Journal of Intelligence and Information Systems (지능정보연구)

Korea Intelligent Information System Society (한국지능정보시스템학회)
권호 표지
DOI QR코드

DOI QR Code

A study of the impact of Metaverse attributes on intention to use - based on the Extended Technology Acceptance Model

메타버스특성이 이용의도에 미치는 영향에 관한 연구 - 확장된 기술수용모델을 기반으로

  • Received : 2023.05.21
  • Accepted : 2023.05.29
  • Published : 2023.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

This study analyzed the factors influencing users' intention to use the Metaverse by applying the extended technology acceptance model. In other words, the factors affecting users' intention to use the Metaverse were defined as technical characteristics (telepresence, interoperability, seamlessness, concurrence, and economy flow) and personal characteristics (social influence and perceived enjoyment) from the perspective of the Extended Technology Acceptance Model. For this purpose, a survey was conducted among men and women of various ages ranging from teenagers to 60s, and the data collected from 327 participants were analyzed using SPSS 22.0 and Smart PLS 4.0. The results showed that perceived usefulness and perceived ease of use, which are antecedents of the Extended Technology Acceptance Model, influence the intention to use Metaverse, and perceived ease of use influences perceived usefulness. Telepresence, interoperability and economy flow were found to have a positive effect on perceived usefulness, and interoperability, seamlessness and concurrence were found to have a positive effect on perceived ease of use. In addition, social influence and perceived enjoyment had a positive effect on intention to use the Metaverse. This study is significant in that it empirically analyzed the factors of users' acceptance of the Metaverse, which is attracting attention as a new platform that will bring significant changes to our daily lives and platform consumption environments.

본 연구에서는 확장된 기술 수용 모델을 적용하여 사용자의 메타버스 사용 의도에 영향을 미치는 요인을 분석했습니다. 즉, 확장된 기술수용모델의 관점에서 메타버스 이용의도에 영향을 미치는 요인을 기술적 특성(원격실재감, 상호운용성, 연속성, 동시성, 경제적 흐름)과 개인적 특성(사회적 영향력, 지각된 즐거움)으로 정의하고, 메타버스 이용의도에 영향을 미치는 요인들을 분석했습니다. 이를 위해 10대부터 60대까지 다양한 연령대의 남녀를 대상으로 설문조사를 실시했으며, 327명의 참여자로부터 수집된 데이터는 SPSS 22.0과 Smart PLS 4.0을 사용하여 분석했습니다. 그 결과 확장된 기술 수용 모델의 선행 요인인 지각된 유용성과 지각된 사용 용이성이 메타버스 사용 의도에 영향을 미치고, 지각된 사용 용이성은 지각된 유용성에 영향을 미치는 것으로 나타났습니다. 원격실재감, 상호운용성, 경제성 흐름은 인지된 유용성에 긍정적인 영향을 미치는 것으로 나타났으며, 상호운용성, 연속성, 동시성은 인지된 사용 용이성에 긍정적인 영향을 미치는 것으로 나타났습니다. 또한 사회적 영향력과 지각된 즐거움은 메타버스 사용 의도에 긍정적인 영향을 미치는 것으로 나타났습니다. 본 연구는 우리의 일상과 플랫폼 소비 환경에 큰 변화를 가져올 새로운 플랫폼으로 주목받고 있는 메타버스에 대한 사용자의 수용 요인을 실증적으로 분석했다는 점에서 의의가 있습니다.

Keywords

Acknowledgement

This research is financially supported by Hansung university.

