DOI QR코드

DOI QR Code

SNS를 활용한 K-POP 기록물 수집활동에 대한 지속의도 통합모델 연구

A Study on the Integration Model of Continuous Intention to Collect K-POP Records Using SNS

  • 김건 (전북대학교 기록관리대학원) ;
  • 윤승욱 (전북대학교 문화융복합아카이빙연구소) ;
  • 김현태 (전북대학교 프랑스.아프리카학과)
  • Kim, Geon (Graduate School of Archives and Records Management, Jeonbuk National University) ;
  • Yun, Sung-uk (Institute of Culture Convergence Archiving, Jeonbuk National University) ;
  • Kim, Hyun-Tae (Department of French & African Studies, Jeonbuk National University)
  • 투고 : 2020.02.28
  • 심사 : 2020.05.20
  • 발행 : 2020.05.28

초록

본 연구는 SNS를 이용하여 K-POP 기록물 수집활동을 하고 있는 SNS 이용자들을 대상으로 설문조사를 실시하여 K-POP 기록물 수집활동 지속의도에 영향을 미치는 요인을 검증하였다. 주요 분석방법은 SPSS 21.0 프로그램과 AMOS 21.0 프로그램을 이용하여 탐색적 요인분석과 확인적 요인분석, 상관관계분석, 경로분석을 수행하였다. 주요 결과를 요약, 제시하면 다음과 같다. 첫째, 인지된 혁신특성이 인지된 유용성과 인지된 용이성에 미치는 영향을 살펴본 결과, SNS를 통한 K-POP 관련 기록물 수집활동에 대한 적합성은 인지된 유용성에 정(+)의 영향을 미치는 것으로 나타났고, 관찰가능성은 인지된 용이성에 정(+)의 영향을 미치는 것으로 나타났다. 또한 시험가능성은 인지된 유용성과 인지된 용이성에 정(+)의 영향을 미치는 것으로 나타났다. 둘째, SNS를 이용한 K-POP 기록물 수집활동에 대한 인지된 용이성이 인지된 유용성에 미치는 영향을 살펴본 결과, 인지된 용이성은 인지된 유용성에 정(+)의 영향을 미치는 것으로 나타났다. 셋째, SNS를 이용한 K-POP 기록물 수집활동에 대한 인지된 유용성과 인지된 용이성이 K-POP 기록물 수집 활동 지속의도에 미치는 영향을 살펴본 결과, 인지된 유용성과 인지된 용이성은 K-POP 기록물 수집활동 지속의도에 정(+)의 영향을 미치는 것으로 나타났다. 본 연구의 결과는 혁신확산이론과 기술수용모델의 통합을 통해 SNS를 이용한 K-POP 기록물 수집활동의 지속의도를 설명할 수 있음을 시사한다.

This study conducted a questionnaire survey on SNS users who are conducting K-POP record collection activities using SNS and verified factors affecting the intention to continue K-POP record collection activities. The main methods of analysis were exploratory factor analysis, confirmatory factor analysis, correlation analysis, and path analysis using SPSS 21.0 program and AMOS 21.0 program. The results are summarized as follows. First, compatibility for K-POP record collection activities through SNS has a positive effect on perceived usefulness, and observability also has a positive effect on perceived usefulness and perceived ease of use. Second, perceived ease of use for K-POP records collection using SNS has a positive effect on perceived usefulness. Third, perceived usefulness and perceived ease of use for K-POP records collection using SNS have a positive effect on continuous intention of K-POP records collection activity through SNS. As a result of this study, it suggests that the intention to continue the collection activities of K-POP records using SNS can be explained through the integration of innovation diffusion theory and technology acceptance model.

