Online social anxiety and mobile instant messaging adoption and continuance usage intention: How does it relate to social, technical, and mobility factors?

References

• Aguilera, A., Hernandez-Ramos, R., Haro-Ramos, A. Y., Boone, C. E., Luo, T. C., Xu, J., Chakraborty, B., Karr, C., Darrow, S., & Figueroa, C. A. (2021). A text messaging intervention (StayWell at Home) to counteract depression and anxiety during COVID-19 social distancing: Pre-post study. JMIR Mental Health, 8(11), e25298. https://doi.org/10.2196/25298
   PubMed Web of Science ®Google Scholar
• Akdim, K., Cassló, L. V., & Flavián, C. (2022). The role of utilitarian and hedonic aspects in the continuance intention to use social mobile apps. Journal of Retailing and Consumer Services, 66, 102888. https://doi.org/10.1016/j.jretconser.2021.102888
   Web of Science ®Google Scholar
• Baker, R. K., & White, K. M. (2010). Predicting adolescents’ use of social networking sites from an extended theory of planned behaviour perspective. Computers in Human Behavior, 26(6), 1591–17. https://doi.org/10.1016/j.chb.2010.06.006
   Web of Science ®Google Scholar
• Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921
   Web of Science ®Google Scholar
• Bonnette, A., Robinson, A., Dailey, S., Ceballos, N. A., & Howard, K. (2019). Upward social comparisons and posting under the influence: Investigating social media behaviors of us adults with generalized anxiety disorder. Spotlight on Mental Health Research. https://doi.org/10.3583/1sor.mh.bonnette19
   Google Scholar
• Boukhechba, M., Chow, P., Fua, K., Teachman, B. A., & Barnes, L. E. (2018). Predicting social anxiety from global positioning system traces of college students: Feasibility study. JMIR Mental Health, 5(3), e10101. https://doi.org/10.2196/2F10101
   PubMed Web of Science ®Google Scholar
• Burgoon, J. K., & Walther, J. B. (1990). Nonverbal expectancies and the evaluative consequences of violations. Human Communication Research, 17(2), 232–265. https://doi.org/10.1111/j.1468-2958.1990.tb00232.x
   Web of Science ®Google Scholar
• Business Guide, . (2021). LINE Business Guide (Summary). Retrieved 10 August, 2022, from https://www.linebiz.com/sites/default/files/media/jp/download/EN_LINE%20Business%20Guide_202101-06_summary.pdf
   Google Scholar
• Cheng, M.-J., Hung, S.-W., Tsai, -H.-H., & Chen, P.-W. (2016). The adoption intentions of mobile applications. 2016 IEEE/ACIS 15th international conference on computer and information science (ICIS): IEEE, pp. 1–3.
   Google Scholar
• Choi, G., & Chung, H. (2013). Applying the technology acceptance model to social networking sites (sns): Impact of Subjective Norm and Social Capital on the Acceptance of Sns. International Journal of Human-Computer Interaction, 29(10), 619–628. https://doi.org/10.1080/10447318.2012.756333
   Web of Science ®Google Scholar
• Dallal, A. (2022). Most popular messaging apps around the globe. similarweb.com (Updated: May 2022) https://www.similarweb.com/corp/blog/research/market-research/worldwide-messaging-apps/
   Google Scholar
• Daştan, İ., & Gürler, C. (2016). Factors affecting the adoption of mobile payment systems: An empirical analysis. EMAJ: Emerging Markets Journal, 6(1), 17–24. https://doi.org/10.5195/emaj.2016.95
   Google Scholar
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. DOI:10.2307/249008
   Web of Science ®Google Scholar
• Erwin, B. A., Turk, C. L., Heimberg, R. G., Fresco, D. M., & Hantula, D. A. (2004). The Internet: Home to a severe population of individuals with social anxiety disorder? Journal of Anxiety Disorders, 18(5), 629–646. https://doi.org/10.1016/j.janxdis.2003.08.002
   PubMed Web of Science ®Google Scholar
• Foroughi, B., Iranmanesh, M., & Hyun, S. S. (2019). Understanding the determinants of mobile banking continuance usage intention. Journal of Enterprise Information Management, 32(6), 1015–1033. https://doi.org/10.1108/JEIM-10-2018-0237
   Web of Science ®Google Scholar
