Influencing Factors and Models of the Millennial Generation’s Willingness to Use Smart TV
DOI:
https://doi.org/10.54097/hbem.v9i.9242Keywords:
Technology Acceptance Model; Advertisement Avoidance Model; Willingness to Use; Free Mindset; Millennial Generation; Smart TV.Abstract
With young people becoming the main purchase force in the smart TV industry, their user experience of smart TV is highly valued. However, the use rate and preference of the youth for TV are low at present. What is the reason for their pessimistic willingness to use TV? Focusing on the influencing factors of the millennial generation’s willingness to use a smart TV, this paper theoretically based on the technology acceptance model (TAM) and advertisement avoidance model introduces the free mindset, constructs the model, and puts forward research hypotheses, so as to analyze this phenomenon from the perspectives of communication, behavioral science, and social psychology. It is shown that perceived usefulness, perceived ease of use, perceived goal impediment, and perceived advertising clutter are important independent variables that affect millennial willingness to use the smart TV. Consistent with previous research conclusions, perceived usefulness still acts as a key intermediary variable in the TAM model. In addition, the study also found that the free mindset has a significantly positive impact on the willingness to use, but there is no moderating effect in this model.
Downloads
References
All View Cloud. (2023). 2022 Annual Report of Color TV Market in China. Retrieved from 9 May, https:// mp. weixin. qq. com/s/qhLSX_uEfUZA1bSmO6O3NQ.
Perse, E. M. & Ferguson, D. A. (1993). The impact of the newer television technologies on television satisfaction. Journalism Quarterly, 70(4):843-853.
Abrams, J. R. (2010). Asian American television activity: Is it related to out-group vitality?. International Journal of Intercultural Relations, 34(6):541-550.
Ren, T. F. (2007). The research on demand factors influencing the audience’s watching behavior. Shanghai: Master Dissertation of Donghua University.
Zhang, T. D. & Li, D. (2003). The viewing behavior and the viewing mode of Beijingsee. Social Sciences of Beijing, (02), 137-142.
Mares, M. L. & Iv, E. H. W. (2006). In search of the older audience: Adult age differences in television viewing. Journal of Broad casting & Electronic Media, 50(04), 595-614.
Pool, I. D. S. (1983). Technologies of freedom. Cambridge:Belknap Press.
Jiang, Y. (2008). Research on the Chinese network TV audience interactions. Nanjing: Master of Nanjing Normal University.
Liu, Y. (2016). TV transformation and upgrading: Big screen ecology--Based on the Smart TV User Behavior and Media Ecology Theory. TV Research, 317(04), 1130-1140.
Liou, D. K., Hsu, L. C. & Chih, W. H. (2015). Understanding broadband TV users’ continuance intention to use. Industrial Management & Data Systems.
Park, J. H. & Kim, M. K. (2016). Factors influencing the low usage of smart TV services by the terminal buyer sin Korea. Telematics & Informatics, 33(4), 1130-1140.
Horning, M. A. (2017). Interacting with news: Exploring the effects of modality and perceived responsiveness and control on news source credibility and enjoyment among the second screen viewers science direct. Computers in Human Behavior, (73), 273-283.
Guan, C. L., Mo, L. Y. & Peng, R. (2018). Research and optimization of smart TV interaction based on physical and mental characteristics of the elderly. Public Communication of Science & Technology, 10(24), 194-196+135.
Liu, W. (2021). Nursing the old: Problems, current situation and path of smart TV suitable for the old. West China Broadcasting TV, 42(11), 21-23.
Prensky, M. (2001). Digitalnatives and digitalimmigrants I. Onthehorizon, 9(5), 1-6.
Deng, X. X. (2012). Investigation and analysis of network TV use influence factors based on Xi’an college students. Southeast Communication, 92(04), 89-91.
Yu, J. J. (2013). The network television viewing behavior and impact study on female college students in TV 2.0 age. Chongqing: Master Dissertation of Southwest University.
Swidan, A., Al-Shalabi, H., Jwaifell, M. et al. (2013). The intensity and the factors affecting the use of social network sites among the students of Jordanian Universities. International Journal of Computer Science Issues, 10(1), 492-498.
Marketing Sherpa. (2016). Customers at is faction research study: data from 2,400 customers reveals how far companies must got to please (oralienate) customers.