키워드

참고문헌

  1. Z. H. Song. (2012). A study on SNS as a records management: Focusing on facebook, twitter, blog, youtube. Master's Thesis, Hankuk University of Foreign Studies.
  2. S. H. Kim & J. S. Sim. (2019). A study on the recognition of the archival values and use of photographic records of modern Korea. Journal of the Korean Biblia Society for Library and Information Science, 30(2), 245-261. https://doi.org/10.14699/KBIBLIA.2019.30.2.245
  3. S. J. Sohn. (2018). A study on the preference of K-culture in Argentina through contents analysis of local press reports and social media. Korean Journal of Tourism Research, 33(5), 67-88. DOI : 10.21719/ijtms.33.5.4
  4. B. C. Cho & H. Sim. (2013). Success factor analysis of K-pop and a study on sustainable Korean wave: focus on smart media based on realistic contents. Journal of the Korea Contents Association, 13(5), 90-102. DOI : 10.5392/JKCA.2013.13.05.090
  5. D. Zhang & S. J. Yoon. (2018). Social media, information presentation, consumer involvement, and cross-border adoption of pop culture products. Electronic Commerce Research and Applications, 27, 129-138. DOI : 10.1016/j.elerap.2017.12.005
  6. Y. J. Lee, H. J. Oh, & S. K. An. (2019). Characteristics analysis and utilization plans of K-POP fandom records for popular music archived: Focused on the case of BTS fandom, ARMY. The Korean Journal of Archival Studies, 60, 161-194.
  7. J. W. Seo, J. H. Park, H. J. Oh, & E. H. Youn. (2016). A study on the issue analysis of national archives of Korea based on SNS analysis between 2014-2015. The Korean Journal of Archival Studies, 50, 139-175.
  8. C. P. Lin & A. Bhattacherjee. (2008). Elucidating individual intention to use interactive information technologies: The role of network externalities. International Journal of Electronic Commerce, 13(1), 85-108. DOI : 10.2753/JEC1086-4415130103
  9. Lin, K. Y., & Lu, H. P. (2011). Why people use social networking sites: An empirical study integrating network externaliteis and motivation theory. Computers in Human Behavior, 27(3), 1152-1161. DOI : 10.1016/j.chb.2010.12.009
  10. P. J. Cunningham. (2003). IM: Invaluable new business tool or records management nightmare. The Information Management Journal, 37(6), 27.
  11. M. Caswell. (2009). Instant documentation: Cell-phone-generated records in the archives. American Archivist, 72(1), 133-145. DOI : 10.17723/aarc.72.1.k7186478626823x9
  12. J. M. Kang, Y. J. Song, & M. K. Choi. (2013). Social phenomena and challenges for internet fandom culture: Be focused on the method of link value and scalability for Korea wave fandom, The Journal of the Institute of Internet Broadcasting and Communication, 13(1), 235-241. DOI : 10.7236/jiibc.2013.13.1.235
  13. E. M. Rogers. (1995). Diffusion of innovation (4th edition). New York: Free Press.
  14. E. C. Hirschman. (1980). Innovativeness, novelty seeking, and consumer creativity. Journal of Consumer Research, 7(3), 283-295. https://www.jstor.org/stable/2489013 https://doi.org/10.1086/208816
  15. E. M. Rogers. (2003). Diffusion of innovations (5th ed.). New York: Free Press.
  16. Y. J. Kim, J. M. Jung, & E. J. Lee. (2011). What drives the adoption and usage of smartphone applications?: Factors affecting degree of use, continuous use, and recommendation, Korean Journal of Journalism & Communication Studies, 55(6), 227-252.
  17. H. S. Chiang. (2013). Continuous usage of social networking sites: The effect of innovation and gratification attributes. Online Information Review, 37(6), 851-871. DOI : 10.1108/oir-08-2012-0133
  18. M. J. Kim, C. K. Lee, & N. S. Contractor. (2019). Seniors' usage of mobile social network sites: Applying theories of innovation diffusion and uses and gratifications. Computers in Human Behavior, 90, 60-73. DOI : 10.1108/OIR-08-2012-0133
  19. V. Venkatesch, M. G. Morris, G. B. Davis, & F. D. Davis. (2003). User acceptance of information technology: Toward a unified view. Information Management, 27(3), 425-478. DOI : 10.2307/30036540
  20. Y. W, Song, M. H. Rim, K. Motohashi, & S. H. Kim. (2010). Innovative converged service and it's adoption, use and diffusion: A holistic approach to diffusion of innovations, combining adoption-diffusion and use diffusion paradigms. Journal of Information Technology Applications & Management, 17(2), 187-205.
  21. G. C. Moore, & I. Benbasat. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222. DOI : 10.1287/isre.2.3.192
  22. L. G. Tornatzky & K. J. Klein. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on engineering management, 29(1), 28-45.
  23. F. D. Davis. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. DOI : 10.2307/249008
  24. D. Adams, R. Nelson, & P. Todd. (1992). Perceived usefulness, ease of use, and usage of information technology: A replication. MIS quarterly, 16(2), 227-248. DOI : 10.2307/249577
