Analysing younger online viewers’ motivation to watch video game live streaming through a positive perspective

Authors

DOI:

https://doi.org/10.58567/jea02020004

Keywords:

Younger online viewer, Video game live streaming, the COVID-19 pandemic, the P-O-D theory, Watching motivation

Abstract

The paper focuses on younger online viewers’ motivation to watch video game live streaming on live streaming platforms. Unlike existing scholars, it analyses younger online viewers’ watching motivation through a positive perspective and draws on the Play-Others-Downtime theory (P-O-D theory) and the motivation theory to establish the research model. By analysing 397 samples based on the variance-based structural equation modelling and partial least squares path modelling (SEM-PLS), the results present that younger viewers’ entertainment, social and leisure purposes positively affect their watching motivation. Control variables (i.e., gender, education background, and income level) demonstrate insignificant effects across the model. Considering the influence of the COVID-19 pandemic, watching video game live streaming is essential entertainment and social activities for younger adults. Future studies should identify the positive impact of video game live streaming and guide younger viewers to participate appropriately in this activity.

References

Alkutbi, S., Alrajawy, I., Nusari, M., Khalifa, G. S., & Abuelhassan, A. E. (2019). Impact of Ease of Use and Usefulness on the Driver Intention to Continue Using Car Navigation Systems in the United Arab Emirates. International Journal of Management and Human Science (IJMHS), 3(1), 1-9. https://ejournal.lucp.net/index.php/ijmhs/article/view/790

Aminu, I. M., & Shariff, M. N. M. (2014). Strategic orientation, access to finance, business environment and SMEs performance in Nigeria: Data screening and preliminary analysis. European Journal of Business and Management, 6(35), 124-132. https://core.ac.uk/reader/234626040

Asghar, M. Z., Arif, S., Iqbal, J., & Seitamaa-Hakkarainen, P. (2022). Social Media Tools for the Development of Pre-Service Health Sciences Researchers during COVID-19 in Pakistan. International journal of environmental research and public health, 19(1), 581. https://doi.org/10.3390/ijerph19010581

Benke, C., Autenrieth, L. K., Asselmann, E., & Pané-Farré, C. A. (2020). Stay-at-home orders due to the COVID-19 pandemic are associated with elevated depression and anxiety in younger, but not older adults: results from a nationwide community sample of adults from Germany. Psychological Medicine, 1-2. https://doi.org/10.1017/S0033291720003438

Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of computer‐mediated Communication, 13(1), 210-230. https://doi.org/10.1111/j.1083-6101.2007.00393.x

Bulo, A. A., & Tumbuan, W. A. (2015). The Effect of Intrinsic and Extrinsic Motivation on Employee Performance at 21cineplex, Manado. Jurnal EMBA: Jurnal Riset Ekonomi, Manajemen, Bisnis dan Akuntansi, 3(3). https://doi.org/10.35794/emba.3.3.2015.9384

Cabeza-Ramírez, L. J., Muñoz-Fernández, G. A., & Santos-Roldán, L. (2021). Video game streaming in young people and teenagers: Uptake, user groups, dangers, and opportunities. Paper presented at the Healthcare. https://doi.org/10.3390/healthcare9020192

Cai, J., Wohn, D. Y., Mittal, A., & Sureshbabu, D. (2018). Utilitarian and hedonic motivations for live streaming shopping. Paper presented at the Proceedings of the 2018 ACM international conference on interactive experiences for TV and online video. https://doi.org/10.1145/3210825.3210837

Chen, C.-Y., & Chang, S.-L. (2019). Moderating effects of information-oriented versus escapism-oriented motivations on the relationship between psychological well-being and problematic use of video game live-streaming services. Journal of behavioral addictions, 8(3), 564-573. https://doi.org/10.1556/2006.8.2019.34

Chen, T., Peng, L., Yang, J., Cong, G., & Li, G. (2021). Evolutionary game of multi-subjects in live streaming and governance strategies based on social preference theory during the COVID-19 pandemic. Mathematics, 9(21), 2743. https://doi.org/10.3390/math9212743

