An exploration of values in ethical consumer decision making

Consumer concern for ethical issues has been well documented across much of the developed world. Research on values is also prominent in the literature. Neglected in consumer behaviour is an understanding of the pertinence of particular values in ethical decision making contexts. This paper outlines the results of qualitative research, which explores those values pertinent to ethical consumers in decision making and the nature of their influence in grocery consumption contexts. A questionnaire was used to ascertain the dominance and nature of values influencing consumer decision making in this context.     

Perspectives on consumer decision making: an integrated approach

In the consumer behaviour literature several perspectives on consumer decision making have been considered, including the ‘value perspective’, the ‘information processing perspective’, the ‘emotional perspective’ and ‘cue utilisation theory’. In this paper, a framework which integrates several perspectives on consumer decision making and hypothesises possible links between several basic constructs is developed. The framework is tested by the use of two experimental designs. The results of this study support the complexity of consumer decision making with the following findings. First, consumers do not use their cognitive and affective skills independently, rather they affect each other. Secondly, the cognitive, evaluative constructs of quality and attitude had significant direct effects on buying intention in both experiments, whereas the affective construct of emotion had no significant effects on buying intention in both experiments. Thirdly, in both experiments price affected perceived quality, which in turn affected attitude, which in turn affected buying intention. At the same time, price had no direct effect on buying intention. Copyright © 2005 John Wiley & Sons, Ltd.     

Self‐regulation of consumer decision making and behavior: The role of implementation intentions

People may use the self-regulatory strategy of forming implementation intentions (i.e., if-then plans) to make better consumer decisions and facilitate the translation of those decisions into action. First, research on the mechanisms and effects of implementation intentions is reviewed. Second, we discuss how implementation intentions can be used to improve consumer decision making by promoting attention control and information elaboration, and overcoming disruptive influences. Third, we consider the various problems that militate against the enactment of one's decisions, and evidence is presented to show that implementation intentions are still effective even when goal attainment does not seem to be amenable to self-regulation. Finally, potential moderators of implementation intention effects are discussed.     

Mere exposure and the endowment effect on consumer decision making

Previous researchers (e.g., J. A. Bargh, 1992, 2002) demonstrated the importance of nonconscious processes on consumer choice behavior. Using an advertisement, the authors determined the effect of two nonconscious processes--the mere exposure effect, which increases object preference by increasing consumer exposure to an object, and the endowment effect, which increases object valuation by providing consumer possession of an object--on consumer behavior. Although the mere exposure effect and endowment effect did not produce an interaction, they produced independent effects. The endowment effect increased object valuation but not object preference. The mere exposure effect increased object preference but not object valuation. Thus, at the unconscious level, an increase in object preference does not lead to an increase in object valuation, nor does an increase in object valuation lead to an increase in object preference. The authors discuss the importance of developing measures of unconscious process in advertising effectiveness.     

Elaboration and numerical anchoring: Implications of attitude theories for consumer judgment and decision making

Researchers across many domains have examined the impact of externally presented numerical anchors on perceiver judgments. In the traditional paradigm, “anchored” judgments are typically explained as a result of elaborate thinking (i.e., confirmatory hypothesis testing that selectively activates anchor-consistent information in memory). Consistent with a long tradition in attitude change, we suggest that the same judgments can result from relatively thoughtful or non-thoughtful processes, with more thoughtful processes resulting in judgments that have more lasting impact. We review recent anchoring research consistent with this elaboration-based perspective and discuss implications for past anchoring results and theory in judgment and decision making.     

一种新决策模型——量子决策模型

近10年以来, 一些学者基于量子理论研究思想与方法探索出了量子决策模型。由于该模型独特的理论结构, 它可被用于解释传统决策理论所难以解释的问题, 尤其是个体在不确定情况下的决策行为。该模型解释了诸如分离效应、分类决策的干涉效应以及合取谬误等传统决策模型很难解释的问题, 研究者已经证实其中一种称为量子问题等式的决策模型可以精确地预测决策中的顺序效应。作为一个有助于分析心理学中决策现象的新研究领域, 量子决策模型具有深入研究的理论意义和实践意义。     

Systematic research needs for understanding supervisory-based estimates of SDy in utility analysis

In utility analysis, the estimation of the standard deviation of performance. SDy, is often accomplished by techniques which require supervisory estimates of overall worth. Because these techniques involve human judgment, they are subject to psychometric scrutiny, to research on contextual effects, and to research about supervisors' cognitive perceptions of overall worth. The current paper addresses needs in all of these areas. The psychometric domain implies research needs regarding consistent judgments, accuracy, the meaning of percentiles, and the possibility of negative worth. The contextual and cognitive domains imply research needs related to job and organizational context, to the nature of the utility metric, and to decomposition of the estimation process underlying judgments of overall worth. Such research will help to delineate the boundaries for the application of utility analysis, as well as suggest improvements in current methodologies.     

Models for deferred decision making

Deferred decision theory assumes two simple hypotheses, observations that are purchased sequentially, losses for incorrect terminal decisions, and a constant loss per observation which may depend on the true hypothesis. After every observation, the decision maker may either make a terminal decision and incur a terminal loss if he is incorrect or purchase another observation; his objective is to minimize subjectively expected loss.     

