Service-Led Model for the Activation of Smart TV: Case Study in Korea

Insu Cho, Jong H. Lee, Young H. Kwak


Purpose: This study explores the characteristics of STV service to empirically examine effects of the services on adoption and usage of STV to lead sustained growth of the STV industry.

Methodology/Approach: This study employs structural equation modeling as a quantitative approach, to examine causal relationships between service characteristics and user intentions. The survey collects 212 data only from actual users of STV, who have experienced STV functions or services, in South Korea.

Findings: The results of service-oriented model based on extended Technology Acceptance Model (TAM) indicate that ‘interactivity’, ‘content quality’, and ‘simplicity’ as service characteristics influence intention to use STV.

Research Limitation/implication: First, the STV industry should establish a distribution structure that generates sufficient profits for content providers as done in Smartphone market. Second, Services of STV should be provided to allow two-way communication and to allow users to engage in active interactions with other users.

Originality/Value of paper: This study makes contributions to research on both new products and service adoption by providing richer explanations of the mechanisms acting on the actual use of STV. Given that STV is considered a key appliance for the next generation of social media and smart appliance, our findings offer new directions on how to realize high quality services in the STV industry.


Abroud, A., Choong, Y.V., Muthaiyah, S. and Fie, D.Y.G., 2015. Adopting e-finance: decomposing the technology acceptance model for investors. Service Business, [e-journal] 9(1), pp.161-182.

Ajzen, I., 1991. The Theory of Planned Behavior. Organizational Behavior and Decision Processes, [e-journal] 50(2), pp.179-211.

Al-Jabri, I.M. and Sohail, M.S., 2012. Mobile banking adoption: Application of diffusion of innovation theory. Journal of Electronic Commerce Research, 13(4), pp.379-391.

Armstrong, J.S. and Overton, T.S., 1977. Estimating nonresponse bias in mail surveys. Journal of marketing research, 14, pp.396-402.

Bae, Y. and Chang, H., 2012. Adoption of smart TVs: a Bayesian network approach. Industrial Management & Data Systems, 112(6), pp.891-910.

Barclay, D., Higgins, C. and Thompson, R., 1995. The partial least squares (PLS) approach to causal modeling: personal computer adoption and use as an illustration. Technology Studies, 2(2), pp.285-309.

Bere, A., 2014. Exploring determinants for mobile learning user acceptance and use: An application of UTAUT. ITNG 2014, Proceedings of the 11th International Conference on Information Technology: New Generations. Las Vegas, NV, USA, 07-09 April 2014. Washington, DC, USA: IEEE Computer Society. pp.84-90.

Briel, R., 2012. Philips launches new smart TV experience. Broadband TV News, [online]. 27 February 2012. Available at: < > [Accessed 09 October 2015].

Cesar, P. and Chorianopoulos, K., 2009. The evolution of TV systems, content, and users toward interactivity. Foundations and Trends in Human-Computer Interaction, [e-journal] 2(4), pp.373-395.

Cheng, Y.-H. and Yeh, Y.-J., 2011. Exploring radio frequency identification technology’s application in international distribution centers and adoption rate forecasting. Technological Forecasting and Social Change, [e-journal] 78(4), pp.661-673.

Cheong, J.H. and Park, M.C., 2005. Mobile internet acceptance in Korea. Internet Research, 15(2), pp.125-140.

Chin, W.W., Marcolin, B.L. and 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, [e-journal] 14(2), pp.189-217.

Davis, F.D., 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, [e-journal] 13(3), pp.319-339.

Delone, W.H. and McLean, E.R., 1992. Information systems success: the quest for the dependent variable. Information Systems Research, [e-journal] 3(1), pp.60-95.

Fornell, C. and Larcker, D.F., 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, [e-journal] 18(1), pp.39-50.

Gao, Y., Li, H. and Luo, Y., 2015. An empirical study of wearable technology acceptance in healthcare. Industrial Management & Data Systems, [e-journal] 115(9), pp.1704-1723. 10.1108/IMDS-03-2015-0087.

Grobart, S., 2013. Smart TV Sales Don't Mean Smart TV Use. Bloomberg, [online] 03 May 2013. Available at: < > [Accessed 26 May 2016].

Ha, I., Yoon, Y. and Choi, M., 2007. Determinants of adoption of mobile games under mobile broadband wireless access environment. Information & Management, [e-journal] 44(3), pp.276-286.

Henseler, J., Ringle, C.M. and Sinkovics, R.R., 2009. The use of partial least squares path modeling in international marketing. New challenges to international marketing, 20, pp.277-319.

Hodgkins, K., 2011. Nielsen/Yahoo: 86% of mobile users fire up their phone while watching TV. IntoMobile, [online] 29 January 2011. Available at: < > [Accessed 26 May 2013].

Hoelzel, M., 2014. Smart TVs Are On Pace To Take Over The Entire TV Market. BusinessInsider, [online] 26 July 2014. Available at: < > [Accessed 30 May 2015].

Hong, W., Chan, F.K., Thong, J.Y., Chasalow, L.C. and Dhillon, G., 2013. A framework and guidelines for context-specific theorizing in information systems research. Information Systems Research, [e-journal] 25, pp.111-136.

Kim, B. and Oh, J., 2011. The difference of determinants of acceptance and continuance of mobile data services: A value perspective. Expert Systems with Applications, [e-journal] 38(3), pp.1798-1804.

Kim, K., Ahn, C. and Hong, J., 2010. Research of Social TV service technology based on smart TV platform in next generation infrastructure. ICCIT (Computer Sciences and Convergence Information Technology), 5th International Conference on Computer Sciences and Convergence Information Technology. Seoul, South Korea, 30 November - 02 December 2010. IEEE.