Chin, W. W. (1998). Commentary: Issues and opinion on structural equation modeling. In: JSTOR. https://www.jstor.org/stable/249674

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 an electronic-mail emotion/adoption study. Information systems research, 14(2), 189-217. https://doi.org/10.1287/isre.14.2.189.16018

Dawes, J. (2008). Do data characteristics change according to the number of scale points used? An experiment using 5-point, 7-point and 10-point scales. International journal of market research, 50(1), 61-104. https://doi.org/10.1177/147078530805000106

De Wit, J., Van der Kraan, A., & Theeuwes, J. (2020). Live streams on twitch help viewers cope with difficult periods in life. Frontiers in psychology, 11, 586975. https://doi.org/10.3389/fpsyg.2020.586975

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50. https://doi.org/10.1177/002224378101800313

Gros, D., Wanner, B., Hackenholt, A., Zawadzki, P., & Knautz, K. (2017). World of streaming. Motivation and gratification on Twitch. Paper presented at the International conference on social computing and social media. https://doi.org/10.1007/978-3-319-58559-8_5

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: International version. New Jersey, Pearson. https://doi.org/10.4236/oalib.1102796

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. (2010). Multivariate data analysis (7th editio). Harlow: Pearson Education Limited. https://doi.org/10.4236/oalib.1102796

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis (Vol. 5): Prentice hall Upper Saddle River, NJ. https://doi.org/10.4236/jhrss.2017.53017

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European business review. https://doi.org/10.1108/EBR-11-2018-0203

Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM): Sage publications. https://au.sagepub.com/en-gb/oce/a-primer-on-partial-least-squares-structural-equation-modeling-pls-sem/book244583#preview

Huang, Y., & Zhao, N. (2020). Chinese mental health burden during the COVID-19 pandemic. Asian journal of psychiatry, 51, 102052. https://doi.org/10.1016/j.ajp.2020.102052

iResearch. (2021). 2021 China Game Live Streaming Industry Research Report. Retrieved from https://report.iresearch.cn/report/202108/3829.shtml

Jia, A. L., Rao, Y., & Shen, S. (2021). Analyzing and Predicting User Donations in Social Live Video Streaming. Paper presented at the 2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD). https://doi.org/10.1109/CSCWD49262.2021.9437676

Jibril, A. B., Kwarteng, M. A., Chovancova, M., & Pilik, M. (2019). The impact of social media on consumer-brand loyalty: A mediating role of online based-brand community. Cogent Business & Management, 6(1), 1673640. https://doi.org/10.1080/23311975.2019.1673640

Kang, S. K. (2014). The Dolphin Parent: A Guide to Raising Healthy, Happy, and Self-Motivated Kids: Penguin Canada. https://books.google.com.au/books?hl=en&lr=&id=T1n5AgAAQBAJ&oi=fnd&pg=PT9&dq=Kang,+S.+K.+(2014).+The+Dolphin+Parent:+A+Guide+to+Raising+Healthy,+Happy,+and+Self-Motivated+Kids:+Penguin+Canada.&ots=_nHEFSNwsU&sig=6ZdXK2DpeiRAVErHHvP_Vb4EEqM&redir_esc=y#v=onepage&q&f=false

Kleiber, D. A., Hutchinson, S. L., & Williams, R. (2002). Leisure as a resource in transcending negative life events: Self-protection, self-restoration, and personal transformation. Leisure sciences, 24(2), 219-235. https://doi.org/10.1080/01490400252900167

Kline, R. B. (2011). Principles and practice of structural equation modeling (3. Baskı). New York, NY: Guilford. https://www.researchgate.net/profile/Cahyono-St/publication/361910413_Principles_and_Practice_of_Structural_Equation_Modeling/links/62cc4f0ed7bd92231faa4db1/Principles-and-Practice-of-Structural-Equation-Modeling.pdf

Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration (ijec), 11(4), 1-10. https://doi.org/10.4018/ijec.2015100101

