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ORIGINAL RESEARCH

Enabling and Inhibiting Factors of the Continuous Use of Mobile Short Video APP: Satisfaction and Fatigue as Mediating Variables Respectively

ORCID Icon, ORCID Icon, &
Pages 3001-3017 | Received 22 Mar 2023, Accepted 30 Jul 2023, Published online: 05 Aug 2023

References

  • FORWARD-THE ECONOMIST. The panorama of China’s short video industry in 2022. Available from: https://www.qianzhan.com/analyst/detail/220/211012-ebcf4a51.html. Accessed October 12, 2021.
  • Center CINIC. The 49th statistical report on internet development in China. Available from: http://www.cnnic.cn/n4/2022/0401/c88-1131.html. Accessed February 25, 2021.
  • Ant-Group. China Household wealth Index survey report. Available from: https://www.fxbaogao.com/pdf?id=3125527. Accessed April 15, 2022.
  • Securities T. Monthly data tracking of short videos in January. Available from: https://www.fxbaogao.com/pdf?id=3036838. Accessed February 24, 2022.
  • Cheng X, Liu J, Dale C. Understanding the Characteristics of Internet Short Video Sharing: a YouTube-Based Measurement Study. IEEE Trans Multimedia. 2013;15(5):1184–1194. doi:10.1109/tmm.2013.2265531
  • Gomez L, Bernabe K, Alvarado Y, Meléndez L. Snapchat as an influential tool for marketing communication: an exploratory analysis of brands usage: an Abstract. Back to the future: using marketing basics to provide customer value. Developments in Marketing Science: Proceedings of the Academy of Marketing Science; 2018:365–366.
  • Omar B, Dequan W. Watch, share or create: the influence of personality traits and user motivation on TikTok mobile video usage. Intern J Interact Mob Technol. 2020;14(04). doi:10.3991/ijim.v14i04.12429
  • CSM. Short video user value research report. Available from: http://www.199it.com/archives/1332103.html. Accessed October 27, 2021.
  • Sullivan YW, Koh CE. Social media enablers and inhibitors: understanding their relationships in a social networking site context. Int J Inf Manage. 2019;49:170–189. doi:10.1016/j.ijinfomgt.2019.03.014
  • Bernstein E. How Facebook ruins friendships. TecTrends. 2009;25:1–9.
  • Epstein S. Integration of the cognitive and the psychodynamic unconscious. Am Psychol. 1994;49(8):709–724. doi:10.1037/0003-066X.49.8.709
  • Epstein S, Pacini R, V D-R, H H. Individual Differences in Intuitive – experiential and Analytical – rational Thinking styles. J Pers Soc Psychol. 1996;71(2):390. doi:10.1037/0022-3514.71.2.390
  • Huang J, Chen R, Wang X. Factors influencing intention to forward short Internet videos. Soc Behav Personal. 2012;40(1):5–14. doi:10.2224/sbp.2012.40.1.5
  • Zhang X, Wu Y, Liu S. Analysis of influencing factors on browsing and creating behaviors of mobile short video users. Libr Inform Serv. 2019;63:103–115. doi:10.13266/j.issn.0252-3116.2019.06.013
  • Tian X, Bi X, Chen H. How short-form video features influence addiction behavior? Empirical research from the opponent process theory perspective. Inform Technol Peopl. 2022;36(1):387–408. doi:10.1108/itp-04-2020-0186
  • Zhang X, Wu Y, Liu S. Exploring short-form video application addiction: socio-technical and attachment perspectives. Telemat Inform. 2019;42. doi:10.1016/j.tele.2019.101243
  • Liang X, Tao X, Wang Y. Impact analysis of short video on users behavior: users behavior factors of short video evidence from users data of Tik Tok. Presented at: ICEBA 2021: 2021 7th International Conference on E-Business and Applications; 2021.
  • Lee EG, Yu SK. The effect of short video uses on viewing behaviors. Kor J Broadc Telecomm St. 2018;32:65–102.
  • Ye DY, Cho DM. A study on the influence factors of complex user loyalty of short video platform - taking Chinese tiktok users as an example. Kor Soc Sci Art. 2021;39(3):269–288. doi:10.17548/ksaf.2021.06.30.269
  • Chong P. The impact of user perception factors and satisfaction on users’ continuance intention to use mobile short video applications: based on Improved TAM model. Presented at: ICCIR 2021: 2021 International Conference on Control and Intelligent Robotics; 2021.