• Franque, F. B., Oliveira, T., & Tam, C. (2021). Understanding the factors of mobile payment continuance Intention: Empirical Test in an African Context. Heliyon, 7(8), e07807. https://doi.org/10.1016/j.heliyon.2021.e07807
   PubMed Web of Science ®Google Scholar
• Gadhiya, P., & Panchal, N. (2021). Young women’s continuance intentions to use communication and social media apps. Indian Journal of Marketing, 51(3), 41. https://dx.doi.org/10.17010/ijom/2021/v51/i3/158063
   Google Scholar
• Gan, C., & Li, H. (2015). Understanding continuance intention of mobile instant messaging. Industrial Management & Data Systems, 15(4), 646–660. http://dx.doi.org/10.1108/IMDS-11-2014-0331
   Google Scholar
• Gong, X., Lee, M. K. O., Liu, Z., & Zheng, X. (2020). Examining the role of tie strength in users’ continuance intention of second-generation mobile instant messaging services. Information Systems Frontiers, 22(1), 149–170. https://doi.org/10.1007/s10796-018-9852-9
   Web of Science ®Google Scholar
• Good, M. C., & Huhmann, B. A. (2018). Social relationships and social anxiety appeals in direct-to-consumer advertising. Journal of Marketing Communications, 24(4), 393–411. https://doi.org/10.1080/13527266.2018.1432499
   Google Scholar
• Gross, E. F., Juvonen, J., & Gable, S. L. (2002). Internet use and well‐being in adolescence. Journal of Social Issues, 58(1), 75–90. https://psycnet.apa.org/doi/10 .1111/1540-4560.00249
   Web of Science ®Google Scholar
• Gupta, A., Dhiman, N., Yousaf, A., & Arora, N. (2021). Social comparison and continuance intention of smart fitness wearables: An extended expectation confirmation theory perspective. Behaviour & Information Technology, 40(13), 1341–1354. https://doi.org/10.1080/0144929X.2020.1748715
   Web of Science ®Google Scholar
• Hsieh, C.-T. (2007). Mobile commerce: assessing new business opportunities. Communications of the IIMA, 7(1), Article 9. http://scholarworks.lib.csusb.edu/ciima/vol7/iss1/9
   Google Scholar
• Humbani, M., & Wiese, M. (2019). An integrated framework for the adoption and continuance intention to use mobile payment apps. International Journal of Bank Marketing, 37(2), 646–664. https://doi.org/10.1108/IJBM-03-2018-0072
   Web of Science ®Google Scholar
• Hutchins, N., Allen, A., Curran, M., & Kannis-Dymand, L. (2021). Social anxiety and online social interaction. Australian Psychologist, 56(2), 142–153. https://doi.org/10.1080/00050067.2021.1890977
   Web of Science ®Google Scholar
• Hwang, M.-Y., Hong, J.-C., Tai, K.-H., Chen, J.-T., & Gouldthorp, T. (2020). The relationship between the online social anxiety, perceived information overload and fatigue, and job engagement of civil servant line users. Government Information Quarterly, 37(1), 101423. https://doi.org/10.1016/j.giq.2019.101423
   Web of Science ®Google Scholar
• Iqbal, M. (2022). Line revenue and usage statistics (2022). businessofapps.com. https://www.businessofapps.com/data/line-statistics/
   Google Scholar
• Jain, N. K., Kaul, D., & Sanyal, P. (2022). What drives customers towards mobile shopping? An integrative technology continuance theory perspective. Asia Pacific Journal of Marketing and Logistics, 34(5), 922–943. https://doi.org/10.1108/APJML-02-2021-0133
   Web of Science ®Google Scholar
• Jaiswal, D., Kaushal, V., Mohan, A., & Thaichon, P. (2022). Mobile wallets adoption: Pre- and post-adoption dynamics of mobile wallets usage. Marketing Intelligence & Planning, 40(5), 573–588. https://doi.org/10.1108/MIP-12-2021-0466
   Web of Science ®Google Scholar
• Keles, B., McCrae, N., & Grealish, A. (2020). a systematic review: The influence of social media on depression, anxiety and psychological distress in adolescents. International Journal of Adolescence and Youth, 25(1), 79–93. https://doi.org/10.1080/02673843.2019.1590851
   Web of Science ®Google Scholar
• Kerlinger, F. N. (1973). Foundations of behavioral research (2nd) ed.). Rinehart and Winston.
