- E-ISSN2233-5382
- KCI
E-ISSN : 2233-5382
Influences of Motivations on Interactivity in the Live Streaming Commerce
Abstract
Purpose: This study focuses how motivations influence interactivity in the live streaming commerce context. Live streaming commerce involves the provision of e-commerce activities and transactions via a live streaming platform that offers real-time interaction, entertainment, social activities, and commerce. The purpose of study is to examine effects of motivations on perceived interactivity and the effects of perceived interactivity on attitude and intention to use the live streaming commerce. Research design, data and methodology: The study investigates key questions about consumers’ motivation to use live streaming commerce and perceived interactivity by surveying 300 users of live commerce. Participants were asked whether they were live streaming commerce users who had experienced live streaming commerce before participating in the survey. The full survey required live streaming commerce users to respond to all the questions. Results: The study uncovered motivations for using live streaming commerce by finding information, entertainment, pass time, fashion/status and real time and perceived interactivity in the live streaming commerce. The results indicated motivation to use live streaming commerce positively influenced perceived interactivity. Perceived interactivity had positive effects on attitude toward brand. Attitude toward brand had positive effects on intention to use. Conclusions: Live streaming commerce is getting increasing attention from marketers because live streaming commerce has seamlessly integrated commerce, social activities, and hedonic factors. This study clarifies motivations and perceived interactivity in the live streaming commerce context. The study uncovers the relationships between motivations, perceived interactivity, attitude, and intention to use that contributes to the theoretical foundation and practical implications for marketing and management in the live streaming commerce context. Specifically, the study develops the theoretical contributions to perceived interactivity in the in the live streaming commerce context. The results also contribute to the practical implications for new marketing strategies that provides dynamic real-time interaction, exact information, and social and hedonic factors to attract consumers to indulge in the consumption processes. Marketing practitioners will obtain insights that can help them develop and manage brand strategies by understanding the influence of motivation and perceived interactivity in the live commerce context, which offers opportunities for contactless marketing and management.
- keywords
- Live Streaming Commerce, Motivations, Interactivity, Attitude, Intention to Use
Reference
Chen, C., & Lin, Y. (2018). What drives live-stream usage intention? The perspectives of flow, entertainment, social interaction, and endorsement. Telematics and Informatics, 35(1), 293-303.
Churchill Jr., G. A. (1979). A Paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64-73.
Croes, E., & Bartels, J. (2021). Young adults’ motivations for following social influencers and their relationship to identification and buying behavior. Computers in Human Behavior, 124(11), 106910. https://doi.org/10.1016/j.chb.2021.106910.
DeVellis, R. F. (2016). Scale development: Theory and applications. Thousand Oaks, CA: Sage.
Dodoo, N. A., & Youn, S. (2021). Snapping and chatting away:Consumer motivations for and outcomes of interacting with Snapchat AR ad lens. Telematics and Informatics, 57(2), 01514. https://doi.org/10.1016/j.tele.2020.101514.
Flanagin, A. J., & Metzger, M. J. (2001). Internet use in the contemporary media environment. Human Communication Research, 27(1), 153-181.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Hall, L., Paracha, S., Flint, T., MacFarlane, K., Stewart, F., Hagan-Green, G., & Watson, D. (2021). Still looking for new ways to play and learn: Expert perspectives and expectations for interactive toys. International Journal of Child-Computer Interaction, available online 24 July 2021, 100361. https://doi.org/10.1016/j.ijcci.2021.100361.
Hegner, S. M., Lotze, C., & Beldad, A. D. (2021). Emoticons are not for everyone: The role of congruence between hotel brand positioning strategies and communication style in enhancing customers’ brand attitude and booking intention. Tourism and Hospitality Research, 21(3), 317-329. https://doi.org/10.1177/1467358421993901.
Hilvert-Bruce, Z., Neill, J. T., Sjöblom, M., & Hamari, J. (2018). Social motivations of live-streaming viewer engagement on Twitch. Computers in Human Behavior, 84(7), 58-67.
Hooda, A., & Ankur, A. (2018). Acceptance of social media as a marketing tool: A quantitative study east Asian. Journal of Business Management, 8(3), 5-12. https://doi.org/10.13106/eajbm.2018.vol8.no3.5.
Hu, M., Zhang, M., & Wang, Y. (2017). Why do audiences choose to keep watching on live video streaming platforms? An explanation of dual identification framework. Computers in Human Behavior, 75(10), 594-606.
Huang, Y., Sundar, S. S., Ye, Z., & Johnson, A. C. (2021). Do women and extroverts perceive interactivity differently than men and introverts? Role of individual differences in responses to HCI vs. CMC interactivity. Computers in Human Behavior, 123(10), 106881. https://doi.org/10.1016/j.chb.2021.106881.