  • Ren J, Yang J, Zhu M, Majeed S. Relationship between consumer participation behaviors and consumer stickiness on mobile short video social platform under the development of ICT: based on value co-creation theory perspective. Inf Technol Dev. 2021;27(4):697–717. doi:10.1080/02681102.2021.1933882
  • Shao J, Lee S-K. The effect of Chinese Adolescents’ motivation to use Tiktok on satisfaction and continuous use intention. J Conv Cult Technol. 2020;6:107–115. doi:10.17703/JCCT.2020.6.2.107
  • Huang X, Tan L. Research on influencing factors of college students’ willingness to use mobile short video app continuously. Mod Mark. 2020;46:121–125.
  • Meng KS, Leung L. Factors influencing TikTok engagement behaviors in China: an examination of gratifications sought, narcissism, and the Big Five personality traits. Telecommun Policy. 2021;45(7):102172.
  • Mou X, Xu F, Du JT. Examining the factors influencing college students’ continuance intention to use short-form video APP. ASLIB J Inf Manag. 2021;73(6):992–1013. doi:10.1108/ajim-03-2021-0080
  • Song S, Zhao YC, Yao X, Ba Z, Zhu Q. Short video apps as a health information source: an investigation of affordances, user experience and users’ intention to continue the use of TikTok. Int Res. 2021;31(6):2120–2142. doi:10.1108/intr-10-2020-0593
  • Ma X, Sun Y, Guo X, K-h L, Vogel D. Understanding users’ negative responses to recommendation algorithms in short-video platforms: a perspective based on the Stressor-Strain-Outcome (SSO) framework. Electron Mark. 2021;32(1):41–58. doi:10.1007/s12525-021-00488-x
  • Cuesta-Valiño P, Gutiérrez-Rodríguez P, Durán-álamo P. Why do people return to video platforms? Millennials and centennials on TikTok. Media Commun-Lisbon. 2022;10(1):198–207.
  • Yang M, Hu S, Kpandika BE, Liu L. Effects of social attachment on social media continuous usage intention: the mediating role of affective commitment. Hum Syst Manag. 2021;40(4):619–631. doi:10.3233/hsm-201057
  • Zhang M, Long B, Shao X, Liu Y, Zhang Y. Formation mechanism of short video users’ continuance intention and its governance prospects——from the perspective of pseudo-companionship situation. J Mod Inform. 2021;41:49–59. doi:10/3969/j.issn.1008-1821.2021.07.005
  • Tian X, Xinhua B, Yang Y, Wang L. Research on the influencing factors of the continuous participation of government short video users. J Intell. 2022;41:144–151. doi:10.3969/j.issn.1002-1965.2022.04.021
  • Yin G, Cheng X, Zhu L. Understanding continuance usage of social networking services: a theoretical model and empirical study of the Chinese context. Presented at: International Conference on Information Systems 2011; 2011:3500–3512.
  • Kim B. Understanding antecedents of continuance intention in social-networking services. Cyberpsychol Behav Soc Netw. 2011;14(4):199–205. doi:10.1089/cyber.2010.0009
  • Lin X, Featherman M, Sarker S. Understanding factors affecting users’ social networking site continuance: a gender difference perspective. Inf Manag. 2017;54(3):383–395. doi:10.1016/j.im.2016.09.004
  • Bhattacherjee A. Understanding information systems continuance: an expectation-confirmation model. MIS Q. 2001;25(3):352–370. doi:10.2307/3250921
  • Sweller J. Cognitive load during problem solving: effects on learning. Cogn Sci. 1988;12(2):257–285. doi:10.1016/0364-0213(88)90023-7
  • Cenfetelli R. Inhibitors and enablers as dual factor concepts in technology usage. J Assoc Inf Syst. 2004;5(11):472–492. doi:10.17705/1jais.00059
  • Lin H, Fan W, Chau PY. Determinants of users’ continuance of social networking sites: a self-regulation perspective. Inf Manag. 2014;51(5):595–603. doi:10.1016/0364-0213(88)90023-7
  • Chiu CM, Chiu CS, Chang HC. Examining the integrated influence of fairness and quality on learners’ satisfaction and Web-based learning continuance intention. Inform Syst J. 2007;17(3):271–287. doi:10.1111/j.1365-2575.2007.00238.x
