Decision making study: methods and applications of evidential reasoning and judgment analysis

Decision making study has been the multi-disciplinary research involving operations researchers, management scientists, statisticians, mathematical psychologists and economists as well as others. This study aims to investigate the theory and methodology of decision making research and apply them to different contexts in real cases. The study has reviewed the literature of Multiple Criteria Decision Making (MCDM), Evidential Reasoning (ER) approach, Naturalistic Decision Making (NDM) movement, Social Judgment Theory (SJT), and Adaptive Toolbox (AT) program. On the basis of these literatures, two methods, Evidence-based Trade-Off (EBTO) and Judgment Analysis with Heuristic Modelling (JA-HM), have been proposed and developed to accomplish decision making problems under different conditions. In the EBTO method, we propose a novel framework to aid people s decision making under uncertainty and imprecise goal. Under the framework, the imprecise goal is objectively modelled through an analytical structure, and is independent of the task requirement; the task requirement is specified by the trade-off strategy among criteria of the analytical structure through an importance weighting process, and is subject to the requirement change of a particular decision making task; the evidence available, that could contribute to the evaluation of general performance of the decision alternatives, are formulated with belief structures which are capable of capturing various format of uncertainties that arise from the absence of data, incomplete information and subjective judgments. The EBTO method was further applied in a case study of Soldier system decision making. The application has demonstrated that EBTO, as a tool, is able to provide a holistic analysis regarding the requirements of Soldier missions, the physical conditions of Soldiers, and the capability of their equipment and weapon systems, which is critical in domain. By drawing the cross-disciplinary literature from NDM and AT, the JA-HM extended the traditional Judgment Analysis (JA) method, through a number of novel methodological procedures, to account for the unique features of decision making tasks under extreme time pressure and dynamic shifting situations. These novel methodological procedures include, the notion of decision point to deconstruct the dynamic shifting situations in a way that decision problem could be identified and formulated; the classification of routine and non-routine problems, and associated data alignment process to enable meaningful decision data analysis across different decision makers (DMs); the notion of composite cue to account for the DMs iterative process of information perception and comprehension in dynamic task environment; the application of computational models of heuristics to account for the time constraints and process dynamics of DMs decision making process; and the application of cross-validation process to enable the methodological principle of competitive testing of decision models. The JA-HM was further applied in a case study of fire emergency decision making. The application has been the first behavioural test of the validity of the computational models of heuristics, in predicting the DMs decision making during fire emergency response. It has also been the first behavioural test of the validity of the non-compensatory heuristics in predicting the DMs decisions on ranking task. The findings identified extend the literature of AT and NDM, and have implications for the fire emergency decision making

Soldier system assessment under uncertainty with evidential reasoning

Along with the increasing of new equipment based capabilities, the physiological burden on the dismounted soldier keeps on growing, which leads to the limitation in the quantity and types of missions that can be carried out. In this research, a methodology is developed to solve the burden problem from the system assessment point of view. Comparing with other relevant research, the new methodology not only provides quantitative performance estimate of the soldier with the capability of handling fragmentary and incomplete data with hybrid format in nature (qualitative and quantitative), but also restrains the assessment complexity to an acceptable level

Household water consumption: Insight from a survey in Greece and Poland

© 2015 The Authors. Published by Elsevier Ltd. Determining the behavior of domestic water consumers can facilitate a more proactive approach to water demand management, and serves as the foundation for the development of any intervention strategies that seek to bring about sustained and substantial reductions in domestic water consumption. As part of the European Union (EU) funded project Integrated Support System for Efficient Water Usage and Resources Management (ISS-EWATUS), a household water consumption survey was administered to address the question of how water was used within the home in the EU. The survey was distributed by the University of Thessaly in Greece, and the Institute for Ecology of Industrial Areas in Poland. This paper represents the research output of the survey, including the analysis of three major elements pertinent to the behavior of domestic water consumers: end use behaviors; socio-demographic and property characteristics; and psychosocial constructs such as attitudes and beliefs

Incorporating persuasion into a decision support system: The case of the water user classification function

Utility stakeholders often view autonomic feedback systems as valuable tools for moderating consumption of household resources (e.g. electricity). However, to be successful, such technology must be not only informative but also persuasive. This paper presents the water user classification (WUC) function of a decision support system (DSS) for residential water consumers. This function has been designed to harness personal value systems and wider social norms in order to promote water conservation. It uses data on home appliance efficiency, routine water usage and environmental values to attribute DSS users with a water user identity. Where the attributed identity is at odds with a self-defined 'green' identity, users may be prompted to reevaluate their everyday practices. The function also offers 'smart' personalized water saving advice. In these ways, it aims to encourage consumers to adopt sustainable water saving behaviors. This paper describes the design of the WUC function and its contribution to the DSS. It additionally highlights the crucial role of behavior change theory in the delivery of successful technology-based interventions

Fast and frugal heuristics and naturalistic decision making: a review of their commonalities and differences

© 2016 Taylor & Francis Both the fast and frugal heuristics (FFHs) and the naturalistic decision making (NDM) research programmes have identified important areas of inquiry previously neglected in the traditional study of human judgment and decision making, and have greatly contributed to the understanding of people's real-world decision making under environmental constraints. The two programmes share similar theoretical arguments regarding the rationality, optimality, and role of experience in decision making. Their commonalities have made them appealing to each other, and efforts have been made, by their leading academics, to promote synergy and integration. However, there has been little progress towards this during the last decade. This paper seeks to address this gap by seeking to better understand their commonalities and differences. To do so, literature relating to the two programmes is reviewed. The findings of the review indicated that an integration of the two could enhance FFHs' field research in applied settings, facilitate its investigation on boundary conditions of people's decision strategy selection, enable NDM to embrace emerging research opportunities in the age of big data, as well as permit each programme to enlighten the research topics and to validate the research findings of the other