References

  1. Agarwal, R. and Karahanna, E. (2000). "Time Flies When You're Having Fun: Cognitive Absorption and Beliefs about Information Technology Usage," MIS Quarterly, Vol.24, No.4, pp.665-694, 2000. https://doi.org/10.2307/3250951
  2. Anderson, J.C. and Gerbing, D.W. (1988), "Structural equation modeling in practice: a review and recommended two-step approach", Psychological Bulletin, Vol. 103 No. 3, pp. 411-423, https:/doi.org/10.1037/0033-2909.103.3.411.
  3. Anderson, Rolph E., and Swaminathan, Srinivasan (2011), "Consumer satisfaction and Loyalty in e-Markets: A PLS Path Modeling Approach," Journal of Marketing Theory and Practice, 19 (2), 221-234. https://doi.org/10.2753/MTP1069-6679190207
  4. Cammack, R. G. (2010). Location-based service use: A Metaverse investigation. Journal of Location Based Services, 4(1), 53-65. https://doi.org/10.1080/17489721003742827
  5. Carmigniani, J. & Furht, B. (2011). Augmented reality: An overview. In Handbook of augmented reality (pp.3-46). Springer.
  6. Cha, W. (2019). A study on the advertising acceptance of audiences toward the Cinema advertising using NFC technology-using extended technology acceptance model and interactivity. Journal of Digital Contents Society, 20(11), 2131-2140. https://doi.org/10.9728/dcs.2019.20.11.2131
  7. Cho, Nae eul. (2017). A Study on the Continuous Use Intention of the Social Platform. Journal of Knowledge Information Technology and Systems, 12(5), 629-638. https://doi.org/10.34163/jkits.2017.12.5.004
  8. Davis, A., Murphy, J. D., Owens, D., Khazanchi, D., & Zigurs, I. (2009). Avatars, people, and virtual worlds: Foundations for research in Metaverses. Journal of the Association for Information Systems, 10(2), 90-117. https://doi.org/10.17705/1jais.00183
  9. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340.
  10. Davis, F. D., Bagozzi, R. P. & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982
  11. Davis, F. D., Bagozzi, R. P. & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.
  12. Davis, F. D. & Venkatesh, V. (1996). A critical assessment of potential measurement biases in the technology acceptance model: Three experiments. International Journal of Human-Computer Studies, 45(1), 19-45. https://doi.org/10.1006/ijhc.1996.0040
  13. Deutsch, M. and Gerard, H. B. (1955). "A study of normative and informational social influences upon individual judgement," Journal of Abnormal and Social Psychology, Vol.51, pp.629-636, 1955. https://doi.org/10.1037/h0046408
  14. Dinev, T., & Hart, P. (2004). Internet privacy concerns and their antecedents-measurement validity and a regression model. Behaviour & Information Technology, 23(6), 413-422. https://doi.org/10.1080/01449290410001715723
  15. Dionisio, J. D. N., Burns III,W. G., and Gilbert, R. (2013). 3D virtual worlds and the Metaverse: Current status and future possibilities. ACM Computing Surveys(CSUR), 45(3), 1-38. https://doi.org/10.1145/2480741.2480751
  16. 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/10.1177/002224378101800104
  17. Gilbert, R. L. (2011). The prose (psychological research on synthetic environments) project: Conducting in-world psychological research on 3d virtual worlds. Journal For Virtual Worlds Research, 4(1).
  18. Go, Sun-Young, Jeong, Gyun, Jeong, Jong-In, & Shin, Hyeok-Tae. (2021). The concept and development direction of Metaverse. Korea Information Processing Society Review, 28(1), 7-16.
  19. Guo, J., & Chow, A. (2008). Virtual money systems : A phenomenal analysis. In 2008 10th IEEE Conference on E-Commerce Technology and the Fifth IEEE Conference on Enterprise Computing, E-Commerce and E-Services, IEEE, 267-272.
  20. Guthrie, K. L., Phelps, K., & Downey, S. (2011). Virtual worlds: A developmental tool for leadership education. Journal of Leadership Studies, 5(2), 6-13. https://doi.org/10.1002/jls.20214
  21. Hair, Joseph F., William C. Black, Barry J. Babin, and Rolph E. Anderson (2010), Multivariate Data Analysis, Englewood Cliffs, NJ: Prentice-Hall.
  22. Hair, J. F., & Lukas, B. (2014). Marketing research. (Vol. 2). McGraw-Hill Education.
  23. Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2014), A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks, CA: Sage.
  24. Hair Jr, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106-121. https://doi:10.1108/EBR-10-2013-0128
  25. Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) 2nd ed. Sage publications.
  26. Han, Sang-Lin and An, Myoung-a.(2019). Analysis of User Telepresence and Behavioral Intention in Virtual Reality Shopping Environment. Journal of channel and retailing, 24(1), 51-71. https://doi.org/10.17657/jcr.2019.01.31.3
  27. Han, Sang-Yeol (2021). Status and Prospects of Metaverse Platforms. future horizon, 49: 19-24.