   Google Scholar
• Ku, Y.-C., Chen, R., & Zhang, H. (2013). Why do users continue using social networking sites? An exploratory study of members in the United States and Taiwan. Information & Management, 50(7), 571–581. https://doi.org/10.1016/j.im.2013.07.011
   Web of Science ®Google Scholar
• Lai, I. K. W., & Shi, G. (2015). The impact of privacy concerns on the intention for continued use of an integrated mobile instant messaging and social network platform. International Journal of Mobile Communications, 13(6), 641–669. https://doi.org/10.1504/IJMC.2015.072086
   Web of Science ®Google Scholar
• Latimer, A. E., & Martin Ginis, K. A. (2005). The Importance of Subjective Norms for People Who Care What Others Think of Them. Psychology & Health, 20(1), 53–62. https://doi.org/10.1080/08870440412331300002
   Web of Science ®Google Scholar
• Lee, S. Y., & Jang, K. (2019). Antecedents of impression management motivations on social network sites and their link to social anxiety. Media Psychology, 22(6), 890–904. https://doi.org/10.1080/15213269.2019.1580588
   Web of Science ®Google Scholar
• Liao, C., Palvia, P., & Chen, J.-L. (2009). Information technology adoption behavior life cycle: Toward a technology continuance theory (TCT). International Journal of Information Management, 29(4), 309–320. https://doi.org/10.1016/j.ijinfomgt.2009.03.004
   Web of Science ®Google Scholar
• Lőrincz, L., Koltai, J., Győr, A. F., & Takács, K. (2019). Collapse of an Online Social Network: Burning Social Capital to Create It? Social Networks, 57, 43–53. https://doi.org/10.1016/j.ijinfomgt.2009.03.004
   Web of Science ®Google Scholar
• Lu, J., Liu, C., & Wei, J. (2017). How important are enjoyment and mobility for mobile applications? Journal of Computer Information Systems, 57(1), 1–12. https://doi.org/10.1080/08874417.2016.1181463
   Web of Science ®Google Scholar
• Mallat, N., Rossi, M., Tuunainen, V. K., & Öörni, A. (2009). The impact of use context on mobile services acceptance: The case of mobile ticketing”. Information & Management, 46(3), 190–195. https://doi.org/10.1016/j.im.2008.11.008
   Web of Science ®Google Scholar
• McCord, B., Rodebaugh, T. L., & Levinson, C. A. (2014). Facebook: Social uses and anxiety. Computers in Human Behavior, 34, 23–27. https://doi.org/10.1016/j.chb.2014.01.020
   Web of Science ®Google Scholar
• Nayak, J. K. (2018). Relationship among smartphone usage, addiction, academic performance and the moderating role of gender: A study of higher education students in India. Computers & Education, 123, 164–173. https://doi.org/10.1016/j.compedu.2018.05.007
   Web of Science ®Google Scholar
• Nie, N. H., & Hillygus, L. (2002). Erbring Internet use, interpersonal relations, and sociability: A time diary study. In B. Wellman & C. Haythornthwaite (Eds.), The Internet in everyday life, Wiley-Blackwell (pp. 215–243).
