Advances in computation,statistical methods,and testing of discrete choice models

This paper gives a brief overview of recent developments in computation, estimation, and statistical testing of choice models, with marketing applications. Topics include statistical models for discrete panel data with heterogeneous decision-makers, simulation methods for estimation of high-dimension multinomial probit models, specification tests for model structure and for brand and purchase clustering, and innovations in numerical analysis for estimation and forecasting. In collaboration with Denis Bolduc, David Bunch, Michael Keane, Don Kridel, and Steve Stern.     

Efficient choice set designs for estimating availability cross-effects models

Batsell and Polking proposed a discrete choice model which incorporates the availability (presence or absence) of competing brands into the utility of each brand under study. The information on relative impacts of adding or deleting brands is of strategic interest, and models that do not incorporate such effects may be misleading. The designs suggested by Batsell and Polking have 2^m–m–1 choice sets. Even with as few as 10=m brands, this requires over 1000 choice sets. In this paper we provide a catalog of designs for estimating cross effects models in as few as 2m–1 choice sets. This will make cross effects modelling practical in a wide range of academic and commercial settings.     

Experimental analysis of choice

Experimental choice analysis continues to attract academic and applied attention. We review what is known about the design, conduct, analysis, and use of data from choice experiments, and indicate gaps in current knowledge that should be addressed in future research. Design strategies consistent with probabilistic models of choice process and the parallels between choice experiments and real markets are considered. Additionally, we address the issues of reliability and validity. Progress has been made in accounting for differences in reliability, but more research is needed to determine which experiments and response procedures will consistently produce more reliable data for various problems.Sawtooth SoftwareDecision Research     

Incorporating choice dynamics in models of consumer behavior

This paper presents a framework for organizing and discussing factors influencing consumer choice dynamics, how these factors may be incorporated into models of buyer behavior and problems that may arise in estimating such models. The paper identifies research issues and delineates possible approaches. Proceedings of Session on Choice Dynamics at the Banff Symposium on Consumer Decision-Making and Choice Behavior. All authors share equally in content and remaining errors.     

Prospects and problems in modeling group decisions

This paper summarizes some of the major issues related to group decision modeling. We briefly review the existing work on group choice models in marketing and consumer research. We draw some generalizations about which models work well when and use those generalizations to provide guidelines for future research.     

Estimation bias in choice models with last choice feedback

The study compares two estimation methods for choice models with last choice feedback, using simulated and real data. The first method ignores the impact of unobserved heterogeneity on observed choices via presample choices, while the second method approximates this impact by a stochastic relationship. In panels with less than 10 choices per panelist, the first method overstates the impact of last choice on current choice and understates the impact of intrinsic preferences (i.e., brand intercepts). The second method performs significantly better than the first method. Under both methods, an increase in the number of heterogeneous coefficients in the model tends to increase the bias in the estimates. The largest bias occurs when lagged choice coefficients are heterogeneous.     

Information processing and innovative choice

In this paper we examine how the information processing of subjects who make an innovative choice (innovators) differs from that of subjects who make a noninnovative choice (noninnovators). The task involves selection of an alternative within a range of prerated product category innovativeness. We propose that subjects who seek 1) impersonal/uncontrollable sources, 2) higher levels of information, 3) more detailed (versus summary) data, and 4) noncomparative (versus comparative) data are more likely to make innovative choices. The research method is a computerized process tracing experiment utilizing Search Monitor (Brucks 1988).The authors wish to express their gratitude to Merrie Brucks for the use of and help with Search Monitor and to Eric Johnson, Dave Schmittlein, and Mita Sujan for helpful comments on an earlier version of this paper.     

Heterogeneity distributions of willingness-to-pay in choice models

We investigate direct and indirect specification of the distribution of consumer willingness-to-pay (WTP) for changes in product attributes in a choice setting. Typically, choice models identify WTP for an attribute as a ratio of the estimated attribute and price coefficients. Previous research in marketing and economics has discussed the problems with allowing for random coefficients on both attribute and price, especially when the distribution of the price coefficient has mass near zero. These problems can be avoided by combining a parameterization of the likelihood function that directly identifies WTP with a normal prior for WTP. We show that the typical likelihood parameterization in combination with what are regarded as standard heterogeneity distributions for attribute and price coefficients results in poorly behaved posterior WTP distributions, especially in small sample settings. The implied prior for WTP readily allows for substantial mass in the tails of the distribution and extreme individual-level estimates of WTP. We also demonstrate the sensitivity of profit maximizing prices to parameterization and priors for WTP.

