摘要
This paper studies the dynamics of online purchase patterns, focusing on the impact of the channel used on conversion probability, as well as the transition of channel use over time. A novel data set from a major Chinese online travel agency is used for analysis, consisting of four months of data with 24,337 store visits through three types of channels： direct visit, search advertising and referral. Results of a Bayesian multinomial logit model show that the search channel significantly affects consumers＇ conversion probability, and show a high degree of inertia in channel use. This finding contrasts sharply with suggestions of previous research that most future purchases will converge to the direct-visit channel.
This paper studies the dynamics of online purchase patterns, focusing on the impact of the channel used on conversion probability, as well as the transition of channel use over time. A novel data set from a major Chinese online travel agency is used for analysis, consisting of four months of data with 24,337 store visits through three types of channels： direct visit, search advertising and referral. Results of a Bayesian multinomial logit model show that the search channel significantly affects consumers＇ conversion probability, and show a high degree of inertia in channel use. This finding contrasts sharply with suggestions of previous research that most future purchases will converge to the direct-visit channel.
基金
This research is supported by the National Natural Science Foundation of China （No. 71302172 and No. 71202145）.
