The effect of attribute-based and alternative-based processing on consumer choice in context

The current research proposes that the extent to which consumer choices are affected by the decision process depends on the underlying nature of the choice problem. Specifically, choices resulting from substantial inter-brand comparisons and tradeoff analyses are vulnerable to whether product information is evaluated by attribute- or alternative-based processing. By contrast, choices resulting from a minimal cognitive processing are less sensitive to variations in the decision strategy employed. We test our theory in the well-known domain of choice context effects. Across three studies using multiple operationalizations of the decision process (i.e., information display format, product presentation mode, and processing goal), we find converging evidence that the more cognitively involving compromise choice increases when the environment facilitates attribute- versus alternative-based processing. Conversely, the choice of asymmetrically dominating option, which is characterized by relatively little analytical processing, does not depend on the type of decision strategy highlighted by the task.     

Big Data and Information Processing in Organizational Decision Processes

Data-centric approaches such as big data and related approaches from business intelligence and analytics (BI&A) have recently attracted major attention due to their promises of huge improvements in organizational performance based on new business insights and improved decision making. Incorporating data-centric approaches into organizational decision processes is challenging, even more so with big data, and it is not self-evident that the expected benefits will be realized. Previous studies have identified the lack of a research focus on the context of decision processes in data-centric approaches. By using a multiple case study approach, the paper investigates different types of BI&A-supported decision processes, and makes three major contributions. First, it shows how different facets of big data and information processing mechanism compositions are utilized in different types of BI&A-supported decision processes. Second, the paper contributes to information processing theory by providing new insights about organizational information processing mechanisms and their complementary relationship to data-centric mechanisms. Third, it demonstrates how information processing theory can be applied to assess the dynamics of mechanism composition across different types of decisions. Finally, the study’s implications for theory and practice are discussed.     

Organizational Structure and Managerial Decisions

We investigate how the organizational structure of a firm influences the decision making of its top management. Different organizational structures lead information to be processed in different ways by the individual decision makers, potentially creating an informational cascade within the organization. We analyze two organizational structures: the first inducing sequential information processing, the second inducing batch information processing. In particular, we characterize the optimal organizational structure using the signal precision of the top manager, i.e., the value of his private information.     

Linguistic barriers to consumer information processing: Information overload in the hispanic population

The ability of individuals to assimilate and process consumer information appears to have finite limits. If consumers are given information which exceeds their processing capacity, information overload is said to exist and results in less effective decision making. The relationship between information overload and linguistic ability was investigated in this study. Americans and Hispanics were presented with varying amounts of consumer information in their native and non-native language. As predicted, information can act as a stressor, affecting decision making in a non-native language prior to affecting decision making in a dominant language. Information overload occurred sooner in Hispanics and Americans when consumer information was presented in their non-dominant language.     

Means–end analysis: Does the affective state influence information processing style?

Means–end theory aims at explaining how consumers evaluate products by linking relevant attributes to perceived consequences to desired ends in a hierarchical way, based on core assumptions of cognitive psychology about human information processing. This study investigates the influence of affective states on information processing styles in a means–end measurement situation, thus taking into account an important antecedent and correlate of human decision making and behavior that has received scarce attention so far in the methodological literature on means–end chains. The results reveal that a person's affective state indeed influences the style of information processing. Respondents in a positive mood used more general knowledge structures and processed the laddering questionnaire faster than respondents in a negative or neutral mood. The laddering technique, which measures means–end chains, thus seems to be sensitive to situational effects, and this finding indicates that affective states then also might have an influence on product knowledge and the decision‐making process in a purchase situation. © 2004 Wiley Periodicals, Inc.     

Overcoming information overload in retail environments: Imagination and sales promotion in a wine context

Information overload is a common problem in retail environments. Reducing information in a retail environment is not always feasible or desirable given the plethora of products and extent of limitations on retailers in terms of merchandising and display decisions. Therefore, retailers need other ways of overcoming information overload than simply reducing the amount of information. However, extant research is unsettled with respect to arguments in favor of and against adverse effects of information overload. To enhance our understanding of these issues, the present research presents two studies that investigate the moderating role of consumer decision processing approaches in an information overload retail space. The findings reveal that the consumer imagination offers a more efficient processing route, circumventing the frustration associated with information overload and leading to enhanced consumer outcomes compared to the less efficient consideration route. Further, heuristic processing triggered by sales promotions in high information retail environments lead to piqued arousal and enhanced consumer imagination, ultimately bolstering consumer responses to the product. Implications, limitations, and future research directions are discussed.     

