0
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Understanding Live-Streaming Viewers’ Post-Adoption Based on A Relationship Development Perspective

ORCID Icon, ORCID Icon & ORCID Icon
Received 11 Mar 2024, Accepted 22 Jul 2024, Published online: 05 Aug 2024

References

  • Ahearne, M., Bhattacharya, C. B., & Gruen, T. (2005). Antecedents and consequences of customer-company identification: Examining the role of relationship marketing. The Journal of Applied Psychology, 90(3), 574–585. https://doi.org/10.1037/0021-9010.90.3.574
  • Arghashi, V., & Yuksel, C. A. (2022). Interactivity, inspiration, and perceived usefulness! How retailers’ AR-apps improve consumer engagement through flow. Journal of Retailing and Consumer Services, 64, 102756. https://doi.org/10.1016/j.jretconser.2021.102756
  • Bagozzi, R. P., & Lee, K. H. (2002). Multiple routes for social influence: The role of compliance, internalization, and social identity. Social Psychology Quarterly, 65(3), 226–247. https://doi.org/10.2307/3090121
  • Bai, X., Cheng-Xi Aw, E., Wei-Han Tan, G., & Ooi, K.-B. (2024). Livestreaming as the next frontier of e-commerce: A bibliometric analysis and future research agenda. Electronic Commerce Research and Applications, 65, 101390. https://doi.org/10.1016/j.elerap.2024.101390
  • Bendapudi, N., & Berry, L. L. (1997). Customers’ motivation for maintaining relationships with service providers. Journal of Retailing, 73(1), 15–37. https://doi.org/10.1016/S0022-4359(97)90013-0
  • Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921
  • Bostrom, B. R. P., & Heinen, J. S. (1977). MIS problems and failures: A socio-technical perspective, part II: The application of theory. MIS Quarterly, 1(4), 11–28. https://doi.org/10.2307/249019
  • Brannon Barhorst, J., McLean, G., Shah, E., & Mack, R. (2021). Blending the real world and the virtual world: Exploring the role of flow in augmented reality experiences. Journal of Business Research, 122, 423–436. https://doi.org/10.1016/j.jbusres.2020.08.041
  • Buzzorange.com (2017). https://buzzorange.com/techorange/2017/10/06/date-summit-twitch/
  • Cao, X., & Yu, L. (2019). Exploring the influence of excessive social media use at work: A three-dimension usage perspective. International Journal of Information Management, 46, 83–92. https://doi.org/10.1016/j.ijinfomgt.2018.11.019
  • Chen, C., & Lin, Y. (2018). What drives live-stream usage intention? The perspective of flow, entertainment, social interaction, and endorsement. Telematics and Informatics, 35(1), 293–303. https://doi.org/10.1016/j.tele.2017.12.003
  • Chen, Y., & Lin, C. A. (2022). Consumer behavior in an augmented reality environment: Exploring the effects of flow via augmented realism and technology fluidity. Telematics and Informatics, 71, 101833. https://doi.org/10.1016/j.tele.2022.101833
  • Cheng, X., Gu, Y., Hua, Y., & Xin, L. (2021). The paradox of word-of-mouth in social commerce: Exploring the juxtaposed impacts of source credibility and information quality on SWOM spreading. Information & Management, 58(7), 103505. https://doi.org/10.1016/j.im.2021.103505
  • Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189–217. https://doi.org/10.1287/isre.14.2.189.16018
  • Chong, A. Y. L., Lacka, E., Li, B., & Chan, H. K. (2018). The role of social media in enhancing guanxi and perceived effectiveness of E-commerce institutional mechanisms in online marketplace. Information & Management, 55(5), 621–632. https://doi.org/10.1016/j.im.2018.01.003
  • Chou, S.-W., & Chiang, C.-H. (2013). Understanding the formation of software-as-a-service satisfaction from the perspective of service quality. Decision Support Systems, 56, 148–155. https://doi.org/10.1016/j.dss.2013.05.013
  • Csikszentmihalyi, M. (1975). Beyond Boredom and Anxiety. Jossey-Bass.
