The Factors Acceptance of Online Social Media that Influencing the Decision of Consumers for Choosing the Coffee Shop's Service in Bangkok and Metropolitan Area
Article Sidebar
Main Article Content
Abstract
The purpose of this research is to learn about factors affecting acceptance of social media influences on choosing coffee shops for decision making of consumers in Bangkok and metropolitan areas, by a conceptual framework was based on model evaluation (Elaboration Likelihood Model)
and conceptual information adoption model theory Information Adoption Mode). This research is quantitative and uses a questionnaire to collect the data. A stratified random sampling technique was applied to 468 samples
with consumers who used the service by researching social media online data in Bangkok and nearby areas. The sample group was divided according to the range of age and frequency of use of the service. Questionnaire was
used as the research tool and the adoption of a structural equation model was used to analyze the data. Results revealed that the model in this research is consistent with the empirical data, was close to the established criteria
and within acceptable limits and factors affect data acceptance of social media to choose and use the service of the coffee shop, with significant statistics composed of Perceived Risk, Relevance, Conciseness, Trustworthiness,
Scalability, Popularity, Content usefulness, and Information Adoption. As a guideline for people were using coffee shops can use the information to make decisions about choosing a product or service and is information for coffee shop business owners to plan social media marketing for making a business advantage.
Article Details
References
สิริลดา นาดี. (2559). ศึกษารูปแบบเนื้อหาการสื่อสาร และการตอบสนองบนเฟซบุ๊กแฟนเพจผลิตภัณฑ์ความงาม กรณีศึกษา เฟซบุ๊กแฟนเพจ: Oriental Princess Society, Merrezca และ BSC Cosmetology. การค้นคว้าอิสระนิเทศศาสตรมหาบัณฑิต สาขาวิชาการสื่อสารการตลาดดิจิทัล, มหาวิทยาลัยกรุงเทพ.
สุทธิ์ธิดา จันทร์โอกุล. (2558). อิทธิพลของการสื่อสารแบบปากต่อปากที่กระทาผ่านอินเทอร์เน็ตต่อความตั้งใจซื้อสินค้าของผู้บริโภคทางพาณิชย์อิเล็กทรอนิกส์.
วิทยานิพนธ์นี้วิทยาศาสตรมหาบัณฑิต สาขาวิชาระบบสารสนเทศเพื่อการจัดการคณะพาณิชยศาสตร์และการบัญชี, มหาวิทยาลัยธรรมศาสตร์.
Alsaleh, D. A., Elliott, M. T., Fu, F. Q., & Thakur, R. (2019). Cross-cultural Differences in the Adoption of Social Media. Journal of Research in Interactive Marketing, 13(1), 119-140.
Amoroso, D., & Lim, R. (2017). The mediating effects of habit on continuance intention. International Journal of Information Management, 37(6), 693–702.
Bailey, J.E.; Pearson, S.W. (1983). Development of a tool for measuring and analyzing computer user satisfaction. Management Science, 29, 530–545.
Bansal, H. S., & Voyer, P. A. (2000). Word-of-mouth processes within a services purchase decision context. Journal of Service Research, 3(2), 166–177.
Biscaia, A. R., Rosa, M. J., Moura e Sá, P., & Sarrico, C. S. (2017). Assessing customer satisfaction and loyalty in the retail sector. International Journal of Quality & Reliability Management, 34(9), 1508–1529.
Bhattacherjee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32, 201–214.
Cheung, C.M.; Lee, M.K.; Rabjohn, N. (2008). The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities. Internet Research, 18, 229–247.
Cheung, M.Y.; Luo, C.; Sia, C.L.; Chen, H. (2009). Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. International Journal of Electronic Commerce, 13, 9–38.
Chang, H.C. (2010). A new perspective on Twitter hashtag use: Diffusion of innovation theory. Proceedings of the American Society for Information Science and Technology, 47, 1–4.
Chu, S.; Kim, Y. (2011). Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. International Journal of Advertising, 30, 47–75.
Cui, W.; Du, J.; Wang, D.; Kou, F.; Liang, M.; Xue, Z.; Zhou, N. (2019). Extended search method based on a semantic hashtag graph combining social and conceptual information. World Wide Web, 22, 2589–2610.
De Veirman, M.; Cauberghe, V.; Hudders, L. (2017). Marketing through Instagram influencers: The impact of number of followers and product divergence on brand attitude. International Journal of Advertising, 36, 798–828.
De Vries, L.; Gensler, S.; Leeflang, P.S. (2012). Popularity of brand posts on brand fan pages: An investigation of the effects of social media marketing. Journal of Interactive Marketing, 26, 83–91. Diena Dwidienawati, David Tjahjana, Sri Bramantoro Abdinagoro, Dyah
Gandasari, Munawaroh (2020). Customer review or influencerendorsement: which one influences purchase intention more. Heliyon, 6, 1-11.
Erkan, I.; Evans, C. (2018). Social media or shopping websites? The influence of eWOM on consumers’ online purchase intentions. Journal of Marketing Communications, 24, 617–632.