A suggested approach to linking decision styles with business ethics

This essay seeks to link management action with business ethics. It utilizes two conceptual models of decision making (bounded rationality and preferred decision styles) to examine the important processes of information gathering and information processing. This analysis is then related to the ethical aspects of a business decision to help explain differences in the selection of ethical criteria.John E. Fleming is Professor of Management, School of Business Administration, University of Southern California. He worked in industry for fifteen years before joining the faculty at USC. His areas of academic research are business ethics, corporate strategy, and public policy.     

对决策支持系统的认识

管理的核心是“决策”。决策支持系统作为一种新兴的信息技术,能够为企业提供各种决策信息及诸多问题的解决方案,从而减轻了管理者从事低层次信息处理和分析的负担,专注于最需要决策的工作,提高决策的质量和效率。决策支持系统主要应用于销售支持、客户分析、财务分析、企业分析和市场研究等方面,对企业决策至关重要。     

Exploring antecedents of healthy food choices: an Indian experience

Label information on food items is seen as a tool to facilitate better choices. Merely, provision of label information may not lead to the desired outcome. Comprehension and processing of label information during consumer decision making is crucial for better food choices. Based on the primary data obtained from 150 consumers of pre‐packaged food items, the research proposes a conceptual model for healthier food choices. Previously, a number studies related to consumer decision making have employed ‘label reading’ and ‘label use’ interchangeably. Present research advocates that label reading does not amount to label use. Findings from ordered probit model and path analysis suggest that comprehension of label information leads to increase in its perceived usefulness. Further, increased perceived usefulness facilitates better food choice. Instances of better food choices can be maximized by enhancing perceived usefulness and comprehension of label information through educational and awareness campaigns, especially in context of developing countries such as India.     

A heuristic-systematic processing analysis of the effectiveness of product warning labels

In this article we present the heuristic-systematic model (Chaiken, 1980, 1987; Chaiken, Liberman, & Eagly, 1989) as a theoretical framework for research on product warning labels. The model proposes two fundamental information processing modes. When processing systematically, perceivers access, scrutinize, and integrate all useful information to reach their judgment. In contrast, heuristic processing involves the use of learned knowledge structures in the form of simple decision rules, or cognitive heuristics, to reach judgments. In addition to proposing when either or both of these processing modes will occur, and with what effect, the model also specifies three different underlying types of processing motivations, termed accuracy, defense, and impression, each with implications for information processing and judgments. This model is used to explain past findings on the effectiveness of product warning labels, and to suggest new areas for future research as well as practical guidelines for the design of warning labels. © 1998 John Wiley & Sons, Inc.     

Processing and Retrieval of Inferences and Descriptive Advertising Information: The Effects of Message Elaboration

Abstract

Two issues make advertising effectiveness difficult to assess: (1) advertising effects occur both during ad processing and when ad information is retrieved, and (2) the information that consumers derive from advertisements is likely to be some combination of explicit information and inferences. The study reported in this paper addresses these issues, examining the effects of encoding and time delay on advertising processing. Results indicate that while some types of inferences (product features) are more likely to be made under strong than weak encoding conditions, other types of inferences (consumption situation) are not affected by encoding. In addition, at the time of a decision (after a time delay), memory information use depends both upon individual brand accessibility and the relative accessibility of alternative brands in the memory set. Implications for both advertising researchers and managers are offered.     

The role of positive emotions in experiential decisions

This research examines how consumers experience decision making for experiential products such as vacations. We combine data from 1) ethnographic interviews, 2) online community discussion forums, and 3) an introspective vacation-planning task to explore the experience of emotion in the decision process and to develop a new model of decision making that extends extant decision theories. We find that consumers experience a variety of positive emotions as they plan vacations, from facilitative feelings that guide the plan to fantasy feelings consumed for pleasure. Positive emotions are most evident in reaction to imagery and when the consumer's self identity is salient, and often precede more analytic information processing. Overall, this research offers a richer understanding of the emotional nature of consumer decision making for experiential products and services.     

