디지털융복합연구 (Journal of Digital Convergence)

  • 제18권5호
  • /
  • Pages.233-247
  • /
  • 2020
  • /
  • 2713-6434(pISSN)
  • /
  • 2713-6442(eISSN)
한국디지털정책학회 (The Society of Digital Policy and Management)
권호 표지
DOI QR코드

DOI QR Code

소셜 미디어 정보속성이 정보유용성과 고객 태도에 미치는 영향 -정교화 가능성 모델(ELM)을 중심으로-

The effect of Social Media Information Attributes on perceived Information usefulness and Customer Attitudes

  • 류수형 (호서대학교 벤처대학원 정보경영학과) ;
  • 이소영 (호서대학교 벤처대학원 정보경영학과)
  • Ryu, Soo-Hyung (Department Of Information Management, Graduate School Of Venture, Hoseo University) ;
  • Lee, So-young (Department Of Information Management, Graduate School Of Venture, Hoseo University)
  • 투고 : 2020.04.16
  • 심사 : 2020.05.20
  • 발행 : 2020.05.28
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

소셜미디어인 동영상콘텐츠 플랫폼은 높은 몰입도와 이용 편이성 그리고 제약이 낮은 제작 환경으로 다양한 콘텐츠 생산 수단으로 활용되고 있다. 하지만 기존 소셜미디어 관련 연구들은 플랫폼 유형이 따른 차이에도 불구하고 기존의 정보속성과의 차이를 살펴본 연구가 미흡하였다. 이에 본 연구에서는 기존 미디어와 소셜미디어 정보속성에 따른 영향 관계를 살펴보고자 한다. 213명의 동영상콘텐츠 사용자들을 대상으로 설문을 실시하여 연구모형을 분석하였다. 연구모형 분석 결과 정보유희성, 정보적시성과 정보제공자 신뢰성은 정보유용성에 유의한 영향을 미쳤다. 하지만 정보생생함, 정보정확성, 정보중립성과 정보제공자의 전문성은 유의한 영향을 미치지 못했다. 본 연구를 통해 동영상콘텐츠와 기존 미디어나 소셜미디어와의 차이점을 알 수 있었으며, 신뢰성 있는 정보제공자가 적절한 시기에 즐거운 콘텐츠를 제공해야 함을 알 수 있었다. 또한 소셜미디어 성장세의 키플레이어인 동영상콘텐츠의 정보처리과정 이해를 통해 양질의 콘텐츠 제작에 많은 도움이 될 것으로 판단한다.

The video content platform, which is a social media, is used as a means of producing various contents with high immersion, ease of use, and low production conditions. However, existing social media-related studies were insufficient to examine differences in existing information attributes despite the differences in platform types. Therefore, this study intends to examine the relationship between existing media and social media information attributes. The research model was analyzed by surveying 213 video content users. As a result of the research model analysis, information playability, information timeliness, and information provider reliability had a significant effect on information usefulness. However, information vividness, information accuracy, information neutrality, and professionalism of information providers did not have a significant effect. Through this study, the difference between video content and existing media or social media was found, and it was found that a reliable information provider should provide pleasant content at the right time. In addition, through the understanding of the information processing process of video content, which is a key player in the growth of social media, we believe that it will be very helpful in producing quality content.

