Consumer Study on the Acceptance of VR Headsets based on the Extended TAM

확장된 기술수용모델을 활용한 VR기기 수용관련 소비자 연구

  • Chen, Qian Qian (Dept. of International Business, Chungbuk National University) ;
  • Park, Hyun Jung (Dept. of International Business, Chungbuk National University)
  • 진천천 (충북대학교 국제경영학과) ;
  • 박현정 (충북대학교 국제경영학과)
  • Received : 2018.04.18
  • Accepted : 2018.06.20
  • Published : 2018.06.28


This study investigated the antecedents of VR(virtual reality) headsets acceptance and the causal relationships among self-efficacy, content diversity, the perceived usefulness, the perceived easy of use, the perceived playfulness and the adoption intention. We collected 238 survey responses and formed structural equation modeling with AMOS 23.0. The results of the analysis can be summarized as follows. The diversity of contents and self-efficacy had significant effects on perceived usefulness, perceived ease of use and perceived enjoyment, thus increasing the intention of acceptance. Perceived usefulness, perceived ease of use and perceived enjoyment had significant effects on the intention of acceptance. Perceived ease of use indirectly had an effect through increasing perceived enjoyment. The price did not affect the adoption intention and marketing communication increased the intention of acceptance. The results are expected to provide useful information to the companies related to VR.