Fang, Y.; Chiu, C. (2010). In justice we trust: Exploring knowledge-sharing continuance intentions in virtual communities of practice. Computers in Human Behavior, 26, 235–246.
Fang, B.; Ye, Q.; Kucukusta, D.; Law, R. (2016). Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics. Tourism Management, 52, 498–506.
Fuchs, G., & Reichel, A. (2006). Correlates of destination risk perception and risk reduction strategies, Progress in tourism marketing, advances in tourism research, pp. 161–170.
G.T Puspita and H.Hendrayati. (2018). Food Blogger Review on Instagram as an Alternative for Helping Consumer Purchase Decision, Advances in Economics, Business and Management Research, volume 117 3rd Global Conference On Business, Management, and Entrepreneurship.
Hair, J. F., Black, W. C., Babin, B.J., and Anderson, R. E. (2010). Multivariate Data Analysis (7th Edition). Upper Saddle River,New Jersey: Prentice Hall.
Hashim, K.F.; Tan, F.B. (2015). The mediating role of trust and commitment on members’ continuous knowledge sharing intention: A commitment-trust theory perspective. International Journal of Information Management, 35, 145–151.
Hee-Min Lee, Jee-Won Kang and Young Namkung (2021). Instagram Users’ Information Acceptance Process for Food-Content, Sustainability, 13, 2638.
H. Jeong, D. Koo (2015). Combined effects of valence and attributes of e-WOM on consumer judgment for message and product, Internet Research.25 (1) 2–29.
J.J. Wang, L.Y. Wang, M.M. Wang (2018). Understanding the effects of eWOM social ties on purchase intentions: a moderated mediation investigation, Electronic Commerce Research and Applications, 28, 54–62.
Kang, J.W.; Namkung, Y. (2019). The information quality and source credibility matter in customers’ evaluation toward food O2O commerce. International Journal of Hospitality Management, 78, 189–198.
Kim, K.Y.; Kyung, S.B. (2018). The effect of social network service (SNS)-based food content information quality on user satisfaction, intention to use, and information sharing intention. International Journal of Hospitality & Tourism Administration, 32, 177–192.
Kim, W.B.; Kim, D.S.; Park, J. (2019). The effects of hashtag type on evaluations of influencer and fashion information and consumer responses. Journal of the Korean Society of Clothing and Textiles, 43, 1–16.
Lee, C.S.; Ma, L. (2012). News sharing in social media: The effect of gratifications and prior experience. Computers in Human Behavior, 28, 331–339.
Lee, Y.W.; Strong, D.M.; Kahn, B.K.; Wang, R.Y. (2002). AIMQ: A methodology for information quality assessment. Information & Management, 40, 133–146.
Petty, R E., & Cacioppo, J. T. (1984). Source factors and the elaboration likehood model of persuasion. Advances in Consumer Research, 11, 668-672.
Peng, L., Liao, Q., & Wang, X. (2016). Factors affecting female user information adoption: An empirical investigation on fashion shopping guide websites. Electronic Commerce Research, 16(2), 145-169.
Priporas, C. V., Stylos, N., and Fotiadis, A. K. (2017). Generation Z Consumers’ Expectations of Interactions in Smart Retailing: A Future Agenda. Computers in Human Behavior. Vol. 77, pp. 374-381.
Ramachandran, S.; Paulraj, S.; Joseph, S.; Ramaraj, V. (2009). Enhanced trustworthy and high-quality information retrieval system for web search engines. International Journal of Computer Science Issues, Vol. 5, 38–42.
Roehl,W. S., & Fesenmaier, D. R. (1992). Risk perceptions and pleasure travel: An exploratory analysis. Journal of Travel Research, 30, 17–26.
Rubio, N., Oubia, J., & Villaseor, N. (2014). Brand awareness–Brand quality inference and consumer’s risk perception in store brands of food products. Food Quality and Preference, 32(1), 289-298.
Shun-Yao Tseng and Ching-Nan Wang. (2016). Perceived risk influence on dual-route information adoption processes on travel websites. Journal of Business Research 69 (2016) 2289–2296.
Susssman, S. W., & Siegal, W. S. (2003). Informational Influence in Organizations: An Integrated Approach to Knowledge Adoption.
Information Systems Research, 14(1), 47-65.
Shu, M. L., & Scott, N. (2014). Influence of social media on Chinese students’ choice of an overseas study destination: An information adoption model perspective. Journal of Travel & Ourism Marketing, 31(2), 288-302.
Teng, S.; Khong, K.W.; Goh, W.W.; Chong, A.Y.L. (2014). Examining the antecedents of persuasive eWOM messages in social media. Online Information Review, 38, 746–768.
Wu, C.; Shaffer, D.R. (1987). Susceptibility to persuasive appeals as a function of source credibility and prior experience with the attitude object. Journal of Personality and Social Psychology, 52, 677.
Yang, D.; Zhu, R.; Li, Y. (2019). Self-Attentive neural network for hashtag recommendation. Journal of Engineering Science and Technology Review. 12, 104–110.