Experts and Decision Making: First Steps Towards a Unifying Theory of Decision Making in Novices, Intermediates and Experts

Expertise research shows quite ambiguous results on the abilities of experts in judgment and decision making (JDM) classic models cannot account for. This problem becomes even more accentuated if different levels of expertise are considered. We argue that parallel constraint satisfaction models (PCS) might be a useful base to understand the processes underlying expert JDM and the hitherto existing, differentiated results from expertise research. It is outlined how expertise might influence model parameters and mental representations according to PCS. It is discussed how this differential impact of expertise on model parameters relates to empirical results showing quite different courses in the development of expertise; allowing, for example, to predict under which conditions intermediates might outperform experts. Methodological requirements for testing the proposed unifying theory under complex real-world conditions are discussed.Judgment and Decision Making, Expertise, Intermediate Effects, Parallel Constraint Satisfaction, Mental Representation

Aggregation of probabilisitic logically related judgments

Information aggregation is at the core of many problems in computer science. Judgement aggregation models multi-agent decision making by aggregating individual opinions from various sources. It does however assume that the sources are certain in their opinions and also subject to the same logical constraints. We relax both of these assumptions and build a more general framework with uncertain information sources that we model in probabilistic logic. We also propose aggregation functions for this new framework

The role of emotions and cognitive biases in ethical decisions

Ethical sensemaking is a process of gathering and organizing information in a meaningful way to guide understanding of a situation. Ethical situations in organizations are dynamic with new information often emerging over time. How one processes new information and incorporates it into their understanding of a situation can be affected by emotions, decision framing, and the degree to which the new information confirms or conflicts with initial information about the situation. This study examined the impact of the discrete emotions of anger and guilt, ethical framing, and confirmation bias on ethical sensemaking processes and decision ethicality when new information was introduced, information that either conflicted with or was consistent with what participants already knew about a challenging organizational situation. Anger and guilt negatively impacted several sensemaking strategies. Anger led to lower decision ethicality compared to both guilt and neutral conditions. Mediational effects of confirming and conflicting information on emotions and sensemaking processes were also found. Practical and theoretical implications and areas for future research are discussed

Investigating pluralistic data architectures in data warehousing

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonUnderstanding and managing change is a strategic objective for many organisations to successfully compete in a market place; as a result, organisations are leveraging their data asset and implementing data warehouses to gain business intelligence necessary to improve their businesses. Data warehouses are expensive initiatives, one-half to two-thirds of most data warehousing efforts end in failure. In the absence of well-formalised design methodology in the industry and in the context of the debate on data architecture in data warehousing, this thesis examines why multidimensional and relational data models define the data architecture landscape in the industry. The study develops a number of propositions from the literature and empirical data to understand the factors impacting the choice of logical data model in data warehousing. Using a comparative case study method as the mean of collecting empirical data from the case organisations, the research proposes a conceptual model for logical data model adoption. The model provides a framework that guides decision making for adopting a logical data model for a data warehouse. The research conceptual model identifies the characteristics of business requirements and decision pathways for multidimensional and relational data warehouses. The conceptual model adds value by identifying the business requirements which a multidimensional and relational logical data model is empirically applicable

The Role of Clinical Features in the Diagnostic Reasoning of Psychologists

This item is only available electronically.Across health and medical domains, experts rely on idiosyncratic case-based pattern recognition to rapidly and accurately identify significant features that define a case. Understanding how clinical psychologists use features to form a diagnosis can provide valuable insights into changes in diagnostic performance as a function of experience. Previous studies examining the diagnostic accuracy of Clinical Psychologists have demonstrated that practicing Clinical Psychologists are no more accurate at diagnosing mental health conditions than Undergraduate psychology students. This study aimed to explore how the interpretation and use of clinical features develops with experience to facilitate diagnostic reasoning. Undergraduate psychology students (n = 24), Clinical Masters students (n = 2) and Clinical Psychologists (n = 10) were presented with eight mental health case studies. The case studies contained a combination of seven features: those shared between the possible diagnoses and those unique to the primary diagnosis and contextual features. Participants were prompted to give primary and secondary diagnoses for the case studies then asked to rate the extent to which each of the seven features supported the primary and secondary diagnoses. On average, Clinical Psychologists displayed the best diagnostic accuracy. Additionally, tertiary education predicted diagnostic accuracy and the use of unique features but clinical experience was predictive of neither. Rather, clinical experience predicted the use of contextual features (i.e. the character’s age or occupation). Future research should extend on these findings using real-life case studies and non-aggregated feature acquisition data.Thesis (B.PsychSc(Hons)) -- University of Adelaide, School of Psychology, 202

Synthetic Grid: A critical framework to inform the development of social innovation metrics

Overall, Work Package 3 (WP3) of the CRESSI (Creating Economic Space for Social Innovation) project aims to address two overarching questions: 1. What are the relationships between social impact, performance measurement and accountability in the processes of social innovation? 2. How can effective performance measurement enhance the impacts and outcomes of social innovation processes, particularly for the disenfranchised or disempowered? As a foundation for these research objectives, this paper develops a critical accounting framework to inform the development and operationalization of a range of social innovation metrics that will be used elsewhere in the CRESSI project. The ultimate purpose of this work is to help shape appropriate and effective methodologies and indicators by which the empirical material in CRESSI can be tested in terms of its presentation of innovations to alter the structural relations that cause and perpetuate marginalization for target populations. Such analyses will also inform the overall policy and practice recommendations of CRESSI

Coaches' decision making

Frank C, Wright D, Holmes P. Mental simulation and neurocognition: Advances for motor imagery and action observation training in sport. In: Routledge International Encyclopedia of Sport and Exercise Psychology. London: Routledge; 2020: 411-429

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

NATO Code of Best Practice for C2 Assessment

This major revision to the Code of Best Practice (COBP) for C2 Assessment is the product of a NATO Research and Technology Organisation (RTO) sponsored Research Group (SAS-026). It represents over a decade of work by many of the best analysts from the NATO countries. A symposium (SAS-039) was hosted by the NATO Consultation Command Control Agency (NC3A) that provided the venue for a rigorous peer review of the code. This new version of the COBP for C2 assessment builds upon the initial version of the COBP produced by SAS-002. The earlier version focused on the analysis of ground forces at a tactical echelon in mid- to high-intensity conflicts. In developing this new version of the COBP, SAS-026 focused on a changed geopolitical context characterized by a shift from preoccupation with a war involving NATO and the Warsaw Pact to concern for a broad range of smaller military conflicts and Operations Other Than War (OOTW). This version also takes into account the impact of significantly improved information-related capabilities and their implications for reducing the fog and friction traditionally associated with conflict. Significantly reduced levels of fog and friction offer an opportunity for the military to develop new concepts of operations, new organizational forms, and new approaches to C2, as well as to the processes that support it. In addition, SAS-026 was cognizant that NATO operations are likely to include coalitions of the willing that might involve Partnership for Peace (PfP) nations, other partners outside of NATO, international organizations, and NGOs. Cost analyses continue to be excluded because they differ among NATO members, so no single approach would be appropriate. Advances in technology are expected to continue at an increasing rate and spur both sustaining and disruptive innovation in military organizations. It is to be expected that this COBP will need to be periodically revisited in light of these developments.https://digitalcommons.odu.edu/msve_books/1012/thumbnail.jp