Compromising the compromise effect: Brands matter

Consumer behavior research has a long history indicating that preferences are influenced by the relative positions of members of a choice set. The realism of this work, however, is somewhat limited because alternatives are typically labeled with letters rather than with real brand names. We investigate the boundaries of prior research by testing whether preferences for alternatives in compromise and superior positions generalize to a more realistic market scenario that includes choices between real brands. In particular, we conduct two studies that examine if preferences for brands in a choice set are moderated by the inclusion of more or less familiar brand names. We find that consumers prefer extreme brands when compromise brands are relatively less familiar and compromise brands when they are relatively more familiar. In this scenario brand familiarity and not the position of the alternatives determine choice. In situations where a choice alternative is superior, we find no moderation due to brand familiarity.

Quick and easy choice sets: Constructing optimal and nearly optimal stated choice experiments

In this paper we compare a number of common strategies for constructing discrete choice experiments. Two of the strategies, including one based on theoretical constructions for optimal discrete choice experiments, produce designs that are better than those that come about from random grouping and from using the L^MA construction. A simple account of this theoretical construction is given.     

Positive affect moderates the impact of assortment size on choice satisfaction

The present research proposes that positive affect mitigates choice overload. Results from four studies show that whereas people in neutral affect feel less satisfied when choosing from a large relative to a small assortment, people in positive affect do not experience a decline in satisfaction and may even feel more satisfied when choosing from a large, relative to a small assortment. It is proposed that positive affect has these effects by shifting people's attention from the difficulty of the choice task to the quality of the assortment, as a basis for judgment of choice satisfaction.     

Experimental analysis of consumer channel-mix use

Today's consumers have access to multiple consumer distribution channels. To remain competitive, retailers must offer different contact points to consumers. This empirical study examines channel-mix use decisions for 352 online customers' holiday booking preparations. A scenario based experimental approach studies consumer channel-mix use by channel and decision context attributes. The study models effects of time pressure, expected expenditure, channel quality, and access costs on the use of eight channel options, including traditional and online options. Over one-half of respondents use multiple channels to decide trip booking; however, most travelers book trips using the channel they initially investigated for information. Results show expected expenditure does not influence channel use; however, overall cost affects the booking's timing. Time pressures force respondents to visit a travel agent or collect additional brochures to quickly complete the purchase. Results suggest brochures fulfill an important support role.     

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.     

Determinants of retail bank choice in Nigeria: a focus on gender-based choice decisions

As the Nigerian retail banks customers become more sophisticated, it is now very important that retail banks determine the factors that are important and relevant to the customers’ retail bank choice decisions. By using a survey of retail bank customers, this study evaluates the relative importance attached to retail banks’ choice criteria used by male and female customers in Nigeria. The results show that there are some differences in choice factors used by male and female customers in selecting a retail bank for patronage. The recommendation is that bank managers should take both female and male market segments into consideration when making retail bank strategic planning in order to become competitive. The findings can assist retail bank managers in refining their marketing strategies as a means of overcoming the intense competition that exists in the Nigerian banking system.     

Social distancing and store choice in times of a pandemic

Public health officials enforced several measures to contain the COVID-19 pandemic that affected grocery stores, such as limits on store capacities and enforcement of masks and physical distancing among customers. Nevertheless, these measures can provoke queues, which could drive customers away from stores. In this study, we investigate how customers trade off between social distancing measures and increased waiting times during the peak of the COVID-19 pandemic. Our data comes from an online survey applied in New York City in May 2020. This survey included a set of discrete choice experiments framed in virtual stores, as well as a set of psychometric indicators regarding the pandemic. With this data, we estimated a latent class conditional logit model where assignment to classes is correlated with COVID-19 latent variables. We identified three latent classes with preference structures that valued social distancing to varying degrees. In spite of this heterogeneity in preferences, we found that customers were willing to wait longer to access stores with better social distancing measures. This result suggests that stores could increase, rather than decrease, their sales if they enforce public health measures at the expense of longer waiting times.     

