Search results

The purpose of this paper is to explore investigative decision-making processes in the context of major crimes as experienced by the law enforcement agents.

Episodic interviews were conducted with six agents from medium-sized police forces in the UK. Following the framework of naturalistic inquiry, qualitative content analysis took place with the assistance of Atlas.ti software. To ensure the validity of findings, the within method triangulation was preferred, by additionally analysing the interview transcripts with Alceste.

Findings from this study revealed a variety of internal factors at play, shaping the decision-making course into an act of balancing various desired goals. Detectives appear to assess a situation based on their experiences confirming that the naturalistic decision-making model may assist in understanding investigative decision-making.

Due to the busy schedule of law enforcement agents the number of participants was limited and availability difficult; therefore, this study can be thought of as a pilot study that will inspire researchers to use the same method for in-depth understanding of investigative decision-making.

Results captured the ill-defined goals in the police environment and provided ways of decreasing their impact on investigative decision-making thus should help detectives to understand their decision-making limitations and strengths.

This project will enhance the psychological understanding of investigative decision-making.

This project assists in understanding the psychological aspect of investigative decision-making during police duty and provides the opportunity to law enforcement agents to re-evaluate situations in order to improve the investigative decision-making process; while adds to existing literature.

Pew and Mavor (1998) called for an integrative representation of human behavior for use in models of individual combatants and organizations. Models with integrated representation of behavior have only been achieved at rudimentary levels according to those performing the studies (e.g. Pew & Mavor, 1998; Tulving, 2002) and those building the models (e.g. Warwick et al., 2002). This chapter will address aspects of cognitive performance that are important to incorporate into models of combat based on acceptance of theory, strength of empirical data, or for other reasons such as to bridge gaps where incomplete knowledge exists about cognitive behavior and performance. As a starting point, this chapter will assess which of Pew and Mavor’s recommendations are still appropriate as determined by a review of selected literature on cognition and its representation. We will also provide some review and extensions of key literature on cognition and modeling and suggest a way ahead to close the remaining gaps. Different aspects of cognition are described with recent findings, and most are followed by an example of how they have been represented in computer models or a discussion of challenges to their representation in modeling.

The purpose of this paper is to draw on the naturalistic decision making and cognitive science literature to examine how experienced crisis managers utilize the intuitive and analytical strategies when managing complex incidents. A cognitive model that describes the interplay between strategies is presented and discussed, and the specific role that intuition plays in analytical decision making is addressed.

Designed as a conceptual paper, the extant literature is reviewed to advance discussions on the theme of intuitive and analytical decision making in the naturalistic environment. A new model of expert intuition – the information filtering and intuitive decision model – is presented and evaluated against existing cognitive models from the wider literature.

The paper suggests that experts’ ability to make intuitive decisions is strongly hinged on their information processing skills that allow irrelevant cues to be sifted out while the relevant cues are retained. The paper further revealed that experts generally employ the intuitive mode as their default strategy, drawing on the analytical mode only as conditions warrant.

Prior research has shown that experts often make important task decisions using intuitive or analytical strategies or by combining both, but the sequence these should typically follow is still unresolved. Findings from the intuition model reveal that although intuition often precedes analytical thinking in almost all cases, both strategies exist to offer significant values to decision makers if the basis of their application is well understood.

The purpose of this paper is to examine the dominant consumer decision theory models and understand why that theory has received little empirical validation. A “decision waves” theory is proposed – an alternative, multi‐phase approach to decision making using image theory. An approach to validating empirically the multi‐phase theory is outlined.

This conceptual paper examines the foundations of modern consumer decision theory and argues for a more representative model of actual consumer decisions.

Decision waves provide a theoretical approach to represent more accurately consumer decision making and improve understanding in this foundational component of marketing. Decision waves do not change detailed empirical findings: however, they do change the macro perspective of how those findings are assembled for marketing.

An empirical test of decision waves theory is ongoing.

The concepts outlined in this paper will change segmentation, positioning and how tactical plans are developed within the marketing mix, particularly for promotional strategies.

