Abstract
Mobile commerce has changed the decision environment for users who intend to reserve a preferred hotel. This study aims to investigate the factors that affect the dynamic click-through decision (CTD) in mobile online travel agency (OTA) search engines. We propose a dynamic Bayesian inference framework to model individual-level users’ CTDs and examine the effects of item position, price, search cost, and the use of refinement tools. The study uses real-world search log datasets from a global OTA for both mobile and desktop searches. Our results show that (1) the primacy effect is weaker and the effect of item-ranking positions is non-linear in a mobile OTA search compared to a desktop OTA search. Mobile users pay the most attention to the top-ranking results and are less likely to click through the middle or bottom results. (2) Hotel prices have a positive effect on mobile CTDs in the whole mobile searching journey. Additionally, mobile users also tend to seek out hotels with lower price rankings on the current search engine result page. (3) The search cost, measured by the cumulative time duration, has a positive impact on mobile CTDs. The use of refinement tools enhances the effect of search cost. This study extends previous research on position and price effects in an online consumer search from PC-based internet to mobile devices. It also provides managerial implications for mobile OTA search engine marketing and investment for bidding ranking positions.
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More From: Journal of Theoretical and Applied Electronic Commerce Research
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