Evolutionary psychology is not the only productive evolutionary approach to understanding consumer behavior

I respond to Vladas Griskevicius and Douglas T. Kendrick (G&;K) and Gad Saad's (S) defenses of the view that Consumer Studies would benefit from the appeal to evolution in all work aimed at understanding consumer behavior. I argue that G&;K and S's reliance on one theoretical perspective, that of evolutionary psychology, limits their options. Further, I point out some specific problems with the theoretical perspective of evolutionary psychology. Finally, I introduce some alternative evolutionary approaches to studying human behavior that could profitably be adopted in consumer research.     

Computer-augmented decision making

The principal judgmental components of multiattribute decision making are examined here with specific reference to how these components can be captured electronically. Once captured, a function, rule, or algorithm may be executed for the integration of this information and the selection of the optimal alternative(s). Two kinds of algorithms are discussed: one based on linear models, the other on fuzzy-set theory and ratio scaling. With on-line support and certain assumptions about human biases (which lead to nonoptimal decisions), the quality of decisions can be enhanced considerably. The principal concerns are with end-user acceptance of computer augmented decisions.     

Principles in judgment/decision making research pertinent to legal proceedings

Principles in the judgment/decision making literature relevant to the legal community are reviewed. These principles are divided into four areas: the decision process itself, communicating a judgment to others, evaluating a decision, and possible ways of “debiasing.” Several influences on the decision process are enumerated, among them being insufficient consideration of base rates, selective memory for relevant material, the framing of the decision in either the domain of losses or the domain of gains, and consideration of the “cues to causation.” Particular attention is paid to suboptimal consideration of covariation information. In communicating the decision to others the two most prominent findings are overconfidence in expressing one's decision and the inability to describe accurately the bases of one's decision. Evaluating a decision is plagued by two biases. The first is the hindsight bias. After an event has occurred we tend to exaggerate how easily we could have predicted the event beforehand. The second is the outcome bias. We tend to base our evaluation of the decision upon the evaluation of the outcome. Among the debiasing techniques mentioned are the admonition to “consider the opposite” of the preferred option, the reduction of reliance on memory, and the use of decision aids.     

How to improve our understanding of group decision making with the help of artificial intelligence

Within science we primarily obtain knowledge of a specific field by reading the published results of theoretical and empirical studies. It is argued that this approach may lead to a biased and incomplete perspective of a research area. It is proposed to also use methods from Artificial Intelligence to elicit, model and use the knowledge of experts. It is expected that especially their heuristic knowledge is relevant for problem solving and consultancy applications. An illustrative example concludes the paper.     

Numeracy and decision making

A series of four studies explored how the ability to comprehend and transform probability numbers relates to performance on judgment and decision tasks. On the surface, the tasks in the four studies appear to be widely different; at a conceptual level, however, they all involve processing numbers and the potential to show an influence of affect. Findings were consistent with highly numerate individuals being more likely to retrieve and use appropriate numerical principles, thus making themselves less susceptible to framing effects, compared with less numerate individuals. In addition, the highly numerate tended to draw different (generally stronger or more precise) affective meaning from numbers and numerical comparisons, and their affective responses were more precise. Although generally helpful, this tendency may sometimes lead to worse decisions. The less numerate were influenced more by competing, irrelevant affective considerations. Analyses showed that the effect of numeracy was not due to general intelligence. Numerical ability appears to matter to judgments and decisions in important ways.     

Artificial intelligence consumer behavior: A hybrid review and research agenda

The advancement of artificial intelligence (AI) technology and its applications has drastically transformed consumer behavior (CB). As consumers interact with these applications on multiple platforms and touchpoints, it becomes crucial to understand how these interactions affect consumer behavior and its components, including personality, attitude, engagement, decision-making, and trust. The research on the relationship between artificial intelligence and consumer behavior (hereafter referred to as AI CB) revolves around these topics and has grown exponentially in recent years. A rigorous review is required to provide directions for future studies by comprehending the extensive literature, understanding research gaps, and identifying the future directions for scholarly work. This article aims to address this research gap by analyzing 107 AI CB articles using the bibliometric and framework-based methodology to provide insights into publication trends, dominant theories, methods, antecedents, decisions, and outcomes in the AI CB literature. Most importantly, the review identifies clusters of research fronts and provides a thematic framework for current research. These clusters or themes relate to AI interaction with consumer behavior dimensions, including consumer acceptance and trust, consumer interaction and engagement, attitude and personality, decision-making, and adoption. This thematic framework and TCM-ADO analysis offer future research directions to advance theory development and have implications for industry and society.     

Dynamic multi-criteria decision making

Most medium-and long-term decision making in industry and government can be viewed as dynamic multi-criteria decision making (MCDM), in which the decision makers are free to alter the emphasis placed on each objective in the light of developing circumstances. In this paper the problem of time-dependent weights in MCDM is discussed and an analysis of empirical data associated with dynamic decision making is presented.     

Cyber peers’ influence for adolescent consumer in decision‐making styles and online purchasing behavior

Nowadays, there is a boom in online purchasing, especially by adolescents. In fact, scholars and marketers alike have long noticed the emergence of adolescent consumers and their consumption behaviors. This research aims at exploring the effect of adolescent decision‐making styles on online purchasing behavior, with peer influence as a moderating variable. An online questionnaire survey was conducted on 2,419 adolescents and further verified by regression analysis and analysis of covariance. Adolescents with planned purchase behaviors can be considered as rational consumers, in that they do not care about fashion, or recreational, hedonistic shopping consciousness, but rather focus on brand, price value, and high quality. Indeed, adolescent purchase decision making can be strengthened by peer influence.