Causal Factors of the Perceived Benefit of Social Commerce Platform
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Abstract
This research aims to study the causal factors of the perceived benefit of the social commerce platform on the partial least square model. The samples are 270 consumers who had an experience of using social commerce platform for buying goods or services. The research instrument was a questionnaire. In the process of data analysis, Partial Least Square (PLS) technique was used to investigate the structural equation modeling and descriptive statistics were used to analyze. The research found that integrated motivation, intention to sharing information through social commerce platform, and social commerce information sharing behavior had causal factors that affected the perceived benefit of social commerce platforms. The structural equation model can explain the perceived benefit of social commerce platform at 63.00 percent (R2 = 0.630, R2adj = 0.629). The results of this research are beneficial to online business entrepreneurs and stakeholders to increase the perceived benefit of social commerce platform through the social commerce information sharing behavior by the Intention to sharing information through social commerce platform as a result of integrated motivation.
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กุลจิรา นารอง. (2561). โซเชียลคอมเมิร์ซ พลิกโฉมค้าปลีกออนไลน์. วันที่เข้าถึงข้อมูล 1 ธันวาคม 2562, แหล่งที่มา https://www.posttoday.com/economy/news/560480
สำนักงานคณะกรรมการดิจิทัลเพื่อเศรษฐกิจและสังคมแห่งชาติ กระทรวงดิจิทัลเพื่อเศรษฐกิจและสังคม. (2562). นโยบายและแผนระดับชาติว่าด้วยการพัฒนาดิจิทัลเพื่อเศรษฐกิจและสังคม (พ.ศ. ๒๕๖๑ – ๒๕๘๐). วันที่เข้าถึงข้อมูล 27 มกราคม 2563, จาก https://www.etda.or.th_content_files/2/files/05_Thailand_Digital_Plan.pdf
สำนักงานพัฒนาธุรกรรมทางอิเล็กทรอนิกส์ (สพธอ). (2561). ETDA เปิดพฤติกรรมผู้ใช้อินเทอร์เน็ตปี 61 คนไทยใช้เน็ตเพิ่ม 10 ชั่วโมง 5 นาทีต่อวัน. วันที่เข้าถึงข้อมูล 1 ธันวาคม 2562, จาก https:// www.etda.or.th/content/etda-reveals-thailand-internet-user-profile-2018.html
Ajzen, I., & Fishbein, M. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Allen, N. J., & Meyer, J. P. (1996). Affective, continuance, and normative commitment to the organization: An examination of construct validity. Journal of Vocational Behavior, 49(3), 252–276.
Bergami, M., & Bagozzi, R. P. (2000). Self-categorization, affective commitment and group self-esteem as distinct aspects of social identity in the organization. The British Journal of Social Psychology, 39(4), 555–577.
Cheema, U., Rizwan, M., Jalal, R., Durrani, F., & Sohail, N. (2013). The trend of online shopping in 21st century: Impact of enjoyment in tam model. Asian Journal of Empirical Research, 3(2), 131-141.
Chen, A., Lu, Y., & Wang, B. (2017). Customers’ purchase decision-making process in social commerce: A social learning perspective. International Journal of Information Management, 37(6), 627-638.
Chen, Y., Fay, S., & Wang, Q. (2011). The role of marketing in social media: How online consumer reviews evolve. Journal of Interactive Marketing, 25(2), 85–94.
Chin, W. W. (2010). How to write up and report PLS analyses, in Esposito Vinzi, V., Chin, W. W., Henseler, J., & Wang, H. (Eds), Handbook of Partial Least Squares: Concepts, Methods and Applications, Vol. 2, Springer Handbooks of Computational Statistics Series. Springer, Heidelberg, 655-690.
Chesshire, T., & Rowan, D. (2011). Commerce gets social: How social networks are driving what You buy. Retrieved December 14, 2019, from http://www.wired.co.uk/magazine/archive/2011/02/features/social-networks-drive-commerce
Cheung, C. M., & Lee, M. K. (2012). What drives consumers to spread electronic word of mouth in online consumer-opinion platforms. Decision Support Systems, 53(1), 218–225.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.
Deci, E. L., & Ryan, R. M. (2000). The" what" and" why" of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268.
Delone, W.H., & McLean, E.R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30.
Delone, W.H., & Mclean, E.R. (2004). Measuring e-commerce success: Applying the DeLone & McLean information systems success model. International Journal of Electronic Commerce, 9(1), 31–47.
de Vries, L., Gensler, S., & Leeflang, P. S. H. (2012). Popularity of brand posts on brand fan pages: An investigation of the effects of social media marketing. Journal of Interactive Marketing, 26(2). 83–91.
Diamantopoulos, A., & Siguaw, J. A. (2006). Formative vs reflective indicators in measure development: does the choice of indicators matter?. British Journal of Management, 13(4). 263-282.