키워드

참고문헌

  1. DMC MEDIA. (2019). 2019 Social Media Status and Prospect : Market Report Study
  2. E. K. Na (2015). 'Eating broadcasts' and 'Cooking broadcasts' Exploratory study on food media trends: Socio-cultural backgrounds and new media use factors. Koomin Social Science Revies, 28(1), 183-215.
  3. S. M. Kwon & S. M. Lee. (2018). The effects of famous restaurant information service attributes on economic value, satisfaction and customer loyalty. The Korea Academic Society Of Tourism And Leisure, 50, 379-393.
  4. S. J. Park.(2012). The effects of famous restaurant information service attributes on economic value, satisfaction and customer loyalty. Master's degree, SungKyunKwan University, Seoul
  5. J. Lee, H. S. Yoon & H. H. Yoon. (2017). Effect of TV Restaurant Review Program Attributes on Food Service Consumer's Empathy, Attitude, and Visit Intentions. The East Asian Society of Dietary Life, 27(2), 204-214. DOI : 10.17495/eadl.2017.4.27.2.204
  6. H. J. Sung & H. Y. Kim. (2019). The effects of food service information attributes on perceived information usefulness and visit intention in TV food contents broadcasting programs: moderating effect of market mavenism, Journal of Hospitality & Tourism Studies, 21(3), 222-238 DOI : 10.14400/JDC.2016.14.12.1
  7. H. J. Yu & H. Kim. (2020). The Effect of Influencer Factors in Personal Media Contents on Purchase Intention. Journal Of The Korea Contents Association, 20(1), 45-59. https://doi.org/10.5392/JKCA.2020.20.01.045
  8. H. M. Cho. (2011). Introduction of Digital Media and Consequent New Risk Types.
  9. Wood, W. (2000). Attitude Change: Persuasion and Social Influence. Annual Review of Psychology, 51, 539-570. https://doi.org/10.1146/annurev.psych.51.1.539
  10. Bhattacherjee, A., and C. Sanford. (2006). Influence Processes for Information Technology Acceptance: An Elaboration Likelihood Moder, MIS Quarterly, 30(4), 805-825. https://doi.org/10.2307/25148755
  11. Cacioppo, J. T. and R. E. Petty(1984) The Elaboration Likelihood Model of Persuasion, Advances in Consumer Research, 11(1), 673-675.
  12. W. K. Lee. (2008). An Longitudinal Analysis of Changigng Belidfs on the Use in IT Educatee by Elaboration Likelihood Model, Asia Pacific Journal of Information Systems, 18(3), 147-165.
  13. Tam, K. Y. and S. Y. Ho, (2005). Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective, Information Systems Research, 16(3), 271-291. https://doi.org/10.1287/isre.1050.0058
  14. Zhang, K. Z., Lee, M. k., & Zhao, S, J. (2010). Understanding the Informational Social Influence of Online Review Platforms. ICIS, 71.
  15. Ohanian, R.. (1990). Construction and Validation of a scale to measure celebrity endorsers' perceived expertise, trustworthiness, and attractiveness. Journal of Advertising, 19(3), 39-52. https://doi.org/10.1080/00913367.1990.10673191
  16. Stiff, J. (1994). Persuasive Communication, New York : Guilford.
  17. Babin, B. J. Darden, W. R. & Grifin, M(1994). Work and or Fun: Measuring Hedonic and Utilitarian Shopping Value, Journal of consumer research, 20, 644-656. https://doi.org/10.1086/209376
  18. Huzinga, Johan.(1995). Home Indens: A Study of the Play Element in Culture, Boston, MA: The Beacon Press.
  19. Babin, B. J. Darden, W. R. & Grifin, M(1994). Work and or Fun: Measuring Hedonic and Utilitarian Shopping Value, Journal of consumer research, 20, 644-656. https://doi.org/10.1086/209376
  20. Ballow, D. P. and H. L. Pazer(1985). Modeling Data and Process Quality in Multi-input, Multi-output Informatio System, Management Science, 31, 150-162. https://doi.org/10.1287/mnsc.31.2.150
  21. Webster, J. and J. J. Martocchio(1992), Micro Compter Playfulness: Deveopment of a Measure with Workplace Inplications, MIS Quarterly, 16(2), 201-226. https://doi.org/10.2307/249576
  22. B. C. Jung & J. O. Koo. (2013). The Effects of SNS Messengers Traits and Information Charateristics on the Purchase Intention. Korean Corporation Management Review, 48, 251-272
