A Hazard Function Approach to Modeling Consumer Search (2003)

ABSTRACT This study recognizes the stochastic element in the consumer search process and develops a stochastic model of search termination that incorporates the effects of time elapsed since commencing search, individual and product characteristics and unobserved heterogeneity. Results indicate substantial duration dependence. Perceived benefits of search, size of the evoked set and the quality of past experience are found to be important determinants of the hazard function. This study highlights the importance of accounting for unobserved heterogeneity and the sensitivity of the parameter estimates to the specification of its distribution. INTRODUCTION What causes a customer to terminate his search process and purchase? This is a pervasive question faced by numerous marketing managers. Many studies have documented the effects of consumer characteristics on the extent of information search for durable products as well as patterns of search across information sources (Punj & Staelin, 1983; Kiel & Layton, 1981; Furse, Punj & Stewart, 1984; Beatty & Smith, 1987; Srinivasan & Ratchford, 1991; Putsis & Srinivasan, 1994). However, to date, there has been little significant work documenting the termination of consumer search and final purchase. In addition, contemporary marketing literature on the extent of search does not explicitly model the fact that the duration of search is a stochastic process. Thus, a consumer may terminate search early if he/she got lucky and chanced on a good deal early in the search process or he/she may be unlucky and not obtain an acceptable offer until late in the search. A complete model of search behavior would account for this stochastic element. Another shortcoming of the literature on search is that it fails to model the possible effects of unobserved heterogeneity. The most common method of accounting for observed heterogeneity is to include consumer, retailer and product characteristics in the model, and to estimate how the measured extent of search varies with these variables. However, given the difficulty of determining and measuring these characteristics, there are likely to be many variables that affect search that are unmeasured. A complete model of search behavior would explicitly model the effect of this unobserved heterogeneity, and failure to do so may contaminate the estimates of the included variables (Heckman & Singer, 1984). This study focuses on the rate of search termination and its determinants, using a stochastic model of search within the framework of a conditional hazard function. The probability of search termination is modeled as a function of the duration of search, measured consumer characteristics and unobserved factors. HAZARD FUNCTION Hazard function models have been used extensively in economics and statistics literature especially in the areas of research on job search, employment and unemployment (Jones, 1988; Lancaster, 1985; Flinn & Heckman, 1982). It has been used in a study on inter-purchase timing in marketing (Jain & Vilcassim, 1991) but never in the area of search. Since the hazard function can be thought of as the rate at which an event occurs, its application in this area of search termination is very appropriate. For the purpose of this study, let the random variable T be the time a consumer spends searching for external information before purchasing an automobile. Duration T spans between the interval [0,8). The hazard function [lambda](t) can therefore, be defined as: (1.) [lambda](t) = [lim.sub.[DELTA]t[right arrow]0] Pr(t t)/[DELTA]t Equation 1 indicates that the hazard function simply specifies the instantaneous rate of search terminating at time t, given that the consumer is still searching at t. In other words, conditional on the consumer not having purchased, the hazard function measures the likelihood of search ending at time t. …