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Journal of Information Science and Engineering, Vol. 38 No. 3, pp. 531-546

Exploring the Effect of Social Networking Service on Homestay Intention in Vietnam by GM(1, N) and Multiple Regression Analysis

1Department of Information Management
2Department of Business Administration
4Department of General Education Center
Chaoyang University of Technology
Taichung, 41349 Taiwan
E-mail: {cgc; crching}@cyut.edu.tw; stacy8chu@gmail.com4

3Department of International Business
National Taichung University of Education
Taichung, 40345 Taiwan
E-mail: cslai@mail.ntcu.edu.tw; ttdhanh06@gmail.com

A significant area of Social Computing is the Social Network Service (SNS), known as Social Network Applications. In recent years, researchers have commonly used SNS as an instrument for linking and communicating. Homestay travel has been prevalent for a long time with the rise of social media. The goal of this study is to examine the influence of Social Network Service functions on homestay travel intention in Vietnam. Fourteen Social Network Service functions were summarized from the literature review and used as the variables influencing the purpose of homestay travel to develop a five-point Likert scale questionnaire for convenience sampling to perform an online survey. For further study, two hundred and twenty valid respondents were included. The GM(1,N) analysis showed interest sharing, photo sharing, and video sharing as the first to third most principal factors in their highly seasoned weighting towards homestay travel intention. On the other side, helping decision, helping interaction, and helping planning as the last three lists of weighting scores. Besides, multiple regression analysis shows that offering recommenda-tions, helping planning, and sharing interest simultaneously predict homestay travel inten-tion while the others don’t. That means consumers would heavily rely upon the functions of sharing interest of social network services to evaluate their traveling options. It is pro-posed that homestay traveling vendors should pay more attention to the marketing of pre-vious travelers’ experiential interests to provoke the awareness of customers.

Keywords: GM(1,N), social networking service, homestay intention, social computing, multiple regression analysis

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