The influence of price on the relationship between involvement and consideration set size

This study examined the relationship between involvement and consideration set size for a product category featuring wide variability in the price and quality of choice alternatives. The use of a heterogeneous choice domain is considered important because it gives consumers the opportunity to make price and quality tradeoffs in the selection of their consideration sets. The results indicate that in such a choice context, the total effect of involvement on consideration set size is positive. A path analysis of the data indicates the reason for this positive relationship was that high-involvement subjects set wider latitudes of acceptance for price and thus were more likely to consider the more expensive models in the choice domain.     

Information search and consideration set formation in a web-based store environment

The research reported here attempts to understand information search and consideration set formation in a web-based choice environment. A conceptual model is used to propose hypotheses that link information search and consideration set formation with two task environment influences that are typical of online settings. A study that simulates information search and consideration set formation in a web-based choice environment is conducted to test the hypotheses. The results offer insights into how the number of available alternatives and the amount of time available may have an effect on search and evaluation in a web-based store. The research has implications for understanding how consumers shop in online stores.     

The influence of positive affect on consideration set formation in memory-based choice

Although prior research has examined whether positive affect can impact consideration set size in stimulus-based choice, unknown to this point is whether affective influences also characterize memory-based consideration processes. This distinction is important insofar as consideration in memory-based choice entails psychological processes (including those involving the accessibility of brands) that are unique to choice undertaken in memory-based settings. Experiment 1 provides an initial demonstration of positive affect’s ability to shape memory-based consideration by documenting that positive (versus neutral) affect leads to larger consideration sets. Two additional experiments extend these findings by showing that the influence of positive affect on consideration set size is moderated by characteristics of brands (typicality) and consumers (regulatory focus). Experiment 2 demonstrates that this increase in memory-based consideration set size is attributable to a greater number of atypical, but not typical, brands being considered under positive affect. Experiment 3 documents the moderating effect exerted by consumers’ regulatory focus by showing that the ability of positive affect to increase consideration set size is more likely for consumers high (but not low) on promotion focus. The theoretical and managerial implications of these findings are discussed as are suggestions for future research.     

Conjunctive screening in models of multiple discreteness

Consumer demand for products often result in the purchase of multiple goods at the same time. Corner solutions, or the non-purchase of items, occur when consumers have strong preference for some goods that do not satiate and weak preference for other goods. However, if non-purchase arises because a consumer finds particular brands and attributes unacceptable, leading to the formation of consideration sets, then estimates of preference will be too extreme and biased. In this paper, we extend the work on consideration sets and discrete choices to a wider class of models, and develop a model of multiple discreteness with conjunctive screening of the alternatives that remove offerings from consideration. We propose a method for consideration set formation that does not require one to specify a partitioned space of the augmented variable, and that can be adapted into the class of choice models in which an outcome variable is removed. We explore implications for disentangling non-purchase due to consideration set formation using two data sets of ice cream and frozen pizza purchases. The ice cream data, in which responses are both discrete and volumetric, allow us to compare differences in how screening affect purchase incidence versus volumetric demand per incidence. Screening reduces the estimated number of customers with positive demand but leads to an increase in demand for those not screened. In the frozen pizza data, we find that conjunctive screening accounts for many of the observed corner solutions and leads to estimates of preference and satiation that differs from traditional models of multiple-discreteness without screening.     

How consumers use product reviews in the purchase decision process

This paper uses individual level data to examine the influence of product reviews in different stages of the consumer’s purchase decision process. Specifically, a two-stage model consisting of consideration set formation and choice is posited, where the consumer can incorporate information from product reviews in each stage. The model is estimated using an online panel survey about hotel choice. We find that (1) consumers use product reviews more in the consideration set stage and less in the choice stage, (2) Bayesian updating of prior perceived quality better explains how consumers use product reviews compared to two competing updating methods, and (3) the monetary value of a unit increase in the mean of product reviews is computed. Our results suggest that managers should make product review information (their number, average, and variance) available from the beginning of the search process and encourage satisfied customers to write reviews.     

Compromise and attraction effects in food choice

Food choices are being implicated as a key driver in the rising rates of obesity, as well as associated with other health problems that impact both individuals and society as a whole (Cawley and Meyerhoefer). Calorie listings, whether provided on menus or packaged goods, increase consumer's awareness of the calories in potential food choices and, as a result, make consumers more likely to evaluate a product relative to others in the choice set based on this attribute (e.g. choosing a higher or lower calorie option). In this research, we explore whether the provision of calorie information, when presented in the context of other food options, will result in (1) compromise effects, whereby individuals select intermediate (or middle) options in a choice set, and (2) attraction effects, whereby individuals gravitate towards items that are similar to others but also dominate these items in the choice set. In two experimental studies we find evidence for the compromise effect and the attraction effect. These findings extend work demonstrating that the context in which food decisions occur can impact choice, and builds on existing knowledge regarding the consequences of providing calorie information for food items. Although most work has shown that making calories salient has a beneficial impact on the accuracy of consumer calorie estimates and food choice, in this work we show that the compromise and attraction effects – two well‐established findings in decision‐making literature – can actually shift consumers to either higher or lower calorie options. This carries important implications for consumers making choices in information‐rich choice environments.     