VR headsets;Self-Efficacy;Content Diversity;Perseived Enjoyment;Extended TAM


  1. B. J. Sohn, D. S. Park & J. W. Choi. (2016). Attitude Confidence and User Resistance for Purchasing Wearable Devices on Virtual Reality: Based on Virtual Reality Headgear, Journal of Intelligence and Information Systems, 22(3), 165-183.
  2. B. G. Kang, W. B. Lee & S. H. Ryu. (2018). Development of Baekje cultural tourism contents by utilizing portable VR glasses. Journal of the Korea Convergence Society, 9(1), 317-323.
  3. F. D. Davis. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
  4. J. W. Moon & Y. G. Kim. (2001). Extending the TAM for a World-Wide-Web context. Information & management, 38(4), 217-230.
  5. J. Yu, I. Ha, M. Choi & J. Rho. (2005). Extending the TAM for a t-commerce. Information & management, 42(7), 965-976.
  6. C. L. Hsu & J. C. C. Lin. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation, Information & management, 45(1), 65-74.
  7. H. S. Suh & S. H. Park. (2011). Study on the Innovation Acceptance Characteristics for Digital Convergence Products, Journal of Digital Convergence, 9(4), 51-67.
  8. L. Molteni & A. Ordanini. (2003). Consumption patterns, digital technology and music downloading. Long Range Planning, 36(4), 389-406.
  9. N. Dufft, A. Stiehler, D. Vogeley & T. Wichmann. (2005). Digital music usage and DRM-results from an European consumer survey. The Informed Dialogue about Consumer Acceptability of DRM Solutions in Europe.
  10. V. Venkatesh, J. Y. Thong & X. Xu. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178.
  11. C. I. Martins. (2013). Exploring Digital Music Online: User acceptance and adoption of online music services, Doctoral dissertation, Instituto Superior de Economia e Gestao.
  12. D. L. Feltz & C. ARiessinger. (1990). Effects of in vivo emotive imagery and performance feedback on self-efficacy and muscular endurance. Journal of Sport and Exercise Psychology, 12(2), 132-143.
  13. A. D. Stajkovic & F. Luthans. (1998). Self-efficacy and work-related performance: A meta-analysis. Psychological bulletin, 124(2), 240.
  14. R. Agarwal & E. Karahanna. (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage, MIS quarterly, 665-694.
  15. J. G. Park. (2010). Integrative Adoption Model of New Media (IAM-NM), korea communication association, 55(5), 448-479.
  16. J. H. You & C. Park. (2010). A Comprehensive Review of Technology Acceptance Model Researches. Entrue Journal of Information Technology, 9(2), 31-50.
  17. V. Venkatesh & F. D. Davis. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
  18. S. H. Oh & S. H. Kim. (2006). Structural relationships among factors affecting usage of internet banking: Focusing on extended technology acceptance model. The Journal of Marketing Research, 21(1), 1-27.
  19. H. J. Park, K. S. Shin & J. W. Choi. (2017). A Multi-dimensional Structure for User Resistance with the Determinants of Innovative Product Use on Virtual Reality. Journal of Society for e-Business Studies, 21(2), 97-119.
  20. D. R. Compeau & C. A. Higgins. (1995). Computer self-efficacy: Development of a measure and initial test. MIS quarterly, 189-211.
  21. W. Lewis, R. Agarwal & V. Sambamurthy. (2003). Sources of influence on beliefs about information technology use: An empirical study of knowledge workers. MIS quarterly, 657-678.
  22. L. I. Darsono. (2005). Examining information technology acceptance by individual professionals. Gadjah Mada International Journal of Business, 7(2), 155-178.
  23. Y. S. Wang, H. Y. Wang & D. Y. Shee. (2007). Measuring e-learning systems success in an organizational context: Scale development and validation. Computers in Human Behavior, 23(4), 1792-1808.
  24. J. C. Roca, C. M. Chiu & F. J. Martinez. (2006). Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. International Journal of human-computer studies, 64(8), 683-696.
  25. L. M. Lin & H. J. Park. (2017). Effects of Drone Self-Efficacy and Novelty-Seeking on the Perceptions and the Adoption Intention of Drone Delivery Service, The e-Business Studies, 18(5), 91-103.
  26. Y. Jung, B. Perez-Mira & S. Wiley-Patton. (2009). Consumer adoption of mobile TV: Examining psychological flow and media content, Computers in Human Behavior, 25(1), 123-129.
  27. V. Venkatesh, J. Y. Thong & X. Xu. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead.
  28. C. J. Jeong. (2018). Effects of Facebook Advertisement Message's Convergence Type SNS Trait on Brand Attitude, Purchasing Intention. Journal of the Korea Convergence Society, 9(3), 187-201.
  29. K. L. Keller. (2001). Building customer-based brand equity: A blueprint for creating strong brands. Marketing Management.
  30. J. N. Sheth. (1971). Affect, behavioral intention, and buying behavior as a function of evaluative beliefs. Insights in consumer and market behavior. Belgium: Namur University Publications.
  31. K. S. Kim. (2015). Advertising Contents based on Semiotic Methodology. Journal of the Korea Convergence Society, 6(6), 87-93.
  32. L. G. Tornatzky & K. J. Klein. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on engineering management, 1, 28-45.
  33. R. Thompson. (1998). Extending the technology acceptance model with motivation and social factors. AMCIS 1998 Proceedings, 254.
  34. H. Van der Heijden. (2004). User acceptance of hedonic information systems. MIS quarterly, 695-704.
  35. S. Taylor & P. A. Todd. (1995). Understanding information technology usage: A test of competing models. Information systems research, 6(2), 144-176.
  36. Z. Papacharissi & A. M. Rubin. (2000). Predictors of Internet use. Journal of broadcasting & electronic media, 44(2), 175-196.
  37. L. M. Flaherty, K. J. Pearce & R. B. Rubin. (1998). Internet and face‐to‐face communication: Not functional alternatives. Communication Quarterly, 46(3), 250-268.
  38. H. K. Shin, J. H. Hong & K. K. Kim. (2007). The Influence of Website Charateristics on Customer Satisfaction, Customer Loyalty, and Repurchase Intention in Internet Shopping Malls. The Journal of Society for e-Business Studies, 12(1), 41-71.
  39. V. A. Zeithaml. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. The Journal of marketing, 2-22.
  40. J. W. Kang & S. W. Lee. (2007). A User's Adoption of IPTV under a Preannouncing Circumstance : Predictors to Affect IPTV Adoption and Characteristics of Potential Innovators, Korea Association for Broadcasting & Telecommunication Studies, 21(3), 7-46.
  41. A. H. Segars & V. Grover. (1993). Re-examining perceived ease of use and usefulness: A confirmatory factor analysis. MIS quarterly, 517-525.
  42. R. Agarwal & J. Prasad. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision sciences, 28(3), 557-582.