Jin, P.-R., & Lee, J.-H. (2019). The impact of block chain characteristics on the intention to use hotel reservation system in China. Journal of Industrial Distribution & Business, 10(8), 33–44. https://doi.org/10.13106/ijidb.2019.vol10.no8.33.
Kim, Y. (2019). A Study on switching intention of broadcasting service to MCN service by migration theory. Journal of Industrial Distribution & Business, 10(1), 59-67. https://doi.org/10.13106/IJIDB.2019.VOL10.NO1.55.
Kyriazos, T. A. (2018). Applied psychometrics: Sample size and sample power considerations in factor analysis (EFA, CFA) and SEM in general. Psychology, 9(8), 2207-2230. https://doi.org/10.4236/psych.2018.98126.
Lee, J.-H. (2021). Effect of sports psychology on enhancing consumer purchase intention for retailers of sports shops:Literature content analysis. Journal of Distribution Science, 19(4), 5-13. https://doi.org/10.15722/jds.19.4.202104.5.
Lee, S. Y., Kim, Y., & Kim, Y. (2021). Engaging consumers with corporate social responsibility campaigns: The roles of interactivity, psychological empowerment, and identification. Journal of Business Research, 134(1), 507-517.
Lucia-Palacios, L., & Pérez-López, R. (2021). Effects of home voice assistants' autonomy on intrusiveness and usefulness:Direct, indirect, and moderating effects of interactivity. Journal of Interactive Marketing, Available online 24 June 2021. https://doi.org/10.1016/j.intmar.2021.03.005.
MacKenzie, S., Lutz, R. J., & Belch, G. E. (1986). The role of attitude toward the ad as a mediator of advertising effectiveness: A test of competing explanations. Journal of Marketing Research, 23(2), 130-143.
Maidiana, K., & Hidayat, Z. (2021). Distributing goods and information flow: Factors influencing online purchasing behavior of Indonesian consumers. Journal of Distribution Science, 19(7), 5-17. https://doi.org/10.15722/JDS.19.7.202107.5.
McMillan, S. J., & Hwang, J. (2002). Measures of perceived interactivity: An exploration of communication, user control, and time in shaping perceptions of interactivity. Journal of Advertising, 31(3), 29-42.
Nysveen, H., Pedersen, P. E., & Thorbjørnsen, H. (2005). Intentions to use mobile services: antecedents and crossservice comparisons. Journal of Academy of Marketing Science, 33(3), 330‐346.
Peters, O., & Allouch, S. (2005). Always connected: A longitudinal field study of mobile communication. Telematics & Informatics, 22(3), 239‐256.
Ryu, J. S. (2019). Consumer characteristics and shopping for fashion in the omni-channel retail environment. Journal of Business, Economics and Environmental Studies, 9(4), 15-22. https://doi.org/10.13106/jbees.2019.vol9.no4.15.
Sjöblom, M., & Hamari, J. (2017). Why do people watch others play video games? An empirical study on the motivations of Twitch users. Computers in Human Behavior, 75(10), 985-996.
Statista (2020). Age distribution of live streaming e-commerce users in China as of March 2020. Retrieved August 1, 2021 (actual access date), from https://www.statista.com/statistics/1186274/china-age-group-distribution-of-live-streamingusers/
Sun, Y., Shao, X., Li, X., Guo, Y., & Nie, K. (2020). A 2020 perspective on “How live streaming influences purchase intentions in social commerce: An IT affordance perspective.” Electronic Commerce Research and Applications, 40(1), 100958. https://doi.org/10.1016/j.elerap.2020.100958.
Tseng, T-H., Huang, H. H., & Setiawan, A. (2017). How do motivations for commitment in online brand communities evolve? The distinction between knowledge- and entertainment-seeking motivations, Computers in Human Behavior, 77(12), 326-335.
Wongkitrungrueng, A., & Assarut, N. (2020). The role of live streaming in building consumer trust and engagement with social commerce sellers. Journal of Business Research, 117(1), 543-556.
Xia, Y., & Yang, Y. (2019). RMSEA, CFI, and TLI in structural equation modeling with ordered categorical data: The story they tell depends on the estimation methods. Behavioral Research, 51(1), 409-428.
Xu, X., Wu, J., & Li, Q. (2020). What drives consumer shopping behavior in live streaming commerce? Journal of Electronic Commerce Research, 21(3), 144-167.
Zhang, M., Guo, L., Hu, M., & Liu, W. (2017). Influence of customer engagement with company social networks on stickiness: Mediating effect of customer value creation. International Journal of Information Management, 37(3), 229-240.
- Downloaded
- Viewed
- 0KCI Citations
- 0WOS Citations