  • Ravindran T, Yeow Kuan AC, Hoe Lian DG. Antecedents and effects of social network fatigue. J Assoc Inf Sci Technol. 2014;65(11):2306–2320. doi:10.1002/asi.23122
  • Maier C, Laumer S, Weinert C, Weitzel T. The effects of technostress and switching stress on discontinued use of social networking services: a study of Facebook use. Inform Syst J. 2015;25(3):275–308. doi:10.1111/isj.12068
  • Zhang S, Zhao L, Lu Y, Yang J. Do you get tired of socializing? An empirical explanation of discontinuous usage behaviour in social network services. Inform Manag. 2016;53(7):904–914. doi:10.1016/j.im.2016.03.006
  • Bhattacherjee A, Perols J, Sanford C. Information technology continuance: a theoretic extension and empirical test. J Comput Inform Syst. 2008;49(1):17–26. doi:10.1080/08874417.2008.11645302
  • Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989. doi:10.2307/249008
  • Mouakket S. Factors influencing continuance intention to use social network sites: the Facebook case. Comput Human Behav. 2015;53:102–110. doi:10.1016/j.chb.2015.06.045
  • Kim B. An empirical investigation of mobile data service continuance: incorporating the theory of planned behavior into the expectation–confirmation model. Expert Syst Appl. 2010;37(10):7033–7039. doi:10.1016/j.eswa.2010.03.015
  • Liang X, Tao X, Wang Y. Impact analysis of short video on users behavior: users behavior factors of short video evidence from users data of Tik Tok. Presented at: ACM International Conference Proceeding Series; 2021.
  • Davis FD, Bagozzi RP, Warshaw PR. Extrinsic and intrinsic motivation to use computers in the workplace. J Appl Soc Psychol. 1992;22:1111–1132. doi:10.1111/j.1559-1816.1992.tb00945.x
  • Wang Y, Meister DB, Gray PH. Social influence and knowledge management systems use_ evidence from panel data. MIS Q. 2013;37(1):299–313. doi:10.25300/MISQ/2013/37.1.13
  • Zhou T, Li H. Understanding mobile SNS continuance usage in China from the perspectives of social influence and privacy concern. Comput Human Behav. 2014;37:283–289. doi:10.1016/j.chb.2014.05.008
  • Karr-Wisniewski P, Lu Y. When more is too much: operationalizing technology overload and exploring its impact on knowledge worker productivity. Comput Human Behav. 2010;26(5):1061–1072. doi:10.1016/j.chb.2010.03.008
  • Dunbar RIM. Neocortex size as a constraint on group size in primates. J Hum Evol. 1992;22:469–493. doi:10.1016/0047-2484(92)90081-J
  • LaRose R, Connolly R, Lee H, Li K, Hales KD. Connection overload? A cross cultural study of the consequences of social media connection. Inform Sys Manag. 2014;31(1):59–73. doi:10.1080/10580530.2014.854097
  • Maier C, Laumer S, Eckhardt A, Weitzel T. Giving too much social support: social overload on social networking sites. Eur J Inf Syst. 2014;24(5):447–464. doi:10.1057/ejis.2014.3
  • Lee AR, Son S-M, Kim KK. Information and communication technology overload and social networking service fatigue: a stress perspective. Comput Human Behav. 2016;55:51–61. doi:10.1016/j.chb.2015.08.011
  • Zhang S, Zhao L, Lu Y, Yang J. Get tired of socializing as social animal? An empirical explanation on discontinuous usage behavior in social network services; 2015. Available from: http://aisel.aisnet.org/pacis2015/125. Accessed August 2, 2023.
  • Eppler MJ, Mengis J. The concept of information overload_ a review of literature from organization science, accounting, marketing, MIS, and related disciplines. Inform Soc. 2004;20:325–344. doi:10.1080/01972240490507974
  • Angela E, Anne M. The problem of information overload in business organisations_ a review of the literature. Int J Inf Manage. 2000;20:17–28. doi:10.1016/S0268-4012(99)00051-1
  • Dawei Z, Yanxin C, Min W. expectation and confirmation: a preliminary study on the influencing factors of sustainable use of short video platforms——based on SEM and fsQCA. Mod Commun. 2020;42(8):133–140.
