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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

Yenjou Wang¹, Jason C. Hung², Chun-Hong Huan³, Sadiq Hussain⁴, Neil Yen⁵ and Qun Jin⁶

1. Waseda University, 2-579-15 Mikajima, Tokorozawa
   359-1192 Saitama, Japan
   yjwjennifer2021@ruri.waseda.jp
2. National Taichung University of Science and Technology, No. 129, Section 3
   Sanmin Rd, North District, 404Taichung, Taiwan
   jhungc.hung@gmail.com
3. Lunghwa University of Science and Technology, No. 300, Section 1
   Wanshou Rd, Guishan District, 333 Taoyuan, Taiwan
   ch.huang@mail.lhu.edu.tw
4. Dibrugarh University, Dibrugarh
   786004 Dibrugarh Assam, India
   sadiq@dibru.ac.in
5. Aizu University, Aizuwakamatsu City
   965-8580 Fukushima Prefecture, Japan
   neil219@gmail.com
6. Faculty of Human Sciences, Waseda University, 2-579-15 Mikajima, Tokorozawa
   359-1192 Saitama, Japan
   jin@waseda.jp

Abstract

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.

Key words

sharing economy, behavior and trend analysis, TAM model, confirmatory factor analysis, multi-group analysis

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS230323010W

Publication information

Volume 21, Issue 2 (April 2024)
Special Issue on Deep Learning Techniques in Intelligent Internet of Things and 5G Communication Networks
Year of Publication: 2024
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Wang, Y., Hung, J. C., Huan, C., Hussain, S., Yen, N., Jin, Q.: Design of TAM-based Framework for Credibility and Trend Analysis in Sharing Economy: Behavioral Intention and User Experience on Airbnb as an Instance. Computer Science and Information Systems, Vol. 21, No. 2, 547–568. (2024), https://doi.org/10.2298/CSIS230323010W