The influence of moderating factors on consumer usage of OTT platforms

Abstract

This study examines the relationship between technical readiness (TR) and the Unified Theory of Acceptance and Use of Technology (UTAUT) within the framework of Over-the-Top (OTT) media services, particularly Netflix. The study employs the UTAUT model and integrates the TR model's external factors of "optimism," "innovativeness," "inadaptability," and "insecurity" to examine their moderating influences on customer utilisation of Netflix. In 2024, 475 questionnaires were disseminated in this study, of which 453 were considered valid. The study revealed that customer trust in relationships significantly influences user involvement in 'Performance Expectancy' (PE), 'Effort Expectancy' (EE), 'Social Influence' (SI), and 'Facilitating Conditions' (FC). Furthermore, consumers' intention to interact with Netflix's 'Performance Expectancy' (PE), 'Effort Expectancy' (EE), and 'Social Influence' (SI) considerably and positively affects their behaviour. The research employed hierarchical regression analysis to assess the impact of customer willingness to "Intention to Use" on the UTAUT regarding Netflix consumption. The findings indicate that the Trustworthiness Rating of consumers substantially affects the UTAUT dimensions of Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions. Moreover, consumers' inclination to use Netflix is positively influenced by the constructs of Performance Expectancy, Effort Expectancy, and Social Influence. The results demonstrate that consumers' Trustworthiness Rating substantially influences the UTAUT aspects of Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions. Moreover, the constructs of performance expectancy, effort expectancy, and social influence positively affect customers' inclination to utilise Netflix. The results of this study may inform strategic approaches to improve user engagement and satisfaction in the competitive OTT market.

Keywords: {'name': 'Theory of Technology Readiness (TR)'}, {'name': ', Netflix, Technology Acceptance (TAM), Moderating variable, and Over-the-top media services (OTT)'}

Authors & affiliations

Wan-Yu Chu
Affiliation not supplied

Yu-Lung Wu
Affiliation not supplied

Deposited references

Supplied references, not a list of publications citing this article.

DOI: 10.1080/14792779943000116

Al-Sharafi, M. A., Al-Qaysi, N., & Zaid, M. (2023). Understanding user acceptance of mobile applications: A study based on UTAUT. Journal of Business Research, 148, 270-282. https://doi.org/10.1016/j.jbusres.2022.12.015

Ally, M., & Gardiner, M. (2012, January). The moderating influence of device characteristics and usage on user acceptance of smart mobile devices. In ACIS 2012: Location, Location, Location: Proceedings of the 23rd Australasian Conference on Information Systems 2012 (pp. 1-10).

DOI: 10.1057/palgrave.jit.2000125

DOI: 10.1002/9781118619179

DOI: 10.1145/1007965.1007968

DOI: 10.1016/j.jbusres.2021.09.058

Deloitte. (2023). Digital Media Trends: 17th Edition.

DOI: 10.1561/9781680831436

DOI: 10.1177/002224379102800305

DOI: 10.2307/249008

DOI: 10.1287/mnsc.35.8.982

European Commission. (2018). General Data Protection Regulation (GDPR) compliance guidelines. https://www.eugdpr.org/

DOI: 10.1177/002224378101800313

DOI: 10.1108/08876041011040631

DOI: 10.1016/j.tele.2018.09.001

Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th ed.). New York: Macmillan.

DOI: 10.2753/MTP1069-6679190202

Hsu, C.-L., & Lin, J. C.-C. (2022). Technology readiness and consumer acceptance of streaming services. Internet Research.

Johnson, M. (2023). The impact of social media on consumer engagement: A case study of Netflix. Journal of Digital Marketing.

Kim, Y. S., Lee, J. H., & Suh, K. S. (2009). The role of trust in customer loyalty to online services. Journal of Internet Commerce, 8(3), 252-271.

Kumar, A., & Sharma, R. (2023). The future of OTT: Trends and forecasts for 2023-2025. International Journal of Information Management, 65, 102-113.

DOI: 10.1108/02635571311322793

Li, Y., & Wu, J. (2022). The impact of COVID-19 on online streaming services: A global perspective. Journal of Business Research, 138, 123-135.

DOI: 10.2307/25148817

Mansoor, W., & Ali, S. (2023). Effects of mobile data usage on streaming services during the pandemic. Telecommunications Policy, 47(2), 102-116.

Nielsen. (2023). Total audience report: Insights on media consumption trends.

Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.

DOI: 10.1177/109467050024001

Smith, R., & Lee, T. (2023). Big data algorithms in media: Enhancing user experience. Journal of Media Economics.

DOI: 10.2190/ET.38.3.e

Van Raaij, W. F., & van der Wal, T. (2008). The acceptance of electronic banking: A modified technology acceptance model. International Journal of Bank Marketing, 26(6), 410-423. https://doi.org/10.1108/02652320810920164

DOI: 10.2307/30036540

DOI: 10.2307/41410412

DOI: 10.2307/41410412

DOI: 10.1109/IHCI.2012.6481794

DOI: 10.1287/isre.11.4.342.11872

DOI: 10.1111/ijmr.12112

Yusoff, Y., Ismail, H., & Mohamad, N. (2010). The adoption of technology among Malaysian consumers: The role of perceived usefulness and perceived ease of use. International Journal of Business and Management, 5(5), 15-25. https://doi.org/10.5539/ijbm.v5n5p15