Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
권호 표지
DOI QR코드

DOI QR Code

A Study on Acceptance of Online Concerts Based on Mobile Augmented Reality: Focusing on the Extended Technology Acceptance Model

모바일 증강현실 기반 온라인 콘서트 수용에 관한 연구: 확장된 기술수용모델을 중심으로

  • Choi, Bu-Heon (Division of Performing Arts & Media, Howon University)
  • 최부헌 (호원대학교 공연미디어학부)
  • Received : 2021.08.22
  • Accepted : 2021.11.20
  • Published : 2021.11.28
Download PDF
⟨ Previous Next ⟩

Abstract

This study conducted a questionnaire survey on 280 people who had experience of using mobile augmented reality-based online concerts. Using the SPSS 21.0 and AMOS 21.0 programs, the factors affecting the intention to reuse were investigated through statistical analysis(correlation analysis, path analysis, etc.). The main results are as follows. First of all, Presence and interactivity had a positive effect on flow, perceived ease of use and perceived usefulness. Flow had a positive effect on perceived ease of use and perceived usefulness. Perceived ease of use had a positive effect on perceived usefulness, and perceived usefulness had a direct positive effect on intention to reuse whereas perceived ease of use had an indirect effect on intention to reuse through perceived usefulness. In order to increase the intention to reuse of the mobile augmented reality-based online concert, it is necessary to prepare a plan to increase the level of presence, interactivity, and flow experienced by users. This study identified factors that affect the intention to reuse online concerts based on mobile augmented reality in an untact society. Therefore, it will be meaningful in that it presents the implications necessary to prepare a plan that can be efficiently accepted by consumers for the rapidly growing mobile augmented reality-based online concert.

본 연구는 모바일 증강현실 기반 온라인 콘서트 이용 경험이 있는 280명을 대상으로 설문조사를 실시하여 SPSS 21.0과 AMOS 21.0 프로그램을 활용하여 일련의 통계분석(상관관계분석, 경로분석 등)을 통해 재이용의도에 영향을 미치는 요인을 살펴보았다. 주요 결과를 살펴보면, 프레즌스와 상호작용성은 플로우, 인지된 용이성과 인지된 유용성에 정적 영향을 미쳤고, 플로우는 인지된 용이성과 인지된 유용성에 정적 영향을 미치는 것으로 나타났다. 인지된 용이성은 인지된 유용성에 정적 영향을 미쳤으며, 인지된 유용성은 재이용의도에 직접적으로 긍정적 영향을 미친 반면에 인지된 용이성은 인지된 유용성을 통해 재이용의도에 간접적인 영향을 미친 것으로 나타났다. 따라서 모바일 증강현실 기반 온라인 콘서트의 재이용의도를 높이기 위해서는 이용자가 경험하는 프레즌스와 상호작용성, 플로우 수준을 높일 수 있는 방안을 마련해야 할 것이다. 본 연구는 언택트 사회에서 모바일 증강현실 기반 온라인 콘서트 재이용의도에 영향을 미치는 요인을 파악하였다. 이에 빠르게 성장하고 있는 모바일 증강현실 기반 온라인 콘서트가 소비자들에게 효율적으로 수용될 수 있는 방안을 마련하는데 필요한 시사점을 제시하였다는 점에서 그 의의가 있을 것이다.

Keywords

Acknowledgement

This paper was supported by Howon University Research Grant in 2021.

