Computer Science and Information Systems 2024 Volume 21, Issue 2, Pages: 547-568
https://doi.org/10.2298/CSIS230323010W
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Design of TAM-based framework for credibility and trend analysis in sharing economy: Behavioral intention and user experience on Airbnb as an instance
Wang Yenjou (Waseda University, Mikajima, Saitama, Japan), yjwjennifer@ruri.waseda.jp
Hung Jason C. (National Taichung University of Science and Technology, North District, Taichung, Taiwan), jhungc.hung@gmail.com
Huan Chun-Hong (Lunghwa University of Science and Technology, Guishan District, Taoyuan, Taiwan), ch.huang@mail.lhu.edu.tw
Hussain Sadiq (Dibrugarh University, Dibrugarh, Dibrugarh Assam, India), sadiq@dibru.ac.in
Yen Neil (Aizu University, Aizuwakamatsu City, Fukushima Prefecture, Japan), neil@gmail.com
Jin Qun (Faculty of Human Sciences, Waseda University, Mikajima, Saitama, Japan), jin@waseda.jp
Sharing economy redefines the meaning of share. Thanks to it, products provided by suppliers may have rather different standards due to their subjective consciousness. This situation brings high pre-purchase uncertainties to consumers, therefore, trust between suppliers and consumers then becomes a key to succeed in the era of sharing economy. Airbnb, one of the platforms that best describes the concept of sharing economy, is taken as an example in this study. Our team designs a series of scenarios and assumptions that follow the criteria of the Technology Acceptance Model (TAM) to find out various factors that affect customer behavioral intentions and prove that trust is the most important factor in the Sharing economy. Both parties, including host and user on the platform, are considered as subjects, and a three-year-long questionnaire test is implemented to collect data from end-users in order to reach an objective conclusion. Partial Least Squares-Structural Equation Modeling is then applied to verify the hypothesis. In addition, consumption is a continuous action, personal experience may also affect trust in the Airbnb and even consumption propensity. Therefore, Multi-Group Analysis (MGA) is used to explore the impact of consumer experience differences on trust and purchase intention. Finally, the results show that the ease of use of the Airbnb Platform has a greater impact on consumer attitude than all of the information on Airbnb, and then have a positive impact on overall behavioral intentions.
Keywords: sharing economy, behavior and trend analysis, TAM model, confirmatory factor analysis, multi-group analysis
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