Lee, C. S., & Ma, L. (2012). News sharing in social media: The effect of gratifications and prior experience. Computers in human behavior, 28(2), 331-339. https://doi.org/10.1016/j.chb.2011.10.002

Li, L., & Kang, K. (2022a). Impact of opportunity and capability on e-entrepreneurial motivation: a comparison of urban and rural perspectives. Journal of Entrepreneurship in Emerging Economies(ahead-of-print). https://doi.org/10.1108/JEEE-06-2022-0178

Li, L., & Kang, K. (2022b). Understanding the real-time interaction between middle-aged consumers and online experts based on the COM-B model. Journal of Marketing Analytics, 1-13. https://doi.org/10.1057/s41270-022-00196-1

Li, L., & Kang, K. (2023). Why ethnic minority groups’ online-startups are booming in China’s tight cultural ecosystem? Journal of Entrepreneurship in Emerging Economies, 15(2), 278-300. https://doi.org/10.1108/JEEE-08-2021-0322

Li, L., Kang, K., Feng, Y., & Zhao, A. (2022). Factors affecting online consumers’ cultural presence and cultural immersion experiences in live streaming shopping. Journal of Marketing Analytics, 1-14. https://doi.org/10.1057/s41270-022-00192-5

Li, L., Kang, K., & Sohaib, O. (2021). Investigating factors affecting Chinese tertiary students’ online-startup motivation based on the COM-B behaviour changing theory. Journal of Entrepreneurship in Emerging Economies(ahead-of-print). https://doi.org/10.1108/JEEE-08-2021-0299

Li, L., Kang, K., Zhao, A., & Feng, Y. (2022). The impact of social presence and facilitation factors on online consumers' impulse buying in live shopping–celebrity endorsement as a moderating factor. Information Technology & People(ahead-of-print). https://doi.org/10.1108/ITP-03-2021-0203

Li, R., Lu, Y., Ma, J., & Wang, W. (2021). Examining gifting behavior on live streaming platforms: An identity-based motivation model. Information & Management, 58(6), 103406. https://doi.org/10.1016/j.im.2020.103406

Li, Y., Wang, C., & Liu, J. (2020). A systematic review of literature on user behavior in video game live streaming. International journal of environmental research and public health, 17(9), 3328. https://doi.org/10.3390/ijerph17093328

Lu, B., & Chen, Z. (2021). Live streaming commerce and consumers’ purchase intention: An uncertainty reduction perspective. Information & Management, 58(7), 103509. https://doi.org/10.1016/j.im.2021.103509

Lv, X., Zhang, R., Su, Y., & Yang, Y. (2022). Exploring how live streaming affects immediate buying behavior and continuous watching intention: A multigroup analysis. Journal of Travel & Tourism Marketing, 39(1), 109-135. https://doi.org/10.1080/10548408.2022.2052227

Rowley, J. (2014). Designing and using research questionnaires. Management Research Review. https://doi.org/10.1108/MRR-02-2013-0027

Sarstedt, M., & Cheah, J.-H. (2019). Partial least squares structural equation modeling using SmartPLS: a software review. Journal of Marketing Analytics, 7(3), 196-202. https://doi.org/10.1057/s41270-019-00058-3

Sarstedt, M., Ringle, C. M., Cheah, J.-H., Ting, H., Moisescu, O. I., & Radomir, L. (2020). Structural model robustness checks in PLS-SEM. Tourism Economics, 26(4), 531-554. https://doi.org/10.1177/13548166188239

Seifert, T. (2004). Understanding student motivation. Educational research, 46(2), 137-149. https://doi.org/10.1080/0013188042000222421

Shanahan, L., Steinhoff, A., Bechtiger, L., Murray, A. L., Nivette, A., Hepp, U., . . . Eisner, M. (2022). Emotional distress in young adults during the COVID-19 pandemic: evidence of risk and resilience from a longitudinal cohort study. Psychological Medicine, 52(5), 824-833. https://doi.org/10.1017/S003329172000241X

