Modeling Interdependent Consumer Preferences (original) (raw)

Pairwise influences in dynamic choice: network-based model and application

In this paper we study the problem of network discovery and influence propagation and propose an integrated approach for the analysis of lead-lag synchronization in multiple choices. Network models for the processes by which decisions propagate through social interaction have been studied before, but only a few consider unknown structures of interacting agents. In fact, while individual choices are typically observed, inferring individual influences -- who influences who -- from sequences of dynamic choices requires strong modeling assumptions on the cross-section dependencies of the observed panels. We propose a class of parametric models which extends the vector autoregression to the case of pairwise influences between individual choices over multiple items and supports the analysis of influence propagation. After uncovering a collection of theoretical properties (conditional moments, parameter sensitivity, identifiability and estimation), we provide an economic application to music broadcasting, where a set of songs are diffused over radio stations; we infer station-to-station influences based on the proposed methodology and assess the propagation effect of initial launching stations to maximize songs diffusion. Both on the theoretical and empirical side, the proposed approach connects fields which are traditionally treated as separated areas: the problem of network discovery and the one of influence propagation.

Bayesian estimation of random‐coefficients choice models using aggregate data

Journal of Applied Econometrics, 2009

This article discusses the use of Bayesian methods for estimating logit demand models using aggregate data. We analyze two different demand systems: independent samples and consumer panel. Under the first system, there is a different and independent random sample of N consumers in each period and each consumer makes only a single purchase decision. Under the second system, the same N consumers make a purchase decision in each of T periods. Interestingly, there exists an asymptotic link between these two systems, which has important implications for the estimation of these demand models. The proposed methods are illustrated using simulated and real data. Copyright © 2009 John Wiley & Sons, Ltd.

A discrete-choice approach to modeling social influence on individual decision making

2008

Abstract. Individual decision making is commonly studied using discrete choice models. Models of this type are applied extensively to the study of travel behavior, residential location, and employment decisions, among other topics of interest. A notable characteristic of the underlying economic theory is the assumption that individuals seek to maximize utility on the basis of their personal attributes and the attributes of the alternatives available to them.

Observed and Unobserved Preference Heterogeneity in Brand-Choice Models

Marketing Science, 2006

This paper extends the scanner-based choice literature by explicitly incorporating individual-level brand-preference data. We illustrate our model using a unique data set that combines survey and scanner data collected from the same individuals. The addition of individual-specific brand-preference information significantly improves fit and prediction. Furthermore, this “observed” heterogeneity better explains choice than does “unobserved” heterogeneity in the standard scanner model’s parameters. More importantly, we find that the standard model underestimates the importance of consumers’ brand preferences and overestimates both brand loyalties and price sensitivities. Brand loyalty is overestimated because models without preference information confound state dependence, heterogeneity, and preference effects. Price sensitivities are inflated because the “average” preference-based consumer is implicitly assumed to be more willing to switch from his preferred brand than is the “real” p...