Summary: | 碩士 === 國立臺灣大學 === 國際企業學研究所 === 104 === With the global economic development and the raise of leisure consciousness, the travel industry has shown strong and prosperous growth pace. And the rapid evolution of Internet technology and the change of tourist’s consumer behavior, also stimulate the dynamic development online travel e-commerce. This study utilizes inbounding marketing, network externality, eWOM, and AISAS model theories. The purpose of this study is to redefine the contemporary mainstream business models of online travel websites with the exploration of their profit models and inbounding strategies, also to understand the influential factors through user behavior survey for further analysis.
This study redefines the mainstream online travel website into four different types: online travel agency, metasearch engines, user generated content provider, and P2P platform, and chooses 4 representative websites including Expedia, KAYAK, TripAdvisor, and Airbnb as the objects of case study. Based on the approach of case study and comparative analysis, it’s found that member exclusive benefit, review incentive program, friend recommendation mechanism, and market segmentation are commonly used for inbounding strategies. Menwhile, this study concluded that: 1. Online travel industry shows horizontal expansion outside the group and vertical cultivation within the group. 2. The boundaries of each business model become vague even though the core business stays still. 3. The “review” function embodies the importance of e- word of mouth towards online travel industry.
Referring relevant literatures, this study designed a questionnaire regarding the Search-Action-Share behaviors of online travel website’s users. After the result analysis of 544 effective samples, it indicates that “eWOM” will affect user’s “search, action, and share” behavior while using online travel websites. The frequency and scope of use both affect user’s attitude towards eWOM. Users with higher frequency or broad scope of use will be influenced by eWOM more. Another indication is that “Network Externality” will affect user’s “search” behavior while using online travel websites. The time experience of use affects user’s attitude towards network externality. Users with longer experience of using online travel websites will be influenced by network externality more.
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