict between the upper level and the lower level effectively. The obtained results are expected to make great contribution in helping local decision-makers to make decisions on dealing with the water competing conflict between the upper and lower level and the optimal use of water resources under uncertainty.

Comprehensible knowledge model creation for cancer treatment decision making.

Science.gov (United States)

Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

2017-03-01

A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

Strategic enterprise resource planning in a health-care system using a multicriteria decision-making model.

Science.gov (United States)

Lee, Chang Won; Kwak, N K

2011-04-01

This paper deals with strategic enterprise resource planning (ERP) in a health-care system using a multicriteria decision-making (MCDM) model. The model is developed and analyzed on the basis of the data obtained from a leading patient-oriented provider of health-care services in Korea. Goal criteria and priorities are identified and established via the analytic hierarchy process (AHP). Goal programming (GP) is utilized to derive satisfying solutions for designing, evaluating, and implementing an ERP. The model results are evaluated and sensitivity analyses are conducted in an effort to enhance the model applicability. The case study provides management with valuable insights for planning and controlling health-care activities and services.

A Model for Evidence Accumulation in the Lexical Decision Task

Science.gov (United States)

Wagenmakers, Eric-Jan; Steyvers, Mark; Raaijmakers, Jeroen G. W.; Shiffrin, Richard M.; van Rijn, Hedderik; Zeelenberg, Rene

2004-01-01

We present a new model for lexical decision, REM-LD, that is based on REM theory (e.g., Shiffrin & Steyvers, 1997). REM-LD uses a principled (i.e., Bayes' rule) decision process that simultaneously considers the diagnosticity of the evidence for the 'WORD' response and the 'NONWORD' response. The model calculates the odds ratio that the presented…

Ensemble modelling and structured decision-making to support Emergency Disease Management

NARCIS (Netherlands)

Webb, Colleen T.; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P.; Werkman, Marleen; Backer, Jantien; Tildesley, Michael

2017-01-01

Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by

RESEARCH OF MULTICRITERIAL DECISION-MAKING MODEL FOR EDUCATIONAL INFORMATION SYSTEMS

Directory of Open Access Journals (Sweden)

V. V. Serbin

2016-09-01

Full Text Available Subject of Research. Decision-making model is offered for informational and educational systems. The study of multi-criteria model is carried out taking into account knowledge, reaction and doubt. Method. The model of material proficiency by the user is based on identification of the personal characteristics when operating with the system. As a result of personal characteristics tracking in the system, an image is formed for each user that can be used for identifying his state: knowledge level, proportion of error, handwriting information, etc. During registration the user is passing an input test. Multi-criteria test results are automatically stored in the user's personal database (agent matrix and accounted for psychological comfort, formation of the next system content, management of knowledge levels, decision-making when working with the system. The proposed method gives a more clear and "transparent situational picture" for objective decision-making. Main Results. Implementation of multi-criteria decision-making model contributes to the quality of distance education. Also, the method makes it possible to reduce the probability of guessing the correct answer, thus increases the objectivity of knowledge level evaluation in diagnostic systems for management of learning process based on remote technologies. Practical Relevance. Obtained theoretical results of the work are used in training systems on the basis of multi-criteria decision models. Thus, the proposed model leads to an increase in the average score of about 0.3-0.4 points and reduces the training time in 1.5 to 2.0 times.

Insights from quantum cognitive models for organizational decision making

OpenAIRE

White, L.C.; Pothos, E. M.; Busemeyer, J. R.

2015-01-01

Organizational decision making is often explored with theories from the heuristics and biases research program, which have demonstrated great value as descriptions of how people in organizations make decisions. Nevertheless, rational analysis and classical probability theory are still seen by many as the best accounts of how decisions should be made and classical probability theory is the preferred framework for cognitive modelling for many researchers. The focus of this work is quantum proba...