A theoretical approach that represents decision making more accurately will bring us closer to understanding this foundational component of marketing. It provides a basis for differentiation in congested markets.

The purpose of this paper is to call for inclusion of alternative but complementary conceptual perspectives in entrepreneurial decision-making theory and practice.

A conceptual approach, drawing on two sets of theoretical perspectives relating to decision making of entrepreneurs, is adopted.

The paper presents a conceptual framework of entrepreneurial decision making utilising the intersection between a metacognitive model of the entrepreneurial mindset and the recognition-primed decision-making theory. The paper argues that the convergence of these theoretical viewpoints provides a selection of decision-making processes for entrepreneurs in an uncertain business environment.

Decision-making models and tools are available to entrepreneurs; however, the relevance and applicability are restrained by the complexity and uncertainty of business environments in which entrepreneurs operate. New and more inclusive conceptual perspectives are required to improve the accuracy of decision making.

The study offers a framework that integrates two diverse theoretical dimensions of entrepreneurial decision making. The findings of this study provide direction for practice and for future research on entrepreneurial decision making. The paper intends to encourage researchers to support a new combined theoretical approach and to help practitioners better understand the reasons for entrepreneurial decision failure.

Distributed performance arrangements are increasingly used by organizations to structure dyadic and team interactions. Unfortunately, distributed teams are no panacea. This chapter reviews some of the advantages and disadvantages associated with the geographical and temporal distribution of team members. An extended discussion of the implications of distributed team performance for individual, team, and organizational decision making is provided, with particular attention paid to selected cultural factors. Best practices and key points are advanced for those stakeholders charged with offsetting the performance decrements in decision making that can result from distribution and culture.

The paper seeks to explore the role of self‐regulation in the use of decision heuristics by entrepreneurs.

An exploratory mixed‐methods study incorporating qualitative and quantitative data, and generating propositions to guide future research and practice.

The findings suggest that entrepreneurs use heuristics frequently in relation to the evaluation of opportunities, but rely on more systematic decision means during the exploitation phase. In addition, entrepreneurs appear to employ heuristics in an effective fashion by using skills of self‐regulation. This finding questions widespread assumptions about the inherent bias and cognitive errors associated with this type of entrepreneurial decision‐making.

Being an exploratory study of a relatively small sample, the findings are tentative and not generalized to a wider population. However, the study implies that future researchers should explore these topics in greater depth.

Self‐regulatory skills can be primed and enhanced using systematic interventions and the study suggests that these techniques could be used to improve the education and management of heuristic decision making by entrepreneurs.

This study is one of the first to explore the complex role played by self‐regulation in the use of heuristics by entrepreneurs, and also one of the first to explore the conditions surrounding the use of specific decision heuristics. The study also adopts an original approach by assuming that heuristics may be effective and rational decision means.

Technology for training military teams has evolved through a convergence of advances in simulation technology for individual and collective training, methods for analyzing teamwork and designing training solutions, and intelligent tutoring technologies that adapt training to the student, to accelerate learning. A number of factors have slowed this evolution toward intelligent team tutoring systems (ITTS), including the challenges of processing communications data, which are the currency of teamwork, and the paucity of automated and generalizable measures of team work. Several systems fulfill a subset of the features required of an ITTS, namely the use of team training objectives, teamwork models, measures of teamwork, diagnostic capability, instructional strategies, and adaptation of training to team needs. We describe these systems: the Advanced Embedded Training System (AETS), Synthetic Cognition for Operational Team Training (SCOTT), the AWO Trainer, the Benchmarked Experiential System for Training (BEST), and the Cross-Platform Mission Visualization Tool. We close this chapter with recommendations for future research.

The international aviation industry uses a special form of human factors training with their flight deck crews and other teams, called crew resource management (CRM). CRM is designed by psychologists and pilots to reduce errors and accidents and to improve emergency response capability by improving teamwork skills. Key topics include communication, decision making, assertiveness and stress management. CRM courses are now being used in shipping, medicine and the nuclear power industry. Follows an outline of CRM and describes an application in the offshore oil industry with control room operators and emergency command teams.