  • Mou XB, Xu F, Du JT. Explaining students’ continuance intention to use Mobile web 2.0 learning and their perceived learning: an integrated approach. J Educ Comput Res. 2020;57(8):1956–2005. doi:10.1177/0735633118805211
  • Bhattacherjee A. An empirical analysis of the antecedents of electronic commerce service continuance. Decis Support Syst. 2001;32:201–214. doi:10.1016/S0167-9236(01)00111-7
  • Lin CS, Wu S, Tsai RJ. Integrating perceived playfulness into expectation-confirmation model for web portal context. Inform Manag. 2005;42(5):683–693. doi:10.1016/j.im.2004.04.003
  • Moon JW, Kim YG. Extending the TAM for a World-Wide-Web context. Inform Manag. 2001;38:217–230. doi:10.1016/S0378-7206(00)00061-6
  • Bandura A. Social Foundations of Thought and Action. NJ: Englewood Cliffs; 1986:23–28.
  • Viswanath Venkatesh MG, Morris GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Q. 2003;27:425–478. doi:10.2307/30036540
  • Chen YC, Shang RA, Kao CY. The effects of information overload on consumers’ subjective state towards buying decision in the internet shopping environment. Electron Commer Res Appl. 2009;8(1):48–58. doi:10.1016/j.elerap.2008.09.001
  • Lin WS, Wang CH. Antecedences to continued intentions of adopting e-learning system in blended learning instruction: a contingency framework based on models of information system success and task-technology fit. Comput Edu. 2012;58(1):88–99. doi:10.1016/j.compedu.2011.07.008
  • Ayyagari R, Grover V, Purvis R. Technostress_ technological antecedents and implications. MIS Q. 2011;35(4):831–858.
  • Moez L, Hirt SG, Cheung CMK. How habit limits the predictive power of intention: the case of information systems continuance. MIS Q. 2007;31:705–737. doi:10.2307/25148817
  • Podsakoff P, MacKenzie S, Lee J, Podsakoff N. Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol. 2003;88:879–903. doi:10.1037/0021-9010.88.5.879
  • Hair JF, Hult GTM, Ringle CM, Sarstedt M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2 ed. Sage; 2017.
  • Hasan M, Amin M, Moon Z, Afrin F. Role of environmental sustainability, psychological and managerial supports for determining bankers’ green banking usage behavior: an integrated framework. Psychol Res Behav Manag. 2022;15:3751–3773. doi:10.2147/PRBM.S377682
  • Fornell C, Larcker DF. Structural equation models with unobservable variables and measurement error: algebra and statistics. J Mark Res. 1981;18(3):382. doi:10.2307/3150980
  • Bentler PM, Bonett DG. Significance tests and goodness of fit in the analysis of covariance structures. Psychol Bull. 1980;88:599–606. doi:10.1037/0033-2909.107.2.238
  • Baron R, Kenny D. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51(6):1173–1182.
  • Cenfetelli RT, Schwarz A. Identifying and testing the inhibitors of technology usage intentions. Inform Syst Res. 2011;22(4):808–823. doi:10.1287/isre.1100.0295
  • Dalvi-Esfahani M, Wai Leong L, Ibrahim O, Nilashi M. Explaining students’ continuance intention to use mobile web 2.0 learning and their perceived learning: an integrated approach. J Edu Com Res. 2018;57(8):1956–2005. doi:10.1177/0735633118805211
  • Thong JYL, Hong S-J, Tam KY. The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. Int J Hum Comput Stud. 2006;64(9):799–810. doi:10.1016/j.ijhcs.2006.05.001
  • Zhou T, Lu Y. Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Comput Human Behav. 2011;27(2):883–889. doi:10.1016/j.chb.2010.11.013
  • Yoon C, Rolland E. Understanding Continuance Use in Social Networking Services. J Comput Inform Syst. 2015;55(2):1–8. doi:10.1080/08874417.2015.11645751
  • Chen CP, Lai HM, Ho CY. Why do teachers continue to use teaching blogs? The roles of perceived voluntariness and habit. Comput Edu. 2015;82:236–249. doi:10.1016/j.compedu.2014.11.017
  • Gefen D. TAM or just plain habit_ a look at experienced online shoppers. J Organ End User Comput. 2003;15:1–13. doi:10.4018/joeuc.2003070101
  • Evans JS, Stanovich KE. Dual-process theories of higher cognition: advancing the debate. Perspect Psychol Sci. 2013;8(3):223–241. doi:10.1177/1745691612460685
  • Bagozzi RP. The self-regulation of attitudes, intentions, and behavior. Soc Psychol Q. 1992;55:178–204. doi:10.2307/2786945
  • Alison A, Debra H, Helen R. A decade of neglect: reflecting on gender and IS. New Technol Work Employ. 2004;19:222–240. doi:10.1111/j.1468-005X.2004.00139.x