James R. Bettman

Bio: James R. Bettman is an academic researcher from Duke University. The author has contributed to research in topics: Information processing & Consumer behaviour. The author has an hindex of 61, co-authored 151 publications receiving 31312 citations. Previous affiliations of James R. Bettman include Saint Petersburg State University & University of California, Los Angeles.

The adaptive decision maker

Abstract: Preface 1. Adaptive decision behaviour: an introduction 2. Contingencies in decision making 3. Deciding how to decide: an effort/accuracy framework 4. Studying contingent decisions: an integrated methodology 5. Constructive processes in decision making 6. Why may adaptivity fail? 7. Improving decisions and other practical matters 8. The adaptive decision maker: a look backward and a look forward Appendix Footnotes Bibliography.

Constructive Consumer Choice Processes

Abstract: Consumer decision making has been a focal interest in consumer research, and consideration of current marketplace trends (e.g., technological change, an information explosion) indicates that this topic will continue to be critically important. We argue that consumer choice is inherently constructive. Due to limited processing capacity, consumers often do not have well-defined existing preferences, but construct them using a variety of strategies contingent on task demands. After describing constructive choice, consumer decision tasks, and decision strategies, we provide an integrative framework for understanding constructive choice, review evidence for constructive consumer choice in light of that framework, and identify knowledge gaps that suggest opportunities for additional research.

Adaptive Strategy Selection in Decision Making.

Abstract: : The authors examine the role of effort and accuracy in the adaptive use of decision processes. A computer simulation study that used the concept of elementary information processes identified heuristic choice strategies which approximate the accuracy of normative procedures while requiring substantially less effort. However, no single heuristic did well across all task and context conditions. Of particular interest was the finding that under time constraints, several heuristics were clearly more accurate than a normative procedure. Two process tracing studies showed a significant degree of correspondence between the efficient strategies for a given decision problem identified by the simulation and actual decision behavior. People were highly adaptive to changes in the nature of the alternatives available to them and to the presence of time pressure. (Author)

User Acceptance of Computer Technology: A Comparison of Two Theoretical Models

Abstract: Computer systems cannot improve organizational performance if they aren't used. Unfortunately, resistance to end-user systems by managers and professionals is a widespread problem. To better predict, explain, and increase user acceptance, we need to better understand why people accept or reject computers. This research addresses the ability to predict peoples' computer acceptance from a measure of their intentions, and the ability to explain their intentions in terms of their attitudes, subjective norms, perceived usefulness, perceived ease of use, and related variables. In a longitudinal study of 107 users, intentions to use a specific system, measured after a one-hour introduction to the system, were correlated 0.35 with system use 14 weeks later. The intention-usage correlation was 0.63 at the end of this time period. Perceived usefulness strongly influenced peoples' intentions, explaining more than half of the variance in intentions at the end of 14 weeks. Perceived ease of use had a small but significant effect on intentions as well, although this effect subsided over time. Attitudes only partially mediated the effects of these beliefs on intentions. Subjective norms had no effect on intentions. These results suggest the possibility of simple but powerful models of the determinants of user acceptance, with practical value for evaluating systems and guiding managerial interventions aimed at reducing the problem of underutilized computer technology.

Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence:

Abstract: Evidence from past research and insights from an exploratory investigation are combined in a conceptual model that defines and relates price, perceived quality, and perceived value. Propositions ab...

Conceptualizing, measuring, and managing customer-based brand equity

Abstract: The author presents a conceptual model of brand equity from the perspective of the individual consumer. Customer-based brand equity is defined as the differential effect of brand knowledge on consu...

The elaboration likelihood model of persuasion

Abstract: Publisher Summary This chapter outlines the two basic routes to persuasion. One route is based on the thoughtful consideration of arguments central to the issue, whereas the other is based on the affective associations or simple inferences tied to peripheral cues in the persuasion context. This chapter discusses a wide variety of variables that proved instrumental in affecting the elaboration likelihood, and thus the route to persuasion. One of the basic postulates of the Elaboration Likelihood Model—that variables may affect persuasion by increasing or decreasing scrutiny of message arguments—has been highly useful in accounting for the effects of a seemingly diverse list of variables. The reviewers of the attitude change literature have been disappointed with the many conflicting effects observed, even for ostensibly simple variables. The Elaboration Likelihood Model (ELM) attempts to place these many conflicting results and theories under one conceptual umbrella by specifying the major processes underlying persuasion and indicating the way many of the traditionally studied variables and theories relate to these basic processes. The ELM may prove useful in providing a guiding set of postulates from which to interpret previous work and in suggesting new hypotheses to be explored in future research.

Toward a Theory of Situation Awareness in Dynamic Systems

Abstract: This paper presents a theoretical model of situation awareness based on its role in dynamic human decision making in a variety of domains. Situation awareness is presented as a predominant concern in system operation, based on a descriptive view of decision making. The relationship between situation awareness and numerous individual and environmental factors is explored. Among these factors, attention and working memory are presented as critical factors limiting operators from acquiring and interpreting information from the environment to form situation awareness, and mental models and goal-directed behavior are hypothesized as important mechanisms for overcoming these limits. The impact of design features, workload, stress, system complexity, and automation on operator situation awareness is addressed, and a taxonomy of errors in situation awareness is introduced, based on the model presented. The model is used to generate design implications for enhancing operator situation awareness and future directio...