Three Primary Trust Pathways Underlying Ethical Considerations

The role of trust pathways in achieving a competitive advantage is becoming increasingly important for effective ethical consideration policies in all business and non-business sectors. This paper argues that there are three primary trust pathways of rational choice, rule-based trust, and category-based trust that underscore the basis of trust relationships. The implementation of these primary trust pathways is strongly influenced by expertise level, incomplete information, rapidly shifting environments, and/or time-pressure. The refinement of the interaction of information exchange and framing of problems can produce three secondary higher-level trust pathways of third party-based trust, role-based trust, and knowledge-based trust. These six different trust pathways that guide ethical consideration issues are discussed with a Throughput Modeling theoretical approach.     

Multiple-Category Decision-Making: Review and Synthesis

In many purchase environments, consumers use information from a number of product categories prior to making a decision. These purchase situations create dependencies in choice outcomes across categories. As such, these decision problems cannot be easily modeled using the single-category, single-choice paradigm commonly used by researchers in marketing. We outline a conceptual framework for categorization, and then discuss three types of cross-category dependence: cross-category consideration cross-category learning, and product bundling. We argue that the key to modeling choice dependence across categories is knowledge of the goals driving consumer behavior.     

Using stated response choice data to enrich revealed preference discrete choice models

There is growing interest in exploring the view that both revealed preference (RP) and stated preference (SP) data have useful information and that their integration will enrich the overall explanatory power of RP choice models. These two types of data have been independently used in the estimation of a wide variety of discrete choice applications in marketing. In order to combine the two data sources, each with independent choice outcomes, allowance must be made for their different scaling properties. The approach uses a full information maximum likelihood estimation procedure of the hierarchical logit form to obtain suitable scaling parameters to make one or more data sets comparable. We illustrate the advantages of the dual data strategy by comparing the results with those obtained from models estimated independently with RP and SP data. Data collected as part of a study of high speed rail is used to estimate a set of illustrative mode choice models.     

Overcoming data limitations for store choice modelling.: Exploiting retail chain choice data by means of aggregate logit models

This paper reports on research aimed at exploiting certain data sources for store choice modelling purposes. Many databases, such as some consumer panels, only record the firm chosen by consumers and not the specific store at which they shop. Four alternative approaches are proposed in order to use this raw information for studying patronage determinants at store level: (a) an ordinary logit model in which chain utility is averaged across stores within; (b) an ordinary logit model in which the choice set is assumed to be composed of the nearest store for each chain; (c) a straightforward application of an aggregate logit model; and (d) the application of an aggregate logit model with choice sets spatially bounded by a distance threshold representing the maximum distance that consumers are willing to travel for shopping. The models are empirically tested in the context of spatial choice behaviour. Goodness of fit indicators reveal that only models (b), (c) and (d) acceptably represent competitive interaction dynamics. As performance of (b) is slightly better than that of (c), it seems that a priori the ‘nearest store assumption’ is a better approach than the modelling of aggregate choice structures. However, when the latter approach is applied with more reliable choice sets, as suggested in model (d), the best performance is achieved. The results thus lead us to think that the aggregate logit model is a promising methodology for solving the problem at issue, but subject to an appropriate definition of the consumers’ choice sets. In fact, such an approach provides a more suitable modelling solution to the extent that the saturation and the intra-firm store heterogeneity become more intense, because these situations presumably imply that consideration sets include several stores from the same chain.     

A self‐regulatory model of consideration set formation

The goal of this article is to deepen the understanding of the consideration stage in choice processes. The basic questions are: Why do people consider different brands/products in the first place? What cognitive processes lead to the formation of consideration sets? Based on the notion that consumers are volitional decision makers capable of controlling their own behavior according to their goals, a self‐regulatory model of consideration‐set formation is developed. Goals at different levels of abstraction are hypothesized to determine considerationset formation. In contrast to the notion of congruence, which relates the ideal self to consumer choice, the authors focus on the motivational function of the self. Based on a self‐regulatory model, it is shown that the ideal self, as a macrolevel goal, determines desired benefits. Desired benefits, as more specific goals, then determine brand consideration. In contrast to stimulus‐based choice approaches, consideration‐set composition is investigated in a memory‐based, comparable‐choice context of real adult consumers considering the purchase of automobiles. © 2005 Wiley Periodicals, Inc.     

Do consumer perceptions matter in measuring choice variety and variety seeking?

