Trivariate probit models of pre-purchase/purchase shopping channel choice: clothing purchases in Northern California

Abstract

This study analyzes the joint choice of pre-purchase and purchase shopping channels for clothing purchases, using data collected from an internet-based survey of two university towns in Nor­thern California (final Ns=390 and 452). Descriptive analysis clearly shows dependence across these three choices: in particular, the “sticky” combinations of {only-store pre-purchase + store purchase} and {only internet pre-purchase + internet purchase} occurred substantially more often than independent choices would predict. We develop two trivariate probit (TVP) models, consisting of two binary choice equations for the pre-purchase channel (respectively measuring the use of store or not, and the use of internet or not) and one binary choice equation for the pur­chase channel (store or internet). One model allows channel purchase experience variables to enter while the other model excludes them. The results further confirm the dependency among pre-purchase and purchase channel choices, with all three error term correlations strongly signi­ficant. In addition to breadth and depth of experience variables and channel-specific perceptions (post-purchase satisfaction, cost savings, enjoyment, and convenience), significant explanatory variables include general shopping-related attitudes (pro-exercise, shop enjoyment, and store enjoyment), context variables, and sociodemographic traits (age and income). Prediction of joint choice probabil­ities was considerably better for the TVP model than for independent binary choice models, confirming the value of simultaneously modeling pre-purchase and purchase channel choice bundles. Keywords: internet shopping, online shopping, store shopping, pre-purchase channel, purchase channel, multichannel shopping, multivariate probit model, trivariate probit model