Kim, M.-W., Kim, E.J., Song, W.M., Song, S.Y., Khil and A.R., 2012. Efficient recommendation for smart TV contents. In: S. Srinivasa and V. Bhatnaga, eds. 2012. Big Data Analytics. Berlin: Springer. pp.158-167.

Lee, M.K., Cheung, C.M. and Chen, Z., 2007. Understanding user acceptance of multimedia messaging services: An empirical study. Journal of the Association for Information Science and Technology, [e-journal] 58(13), pp.2066-2077.

Lin, J.Ch.-Ch. and Lu, H., 2000. Towards an understanding of the behavioural intention to use a web site. International Journal of Information Management, [e-journal] 20(3), pp.197-208.

Lucia-Palacios, L., Përez-Lõpez, R. and Polo-Redondo, Y., 2016. Enemies of cloud services usage: inertia and switching costs. Service Business, [e-journal] 10(2), pp.447-467.

Mallat, N., 2007. Exploring consumer adoption of mobile payments – A qualitative study. The Journal of Strategic Information Systems, [e-journal] 16(4), pp.413-432.

Martïnez-Torres, M., Dïaz-Fernãndez, M., Toral, S. and Barrero, F., 2015. The moderating role of prior experience in technological acceptance models for ubiquitous computing services in urban environments. Technological Forecasting and Social Change, [e-journal] 91, pp.146-160.

Murschetz, P. and Evens, T., 2013. Smart TV in Germany: how does convergence impact market structure industry and business model venturing in digital television broadcasting?. 6th Conference of the International Media Management Academic Association. Lisabon, Spain. pp.1-31.

Park, J.-H. and Kim, M.K., 2016. Factors influencing the low usage of smart TV services by the terminal buyers in Korea. Telematics and Informatics, [e-journal] 33(4), pp.1130-1140.

Podsakoff, P.M., Mackenzie, S.B., Lee, J.Y. and Podsakoff, N.P., 2003. Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, [e-journal] 88(5), pp.879.

Premkumar, G. and Roberts, M., 1999. Adoption of new information technologies in rural small businesses. Omega, [e-journal] 27(4), pp.467-484.

Shang, R.A., Chen, Y.C. and Shen, L., 2005. Extrinsic versus intrinsic motivations for consumers to shop on-line. Information & Management, [e-journal] 42(3), pp.401-413.

Shin, D.H., 2009. An empirical investigation of a modified technology acceptance model of IPTV. Behaviour & Information Technology, [e-journal] 28(4), pp.361-372.

Shin, D.H., Hwang, Y. and Choo, H., 2013. Smart TV: are they really smart in interacting with people? Understanding the interactivity of Korean Smart TV. Behaviour & Information Technology, [e-journal] 32(2), pp.156-172.

Sonnenwald, D.H., Maglaughlin, K.L. and Whitton, M.C., 2001. Using innovation diffusion theory to guide collaboration technology evaluation: Work in progress. WET ICE, Proceedings Tenth IEEE International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises. Cambridge, MA, USA, 20-22 June 2001. IEEE. pp.114-119.

Tsai, P.H. and Chang, S.C., 2013. Comparing the Apple iPad and non-Apple camp tablet PCs: A multicriteria decision analysis. Technological and Economic Development of Economy, [e-journal] 19(1), pp.S256-S284.

Van der Heijden, H., 2004. User acceptance of hedonic information systems. MIS Quarterly, 28(4), pp.695-704.

Vargo, S.L. and Lusch, R.F., 2004. Evolving to a new dominant logic for marketing. Journal of marketing, [e-journal] 68(1), pp.1-17.

Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D., 2003. User acceptance of information technology: Toward a unified view. MIS Quarterly, [e-journal] 27(3), pp.425-478.

Verkasalo, H., Lõpez-Nicolãs, C., Molina-Castillo, F.J. and Bouwman, H., 2010. Analysis of users and non-users of smartphone applications. Telematics and Informatics, [e-journal] 27(3), pp.242-255.

Wixom, B.H. and Todd, P.A., 2005. A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), pp.85-102.

Wu, J.H. and Wang, S.-C., 2005. What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & Management, [e-journal] 42(5), pp.719-729.

Yeh, C.C., 2015. Using a hybrid model to evaluate development strategies for digital content. Technological and Economic Development of Economy, [e-journal] 23(6), pp.1-15.

Yu, E., Hong, A. and Hwang, J., 2016. A socio-technical analysis of factors affecting the adoption of smart TV in Korea. Computers in Human Behavior, [e-journal] 61, pp.89-102.

Zhou, T., 2013. Understanding continuance usage of mobile sites. Industrial Management & Data Systems, [e-journal] 113(9), pp.1286-1299.


Insu Cho
Jong H. Lee (Primary Contact)
Young H. Kwak
Author Biographies

Insu Cho, Sun Moon University

Assistant Professor, Department of Industrial and Management Engineering, Sun Moon University, Republic of Korea, e-mail:

Jong H. Lee, Yonsei University

Ph.D. Candidate, Department of Industrial Engineering, Yonsei University, Republic of Korea, e-mail: , Tel: +82 2 2123 7776

Young H. Kwak, The George Washington University

Professor, Department of Decision Sciences, The George Washington University, USA, e-mail:
Cho, I., Lee, J. H., & Kwak, Y. H. (2019). Service-Led Model for the Activation of Smart TV: Case Study in Korea. Quality Innovation Prosperity, 23(3), 55–73.
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