Singh, S., Singh, N., Kalinić, Z., & Liébana-Cabanillas, F. J. (2021). Assessing determinants influencing continued use of live streaming services: An extended perceived value theory of streaming addiction. Expert Systems with Applications, 168, 114241. https://doi.org/10.1016/j.eswa.2020.114241

Tabachnick, B. G., & Fidell, L. S. (2001). SAS for windows workbook for Tabachnick and Fidell using multivariate statistics: Allyn and Bacon. https://books.google.com.au/books/about/SAS_for_Windows_Workbook_for_Tabachnick.html?id=Bh1uzgEACAAJ&redir_esc=y

Wang, J., Jing, R., Lai, X., Zhang, H., Lyu, Y., Knoll, M. D., & Fang, H. (2020). Acceptance of COVID-19 Vaccination during the COVID-19 Pandemic in China. Vaccines, 8(3), 482. https://doi.org/10.3390/vaccines8030482

Wang, N., Sun, Y., Shen, X.-L., & Zhang, X. (2018). A value-justice model of knowledge integration in wikis: The moderating role of knowledge equivocality. International Journal of Information Management, 43, 64-75. https://doi.org/10.1016/j.ijinfomgt.2018.07.006

Wang, O., Somogyi, S., & Charlebois, S. (2020). Food choice in the e-commerce era: a comparison between business-to-consumer (B2C), online-to-offline (O2O) and new retail. British Food Journal. https://doi.org/10.1108/BFJ-09-2019-0682

Wang, T., Chen, T., Ye, Z., Lu, Y., & Yu, H. (2022). The Comprehensive Comparison of Huya Live and Twitch. Paper presented at the 2022 2nd International Conference on Enterprise Management and Economic Development (ICEMED 2022). https://doi.org/10.2991/aebmr.k.220603.199

Wong, K. K.-K. (2016). Mediation analysis, categorical moderation analysis, and higher-order constructs modeling in Partial Least Squares Structural Equation Modeling (PLS-SEM): A B2B Example using SmartPLS. Marketing Bulletin, 26. http://marketing-bulletin.massey.ac.nz/V26/MB_v26_T1_Wong_2016.pdf

Xu, C., Ryan, S., Prybutok, V., & Wen, C. (2012). It is not for fun: An examination of social network site usage. Information & Management, 49(5), 210-217. https://doi.org/10.1016/j.im.2012.05.001

Xu, X.-Y., Niu, W.-B., Jia, Q.-D., Nthoiwa, L., & Li, L.-W. (2021). Why do viewers engage in video game streaming? The perspective of cognitive emotion theory and the moderation effect of personal characteristics. Sustainability, 13(21), 11990. https://doi.org/10.3390/su132111990

Yin, L. (2022). From Employment Pressure to Entrepreneurial Motivation: An Empirical Analysis of College Students in 14 Universities in China. Frontiers in psychology, 13. https://doi.org/10.3389/fpsyg.2022.924302

Zainol, Z. B., Yahaya, R., & Osman, J. (2018). Application of relationship investment model in predicting student engagement towards HEIs. Journal of Relationship Marketing, 17(1), 71-93. https://doi.org/10.1080/15332667.2018.1440143

Zhang, G., & Hjorth, L. (2019). Live-streaming, games and politics of gender performance: The case of Nüzhubo in China. Convergence, 25(5-6), 807-825. https://doi.org/10.1177/1354856517738160

Zhou, J., Zhou, J., Ding, Y., & Wang, H. (2019). The magic of danmaku: A social interaction perspective of gift sending on live streaming platforms. Electronic Commerce Research and Applications, 34, 100815. https://doi.org/10.1016/j.elerap.2018.11.002

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Published

2023-04-17

How to Cite

Li, L., Kang, K., & Sohaib, O. (2023). Analysing younger online viewers’ motivation to watch video game live streaming through a positive perspective. Journal of Economic Analysis, 2(2), 56–69. https://doi.org/10.58567/jea02020004

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