The effects of memory set accessibility and relevance on the use of memory information during product choice

The Accessibility-Relevance framework provides a useful perspective to consider the retrieval and use of memory information during product decision making (Alba, Lynch, and Hutchinson, 1990; Lynch, Marmorstein, and Weigold, 1989). However, it considers accessibility on an individual brand basis, while actual product choice often includes information across multiple alternatives. Thus, memory set accessibility (MSA), the relative accessibility across memory brands, is introduced as a potentially important but unexplored issue within the Accessibility-Relevance research stream. This study 1) provides an explanation for how MSA may produce results which significantly expand the current Accessibility-Relevance conceptualization and 2) considers the effects of MSA and relevance on both brand processing and choice.     

The no-choice option and dual response choice designs

Choice set designs that include a constant or no-choice option have increased efficiency, better mimic consumer choices, and allow one to model changes in market size. However, when the no-choice option is selected no information is obtained on the relative attractiveness of the available alternatives. One potential solution to this problem is to use a dual response format in which respondents first choose among a set of available alternatives in a forced-choice task and then choose among the available alternatives and a no-choice option. This paper uses a simulation to demonstrate and confirm the possible gains in efficiency of dual response over traditional choice-based conjoint tasks when there are different proportions choosing the no-choice option. Next, two choice-based conjoint analysis studies find little systematic violation of IIA with the addition/deletion of a no-choice option. Further analysis supports the hypothesis that selection of the no-choice option is more closely related to choice set attractiveness than to decision difficulty. Finally, validation evidence is presented. Our findings show that researchers can employ the dual response approach, taking advantages of the increased power of estimation, without concern for systematically biasing the resulting parameter estimates. Hence, we argue this is a valuable approach when there is the possibility of a large number of no-choices and preference heterogeneity.     

Consideration set influences on consumer decision-making and choice: Issues,models, and suggestions

This paper affords a stylized view of individual consumer choice decision-making appropriate to the study of many marketing decisions. It summarizes issues relating to consideration set effects on consumer judgment and choice. It discusses whether consideration sets really exist and, if so, the factors that affect their composition, structure, and role in decision-making. It examines some new developments in the measurement and modeling of consideration set effects on decision-making. The paper concludes with suggestions for needed research. The authors wish to acknowledge the numerous ideas and perspectives contributed by the other members of the Banff Symposium workshop:Mukesh Bhargava (University of Alberta),Bill Black (Louisiana State University),Gary Gaeth (University of Iowa),Hotaka Katahira (University of Tokyo, Japan),Gilles Laurent (Centre HEC-ISA, France),Irwin Levin (University of Iowa),David Midgley (Australian Graduate School of Management),Thomas Novak (Southern Methodist University), andJames Wiley (University of Alberta). This paper has benefited greatly from their contributions.     

Consumer power and choice deferral: The role of anticipated regret

This paper examines the influence of social power on consumers' propensity to defer choice. Based on the notion that elevated power reduces regret anticipation—the fear of making a wrong choice—it is proposed that power influences the extent of choice deferral by reducing consumers' susceptibility to anticipated regret. Because of the regret-based mechanism, power can increase or decrease consumers' propensity to defer choice, depending upon the situational factors that are associated with anticipated regret, such as salience of regret, outcome reversibility (e.g., return policy), and locus-of-regret (postponing vs. choosing now). Using different manipulations of power, seven studies provide consistent support for the proposed effects and show that situational factors and marketing strategies can induce, turn off, or even reverse the effect of power on deferral. Theoretical contributions and managerial implications are discussed.     

Random regret minimization for consumer choice modeling: Assessment of empirical evidence

This paper introduces to the field of marketing a regret-based discrete choice model for the analysis of multi-attribute consumer choices from multinomial choice sets. This random regret minimization (RRM) model, which has recently been introduced in the field of transport, forms a regret-based counterpart of the canonical random utility maximization (RUM) paradigm. This paper assesses empirical results based on 43 comparisons reported in peer-reviewed journal articles and book chapters, with the aim of finding out to what extent, when, and how RRM can form a viable addition to the consumer choice modeler's toolkit. The paper shows that RRM and hybrid RRM–RUM models outperform RUM counterparts in a majority of cases, in terms of model fit and predictive ability. Although differences in performance are quite small, the two paradigms often result in markedly different managerial implications due to considerable differences in, for example, market share forecasts.