A hierarchical decision making model for the prioritization of distributed generation technologies: A case study for Iran

International Nuclear Information System (INIS)

Zangeneh, Ali; Jadid, Shahram; Rahimi-Kian, Ashkan

2009-01-01

The purpose of this paper is to present an assessment and evaluation model for the prioritization of distributed generation (DG) technologies, both conventional and renewable, to meet the increasing load due to the growth rate in Iran, while considering the issue of sustainable development. The proposed hierarchical decision making strategy is presented from the viewpoint of either the distribution company (DisCo) or the independent power producer (IPP) as a private entity. Nowadays, DG is a broadly-used term that covers various technologies; however, it is difficult to find a unique DG technology that takes into account multiple considerations, such as economic, technical, and environmental attributes. For this purpose, a multi-attribute decision making (MADM) approach is used to assess the alternatives for DG technology with respect to their economic, technical and environmental attributes. In addition, a regional primary energy attribute is also included in the hierarchy to express the potential of various kinds of energy resources in the regions under study. The obtained priority of DG technologies help decision maker in each region how allocate their total investment budget to the various technologies. From the performed analysis, it is observed that gas turbines are almost the best technologies for investing in various regions of Iran. At the end of the decision making process, a sensitivity analysis is performed based on the state regulations to indicate how the variations of the attributes' weights influence the DG alternatives' priority. This proposed analytical framework is implemented in seven parts of Iran with different climatic conditions and energy resources.

Public participation in energy related decision making: Six case studies. Final report

Energy Technology Data Exchange (ETDEWEB)

Clemente, F.; Cole, J.; Kloman, E.; McCabe, J.; Sawicki, P.

1977-12-01

Each of the six case studies documents public participation in Federal and/or state governmental decisions related to energy facility siting. Four of the cases involved decisions on specific facilities at specific sites, namely: (1) various state and federal licensing procedures for the Seabrook, New Hampshire nuclear facility; (2) the Maine Environmental Improvement Commission's denial of a permit for an oil refinery on Sears Island in Penobscot Bay; (3) the Atomic Energy Commission's amendment to the license for the Big Rock Point, Michigan, nuclear reactor to allow an increased level of plutonium-enriched fuel use; (4) the AEC's review, arising from disclosure of a geological fault, of the North Anna River, Virginia, nuclear facility. A fifth case documents a series of public meetings conducted in Pennsylvania by the Governor's Energy Council to consider the energy park concept. The sixth study was a narrative history and analysis of RM-50-1, a rulemaking proceeding conducted by the AEC in 1972 and 73 on emergency core cooling system operating standards.

Modelling and simulation-based acquisition decision support: present & future

CSIR Research Space (South Africa)

Naidoo, S

2009-10-01

Full Text Available stream_source_info Naidoo1_2009.pdf.txt stream_content_type text/plain stream_size 24551 Content-Encoding UTF-8 stream_name Naidoo1_2009.pdf.txt Content-Type text/plain; charset=UTF-8 1 Modelling & Simulation...-Based Acquisition Decision Support: Present & Future Shahen Naidoo Abstract The Ground Based Air Defence System (GBADS) Programme, of the South African Army has been applying modelling and simulation (M&S) to provide acquisition decision and doctrine...

Modeling reproductive decisions with simple heuristics

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Peter Todd

2013-10-01

Full Text Available BACKGROUND Many of the reproductive decisions that humans make happen without much planning or forethought, arising instead through the use of simple choice rules or heuristics that involve relatively little information and processing. Nonetheless, these heuristic-guided decisions are typically beneficial, owing to humans' ecological rationality - the evolved fit between our constrained decision mechanisms and the adaptive problems we face. OBJECTIVE This paper reviews research on the ecological rationality of human decision making in the domain of reproduction, showing how fertility-related decisions are commonly made using various simple heuristics matched to the structure of the environment in which they are applied, rather than being made with information-hungry mechanisms based on optimization or rational economic choice. METHODS First, heuristics for sequential mate search are covered; these heuristics determine when to stop the process of mate search by deciding that a good-enough mate who is also mutually interested has been found, using a process of aspiration-level setting and assessing. These models are tested via computer simulation and comparison to demographic age-at-first-marriage data. Next, a heuristic process of feature-based mate comparison and choice is discussed, in which mate choices are determined by a simple process of feature-matching with relaxing standards over time. Parental investment heuristics used to divide resources among offspring are summarized. Finally, methods for testing the use of such mate choice heuristics in a specific population over time are then described.

