모바일, PC온라인 매체 방문 행동이 쇼핑 사이트 방문에 미치는 영향에 대한 동태적 연구

In the e-commerce, the conversion into the multi-media is the important issue. According to the research by Nielsen Korea, the 83% of customers who purchase the products in the e-commerce utilize multi-channel to buy the products such as mobile and online [3]. Thus, to effectively implement online advertising, marketers should understand the customers’ path [15] in the multi-channel. The study of the multi-site activities plays an important role to predict customers’ purchase [28]. To explain the e-commerce site visit activities of customers, we have developed research model in terms of the online advertising. This research model is based on the study of Moe and Fader [23]. There are two types of composition in the research model. First, general site visit as an exploratory search have net effect on the shopping site visit because customers could acquire or develop information on the e-commerce site via online advertising. Secondly, the e-commerce site visit as a goal-directed search cause threshold of the e-commerce site visit because customers could achieve their goal. When the threshold is increased, the probability of a shopping site visit is decreased and vice versa. Thus, we have investigated the impact of customers’ previous visit activities (general site visit and shopping site visit) on the next e-commerce site visit in terms of dynamic view. Research data was provided by Cheil World Wide. This panel data include mobile and online log data of panelists from Jan. 2013 to March 2013. As the results, the customers’ e-commerce site visit on the online media would decrease the probability of e-commerce site visit because these visit activities increase the threshold of e-commerce site visit. This result is similar with the previous study [23]. Otherwise, since e-commerce site visit on the mobile media decrease the threshold, the customers’ probability of e-commerce site visit would increaseIn summary, the site visit activities on the mobile could improve the probability of e-commerce site visits.