  28. Henseler, J., Ringle, C.M. and Sarstedt, M. (2016), "Testing measurement invariance of composites using partial least squares", International Marketing Review, Vol. 33 No. 3, pp. 405-431, https:/doi.org/10.1108/IMR-09-2014-0304.
  29. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8
  30. Henseler, J., Ringle, C. M. and Sinkovics, R. R. (2009), "The Use of Partial Least Squares Path Modeling in International Marketing," Advances in International Marketing, 20, 277-319. https://doi.org/10.1108/S1474-7979(2009)0000020014
  31. Hong, Su Ji, Han, Sang-Lin.(2020). A Study of the Effect of Shopping Experience in Virtual Reality and Augmented Reality on Consumer Decision Making: Analysis of Mediating Effect of Perceived Value. Korea Business Review, 24, 173-187.
  32. Huh, B., & Lee, H.-Y. (2022). The effect of ESG activities on organizational trust, and organizational identity through employees' organizational justice. Journal of Intelligence and Information Systems, 28(4), 229-250.
  33. Hwang, Jae and Yu, Hongsik. (2016). A Study of Factors Affecting the Intention to use a Mobile Easy Payment Service : An Integrated Extension of TAM with Perceived Risk . The Journal of Information Technology and Architecture, 13(2), 291-306
  34. Jeon, Suyeon and Nam, Yoonjae .(2020). Effects of augmented reality application for e-commerce on user satisfaction and purchase intention? Focusing on experience economy theory, PDA, and cognitive characteristics. The Journal of Internet Electronic Commerce Research, 20(3), 73-86. https://doi.org/10.37272/JIECR.2020.06.20.3.73
  35. Jiao, Li Min and Kim, Chul Jung. (2021). A Study on the Effect of User Factors of Mobile SNS App on User Satisfaction and Sustained Usage Intention: Focused on the moderating effects of social commerce involvement. The e-Business Studies, 22(1), 137-155. https://doi.org/10.20462/TeBS.2021.2.22.1.137
  36. Jung, Jun-Hwa (2021). Current status and future challenges of the Metaverse, Issues and Controversies of the National Assembly Legislative Research Service, No. 1858
  37. Kaplan, F., & Di Lenardo, I. (2020). The advent of the 4D mirror world. Urban Planning, 5(ARTICLE), 307.
  38. Kim, Ahyun, Kim, Yong Jin and Kim, Sang Soo. (2022). A Comparative Study on User Perception by Metaverse Worldview Using SPICE. Knowledge Management Research. 2022, 23(2)
  39. Kim, E (2022). The Creator Economy on the Metaverse Platform. Journal of Intelligence and Information Systems, 28(4), 275-286.
  40. Kim, Sang-Gyun (2020). The Metaverse: A World of Digital Globe-Trotting Things. Plan B Design.
  41. Kim, Sang-Gyun and Shin, Byung-Ho (2021). Metaverse New Opportunities. Vega Books.
  42. Koo, Ja-Hyun, Chang-Keun, Park, Ji-Hye, Park, So-Hyun, Lee, Ga-Young, Lim, Hyun-Do and Yoon, Min-Seop (2021), Understanding the Metaverse Industry and Policy Issues, Service Economy Research Series
  43. Lee, Byong-Kwon. (2021). The Metaverse World and Our Future. The Korea Contents Association Review, 19(1), 13-17.
  44. Lee, Dongseon, Choi, Jeongil & Kang, Juyoung. (2021). A Study on the Factors Affecting the Intention to Use VR-based Digital Content Subscription Service. Korea Business Review, 25(2), 135-162.
  45. Lee, Jihye.(2021). A Study on the Effects of Social Live Streaming Viewing Motivation on Content Usage Behavior: Focusing on the Mediating Effect of Immersion Experience and Interactivity. The Journal of Internet Electronic Commerce Resarch, 21(3), 163-185. https://doi.org/10.37272/JIECR.2021.06.21.3.163
  46. Lee, J. H. (2021). The status and future of the Metaverse. KISO Journal, 43: 17-22.
  47. Lee, Sang-Gun. (2005). An Empirical Study on Mobile Technology Adoption based on the Technology Acceptance Model and Theory of Planned Behavior. Information Systems Review, 7(2), 61-84
  48. Malhotra, Y. & Galletta, D. F. (1999). Extending the technology acceptance model to account for social influence: Theoretical bases and empirical validation., 14 pp.
  49. MarketsandMarkets (2020). Metaverse Market by Component (Hardware, Software (Extended Reality Software, Gaming Engine, 3D Mapping, Modeling & Reconstruction, Metaverse Platform, Financial Platform), and Professional Services), Vertical and Region - Global Forecast to 2027, MarketsandMarkets, 2020
  50. McKerlich, R., Riis, M., Anderson, T., & Eastman, B. (2011). Student perceptions of teaching presence, social presence, and cognitive presence in a virtual world. MERLOT Journal of Online Learning and Teaching, 7(3), 324-336
  51. McMillan, S. J. & Hwang, J. S. (2002). Measures of perceived interactivity: An exploration of the role of direction of communication, user control, and time in shaping perceptions of interactivity. Journal of Advertising, 31(3), 29-42. https://doi.org/10.1080/00913367.2002.10673674