References

  1. M. Yavuz, E. Corbacioglu, A. N. Basoglu, T. U. Daim, & A. Shayganc. (2021). Augmented Reality Technology Adoption: Case of a Mobile Application in Turkey. Technology in Society, 66, 101598. https://doi.org/10.1016/j.techsoc.2021.101598
  2. J. Cabero-Almenara, J. M. Fernandez-Batanero, & J. Barroso-Osuna. (2019). Adoption of Augmented Reality Technology by University Students. Heliyon, 5, e01597. https://doi.org/10.1016/j.heliyon.2019.e01597
  3. T. Hilken, J. Heller, M. Chylinski, D. I. Keeling, D. Mahr, & K. de Ruyter. (2018). Making Omnichannel an Augmented Reality: The Current and Future State of the Art. Journal of Research in Interactive Marketing, 12(4), 509-523. https://doi.org/10.1108/JRIM-01-2018-0023
  4. J. Yoo. (2020). The Effects of Perceived Quality of Augmented Reality in Mobile Commerce: An Application of the Information System Success Model. Informatics, 7(2), 14. https://doi.org/10.3390/informatics7020014
  5. T. Brigham. (2017). Reality Check: Basics of Augmented, Virtual, and Mixed Reality. Medical Reference Services Quarterly, 36(2), 171-178. DOI:10.1080/02763869.2017.1293987
  6. R. Diza. (2016). Augmented Reality versus Virtual Reality: The Battle is Real. https://techcrunch.com/2016/01/04/ar-vs-vr-the-battle-is-real/
  7. JoongAng Ilbo. (2020.08.25.). Fan Meeting and Concert in the Corner of the Room. The Era of Mobile Phone 'AR Enter' brought by Corona. https://news.joins.com/article/23856601
  8. J. Mutterlein, R. E. Kunz, & D. Baier. (2019). Effects of Lead-usership on the Acceptance of Media Innovations: A Mobile Augmented Reality Case. Technological Forecasting & Social Change, 145, 113-124. https://doi.org/10.1016/j.techfore.2019.04.019
  9. F. Bellalouna. (2021). The Augmented Reality Technology as Enabler for the Digitalization of Industrial Business Processes: Case Studies. 28th CIRP Confernece on Life Cycle Engineering, 400-405.
  10. L. Madden. (2011). Professional Augmented Reality Browsers for Smartphones: Programming for Junaio, Layar and Wikitude. John Wiley & Sons.
  11. B. Arnaldi, P. Guitton, & G. Moreau. (2018). Virtual Reality and Augmented Reality: Myths and Realities. John Wiley & Sons.
  12. Korea Policy Briefing. (2020.11.02.). BTS to My Room?...Catch the New Stage That merged due to COVID-19. https://www.korea.kr/news/policyNewsView.do?newsId=148879365#sitemap-layer
  13. L. Shore, V. Power, A. de Eyto, & L. O'Sullivan. (2018). Technology Acceptance and User-Centred Design of Assistive Exoskeletons for Older Adults: A commentary. Robotics, 7, 3. DOI:10.3390/robotics7010003
  14. F. D. Davis, R. P. Bagozzi, & P. R. Warshaw. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982-1003. DOI:10.1287/mnsc.35.8.982
  15. J. R. Rossiter and B. Braithwaite. (2013). C-OAR-SE-based Single-item Measure for the Two-Stage Technology Acceptance Model. Australasian Marketing Journal, 21(1), 30-35. https://doi.org/10.1016/j.ausmj.2012.08.005
  16. J. Iqbal & M. S. Sidhu. (2019). A Taxonomic Overview and Pilot Study for Evaluation of Augmented Reality Based Posture Matching Technique using Technology Acceptance Model. 16th International Learning & Technology Conference, 345-351. https://doi.org/10.1016/j.procs.2019.12.117
  17. F. D. Davis. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
  18. S. Taylor & P. A. Todd. (1995). Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6(2), 144-176. https://doi.org/10.1287/isre.6.2.144
  19. V. Venkatesh & F. A. Davis. (2000). Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204. DOI:10.1287/mnsc.46.2.186.11926
  20. M. S. Kim. (2010). A Study on the IPTV Use Perception and Factors Influencing IPTV Adoption. Korean Journal of Communication & Information, 52, 177-202.
  21. J. S. Sung. (2021). Effect of Flow in Convergence Dance Performance on Performace Attitude & Viewing Intention of Technology Acceptance Model. Doctoral Dissertation, Sejong University.
  22. J. H. Suh & J. S. Lee. (2015). Consumer Acceptance of Digital Live Technology: Focusing on Presence and Flow. Journal of Arts Management and Policy, 35, 33-59.
  23. H. Van der Heijden. (2004). User Acceptance of Hedonic Information Systems. MIS Quarterly, 28(4), 695-704. https://doi.org/10.2307/25148660
  24. T. Y. Chun & N. H. Park. (2015). The Effect of Augmented Reality Traits on Presence, Flow, and Relational Continuance Behavior with Smart-Phones. Journal of Distribution Science, 13(5), 45-52. DOI : 10.15722/jds.13.5.201505.45
