A longstanding controversy in economics and finance is whether financial markets are governed by rational forces or by emotional responses. We study the importance of emotion in the decisionmaking process of professional securities traders by measuring their physiological characteristics, e.g., skin conductance, blood volume pulse, etc., during live trading sessions while simultaneously capturing real-time prices from which market events can be detected. In a sample of 10 traders, we find statistically significant differences in mean electrodermal responses during transient market events relative to no-event control periods, and statistically significant mean changes in cardiovascular variables during periods of heightened market volatility relative to normal-volatility control periods. We also observe significant differences in these physiological response across the 10 traders which may be systematically related to the traders’ levels of experience.

Performers in time-stressed, information-rich tasks develop rule-based, simplification strategies to cope with the severe cognitive demands imposed by judgment and decision making. Linear regression modeling, proven useful for describing judgment in a wide range of static tasks, may provide misleading accounts of these heuristics. That approach assumes cue-weighting and cueintegration are well described by compensatory strategies. In contrast, evidence suggests that heuristic strategies in dynamic tasks may instead reflect rule-based, noncompensatory cue usage. We therefore present a technique, called Genetics-Based Policy Capturing (GBPC), for inferring noncompensatory, rule-based heuristics from judgment data, as an alternative to regression. In GBPC, rule-base representation and search uses a genetic algorithm, and fitting the model to data uses multi-objective optimization to maximize fit on three dimensions: a) completeness (all human judgments are represented); b) specificity (maximal concreteness); and c) parsimony (no unnecessary rules are used). GBPC is illustrated using data from the highest and lowest scoring participants in a simulated dynamic, combat information center (CIC) task. GBPC inferred rulebases for these two performers that shed light on both skill and error. We compare the GBPC

The purpose of this work is to improve understanding of existing and proposed decision systems, ideally to improve the design of future systems. A "decision system " is defined as a collection of information-processing components-- often involving humans and automation (e.g., computers)-- that interact towards a common set of objectives. Since a key issue in the design of decision systems is the division of work between humans and machines (a task known as "function allocation"), this report is primarily intended to help designers incorporate automation more appropriately within these systems. This report does not provide a design methodology, but introduces a way to qualitatively analyze potential designs early in the system design process. A novel analytical framework is presented, based on the concept of "semi-Structured " decision processes. It is believed that many decisions involve both well-defined "Structured " parts (e.g., formal procedures, traditional algorithms) and ill-defined "Unstructured " parts (e.g., intuition, judgement, neural networks) that interact in a known manner. While Structured processes are often desired because they fully prescribe how a future decision (during "operation") will be made, they are limited by what is explicitly understood prior to operation. A system designer who incorporates Unstructured processes into

The success of simulation environments will depend partly on how realistically the models mimic human behavior. While human behavior is affected by various moderators (see Pew and Mavor [28], for an initial list), cognitive models typically do not take into account the effects of many of these moderators. We propose that cognitive models can be augmented to account for such effects by modifying either their knowledge or the parameters of the architecture that they are built with. To provide an example of the two ways in which cognitive models can be modified to capture the effects of behavior moderators, we present an ACT-R model that performs a cognitive task while being affected by the moderators of as anxiety and pre-task appraisal. These changes are validated in a preliminary way by comparison with human data, which shows us where these models can be improved and provides lessons for further work. Most importantly, we argue that more realistic models of human behavior reflecting these moderators and individual differences can be achieved by implementing similar modifications within other cognitive models and by reusing these modifications for an existing architecture as an overlay.

Brandstätter, Gigerenzer and Hertwig (2006) put forward the priority heuristic (PH) as a fast and frugal heuristic for decisions under risk. According to the PH, individuals do not make trade-offs between gains and probabilities, as proposed by expected utility models such as cumulative prospect theory (CPT), but use information in a non-compensatory manner and ignore information. We conducted three studies to test the PH empirically by analyzing individual choice patterns, decision times and information search parameters in diagnostic decision tasks. Results on all three dependent variables conflict with the predictions of the PH and can be better explained by the CPT. The predictive accuracy of the PH was high for decision tasks in which the predictions align with the predictions of the CPT but very low for decision tasks in which this was not the case. The findings indicate that earlier results supporting the PH might have been caused by

Annual Technical Conference and

Even though intuition is recognized as imperative in strategic thinking management literature is surprisingly silent on the issue. This inquiry thus provides an historical and hermeneutic review of philosophical, psychological and management theory on intuition. It reveals that philosophers conceive intuition as rational while psychologists tend not to. Philosophers do so primarily because intuition is anchored in Ideas, Forms and Archetypes, which are perceived as a priori laws governing and conditioning all existence. The argument is that intuition is the ontological foundation for any normative theory of rationality. Implications for the rationality debate are discussed. Three levels of intuition are discerned and contrasted with analytical thinking. The first and second levels correspond to intuitions from the personal and collective unconscious experience respectively. They can be either introverted or extraverted. The third level corresponds to what some philosophers call the non-dual, integral state of mind. An empirical study including personal interviews with 105 Norwegian top managers indicate that in strategic thinking more emphasis is put on intuition than analysis, especially in exploration of new terrain and technology. They define intuition primarily in accordance with level one. In describing its key features they focus on foresight, new ideas and synthesis. Finally Myers Briggs Type Indicator ® was applied, revealing that they have a strong personality preference for intuition.

Abstract — In this paper a computational model for decision making based on experiences is presented, inspired by the Somatic Marker Hypothesis. The use of the model is illustrated for the domain of fighter pilot decision making. Hereby, simulation runs have been performed upon this scenario, and the results thereof have been formally verified based upon properties inspired on Damasio’s Somatic Marker Hypothesis. Keywords-Decision making, Somatic markers

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The integrative framework of technology use (IFTU) posits that to fully explain technology adoption and sustained usage, four mechanisms—namely, reason-oriented action, sequential updating, feedback, and habit—should be taken into account simultaneously in a unified model. Recently, a TAM-based two-wave panel model drawing on the IFTU paradigm has been shown to be superior to other partial models in explaining individuals ’ use of a Web-based portal. In a continuing effort to reinforce the IFTU paradigm, this study first develops and tests a TPB-based three-wave panel model to explain individuals ’ use of a software application in an organizational context. In addition, this study attempts to refine the IFTU paradigm by examining long-time (as opposed to short-time) effects of the four mechanisms that cannot be systematically examined in a two-wave setting. The findings of this three-wave panel study indicate that the proposed model integrating the four mechanisms represents technology use better than other conventional models. Yet, this research also shows that IFTU should be refined further in a way to represent the distal effects of sequential updating and habit on post-adoption phenomena. Overall, this research clearly reveals that a refined IFTU paradigm will be a simple, but powerful, conceptual tool for explaining how user evaluations and behavior evolve with experience. This article concludes with a discussion of distal effects vis-à-vis proximal effects and suggestions of interesting avenues for further development of the IFTU paradigm.