Ellemers, N., Kortekaas, P., & Ouwerkerk, J. W. (1999). Self‐categorisation, commitment to the group and group self-esteem as related but distinct aspects of social identity. European Journal of Social Psychology, 29(23), 371–389.
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1). 39-50.
Gensler, S., Volckner, F., Liu-Thompkins, Y., & Wiertz, C. (2013). Managing brands in the social media environment. Journal of Interactive Marketing, 27(4). 242–256.
Goh, K. Y., Heng, C. S., & Lin, Z. (2013). Social media brand community and consumer behavior: Quantifying the relative impact of user- and marketer-generated content. Information Systems Research, 24(1). 88–107.
Goldfarb, Avi, & Tucker, C.E. (2011). Privacy Regulation and Online Advertising. Management Science, 57(1), 57–71.
Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2010). Multivariate Data Analysis. 7th ed. Upper Saddle River, NJ: Prentice Hall.
Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2013). A primer on partial least squares structural equation modeling (PLS-SEM): Sage Publications.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2nd ed. Thousand Oaks, CA: Sage.
Hajli, N., Sims, J., Zadeh, A. H., & Richard, M. O. (2017). A social commerce investigation of the role of trust in a social networking site on purchase intentions. Journal of Business Research, 71. 133-141.
Jöreskog, K., & Sorbom, D. (1993) LISREL 8: Structural Equation Modelling with the SIMPLIS Command Language. Scientific Software International Inc., Chicago.
Kankanhalli, A., Tan, B. C., & Wei, K.-K. (2005). Contributing knowledge to electronic knowledge repositories: An empirical investigation. MIS Quarterly, 29(1), 113–143.
Ke, W., & Zhang, P. (2010). The effects of extrinsic motivations and satisfaction in open source software development. Journal of the Association for Information Systems, 11(12), 784.
Laroche, M., Habibi, M. R., Richard, M. O., & Sankaranarayanan, R. (2012). The effects of social media based brand communities on brand community marker, value creation practice, brand trust and brand loyalty. Computers in Human Behavior, 28(5). 1755–1767.
Liang, T. -P., Ho, Y. -T., Li, Y. –W., & Turban, E. (2011). What drives social commerce: The role of social support and relationship quality. International Journal of Electronic Commerce, 16(2), 69–90.
Ng, C.S.-P. (2013). Intention to purchase on social commerce websites across cultures: A cross-regional study. Information & Management, 50(8), 609–620.
Pan, S. C., & Rickard, T. C. (2018). Transfer of test-enhanced learning: Meta-analytic review and synthesis. Psychological Bulletin, 144(7), 710.
Petter, S., DeLone, W., & McLean, E. R. (2012). The past, present, and future of" IS Success". Journal of the Association for Information Systems, 13(5), 341.
Ringle, C. M., Götz, O., Wetzels, M., & Wilson, B. (2015). On the use of formative measurement specifications in structural equation modeling: A Monte Carlo simulation study to compare covariance-based and partial least squares model estimation methodologies. METEOR Research Memoranda (RM/09/014).
Rovinelli, R. J., & Hambleton, R. K. (1977). On the use of content specialists in the assessment of criterion-referenced test item validity. Dutch Journal of Educational Research, 2, 49-60.
Ryan, R.M., & Deci, E.L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. The American Psychologist, 55(1): 68-78.
Sarstedt, M., Ringle, C. M., Smith, D., Reams, R., & Hair, J. F. (2014). Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers. Journal of Family Strategy, 5(1), 105-115.
Schilling, M. A., Vidal, P., Ployhart, R. E., & Marangoni, A. (2003). Learning by doing something else: Variation, relatedness, and the learning curve. Management Science, 49(1), 39–56.
Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. The Journal of Consumer Research, 15(3), 325–343.
Stewart, K. J., & Gosain, S. (2006). The impact of ideology on effectiveness in open source software development teams. MIS Quarterly, 30(2), 291–314.
Venkatesh, V., Morris, M.G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. Journal of the Association for Information Systems, 17(5), 328-376.
Wang, X. (2014). How do people participate in social network sites after crises? A self-determination perspective. Social Science Computer Review, 32(5), 662–677.
Wang, X., Clay, P. F., & Forsgren, N. (2015). Encouraging knowledge contribution in IT support: Social context and the differential effects of motivation type. Journal of Knowledge Management, 19(2), 315–333.
Wang, X., Lin, X., & Spencer, M.K. (2019). Exploring the effects of extrinsic motivation on consumer behaviors in social commerce: Revealing consumers’ perceptions of social commerce benefits. International Journal of Information Management, 45(2019), 163–175.
Zhang, Hong & Lu, Yaobin & Gupta, Sumeet & Zhao, Ling. (2014). What motivates customers to participate in social commerce? The impact of technological environments and virtual customer experiences. Information & Management. 51.