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유튜브 '먹방' 콘텐츠 이용 동기와 지속이용의도 통합모델: 이용과 충족접근, 기술수용모델을 중심으로
An Integrated Model for the YouTube 'Mukbang' Content use Motivation and Continuous Use Intention: Focusing on Uses and Gratifications Approach and Technology Acceptance Model 원문보기

디지털융복합연구 = Journal of digital convergence, v.19 no.12, 2021년, pp.413 - 425  

권오천 (경남도립남해대학)

초록
AI-Helper 아이콘AI-Helper

본 연구는 이용과 충족접근, 기술수용모델을 통합 적용하여 유튜브 '먹방'콘텐츠 이용동기와 지속이용의도를 살펴보았다. 본 연구에서는 유튜브 '먹방' 콘텐츠 이용자 358명을 대상으로 설문조사를 통해 SPSS 21.0 프로그램과 AMOS 21.0 프로그램을 활용, 탐색적/확인적 요인분석경로분석 등을 실시하여 핵심 결과를 도출하였다. 결과를 제시하면, 첫째, 유튜브 '먹방' 콘텐츠 이용 동기 중 정보추구 동기와 스트레스 해소 동기, 시간보내기 동기는 인지된 유용성에, 정보추구 동기와 시간보내기 동기는 인지된 용이성에 정적 영향을 미쳤다. 둘째, 정보추구 동기, 스트레스 해소 동기, 시간보내기 동기는 공통적으로 인지된 즐거움과 인지된 독창성에 정적 영향을 미쳤다. 셋째, 인지된 즐거움은 인지된 용이성에는 정적 영향을 미쳤다. 넷째, 인지된 즐거움과 인지된 독창성은 모두 지속이용의도에 정적 영향을 미쳤다. 다섯째, 인지된 용이성은 인지된 유용성에 대해 정적 영향을 미쳤으며, 인지된 용이성과 인지된 유용성 모두 지속이용의도에 정적 영향을 미쳤다. 본 연구는 이용과 충족접근, 기술수용모델을 통합 적용하여 유튜브 '먹방' 콘텐츠의 지속이용을 파악할 수 있는 모델을 정교화하였다는 점에서 학술적 의의가 있을 것이다. 후속연구에서는 유튜브 '먹방' 콘텐츠의 지속이용의도 관련 모델의 정교화를 위해 다양한 이론과 모델들을 통합 적용해 볼 필요가 있을 것이다.

Abstract AI-Helper 아이콘AI-Helper

This study examines the motivation for using YouTube 'mukbang' content by integrating the use and satisfaction approach and the technology acceptance model, and identified the determinants that affect the continuous use intention. A survey was conducted on 358 YouTube 'mukbang' content users, and ma...

주제어

표/그림 (7)

참고문헌 (52)

  1. M. J. Kang & C. H. Cho. (2020). A Study on Use Motivation, Consumers' Characteristics, and Viewing Satisfaction of Need Fulfillment Video Contents(Vlog/ASMR/Muk-bang). The Journal of the Korea Contents Association, 20(1), 73-98. DOI: 10.5392/JKCA.2020.20.01.073 

  2. Y. J. Jang & M. R. Kim. (2016). Need for Interaction or Pursuit of Information and Entertainment?: The Relationship among Viewing Motivation, Presence, Parasocial Interaction, and Satisfaction of Eating and Cooking Broadcasts. Korean Journal of Broadcasting and Telecommunication Studies, 30(4), 152-185. 

  3. Kobaco. (2019). Media & Consumer Research. 

  4. Tube Road. (2021.02.18.). Top 10 Mukbang YouTubers Earnings Rankings. http://www.tuberoad.net/news/articleView.html?idxno2552 

  5. S. T. An & J. Y. Lee. (2021). Effects of AD Disclosure and Motivation for Watching Mukbang on Viewers' Eating Intent. Korean Journal of Journalism & Communication Studies, 65(3), 39-79. DOI : 10.20879/kjjcs.2021.65.3.002 

  6. S. T. An, Y. J. Lim, & H. N. Lee. (2020a). A Study of Viewers' Comments on Online Mukbang Videos: A Big Data Analysis of Perceptions Toward Eating Behavior. Korean Journal of Journalism & Communication Studies, 64(2), 269-310. 

  7. F. Kaufman. (2005). Debbie Does Salad: The Food Network at the Frontiers of Pornography. Harper's Magazine, Oct. https://harpers.org/archive/2005/10/debbie-does-salad/ 

  8. E. K. Na. (2015). "Eating Broadcasts" and "Cooking Broadcasts" Exploratory Study on Food Media Trends: Socio-Cultural Backgrounds and New Media Use Factors. Kookmin Social Science Reviews, 28(1), 183-215. 

  9. S. T. An, Y. J. Lim, & H. N. Lee. (2020b). A Content Analysis of Eating Show (Mukbang) Programs on Television and Online Program Content in South Korea. Korean Journal of Broadcasting and Telecommunication Studies, 34(4), 39-79. 