Multi-criteria decision model for retrofitting existing buildings

Directory of Open Access Journals (Sweden)

M. D. Bostenaru Dan

2004-01-01

Full Text Available Decision is an element in the risk management process. In this paper the way how science can help in decision making and implementation for retrofitting buildings in earthquake prone urban areas is investigated. In such interventions actors from various spheres are involved. Their interests range among minimising the intervention for maximal preservation or increasing it for seismic safety. Research was conducted to see how to facilitate collaboration between these actors. A particular attention was given to the role of time in actors' preferences. For this reason, on decision level, both the processural and the personal dimension of risk management, the later seen as a task, were considered. A systematic approach was employed to determine the functional structure of a participative decision model. Three layers on which actors implied in this multi-criteria decision problem interact were identified: town, building and element. So-called 'retrofit elements' are characteristic bearers in the architectural survey, engineering simulations, costs estimation and define the realms perceived by the inhabitants. This way they represent an interaction basis for the interest groups considered in a deeper study. Such orientation means for actors' interaction were designed on other levels of intervention as well. Finally, an 'experiment' for the implementation of the decision model is presented: a strategic plan for an urban intervention towards reduction of earthquake hazard impact through retrofitting. A systematic approach proves thus to be a very good communication basis among the participants in the seismic risk management process. Nevertheless, it can only be applied in later phases (decision, implementation, control only, since it serves verifying and improving solution and not developing the concept. The 'retrofit elements' are a typical example of the detailing degree reached in the retrofit design plans in these phases.

Multi-criteria decision model for retrofitting existing buildings

Science.gov (United States)

Bostenaru Dan, M. D.

2004-08-01

Decision is an element in the risk management process. In this paper the way how science can help in decision making and implementation for retrofitting buildings in earthquake prone urban areas is investigated. In such interventions actors from various spheres are involved. Their interests range among minimising the intervention for maximal preservation or increasing it for seismic safety. Research was conducted to see how to facilitate collaboration between these actors. A particular attention was given to the role of time in actors' preferences. For this reason, on decision level, both the processural and the personal dimension of risk management, the later seen as a task, were considered. A systematic approach was employed to determine the functional structure of a participative decision model. Three layers on which actors implied in this multi-criteria decision problem interact were identified: town, building and element. So-called 'retrofit elements' are characteristic bearers in the architectural survey, engineering simulations, costs estimation and define the realms perceived by the inhabitants. This way they represent an interaction basis for the interest groups considered in a deeper study. Such orientation means for actors' interaction were designed on other levels of intervention as well. Finally, an 'experiment' for the implementation of the decision model is presented: a strategic plan for an urban intervention towards reduction of earthquake hazard impact through retrofitting. A systematic approach proves thus to be a very good communication basis among the participants in the seismic risk management process. Nevertheless, it can only be applied in later phases (decision, implementation, control) only, since it serves verifying and improving solution and not developing the concept. The 'retrofit elements' are a typical example of the detailing degree reached in the retrofit design plans in these phases.

Proposal optimization in nuclear accident emergency decision based on IAHP

International Nuclear Information System (INIS)

Xin Jing

2007-01-01

On the basis of establishing the multi-layer structure of nuclear accident emergency decision, several decision objectives are synthetically analyzed, and an optimization model of decision proposals for nuclear accident emergency based on interval analytic hierarchy process is proposed in the paper. The model makes comparisons among several emergency decision proposals quantified, and the optimum proposal is selected out, which solved the uncertain and fuzzy decision problem of judgments by experts' experiences in nuclear accidents emergency decision. Case study shows that the optimization result is much more reasonable, objective and reliable than subjective judgments, and it could be decision references for nuclear accident emergency. (authors)

Rigorously testing multialternative decision field theory against random utility models.