The nature of information and overconfidence on venture capitalists' decision making

Venture capitalists (VCs) are considered experts in identifying high potential new ventures—gazelles. Thus, the VC decision process has received tremendous attention within the entrepreneurship literature. Yet, most studies on VC decision-making focus on which decision criteria are central to selecting gazelles. Although informative, the majority of these studies has neglected cognitive differences in how VCs make decisions. This is surprising considering the influence cognitive differences are likely to have on the exploitation of an opportunity as well as its influence on likely success. The current study investigates whether VCs are overconfident, as well as the factors surrounding the decision that lead to overconfidence.Overconfidence describes the tendency to overestimate the likely occurrence of a set of events. Overconfident people make probability judgments that are more extreme than they should, given the evidence and their knowledge. In the case of the new venture investment decision, overconfident VCs may overestimate the likelihood that a funded company will succeed.The results of the current study indicate that VCs are indeed overconfident (96% of the 51 participating VCs exhibited significant overconfidence) and that overconfidence negatively affects VC decision accuracy (the correlation between overconfidence and accuracy was 0.70). The level of overconfidence depended upon the amount of information, the type of information, and whether the VC strongly believes the venture will succeed or fail.As more information becomes available, people tend to believe they will make better decisions; they are making a “more informed decision.” More information ideally should enable the VCs to assess any potential pitfalls. However, additional information makes the decision more complex. Information factors may contradict and relate to other information in unexpected ways. Even if more information is available, people usually don't analyze all of it (even though they believe they do). Thus, more information creates greater confidence, but it also leads to lower decision accuracy.The type of information that is available also impacts overconfidence and decision accuracy. VCs are intuitive decision makers. When people are familiar with a decision and the structure of the information surrounding that decision, they resort to automatic information processing. On the other hand, if information surrounding the decision is structured in an unfamiliar way, people need to decipher what each piece of information means and how that impacts their overall accuracy. In the case of expert VCs, that means they must deviate from their intuitive style. It seems that forcing them outside their “comfort zone” has a negative effect on their confidence and has an even greater effect (negative) on their accuracy.There is evidence of an “availability bias” in VC decision-making; VCs rely on how well the current decision matches past successful or failed investments. VCs are overconfident in their prediction of venture success when they predict a very high level of success. VCs are also overconfident in their prediction of venture failure when they predict a very low likelihood of success. This high level of overconfidence in success predictions (or failure predictions) may encourage the VC to limit information search and fund a lower potential investment (or prematurely reject a stronger potential investment).Although overconfidence in itself does not necessarily lead to a wrong decision, the bias is likely to inhibit learning and improving the decision process. Overconfident VCs may not fully consider all relevant information, nor search for additional information to improve their decision. Moreover, the natural tendency for people to recall past successes rather than failures may mean that VCs will make the same mistakes again. VCs can take simple steps to reduce the effect of overconfidence, including counterfactual thinking (i.e., imaging scenarios where current assumptions might not hold), formally recording how past decisions were made at the time of the decision (versus trying to recall how that decision was made from memory), and using actuarial decision aids that decompose decisions into core components. Reducing overconfidence may lead to stronger decisions. It is hoped that this study illustrates the power of cognitive theories for understanding VC decision-making.     

The influence of past behavior on behavioral intent: An information‐processing explanation

Despite considerable research on the impact of past behavior on decision making over the past two decades, little is yet known about how past experience moderates decision theoretic factors within models of behavioral intent. This research explores the implications of past behavior within the theory of planned behavior (TPB), and how it influences key decision‐making variables. A theoretical model of how past behavior can induce deliberative versus heuristic processing of information is developed and tested. Consumer implications of the impact of past behavior on behavioral intentions are discussed, highlighting the importance of addressing one's experience when making a decision. © 2008 Wiley Periodicals, Inc.     

Customer Experience Management in Retailing: Understanding the Buying Process

Retailers recognize that greater understanding of customers can enhance customer satisfaction and retail performance. This article seeks to enrich this understanding by providing an overview of existing consumer behavior literature and suggesting that specific elements of consumer behavior—goals, schema, information processing, memory, involvement, attitudes, affective processing, atmospherics, and consumer attributions and choices—play important roles during various stages of the consumer decision process. The authors suggest ways in which retailers can leverage this understanding of consumer behavior. Each of these conceptual areas also offers avenues for further research.     

Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making

Artificial intelligence (AI) has penetrated many organizational processes, resulting in a growing fear that smart machines will soon replace many humans in decision making. To provide a more proactive and pragmatic perspective, this article highlights the complementarity of humans and AI and examines how each can bring their own strength in organizational decision-making processes typically characterized by uncertainty, complexity, and equivocality. With a greater computational information processing capacity and an analytical approach, AI can extend humans’ cognition when addressing complexity, whereas humans can still offer a more holistic, intuitive approach in dealing with uncertainty and equivocality in organizational decision making. This premise mirrors the idea of intelligence augmentation, which states that AI systems should be designed with the intention of augmenting, not replacing, human contributions.     

Decision rules used by male and female business students in making ethical value judgments: Another look

This study was conducted to corroborate findings that females invoke a decision rule that is significantly different from that of their male counterparts when making ethical value judgements. In addition, the study examines whether the same decision rule is used by men and women for all types of ethical situations. The results show that males and females use different decision rules when making ethical evaluations, although there are types of situations where there are no significant differences in decision rules used by men and women. The results do not suggest that any one particular decision rule is used by the majority of either males or females in different types of ethical judgements. There is a greater diversity in decision rules used by females than by males.Sharon Galbraith, Ph.D., is an Assistant Professor in the Albers School of Business and Economics at Seattle University, Seattle, Washington. She teaches Marketing and does research in the areas of consumer information processing, pedagogy, and business ethics.Harriet Stephenson, Ph.D., Professor of Management in the Albers School of Business and Economics, is Director of The Entrepreneurship Center at Seattle University. She teaches Entrepreneurship and Small Business Management and Business Policy and Organization and does research in areas of business ethics and entrepreneurship, and marketing for small business.This study deals only with the decision processes used in evaluating acceptability or unacceptability of certain actions. This is a sample question from the questionnaire.     

Cutting Through the Online Review Jungle — Investigating Selective eWOM Processing

Consumers frequently rely on online reviews, a prominent form of electronic word-of-mouth (eWOM), before making a purchase decision. However, consumers are usually confronted with hundreds of reviews for a single product or service, as well as rich information cues on online review websites (review texts, helpfulness ratings, author information, etc.). In turn, consumers face more information cues on online review websites than they can or want to process, and are likely to proceed selectively. This paper investigates selective processing of such eWOM information cues. Results of Study 1, an exploratory study using verbal protocols, confirm that consumers display selective eWOM processing patterns and are able to articulate them. Study 2 develops and applies a measurement instrument to capture these patterns. A subsequent cluster analysis on members of a large-scale online panel (N = 2,295) indicates five prominent eWOM processing types, termed “The Efficients”, “The Meticulous”, “The Quality-Evaluators”, “The Cautious Critics”, and “The Swift Pessimists”. Insights of this research can help firms to better understand consumers' eWOM processing and improve the user-friendliness of online review websites.     

Information Collection Strategic Design in Experts-assisted Decision Making Paradigm

In an experts-assisted decision making paradigm, the information collection design becomes a strategic variable under a weak assumption that the final decision is dependent on the design used to collect information as well. As a result, the same information of the experts and the decision maker about the problem can potentially produce different final decisions for different information collection designs. The implication is that a decision maker can strategically select a design which serves his/her objective. This paper uses a Bayesian estimation methodology for combining experts' information with the decision maker's prior. An information collection process is designed by setting constraints on this model. Several designs are developed here using such controlled factors as a one-stage versus a two-stage decision process, experts' rank ordering, and group versus individual lobbying/consultation. An example is provided to illustrate the applicability of the concept. It is shown that the information produced in the process of producing a decision can also give insights into the impacts of the decision maker and the experts on the decision.     

Information format‐option characteristics compatibility and the compromise effect

When consumers make a decision under preference uncertainty, they often select the compromise choice. Since the compromise effect of the middle option stems from the relational properties of the choice alternatives, an information format compatible with their characteristics makes the middle option more salient and attractive. Focusing on three studies, this article demonstrates that the middle option is (1) more attractive when presented in the middle position; (2) more attractive when information is presented jointly rather than separately; and (3) most attractive when presented in an information display board format, less attractive in a list by attribute condition, and least attractive in a list by alternative condition. These findings imply that information processing strategies and information format‐option characteristics compatibility work in tandem. These three studies thereby show that the information format‐option characteristics compatibility effect is robust and that such compatibility effect is not due to different information processing strategies, which makes these results meaningful for marketing practice. © 2008 Wiley Periodicals, Inc.