  • Csikszentmihalyi, M. (2014). Applications of Flow in Human Development and Education: The collected Work of Mihaly Csikszentmihalyi. Springer. https://doi.org/10.1007/978-94-017-9094-9
  • Dong, X., & Wang, T. (2018). Social tie formation in Chinese online social commerce: The role of IT affordance. International Journal of Information Management, 42, 49–64. https://doi.org/10.1016/j.ijinfomgt.2018.06.002
  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement errors. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
  • Gefen, D, Drexel University (2002). Customer loyalty in e-commerce. Journal of the Association for Information Systems, 3(1), 27–53. https://doi.org/10.17705/1jais.00022
  • Gong, X., Liu, X., & Xiao, Z. (2022). A dedication-constraint model of consumer switching behavior in mobile payment applications. Information & Management, 59(4), 103640. https://doi.org/10.1016/j.im.2022.103640
  • Guo, Z., Xiao, L., Toorn, C. V., Lai, Y., & Seo, C. (2016). Promoting online learners’ continuance intention: An integrated flow framework. Information & Management, 53(2), 279–295. https://doi.org/10.1016/j.im.2015.10.010
  • Heide, J. B., & Weiss, A. M. (1995). Vendor consideration and switching behavior for buyers in high-technology markets. Journal of Marketing, 59(3), 30–43. https://doi.org/10.2307/1252117
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International Marketing Review, 33(3), 405–431. https://doi.org/10.1108/IMR-09-2014-0304
  • 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, 58–67. https://doi.org/10.1016/j.chb.2018.02.013
  • Hsu, C.-L. (2020). How vloggers embrace their viewers: Focusing on the roles of para-social interactions and flow experience. Telematics and Informatics, 49, 101364. https://doi.org/10.1016/j.tele.2020.101364
  • 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, 594–606. https://doi.org/10.1016/j.chb.2017.06.006
  • Hyun, H., Thavisay, T., & Lee, S. H. (2022). Enhancing the role of flow experience in social media usage and its impact on shopping. Journal of Retailing and Consumer Services, 65, 102492. https://doi.org/10.1016/j.jretconser.2021.102492
  • Johnson, R. A., & Wichern, D. W. (2002). Applied multivariate statistical analysis (6th ed.). Prentice Hall.
  • Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2002). Why consumer stay: Measuring the underlying dimensions of service switching costs and managing their differential strategic outcomes. Journal of Business Research, 55(6), 441–450. https://doi.org/10.1016/S0148-2963(00)00168-5
  • Kelman, H. C. (1974). Further thoughts on the processes of compliance, identification, and internalization. In J. T. Tedeschi (Ed.), Perspectives on social power (pp. 126–171). Aldine.
  • Kim, M. (2022). How can I be as attractive as a fitness YouTurber in the era of COVID-19? The impact of digital attributes on flow experience, satisfaction, and behavioral intention. Journal of Retailing and Consumer Services, 64, 102778. https://doi.org/10.1016/j.jretconser.2021.102778
  • Kim, M. J., & Hall, C. M. (2019). A hedonic motivation model in virtual reality tourism: Comparing visitors and non-visitors. International Journal of Information Management, 46, 236–249. https://doi.org/10.1016/j.ijinfomgt.2018.11.016
  • Kim, M., & Kim, H.-M. (2022). What online game spectators want from their twitch streamers: Flow and well-being perspectives. Journal of Retailing and Consumer Services, 66, 102951. https://doi.org/10.1016/j.jretconser.2022.102951
  • Kim, S. S. and Son, J. Y. (2009). Out of dedication or constraint? A dual model of post-adoption phenomena and its empirical test in the context of online services. MIS Quarterly, 33(1), 49–70. https://doi.org/10.2307/20650278
  • Lam, S. Y., Shankar, V., Erramilli, M. K., & Murthy, B. (2004). Customer value, satisfaction, loyalty, and switching costs: An illustration from a business-to-business service context. Journal of the Academy of Marketing Science, 32(3), 293–311. https://doi.org/10.1177/0092070304263330
  • Nakamura, J., & Csikszentmihalyi, M. (2002). The concept of flow. In C. R. Snyder, S. J. Lopez (Eds.), Handbook of positive psychology (pp. 89–105). Oxford University Press Inc.
