Probabilistic choice (models) as a result of balancing multiple goals

We conceptualize probabilistic choice as the result of the simultaneous pursuit of multiple goals in a vector optimization representation, which is reduced to a scalar optimization that implies goal balancing. The majority of prior theoretical and empirical work on such probabilistic choice is based on random utility models, the most basic of which assume that each choice option has a valuation that has a deterministic (systematic) component plus a random component determined by some specified distribution. An alternate approach to probabilistic choice has considered maximization of one quantity (e.g., utility), subject to constraints on one or more other quantities (e.g., cost). The multiple goal perspective integrates the results regarding the well-studied multinomial logit model of probabilistic choice that has been derived from each of the above approaches; extends the results to other models in the generalized extreme value (GEV) class; and relates them to recent axiomatic work on the utility of gambling.

Are food choices really habitual? : integrating habits, variety-seeking, and compensatory choice in a utility-maximizing framework

Given the large number of food choices that consumers make each day it seems likely that they will adopt decision strategies that minimize cognitive effort. To examine this issue, we develop a conceptual and empirical model of habitual choice, and the factors that result in transitions to two strategies other than habitual selection: utility-maximizing choice and a variety-seeking strategy. Our approach provides an alternative to traditional state dependence methods used in this type of panel data. We apply this framework to the choice of two food products that illustrate the heterogeneity across types of products in decision strategies and routine choice patterns.

Antecedents of true brand loyalty

We examine a model of six latent constructs and propose that true brand loyalty can be explained as a result of five distinct antecedents: brand credibility, affective brand conviction, cognitive brand conviction, attitude strength, and brand commitment. Data from experimental conditions with manipulations of eight product classes and two involvement levels lend support for the proposed model, demonstrating that brand loyalty can be considered as truly loyal only when mediated by a high degree of affective and cognitive brand conviction, and attitude strength. Advertising and marketing implications for the relationships among the six constructs under different manipulation conditions are discussed.

Distortions in willingness-to-pay for public goods induced by endemic distrust in institutions

In this paper, we analyze the implications for the economic valuation of the provision of public goods, considering respondents’ perceptions of the institution(s) that provide the service. The specific behavioral mechanism whereby institutional distrust (ID) shows itself is through the activation of screening of choice options (choice set formation). However, ID-induced choice set formation might be confounded with the consumer budget constraint, especially in a developing country context, leading to biased welfare estimates for service improvement. We formulate a semi-compensatory hybrid choice set formation (SC-HCSF) model that enables us to 1) discriminate the effect of a budget constraint from that of ID-induced choice set formation and 2) characterize their separate impacts on welfare estimates using a spatial framework. We compare our model results to those from a standard Random Parameters Logit (RPL) Model. The RPL underestimates (overestimates) welfare when individuals have a low (high) ID. Based on our empirical model results, we demonstrate that the impacts of ignoring institutional trust issues can be highly deleterious to project appraisals, particularly in settings where legislative and regulatory institutions are perceived to be endemically corrupt

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.