  25. T. P. Novak, D. L. Hoffman, & Y. F. Yung. (2000). Measuring the Customer Experience in Online Environments: A Structural Modeling Approach. Marketing Science, 19(1), 22-42. DOI:10.1287/mksc.19.1.22.15184
  26. D. Weibel, B. Wissmath, S. Habegger, Y. Steiner, & R. Groner. (2008). Playing Online Games against Computer vs. Human-Controlled Opponents: Effects on Presence, Flow, and Enjoyment. Computers in Human Behavior, 24(5), 2274-2291. https://doi.org/10.1016/j.chb.2007.11.002
  27. J. C. Oh. (2012). Haptic Enabling Technology Acceptance Model(HE-TAM): Combined TAM and IDT. The e-Business Studies, 13(5), 323-346. DOI : 10.15719/geba.13.5.201212.323
  28. D. H. Shin. (2009). An Empirical Investigation of A Modified Technology Acceptance Model of IPTV. Behaviour & Information Technology, 28(4), 361-372. https://doi.org/10.1080/01449290701814232
  29. G. McLean & A. Wilson. (2019). Shopping in the Digital World: Examining Customer Engagement Through Augmented Reality Mobile Applications. Computers in Human Behavior, 101, 210-224. https://doi.org/10.1016/j.heliyon.2020.e04667
  30. D. Wang, S. Park, & D. R. Fesenmaier. (2012). The Role of Smartphones in Mediating the Touristic Experience. Journal of Travel Research, 51(4), 371-387. DOI:10.1177/0047287511426341
  31. J. W. Nam & T. Y. Park. (2014). A Study on Structural Relationship among Perceived Interactivity and User related Variables in Health Information Website. Journal of the Korean Society for Information Management, 31(4), 103-131. https://doi.org/10.3743/KOSIM.2014.31.4.103
  32. G. Wu. (2000). The Role of Perceived Interactivity in Interactive AD Processing. Ph. D. Dissertation. The University of Texas at Austin. Austin, TX, USA.
  33. H. J. Lee & D. H. Chung. (2012). Difference in Interactivity, Flow, Mood, Attitude, and Intention According to Smartphone Game Sensor. Korean Journal of Broadcasting and Telecommunication Studies, 26(1), 126-166.
  34. D. S. Kwak, K. H. Yim, & J. H. Kwon. (2012). Study on the Influence of Mobile Application Interactivity on Flow and Purchase Intention. Journal of Digital Convergence, 10(10), 165-176. https://doi.org/10.14400/JDPM.2012.10.10.165
  35. T. Y. Park & J. W. Nam. (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. https://doi.org/10.3743/KOSIM.2017.34.3.151
  36. W. S. Cha. (2021). A Study on the Effects of Digital Signage Advertising Linked with Voice Recognition Mobile App: Using Interactivity and Extended Technology Acceptance Model. Advertising Research, 129, 67-91. https://doi.org/10.16914/ar.2021.129.67
  37. K. S. Han & J. H. Choi. (2020). The Effect of Presence and Flow of Augmented Reality Advertising on the Advertising toward Attitude and Recall. Journal of Digital Convergence, 18(8), 29-35. DOI : 10.14400/JDC.2020.18.8.029
  38. D. L. Hoffman & T. P. Novak. (1997). Measuring the Flow Experience among Web Users. Nashville, TN: Vanderbilt University.
  39. S. B. Jung, D. Y. Won, & Y. M. Chung. (2015). A Study on the Intention to use of Flow Experience the Mobile Sports News: Applying the Technology Acceptance Model(TAM0 and Theory of Reasoned Action(TRA). Korean Journal of Sports Management, 20(6), 35-53.
  40. J. R. Kim & T. S. Cho. (2018). A Study on a Golf Supplies Company O2O-based Service App and its Reutilization Using the Extended Technology Acceptance Model. Journal of Sport and Leisure Studies, 71, 107-124. https://doi.org/10.51979/KSSLS.2018.02.71.107
  41. T. M. Kim & T. K. Kim. (2010). A Study on Development Direction of the Advertisement Which was applied Augmented Reality: Focused on Presence and Satisfaction. InfoDESIGN ISSUE24, 9(5), 59-69.
  42. C. M. Heo. (2018). Structural Relationship among Presence, Enjoyment, Brand Attitude and Purchase Intention of Augmented Reality-Based Sports Brand Advertising. Journal of Digital Contents Society, 19(3), 461-470. https://doi.org/10.9728/DCS.2018.19.3.461
  43. J. H. Kwon. (2014). A Study on the Effect of Mobile Shopping Application Characteristics on Customer Preference and Repurchase Intention. Doctoral Dissertation, Chungang University.
  44. D. L. Hoffman & T. P. Novak. (2009). Flow Online: Lessons Learned and Future Prospects. Journal of Interactive Marketing, 23(1), 23-34. https://doi.org/10.1016/j.intmar.2008.10.003