Ivan, L., Nika, G., Cruz, P., Trisha, C. B., Luzaran, J. R., Antonio, E. & Etrata. (2022). Gen Z and TV: An analysis of traditional advertising medium and perception. Millennium Journal of Humanities and Social Sciences, 50-67.
Bondad-Brown, B. A., Rice, R. E. & Pearce, K. E. (2012). Influences on TV viewing and online user-shared video use: Demographics, generations, contextual age, media use, motivations, and audience activity. Journal of Broadcasting & Electronic Media, 56(4),471–493.
Lee, T. K. & Taylor, L. D. (2013). The motives for and consequences of viewing television medical dramas. Health Communication, 29(1),13–22.
Davis, F. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MISQuarte, 13(3), 319-341.
Wu, X. Y. & Jiao, Y. B. (2008). A study of factors affecting customers’ adoption of Internet banking. Nankai Business Review, 11(06), 18-27.
Kuang, W. B., Lv, C. C. & Zhang, H. Y. (2020). The STIP model of new media research. Journal of Renmin University of China, 34(04), 125-134.
Speck, P. S., Eliott, M. T. (1997). Predictors of advertising avoidance in print and broadcast medial. Journal of Advertising, 2613, 61-76.
Yang, W. X. & Su, Y. (1995). Analysis of Zapping in advertisements--Avoiding advertisements. Journal of Intelligence, (4), 51-52.
Kaatz, R. B. (1986). Media Connections in a changing consumer environment. Journal of Advertising Research, 26(2), RC3-RC7.
Kitchen, P. J. (1986). Zipping, zapping and nipping. International Journal of Advertising, 5(2), 343-352.
Cho, C. H. & Cheon, H. J. (2004). Why do people avoid advertising on the Internet. Journal of Advertising, 33(4), 89-97.
Davis, F. (1989). Perceived usefulness,perceived ease of use and user acceptance of information technology. MISQuarte,13(3), 319-341.
Dou, W. (2004). Will Internet users pay for online content? Journal of Advertising Research, 44(4), 349-359.
Chen, Q. W. (2012). Charges of cable digital television service and related policies performance appraisal: A case study of Guangdong province. Guangzhou: Master Dissertation of South China University of Technology.
Kahneman, D. & Tversky, A. (1979). On the interpretation of intuitive probability: A reply to Jona than Cohen. Cognition, 7(4), 409–411.
Shampanier, K., Mazar, N. & Ariely, D. (2007). Zeroasa special price: The true value of free products. Marketing Science, 26(6), 742–757.
Goyanes, M., Demeter, M. & Grado, L. (2020). The culture of free: Construct explication and democratic ramifications for readers willingness to pay for publican fairs news. Journalism, 23(1), 207–223.
Moreno, F. M., Lafuente, J. G., Carre, F. A. & Moreno, S. M. (2017). The characterization of the millennial and their buying behavior. International Journal of Marketing Studies, 9(5), 135–44.
Singal, J. (2017). Snapchat? No, thanks. I’m an old millennial. CNN. Retrieved from May 1 https://www.cnn.com/217/05/01/health/young-old-millennial-partner/index.html.
Mangold, W. G. & Smith, K. T. (2012). Selling to millennial with online reviews. Business Horizons, 55(2), 141–53.
Chi, H. H. (2011). Interactive digital advertising vs.virtual brand community: Exploratory study of user motivation and social media marketing responses in Taiwan. Journal of Interactive Advertising, 12(1), 44–61.
Kelly, L., Kerr, G. & Drennan, J. (2010). Avoidance of advertising in social net working sites: The teenage perspective. Journal of Interactive Advertising, 10(2), 16–27.
Malthouse, E. C., Haenlein, M., Skiera, B., Wege, E. & Zhang, M. (2013). Managing customer relationships in the social media era:Introducing the social CRM house. Journal of Interactive Marketing, 27(4), 270–280.
Hu, Z. M., Cheng, Y. & Cui, H. Y. (2016). What converts online content consumers from free to free: perspective from mental inertia based on value-added experience. Management Review, 28(11), 116-128.
Niemand, T., Mai, R. & Kraus, S. (2019). The zero-price effect in freemium business models: The moderating effects of free mentality and price-quality inference. Psychology & Marketing, 36(8), 773–790.
Milne, G. R. & Gordon, M. E. (1993). Direct mail privacy-effectiveness trade-offs within an implied social contract framework. Journal of Public Policy & Marketing, 12(2), 206-15.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.