   Google Scholar
• Oghuma, A. P., Libaque-Saenz, C. F., Wong, S. F., & Chang, Y. (2016). An expectation-confirmation model of continuance intention to use mobile instant messaging. Telematics and Informatics, 33(1), 34–47. https://doi.org/10.1016/j.tele.2015.05.006
   Web of Science ®Google Scholar
• Peng, X., Zhao, Y., & Zhu, Q. (2016). Investigating user switching intention for mobile instant messaging application: Taking WeChat as an example. Computers in Human Behavior, 64, 206–216. https://doi.org/10.1016/j.chb.2016.06.054
   Web of Science ®Google Scholar
• Pierce, T. (2009). Social anxiety and technology: Face-to-face communication versus technological communication among teens. Computers in Human Behavior, 25(6), 1367–1372. https://doi.org/10.1016/j.chb.2009.06.003
   Web of Science ®Google Scholar
• Prizant-Passal, S., Shechner, T., & Aderka, I. M. (2016). Social anxiety and internet use – A meta-analysis: What do we know? What are we missing? Computers in Human Behavior, 62, 221–229. https://doi.org/10.1016/j.chb.2016.04.003
   Web of Science ®Google Scholar
• Rahi, S., Khan, M. M., & Alghizzawi, M. (2021). Extension of technology continuance theory (TCT) with task technology fit (TTF) in the context of Internet banking user continuance intention. International Journal of Quality & Reliability Management, 38(4), 986–1004. https://doi.org/10.1108/IJQRM-03-2020-0074
   Web of Science ®Google Scholar
• Schlenker, B. R., & Leary, M. R. (1982). Social anxiety and self-presentation: A conceptualization model. Psychological Bulletin, 92(3), 641–669. https://doi.org/10.1037/0033-2909.92.3.641
   PubMed Web of Science ®Google Scholar
• Shalom, J. G., Israeli, H., Markovitzky, O., & Lipsitz, J. D. (2015). Social Anxiety and Physiological Arousal During Computer Mediated Vs. Face to Face Communication. In Computers in Human Behavior, 44, 202–208. https://doi.org/10.1016/j.chb.2014.11.056
   Google Scholar
• Sheer, V. (2011). “Teenagers’ use of msn features, discussion topics, and online friendship development: The impact of media richness and communication control. Communication Quarterly, 59(1), 82–103. https://doi.org/10.1080/01463373.2010.525702
   Google Scholar
• Spencer, D. (2021). Time to ban LINE over China links? Taiwan News. taiwannews.com. https://www.taiwannews.com.tw/en/news/4166349
   Google Scholar
• Statista Research Development. (2021). Global mobile app three month user retention and churn 2018. Retrieved October 26, 2021, from https://www.statista.com/statistics/384224/monthly-app-launches-churn/
   Google Scholar
• Sun, Y., & Wang, S. (2019). Understanding consumers’ intentions to purchase green products in the social media marketing context. Asia Pacific Journal of Marketing and Logistics, 32(4), 860–878. https://doi.org/10.1108/APJML-03-2019-0178
   Web of Science ®Google Scholar
• Tam, C., Santos, D., & Oliveira, T. (2020). Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Inf Syst Front, 22(1), 243–257. https://doi.org/10.1007/s10796-018-9864-5
   Web of Science ®Google Scholar
• Tang, Y., & Hew, K. F. (2022). Effects of using mobile instant messaging on student behavioral, emotional, and cognitive engagement: A quasi-experimental study. International Journal of Educational Technology in Higher Education, 19(3), 2022. https://doi.org/10.1186/s41239-021-00306-6
   Google Scholar
• Trevino, L. K., & Webster, J. (1992). Flow in computer-mediated communication: electronic mail and voice mail evaluation and impacts. Communication Research, 19(5), 539–573. https://doi.org/10.1177/009365092019005001
   Web of Science ®Google Scholar
• 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. https://psycnet.apa.org/doi/10 .2307/30036540
   Web of Science ®Google Scholar
• Walther, J. B. (1996). Computer-Mediated Communication: Impersonal, Interpersonal, and Hyperpersonal Interaction. Communication Research, 23(1), 3–43. https://doi.org/10.1177/009365096023001001
   Web of Science ®Google Scholar
• Walther, J. B. (2007). Selective self-presentation in computer-mediated communication: Hyperpersonal dimensions of technology, language, and cognition. Computers in Human Behavior, 23(5), 2538–2557. https://doi.org/10.1016/j.chb.2006.05.002
   Web of Science ®Google Scholar
• Wang, X., & Qian, Y. (2015). Examining the determinants of users’ continuance intention in the context of mobile instant messaging: The case of wechat. 2015 International conference and workshop on computing and communication (IEMCON), pp. 1–9, https://doi.org/10.1109/IEMCON.2015.7344464.