  • Oliver, R. L. (1999). Whence consumer loyalty? Journal of Marketing, 63(4_suppl1), 33–44. https://doi.org/10.2307/1252099
  • Ou, C. X., Pavlou, P. A., & Davison, R. M, Tilburg University (2014). Swift guanxi in online marketplaces: The role of computer-mediated communication technologies. MIS Quarterly, 38(1), 209–230. https://doi.org/10.25300/MISQ/2014/38.1.10
  • Pelet, J., Ettis, S., & Cowart, K. (2017). Optimal experience of flow enhanced by telepresence: Evidence from social media use. Information & Management, 54(1), 115–128. https://doi.org/10.1016/j.im.2016.05.001
  • Perugini, M., & Bagozzi, R. (2001). The role of desires and anticipated emotions in goal-directed behaviors: Broadening and deepening the theory of planned behavior. The British Journal of Social Psychology, 40(Pt 1), 79–98. https://doi.org/10.1348/014466601164704
  • Podsakoff, P., MacKenzie, S., Lee, J., & Podsakoff, N. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. The Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
  • Reichheld, F. F., Markey, R. G., Jr., & Hopton, C. (2000). E-customer loyalty—Applying the traditional rules of business for online success. European Business Journal, 12(4), 173–179.
  • Seidler, J. (1974). On using informants: A technique for collecting quantitative data and controlling measurement error in organization analysis. American Sociological Review, 39(6), 816–831. https://doi.org/10.2307/2094155
  • Shernoff, D. J., Csikszentmihalyi, M., Shneider, B., & Shernoff, E. S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18(2), 158–176. https://doi.org/10.1521/scpq.18.2.158.21860
  • Stever, G. S. (2011). Fan behavior and lifespan development theory: Explaining parasocial and social attachment to celebrities. Journal of Adult Development, 18(1), 1–7. https://doi.org/10.1007/s10804-010-9100-0
  • Thatcher, J. B., & George, J. F. (2004). Commitment, trust, and social involvement: An exploratory study of antecedents to Web shopper loyalty. Journal of Organizational Computing and Electronic Commerce, 14(4), 243–268. https://doi.org/10.1207/s15327744joce1404_2
  • Törhönen, M., Sjöblom, M., Hassan, L., & Hamari, J. (2019). Fame and fortune, or just fun? A study on why people create content on video platforms. Internet Research, 30(1), 165–190. https://doi.org/10.1108/INTR-06-2018-0270
  • Twitch (2021). Income of Twitch streamers in 2021. https://tw.news.yahoo.com/news/twitch
  • Tsai, H., & Bagozzi, R, National Taipei University (2014). Contribution behavior in virtual communities: Cognitive, emotional, and social influences. MIS Quarterly, 38(1), 143–163. https://doi.org/10.25300/MISQ/2014/38.1.07
  • Xue, J., Liang, X., Xie, T., & Wang, H. (2020). See now, act now: How to interact with customers to enhance social commerce engagement. Information & Management, 57(6), 103324. https://doi.org/10.1016/j.im.2020.103324
  • Wan, J., Lu, Y., Wang, B., & Zhao, L. (2017). How attachment influences users’ willingness to donate to content creators in social media: A socio-technical systems perspective. Information & Management, 54(7), 837–850. https://doi.org/10.1016/j.im.2016.12.007
  • Wulf, K. D., & Odekerken‐Schröder, G. (2001). A critical review of theories underlying relationship marketing in the context of explaining consumer relationships. Journal for the Theory of Social Behaviour, 31(1), 73–101. https://doi.org/10.1111/1468-5914.00147
  • Zaman, M., Anandarajan, M., & Dai, Q. (2010). Experiencing flow with instant messaging and its facilitating role on creative behaviors. Computers in Human Behavior, 26(5), 1009–1018. https://doi.org/10.1016/j.chb.2010.03.001
  • Zhou, Z., Fang, Y., Vogel, D. R., Jin, X. L., & Zhang, X. (2012). Attracted or locked in? Predicting continuance intention in social virtual world services. Journal of Management Information Systems, 29(1), 273–306. https://doi.org/10.2753/MIS0742-1222290108

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.