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     

Decision Strategy and Structure in Households: A “Groups” Perspective

From a practical perspective, (arguably) most consumer decisions are not made in isolation of the households in which consumers are inserted, yet we commonly treat them econometrically as if they were. The purpose of this workshop was to take some initial steps in defining needed research in household decision making that structurally accounts for goal sharing, utility interdependence, taste heterogeneity, choice set formation, power structures, group size and composition, and so forth. We also considered conditions under which aggregation of tastes, utility and choices might occur and make sense from both behavioral and modeling perspectives.     

Brand Equity, Consumer Learning and Choice

The aim of this paper is to explore the links between brand equity, consumer learning and consumer choice processes in general and considering two recent trends in the market place: store brands and the Internet. We first review the advances that have occurred in brand equity research in marketing in the past decade, with particular emphasis on integrating the separate streams of research emanating from cognitive psychology and information economics. Brand equity has generally been defined as the incremental utility with which a brand endows a product, compared to its non-branded counterpart. We amplify this definition: we propose that brand equity be the incremental effect of the brand on all aspects of the consumer's evaluation and choice process. We propose an agenda of research based on this amplified definition.     

A structural equation model of latent segmentation and product choice for cross-sectional revealed preference choice data

We consider the problem of simultaneously performing market segmentation and predicting product choice for a given population of consumers. This behaviour-based segmentation model uses several types of information characterizing individual consumers and their market context: sociodemographic, psychographic and product choice data. These data are combined in a normative conceptual framework that posits the formation of latent segments, each of which displays differing degrees of sensitivity to relevant product attributes. This permits results obtained by the proposed model structure to differ significantly from those of traditional segmentation techniques, which usually produce a set of groups characterized by smaller within-group than between-group variation in sociodemographic and/or psychographic variables. By making the segments behaviour-based, it is argued that the segments produced by the model will be more actionable and more directly relevant to management decision-making. The proposed model is applied to a data set involving choice of a beauty product offered by five national brands. The results show that the explanatory power of the latent segmentation and choice model is far greater than that of the MNL model, which is nested within our more general specification. The types of results available from the model are illustrated through the application.     

Context Dependence and Aggregation in Disaggregate Choice Analysis

There is an emerging consensus among disciplines dealing with human decision making that the context in which a decision is made is an important determinant of outcomes. This consensus has been slow in the making because much of what is known about context effects has evolved from a desire to demonstrate the untenability of certain common assumptions upon which tractable models of behavior have generally been built. This paper seeks tobring disparate disciplinary perspectives to bear on the relation between context and choice, to formulate (1) recommendations for improvements to the state-of-the-practice of Random Utility Models (RUMs) of choice behavior, and (2) a future research agenda to guide the further incorporation of context into these models of choice behavior.     

Behavioral frontiers in choice modeling

We review the discussion at a workshop whose goal was to achieve a better integration among behavioral, economic, and statistical approaches to choice modeling. The workshop explored how current approaches to the specification, estimation, and application of choice models might be improved to better capture the diversity of processes that are postulated to explain how consumers make choices. Some specific challenges include how to capture and parsimoniously describe heterogeneous mixes of heuristic choice rules, methods for building realistic models of choice, and nontraditional methods for estimating models. An agenda for important future work in these areas is also proposed.     

Attribute Range Effects in Binary Response Tasks

This paper investigates attribute range effects in binary response conjoint analysis tasks. We investigate a long-standing conjecture that the regression estimates of attributes in choice tasks are influenced by a researcher's selected range of attribute levels across choice sets. Specifically, we examine the effect(s) of varying attribute ranges systematically over two ranges of levels (1=wide range, 2=levels in the middle of the wide range) in a public bus choice context. A master 2³ design is used to vary the range (i.e., wide, middle) of three numerical attributes (fare, service and time). In each of the eight master range conditions a 2³ factorial creates bus profiles, and a ninth condition is added to test for response non-linearity. Our results suggest that attribute range impacts attribute main effects to a small degree, yet exhibit substantial and systematic effects on attribute interactions and model goodness-of-fit. Implications of these results for practical design of academic and commercial choice-based conjoint analysis tasks are discussed.