  25. B. Park. (2011). Integrative adoption model of new media, Korean Journal of Journalism & Communication Studies 55(5), 448-479.
  26. B. H. Chang & Y. G. Kim. (2007). An exploratory study on factors affecting the adoption intent of triple play service: Focusing on college students, Korean Journal of Boradcasting, 21(5), 165-203.
  27. R. Scherer, F. Siddiq, & J. Tondeur. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers' adoption of digital technology in education. Computers & Education, 128, 13-35. https://doi.org/10.1016/j.compedu.2018.09.009
  28. R. Agarwal & J. Prasad. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204-215. DOI : 10.1287/isre.9.2.204
  29. V. Venkatesh, M. G. Morris, G. B. Davis, & F. D. Davis. (2003). User acceptance of information technology: Toward a unified view. Information Management, 27(3), 425-478. DOI : 10.2307/30036540
  30. C. W. Kim & C. K. Suh. (2017). The interrelationship between the functional characteristics and the intelligent personal assistant. Journal of Information Systems, 26(4), 163-188. https://doi.org/10.5859/KAIS.2017.26.4.163
  31. H. Choi. (2016). A study on the effects of product characteristics of digital convergence on acceptance intention via perceived usefulness and ease of use: The moderating effects of gamiifcation. Master's Thesis, Jeonbuk National University.
  32. J. S. Lee & M. Y. Lee. (2006a). Examining factors affecting the adoption of terrestrial DMB phones using modified technology acceptance model2(TAM2). Studies of Broadcasting Culture, 18(2), 251-283.
  33. J. S. Lee & M. Y. Lee. (2006b). Examining factors affecting the intention to use IP-TV with the extended technology acceptance model(TAM), Broadcasting & Communication, 7(1), 100-131.
  34. S. Taylor, & P. A. Todd. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 19(2), 561-570. DOI : 10.2307/249633
  35. H. Verkasalo, C. Lopez-Nicolas, F. J. Molina- Castillo, & H. Bouwman. (2010). Analysis of users and non-users of smartphone applications. Telematics and Informations, 27(3), 242-255. DOI : 10.1016/j.tele.2009.11.001
  36. S. Y. Yousafzai, G. R. Foxall, & J. g. Pallister. (2007). Technology acceptance: A meta-analysis of the TAM: Part 1. Journal of Modelling in Management, 2(3), 251-280. DOI : 10.1108/17465660710834453
  37. B. Park. (2012). An integrative adoption model of tablet-PCs: Focusing on the validation of the integrative adoption model of new media. Journalism & Culture Research, 19, 62-103.
  38. S. K. Han. (2009). A study on the factors affecting adoption of the IPTV, Doctoral Dissertation Hanyang University.
  39. Y. J. Han & J. Y. Ha. (2019). Factors affecting the use of user generated content on the web. Journal of Broadcasting and Telecommunications Research, 152-190.
  40. H. J. Woo. (2009). Exploring the influence on technology acceptance factors and perceived brand qualities affecting the internet radio player usage: Focusing on KBS Kong, MBC Mini, SBS Gorilla, Journal of Media Economics & Culture, 7(4), 7-45.
  41. M. J. Kim, C. K. Lee, & M. Bonn. (2016). The effect of social capital and altruism on seniors' revisit intention to social network sites for tourism-related purposes. Tourism Management, 53, 96-107. DOI : 10.1016/j.tourman.2015.09.007
  42. M. J. Kim, C. K. Lee, & M. W. Preis. (2016). Seniors' loyalty to social network sites: Effects of social capital and attachment. International Journal of Information Management, 36(6), 1020-1032. DOI : 10.1016/j.ijinfomgt.2016.04.019
  43. D. H. Sung. (2011). A study on the e-Book usage intention and adopting decision factor in the generation of smart media. Doctoral Dissertation, Chungang University.
  44. S. S. Suh. (2011). Exploration of digital textbook adoption and implementation based on an extended technology acceptance model, Journal of the Korean Association of Information Education, 15(2), 265-275.
  45. S. H. Yoo. (2013). Initial mobile instant messenger users' behavioral studies using the technology acceptance model. Master's Thesis, Hong-ik University.
  46. O, S. Kim. (2017). A study on factors influencing purchase intention of personal VR devices. Master's Thesis, Yonsei University.
  47. B. S. Kim & H. J. Woo. (2019). A study on the intention to use AI speakers: Focusing on extended technology acceptance model. Journal of the Korea Contents Association, 19(9), 1-10. https://doi.org/10.5392/JKCA.2019.19.09.001
  48. J. M. Lee. (2012). What drives a successful e-learning: Focusing on the critical factors influencing e-learning satisfaction. Korean Journal of Business Administration, 24(4), 2245-2257.
  49. J. K. Lee & K. S. Kang. (2015). A study on the determinants of acceptance intention in customized smart advertising: With a focus on a group of college students. Journal of Speech, Media & Communication Association, 26, 85-114.