  10. H. S. Kwon. (2019). A Study on the Effect of View Motives on the View Satisfaction and Behavior Intentions of One-Person Media Food Contents: Focused on 'Mokbang' and 'Cookbang'. Culinary Science & Hospitality Research, 25(6), 102-112. DOI : 10.20878/cshr.2019.25.6.010 

  11. E. J. Park & K. S. Cho. (2020). The Effect of Muk-Bang Channel Viewing Motivation on Viewing Attitude, Viewing Satisfaction, and Word of Mouth Intention. Journal of Public Policy Studies, 37(2), 355-375. 

  12. D. Lupton. (2015). Food, the Body and the Self. London: Sage Publications. 

  13. L. Pope, L. Latimer, & B. Wansink. (2015). Viewers vs. Doers. The Relationship between Watching Food Television and BMI. Appetite, 90, 131-135. DOI: 10.1016/j.appet.2015.02.035 

  14. E. Katz, J. G. Blumler, & M. Gurevitch. (1974). Utilization of Mass Communication by the Individual. In J. G. Blumler & E. Katz (Eds.), The Users of Mass Communications: Current Perspective on Gratification Research (pp. 19-32). Beverly Hills, CA: Sage. 

  15. D. W. Kim & Y. J. Lee. (2014). The Impact of Watching Motives of Parenting Reality TV Program on User Satisfaction and Rewatching. Journal of Broadcasting Engineering, 19(6), 925-933. DOI : 10.5909/JBE.2014.19.6.925 

  16. A. M. Rubin. (2009). Uses and Gratifications Perspective on Media Effects. In J. Bryant and M. B. Oliver (Eds.), Media Effects: Advances in Theory and Research. Routledge, 165-184. 

  17. A. M. Rubin. (2002). The Uses-and-Gratifications Perspective of Media Effects. In J. Bryant & D. Zillmann (Eds.), Media Effects: Advances in Theory and Research (pp. 525-548). Lawrence Erlbaum Associates Publishers. 

  18. J. K. Lee, M. E. Choi, & S. B. Park. (2012). A Study on College Students Intention to Accept Paid Mobile News Content Provided by Daily Newspapers: Application of a Combined Model between TAM and Uses & Gratification. Journal of Media Economics & Culture, 10(3), 129-172. 

  19. C. R. Plouffe, J. S. Hulland, & M. Vandenbosch. (2001). Research Report: Richness Versus Parsimony in Modeling Technology Adoption Decisions-Understanding Merchant Adoption of a Smart Card-based Payment System. Information Systems Research, 12(2), 208-222. DOI:10.1287/isre.12.2.208.9697 

  20. D. Gefen, E. Karahanna, & D. W. Straub. (2003). Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly, 27(1), 51-90. https://doi.org/10.2307/30036519 

  21. V. Venkatesh & H. Bala. (2008). Technology Acceptance Model 3 and A Research Agenda on Interventions. Decision Sciences, 39(2), 273-315. https://doi.org/10.1111/j.1540-5915.2008.00192.x 

  22. J. R. Kim, K. H. Lee, & Y. K. Choi. (2011). A Study of Motivations and Intentions to Use Smart Phone Applications as Advertising Media: An Extension of Technology Acceptance Model. Advertising Research, 89, 229-254. 

  23. B. N. Park. (2011). Integrative Adoption Model of New Media (IAM-NM). Korean Journal of Journalism & Communication Studies, 55(5), 448-479. 

  24. Z. Y. Wang & S. W. Choo. (2021). The Effects of Chinese Tourist Motivation for Using Smartphone and Smart Tourism Experience on Behavior Intention by TAM. Journal of Tourism and Leisure Research, 33(6), 61-80. DOI : 10.31336/JTLR.2021.6.33.6.61 

  25. Y. B. Jang. (2019). Effects of AI Speaker User's Usage Motivations and Perception of Relationship Type with AI Speaker on Enjoyment. The Journal of the Korea Contents Association, 19(11), 558-566. DOI : 10.5392/JKCA.2019.19.11.558 

  26. M. H. Choi. (2014). The Study on a Teenager's Credibility on Social Media: Focusing on Their Motivation, Attitude and Social Capital. Master's Thesis, Sogang University. 

  27. W. H. Na & H. L. Dong. (2021). Factors for Intention to Use for Digital Contents Subscription Service in Korea. Journal of Digital Contents Society, 22(5), 755-766. 

  28. V. Venkatesh & M. G. Morris. (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 

  29. E. G. Kim. (2019). A Study on Factors Affecting the Use of 'Eating' TV Program and 'Cooking' TV Program. Master's Thesis, Sungkyunkwan University. 

  30. K. Ray. (2007). Domesticating Cuisine: Food and Aesthetics on American Television. Gastronomica: The Journal of Food and Culture, 7(1), 50-63. 

