This article reviews the now extensive research literature addressing the impact of accountability on a wide range of social judgments and choices. It focuses on 4 issues: (a) What impact do various accountability ground rules have on thoughts, feelings, and action? (b) Under what conditions will accountability attenuate, have no effect on, or amplify cognitive biases? (c) Does accountability alter how people think or merely what people say they think? and (d) What goals do accountable decision makers seek to achieve? In addition, this review explores the broader implications of accountability research. It highlights the utility of treating thought as a process of internalized dialogue; the importance of documenting social and institutional boundary conditions on putative cognitive biases; and the potential to craft empirical answers to such applied problems as how to structure accountability relationships in organizations. Accountability is a modern buzzword. In education (Fairchild &

Strategy descriptions like the "Take The Best"-heuristic (G. Gigerenzer et al., 1991), the weighted additive rule, and the equal weight decision rule are competing theories on information integration in probabilistic inference tasks. Behavioral decision research is confronted with the problem of drawing conclusions about unobservable decision strategies from behavioral data. Although there has been considerable progress due to methodical traditions like "Structural Modeling" and "Process Tracing", these paradigms have certain limitations in testing specific hypotheses about individual strategies. Some of these problems are summarized briefly. A deductive method for classifying individual response patterns is introduced. Predictions about regression coefficients are deduced from competing substantial hypotheses about strategies for probabilistic inferences. These can be tested at the level of individual participants. The validity of this classification procedure is demonstrated with a Monte Carlo simulation. Some useful applications of the method are described, limitations of the method and potential generalizations are discussed.

Abstract not found

Cockpit displays of traffic information are designed to support pilots ’ abilities to perform conflict detection and resolution tasks. Three experiments investigated the effects of display dimensionality, conflict geometry, and time pressure of in-flight conflicts on performance. The results indicated that interactive viewpoints in 2 3–D displays eliminated ambiguity costs, resulting in performance on both tasks comparable to a 2–D coplanar display. Viewpoint interactivity in the 3–D displays was vulnerable to increased workload, although corresponding performance was no worse than the 2–D coplanar. All 3 display formats showed performance decrements for nonlevel conflict geometries and increased time pressure. Currently, cockpit displays of traffic information (CDTIs) provide airspace information to the pilot in an ownship-centric format, enabling the pilot to understand the relative positions of other aircraft in the airspace and perform self-separation tasks. As part of an effort to assign more enroute responsibility from air traffic control to the individual pilots, the Federal Aviation Administration (FAA) is developing human factors certification criteria for the use of

Abstract Grouping behaviour occurs often in crowd evacuation. On the one hand, groups are needed for efficient evacuation. On the other hand, large uncontrolled groups (herds) may cause clogging and increase panic. The mechanisms of emergence of leaders and groups in complex socio-technical systems with intelligent technical components are not well understood. This paper presents the first attempt to unveil the role of AmI technology in formation of spontaneous groups in crowd evacuation. To this end several hypotheses were formulated, which were tested by simulation experiments based on a cognitive agent model. The checking of the hypotheses was done in the context of a train station evacuation scenario. The general outcome is that in a system with scarce and uncertain information, AmI technology can be used to stimulate emergence of leaders and groups to increase the efficiency of evacuation. Furthermore, a large penetration rate of ambient devices may be unnecessary and even not appropriate for fluent evacuation. 1

This paper offers a refined conceptualization of consensus formation and demonstrates in three organizations how this conceptualization enables us to uncover new patterns of consensus building. It describes a longitudinal study which investigated consensus formation in three organizations undergoing major strategic change. The study explored whether consensus building occurred during the strategic change, and if so, how. Initial participants of consensus were also investigated as well as changes in the scope of participants in consensus. Consensus building did occur, but contrary to some views, less through an increase in the strength of consensus and more through an increase in the scope of consensus. Additionally, initial consensus was not located among members of the top management team, but more within an interest group whose members benefited from the given direction of the change.

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier’s archiving and manuscript policies are

The hedonic value of an outcome can be influenced by the alternatives to which it is compared, which is why people expect to be happier with outcomes that maximize comparative value (e.g., a job that pays them $45,000 and pays others $40,000) than with outcomes that maximize absolute value (e.g., a job that pays them $50,000 and pays others $55,000). Eight experiments showed that affective forecasters tend to overestimate the importance of comparative value because they do not realize that noticing differences between a target and a standard experience requires cognitive resources, and that hedonic experiences consume more attention than mental representations of those experiences (which are what their forecasts are based on). The results suggest that affective forecasters mispredict the hedonic value of future experiences because they overestimate the extent to which they will think about what they didn’t get while experiencing what they got.