Science.gov (United States)

Berkowitsch, Nicolas A J; Scheibehenne, Benjamin; Rieskamp, Jörg

2014-06-01

Cognitive models of decision making aim to explain the process underlying observed choices. Here, we test a sequential sampling model of decision making, multialternative decision field theory (MDFT; Roe, Busemeyer, & Townsend, 2001), on empirical grounds and compare it against 2 established random utility models of choice: the probit and the logit model. Using a within-subject experimental design, participants in 2 studies repeatedly choose among sets of options (consumer products) described on several attributes. The results of Study 1 showed that all models predicted participants' choices equally well. In Study 2, in which the choice sets were explicitly designed to distinguish the models, MDFT had an advantage in predicting the observed choices. Study 2 further revealed the occurrence of multiple context effects within single participants, indicating an interdependent evaluation of choice options and correlations between different context effects. In sum, the results indicate that sequential sampling models can provide relevant insights into the cognitive process underlying preferential choices and thus can lead to better choice predictions. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Risk Decision Making Model for Reservoir Floodwater resources Utilization

Science.gov (United States)

Huang, X.

2017-12-01

Floodwater resources utilization(FRU) can alleviate the shortage of water resources, but there are risks. In order to safely and efficiently utilize the floodwater resources, it is necessary to study the risk of reservoir FRU. In this paper, the risk rate of exceeding the design flood water level and the risk rate of exceeding safety discharge are estimated. Based on the principle of the minimum risk and the maximum benefit of FRU, a multi-objective risk decision making model for FRU is constructed. Probability theory and mathematical statistics method is selected to calculate the risk rate; C-D production function method and emergy analysis method is selected to calculate the risk benefit; the risk loss is related to flood inundation area and unit area loss; the multi-objective decision making problem of the model is solved by the constraint method. Taking the Shilianghe reservoir in Jiangsu Province as an example, the optimal equilibrium solution of FRU of the Shilianghe reservoir is found by using the risk decision making model, and the validity and applicability of the model are verified.

Software Tools For Building Decision-support Models For Flood Emergency Situations

Science.gov (United States)

Garrote, L.; Molina, M.; Ruiz, J. M.; Mosquera, J. C.

The SAIDA decision-support system was developed by the Spanish Ministry of the Environment to provide assistance to decision-makers during flood situations. SAIDA has been tentatively implemented in two test basins: Jucar and Guadalhorce, and the Ministry is currently planning to have it implemented in all major Spanish basins in a few years' time. During the development cycle of SAIDA, the need for providing as- sistance to end-users in model definition and calibration was clearly identified. System developers usually emphasise abstraction and generality with the goal of providing a versatile software environment. End users, on the other hand, require concretion and specificity to adapt the general model to their local basins. As decision-support models become more complex, the gap between model developers and users gets wider: Who takes care of model definition, calibration and validation?. Initially, model developers perform these tasks, but the scope is usually limited to a few small test basins. Before the model enters operational stage, end users must get involved in model construction and calibration, in order to gain confidence in the model recommendations. However, getting the users involved in these activities is a difficult task. The goal of this re- search is to develop representation techniques for simulation and management models in order to define, develop and validate a mechanism, supported by a software envi- ronment, oriented to provide assistance to the end-user in building decision models for the prediction and management of river floods in real time. The system is based on three main building blocks: A library of simulators of the physical system, an editor to assist the user in building simulation models, and a machine learning method to calibrate decision models based on the simulation models provided by the user.

The Role of Principles, Character, and Professional Values in Ethical Decision-Making

Science.gov (United States)

Humphrey, Elaine; Janosik, Steven M.; Creamer, Don G.

2004-01-01

The role of ethical principles, character traits, and professional values in ethical decision-making is examined and depicted through an integrated and comprehensive model. A case study provides an illustration of improved decision-making when using the model.

ADVISHE: A new tool to report validation of health-economic decision models