   Google Scholar
• Wang, C., Teo, T. S., & Liu, L. (2020). Perceived value and continuance intention in mobile government service in China. Telematics and Informatics, 48, 101348. doi:10.1109/IEMCON.2015.7344464
   Web of Science ®Google Scholar
• Weidman, A. C., Fernandez, K. C., Levinson, C. A., Augustine, A. A., Larsen, R. J., & Rodebaugh, T. L. (2012). Compensatory internet use among individuals higher in social anxiety and its implications for well-being. Personality and Individual Differences, 53(3), 191–195. doi:10.1016/j.paid.2012.03.003
   PubMed Web of Science ®Google Scholar
• Weng, G. S., Zailani, S., Iranmanesh, M., & Hyun, S. S. (2017). Mobile taxi booking application service’s continuance usage intention by users. Transportation Research Part D: Transport and Environment, 57, 207–216. https://doi.org/10.1016/j.trd.2017.07.023
   Web of Science ®Google Scholar
• Westland, J. C., Hao, J. X., Xiao, X., & Shan, S. (2016). Substitutes, complements and network effects in instant messaging services. Networks and Spatial Economics, 16(2), 525–543. https://doi.org/10.1007/s11067-015-9287-5
   Web of Science ®Google Scholar
• Wixom, B., & Watson, H. (2001). An empirical investigation of the factors affecting data warehousing success. MIS Quarterly, 25(1), 17–29. https://doi.org/10.2307/3250957
   Web of Science ®Google Scholar
• Yang, K., & Jolly, L. D. (2009). The effects of consumer perceived value and subjective norm on mobile data service adoption between American and Korean consumers. Journal of Retailing and Consumer Services, 16(6), 502–508. https://doi.org/10.1016/j.jretconser.2009.08.005
   Google Scholar
• Yen, Y.-S., & Wu, F.-S. (2016). Predicting the adoption of mobile financial services: The impacts of perceived mobility and personal habit. Computers in Human Behavior, 65, 31–42. https://doi.org/10.1016/j.chb.2016.08.017
   Web of Science ®Google Scholar
• Yen, J.-Y., Yen, C.-F., Chen, C.-S., Wang, P.-W., Chang, Y.-H., & Ko, C.-H. (2012). Social anxiety in online and real-life interaction and their associated factors. Cyberpsychology, Behavior and Social Networking, 15(1), 7–12. https://doi.org/10.1089/cyber.2011.0015
   PubMed Web of Science ®Google Scholar
• Yoon, C., Jeong, C., & Rolland, E. (2015). Understanding individual adoption of mobile instant messaging: A multiple perspectives approach. Information Technology Management, 16(2), 139–151. https://doi.org/10.1007/s10799-014-0202-4
   Web of Science ®Google Scholar
• Zhou, T., & Lu, Y. (2011). Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Computers in Human Behavior, 27(2), 883–889. https://doi.org/10.1016/j.chb.2010.11.013
   Web of Science ®Google Scholar