  52. Nevelsteen, K. J. (2018). Virtual world, defined from a technological perspective and applied to video games, mixed reality, and the Metaverse. Computer Animation and Virtual Worlds, 29(1), e1752.
  53. Noor, A. K. (2010). Potential of virtual worlds for remote space exploration. Advances in Engineering Software, 41(4), 666-673. https://doi.org/10.1016/j.advengsoft.2009.12.013
  54. Oh, Ji-Hee.(2021). A Study on Factors Affecting the Intention to Use the Metaverse by Applying the Extended Technology Acceptance Model (ETAM) : Focused on the Virtual World Metaverse. JOURNAL OF THE KOREA CONTENTS ASSOCIATION,21(10), 204-216.
  55. Oh, Ji-Hee (2022). Effects of University Students' Metaverse Use Motivations on Satisfaction and Continued Use Intention : Focused on the Virtual World Metaverse. Journal of the Korea Entertainment Industry Association, 16(2), 1-17. https://doi.org/10.21184/jkeia.2022.2.16.2.1
  56. Pang, Dong-Hyun & Kang, So-Hyun. (2021). The trend is the Metaverse... Roblox Economy 'Eyes'. MoneyS.
  57. Park, hyungil.(2021). Metaverse World. Excellence Marketing for Customer, 55(5), 42-51.
  58. Park, Jung-Sook and Byun, Jung-Woo.(2013). The Effect of SNS's Perceived Enjoyment on Customer Satisfaction and the Intention of Use Using TAM : Focused on the F&B division of Hotel. Journal of Tourism and Leisure Research, 25(1), 419-435.
  59. Park, Sunkyung and Kang, Yoon Ji (2021). A Study on the intentions of early users of Metaverse platforms using the Technology Acceptance Model. Journal of Digital Convergence, 19(10), 275-285. https://doi.org/10.14400/JDC.2021.19.10.275
  60. Park, T-Y. & Nam, J-W. (2017). The effects of perceived interactivity on information acceptance in mobile health information service. Journal of the Korean Society for Information Management, 34(3), 151-177.
  61. Park, Young-A and Hyun, Yong-Ho.(2013). A Verification of the Structural Relationships between Consumer Review Characteristics and Acceptance Intention to Smartphone Application by Applying Extended TAM Model - A Focus on the Mediating role of Information Quality -.Korean Journal of Business Administration, 26(11), 2851-2871.
  62. Prema, K. N. & Roopa, B. S. (2018). Virtual reality : A survey. International Research Journal of Engineering and Technology, 5(7), 1567-1569.
  63. PwC Consulting (2020). 'Seeing is Believing', https://www.pwc.com/SeeingIsBelieving
  64. Qiao, Rongrong and Han, Dongsoong.(2019). A Study on the Reuse Intention of Virtual Reality(VR) Content Using Technology Acceptance Model. Journal of Korea Game Society, 19(5), 115-131. https://doi.org/10.7583/JKGS.2019.19.5.115
  65. Ricci, A., Piunti, M., Tummolini, L. & Castelfranchi, C. (2015). The mirror world: Preparing for mixed-reality living. IEEE Pervasive Computing, 14(2), 60-63. https://doi.org/10.1109/MPRV.2015.44
  66. Seok, Wanghun. (2021). Analysis of Metaverse Business Model and Ecosystem. Electronics and Telecommunications Trends, 36(4), 81-91. https://doi.org/10.22648/ETRI.2021.J.360408
  67. Shah, R. and Goldstein, S.M. (2006) Use of Structural Equation Modeling in Operations Management Research: Looking Back and Forward. Journal of Operations Management, 24, 148-169. https://doi.org/10.1016/j.jom.2005.05.001
  68. Son, Hyun-Jung, Lee, Sang-Won and Cho, Moon-Hee (2014). Influential Factors of College Students' Intention to Use Wearable Device - An Application of the UTAUT2 Model. Korean Journal of Communication & Information, 68(4), 7-33.
  69. Tasa, U. B., & Gorgulu, T. (2010). Meta-art: Art of the 3-D user-created virtual worlds. Digital Creativity, 21(2), 100-111.
  70. Venkatesh, V. & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481. https://doi.org/10.1111/j.1540-5915.1996.tb01822.x
  71. Venkatesh, V. & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
  72. Venkatesh, V., & Morris, M. G. (2000). Why Don't Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior. MIS Quarterly, 24(1), 115-139. https://doi.org/10.2307/3250981
  73. Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425-478.
  74. Yang, Hee Dong and Choi, In Young. (2001). The Impact of Social Influence on Information Systems Adoption : An Extension to the Technology Acceptance Model. Asia Pacific Journal of Information Systems, 11(3), 165-184.
  75. Yoon, Jae-Hyun and Kim, Han-Ku.(2018). The Effect of Online Interactivity, Self-Presentation and Personal Information Concern on WOM of SNS Advertisement and SNS Continuous Use Intention through Presence Experience. The Journal of Internet Electronic Commerce Research, 18(3), 125-143. https://doi.org/10.37272/JIECR.2018.06.18.3.125
  76. Yun, H., An, J., & Park, S. C. (2023). An Exploratory Study for Metaverse Governance in the Public Sector. Journal of Intelligence and Information Systems, 29(1), 353-376.