This research marries scanner panel choice data of consumers in single member households to their survey-based perception data and draws upon behavioral and modeling research to contribute to the variety seeking literature. It presents a new consumer-based measure of choice variety based on inter-product similarity perceptions and illustrates that others-based (i.e., researchers, managers, and retailers) measures of choice variety such as number of brand switches underestimate choice variety. Moreover, incorporating the consumer-based measure instead of others-based measures in latent class models improves their efficiency of classifying households into high versus low variety seeking. The consumer-based measure of choice variety is valid in terms of its positive relationship with consumer's intrinsic or trait-based variety seeking tendency. Theoretical (market structure, consideration set) and managerial implications (targeting of price promotions to reduce spending, product design, cross-price elasticity) of the findings are offered.     

The effect of buying decisions on consumers' assessment of their tastes

Building on the notion that consumers are often uncertain about their tastes or weights, this research examines the proposition that consumers might infer their importance weights from their choices and the choice sets they evaluate. It is also hypothesized that the degree to which choice affects self-assessed weights depends on the consumer's familiarity with the product category and the available product information. The results of an experiment demonstrated that consumers' assessments of their importance weights can be influenced by the choice set they previously evaluated. This effect, however, was not moderated by familiarity or provided product information.     

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.     

An empirical analysis of the factors raising the interest in new shopping destinations

The relationship among the factors in the rising interest in new alternatives is empirically investigated in the context of shopping destination choice behavior. The hypothetical causal relationship is that the rising interest in new alternatives requires both active information search and considerable benefit, which is supported by the results of the mixture structural equation models using a data set containing revealed shopping behaviors and attitudes toward shopping destinations in the Tokyo metropolitan area: a lower level of satisfaction with the current choice set incites external information search for all subjects; however, the benefit of adding new alternatives affects the interest in new alternatives only in the group that engages in active information search.     

A simple method for estimating preference parameters for individuals

This paper demonstrates a method for estimating logit choice models for small sample data, including single individuals, that is computationally simpler and relies on weaker prior distributional assumptions compared to hierarchical Bayes estimation. Using Monte Carlo simulations and online discrete choice experiments, we show how this method is particularly well suited to estimating values of choice model parameters from small sample choice data, thus opening this area to the application of choice modeling. For larger sample sizes of approximately 100–200 respondents, preference distribution recovery is similar to hierarchical Bayes estimation of mixed logit models for the examples we demonstrate. We discuss three approaches for specifying the conjugate priors required for the method: specifying priors based on existing or projected market shares of products, specifying a flat prior on the choice alternatives in a discrete choice experiment, or adopting an empirical Bayes approach where the prior choice probabilities are taken to be the average choice probabilities observed in a discrete choice experiment. We show that for small sample data, the relative weighting of the prior during estimation is an important consideration, and we present an automated method for selecting the weight based on a predictive scoring rule.     

The role of consideration sets in brand choice: The moderating role of product characteristics

This study investigates the role of consideration sets in brand choice. Brand‐level aggregated data are used to capture the responses of consumers who face a number of international and domestic brands in markets rather than two or three brands in experimental designs, as in Chaudhuri and Holbrook (2001). Empirical evidence from path analysis shows that the consideration set for hedonic products includes a smaller number of dominant brands, whereas the consideration set for utilitarian products includes more and diverse brands. The probability of being finally chosen from the consideration set differs according to product characteristics: hedonic vs. utilitarian. The authors discuss managerial implications and suggestions for future research. © 2009 Wiley Periodicals, Inc.     

Learning About Computers: An Analysis of Information Search and Technology Choice

We estimate a dynamic model of how consumers learn about and choose between different brands of personal computers (PCs). To estimate the model, we use a panel data set that contains the search and purchase behavior of a set of consumers who were in the market for a PC. The data includes the information sources visited each period, search durations, as well as measures of price expectations and stated attitudes toward the alternatives during the search process. Our model extends recent work on estimation of Bayesian learning models of consumer choice behavior in environments characterized by uncertainty by estimating a model of active learning—i.e., a model in which consumers make optimal sequential decisions about how much information to gather prior to making a purchase. Also, following the suggestion of Manski (2003), we use our data on price expectations to model consumers’ price expectation process, and, following the suggestion of McFadden (1989a), we incorporate the stated brand quality information into our likelihood function, rather than modeling only revealed preference data.Our analysis sheds light on how consumer forward-looking price expectations and the process of learning about quality influence the consumer choice process. A key finding is that estimates of dynamic price elasticities of demand exceed estimates that ignore the expectations effect by roughly 50%. This occurs because our estimated expectations formation process implies that consumers expect mean reversion in price changes. This enhances the impact of a temporary price cut. Finally, while our work focuses specifically on the PC market, the modeling approach we develop here may be useful for studying a wide range of high-tech, high-involvement durable goods markets where active learning is important.JEL Classification: C15, C33, C35, C42, C51, C52, D83, D84