  31. C. Ketchum. (2005). The Essence of Cooking Shows: How the Food Network Constructs Consumer Fantasies. Journal of Communication Inquiry, 29(3), 217-234. DOI:10.1177/0196859905275972 

  32. J. Webster, L. K. Trevino, & L. Ryan. (1993). The Dimensionality and Correlates of Flow in Human-Computer Interaction. Computers in Human Behavior. 9, 411-426. https://doi.org/10.1016/0747-5632(93)90032-N 

  33. C. S. Lin, S. Wu, & R. J. Tsai. (2005). Integrating Perceived Playfulness into Expectation-Confirmation Model for Web Portal Context. Information & Management, 42(5), 683-693. https://doi.org/10.1016/j.im.2004.04.003 

  34. R. Agarwal & E. Karahanna. (2000). Time Flies When You're Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage. MIS Quarterly, 24(4), 665-694. DOI:10.2307/3250951 

  35. Q. Q. Chen & H. J. Park. (2018). Consumer Study on the Acceptance of VR Headsets based on the Extended TAM. Journal of Digital Convergence, 16(6), 117-126. DOI : 10.14400/JDC.2018.16.6.117 

  36. H. J. Jang & G. Y. Noh. (2017). Extended Technology Acceptance Model of VR Head-Mounted Display in Early Stage of Diffusion. Journal of Digital Convergence, 15(5), 353-361. DOI : 10.14400/JDC.2017.15.5.353 

  37. J. S. Park & J. W. Byun. (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 & Leisure Research, 25(1), 419-435. 

  38. S. J. Lee, J. H. Park, & J. W. Kim. (2010). Effects of Content Characteristics on the Flow and Perceived Novelty: Focused on Characters and Narratives of Video UCC. Journal of Korean Society of Design Science, 23(3), 53-68. 

  39. S. S. Han. (2017). Influence Factor Analysis of Mobile Game Using Time. Master's Thesis, Kwangwoon University. 

  40. J. S. Hwang. (2020). A Study on the Influence of Consumers' Continuous Use Intention on Beauty Contents of Social Media System. Doctoral Dissertation, Soongsil University. 

  41. S. W. Byun. (2019). The Influence of YouTube Attributes on the Purchase Intention of Fashion Products: The Mediating Effect of Content Flow and Channel Continuance Usage Intention. Doctoral Dissertation, Kyunghee University. 

  42. J. M. Shin. (2020). An Effect of Travel YouTube Attributes on Flow and Continuous Using Intention: Focusing on Moderating Effect of YouTube User's Sensation Seeking and Need for Cognition. Master's Thesis, Donga University. 

  43. F. D. Davis. (1993). User of Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts. Journal of Man-Machine Studies, 38(3), 475-487. https://doi.org/10.1006/imms.1993.1022 

  44. F. D. Davis, Bagozzi, R. P., & P. R. Warshow. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology, 22, 1111-1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x 

  45. M. K. Lee, W. J. Kim, & M. H. Song. (2019). A Study on the Factors Influencing Continuous Intention to Use of OTT Service Users: Focused on the Extension of Technology Acceptance Model. Journal of Digital Convergence, 17(11), 537-546. DOI : 10.14400/JDC.2019.17.11.537 

  46. P. Ketikidis, T. Dimitrovski, L. Lazuras, & P. A. Bath. (2012). Acceptance of Health Information Technology in Health Professionals: An Application of the Revised Technology Acceptance Model. Health Informatics Journal, 18(2), 124-134. DOI: 10.1177/1460458211435425 

  47. S. K. Kim, J. Y. Kim, H. K. Kim, S. T. An, Y. J. Lim, & H. S. Park. (2020). Association Between Food-related Media Program Watching and Dietary Behaviors in Korean Adolescents. Korean Public Health Research, 46(3), 31-46. DOI : 10.22900/kphr.2020.46.3.003 

  48. H. S. Eu & J. S. Lee. (2019). The Effects of Youtube Based Beauty Content Usage Motivation on Perceived Usefulness, Perceived Ease of Use and Continuous Use Intention of Young Women. Journal of Investigative Cosmetology, 15(1), 95-105. DOI : 10.15810/jic.2019.15.1.011 

  49. 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 

  50. K. S. Lee, J. P. Yu, & S. A. Lim. (2020). A Study on Factors Affecting the Intention to Use Artificial Intelligence(AI) Speakers: Focusing on the Extended Technology Acceptance Model(E-TAM). The Society of Convergence Knowledge Transactions, 8(4), 59-69. 

  51. J. E. Woo. (2008). The Effects of Interactivity and Vividness on E-Brand Loyalty in Fashion Internet Shopping Mall: Focus on the Role of Shopping Value and Web Stickiness as a Mediating Variable. Master's Thesis, Ewha Womans University. 

  52. S. J. Moon. (2019). The Effects of Characteristics of YouTube-based Beauty Contents on Contents Satisfaction and Continuous Use Intention: Focused on Level of Involvement (Low vs. High). Master's Thesis, Sungkyunkwan University. 

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