  23. H. J. Park, J. H. Park, J. H. Yoon & Y. H. Kim. (2014). A Study on the Effect of Tourist-Tourism Information Sharing Intention in Tourism Social Network Service(SNS): Considering Tourism Information Quality. Journal of Tourism and Leisure Research, 26(2), 259-277.
  24. J. H. Lee & K. H. Kim. (2002). A Study on the Training en Expert in Tourism Information Management. The Foodservice Management Society Of Korea, 5(2), 183-201.
  25. N Agarwal & Y. Yiliyasi. (2010). Information quality challenges in social media. Department of information Science The University of Arkansas at Little Rock.
  26. Olshavky, Richard W. and Donald H. Granbois (1979), "Consumer Decision Making: Fact or Fiction?" Journal of Consumer Research, 6 (September), 93-100. https://doi.org/10.1086/208753
  27. S. H. Park. (2009) Acceptance Process of Word-of-Mouth on Internet Consumer Community Doctoral dissertation. Yeosei University, Seoul
  28. Chatterjee, P. (2001). Online reviews: Do consumers use them? 65 Advances in Consumer Research, 28, 129-133.
  29. C. Park & C. J. Yoo. (2006). Study on the effects fo consumer's word of mouth about brand experience and responses on brand evalutions at online context. Journal of consumer studies, 17(1), 73-93.
  30. J. H. Lee, S. J. Doh & J. S. Hwang. (2011). The Effectiveness of Online WOM(Words-of-Mouth): The Role of Direction, Usefulness, and IR(Interaction Readiness). The korean journal of consumer and advertising psychology, 12(2), 283-307. https://doi.org/10.21074/KJLCAP.2011.12.2.283
  31. S. Y. Jun & K. H. Kim. (2012). The Influence of Two-sided WOM on Consumers' Brand Attitudes in an Online Context. Korean journal of marketing, 27(1), 45-66.
  32. S. H. Kim. (2013). Online Product Word-of-Mouth is Information Whether Persuade Knowledge or Valuable for Consumers -The Moderation of Regulatory Focus on Customer Purchase Intention. Advertising Research, 96, 7-46.
  33. Smithson, M. (1999). Conflict aversion: Preference for ambiguity vs conflict in sources and evidence. Organizational Behavior and Human Decision Processes, 79(3), 179-198. https://doi.org/10.1006/obhd.1999.2844
  34. T. W. Park & K. Y. Lee. (2014). An Integrated Model of Information Processing of eWOM in Social Network Service. Advertising Research, 100, 172-224.
  35. H. S. Lee & D. R. Lee. (2004). A study on the effects of online postscript as Word-of-Mouth, Journal of public relations 8(2), 234-268.
  36. Elliott, D., Lavrysen, A., Helsen, W. F., & Adam, J. J. (2002). The one-target advantage: Advanced preparation or online processing? Motor Control, 6(3), 230-245. https://doi.org/10.1123/mcj.6.3.230
  37. Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source versus message cues in persuasion. Journal of personality and social psychology, 39(5), 752-766 https://doi.org/10.1037/0022-3514.39.5.752
  38. Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: an integrated approach to knowledge adoption. Information Systems Research, 14(1), 47-65. https://doi.org/10.1287/isre.14.1.47.14767
  39. Jones, Lee W, Sinclair, Robert C, Courneya, Kerry S. (2003). The Effects of Source Credibility and Message Framing on Exercise Intentions, Behaviors, and Attitudes: An Integration of the Elaboration Likelihood Model and Prospect Theory. Journal of Applied Social Psychology, 33(1), 179-196. https://doi.org/10.1111/j.1559-1816.2003.tb02078.x
  40. Horner, P.M. and Kahle, L.R., (1988), A structural equation test of the - 175 value-attitude-behavior hierarchy, Journal of Personality and Social Psychology, 54(4) : 638-646 https://doi.org/10.1037/0022-3514.54.4.638
  41. Giffin, K. (1967). The contribution of studies of source credibility to a theory of interpersonal trust in the communication process. Psychological bulletin, 68(2), 104-120. https://doi.org/10.1037/h0024833
  42. Salo, J., & Karjaluoto, H. (2007). A conceptual model of trust in the online environment. Online Inforamtion Review, 31(5), 604-621. https://doi.org/10.1108/14684520710832324
  43. Zhang W., & Watts S. (2008). Capitalizing on content: information adoption in two online communities. Journal of the Association for Information Systems, 9(2), 73–94. https://doi.org/10.17705/1jais.00149
  44. Zhang, W., & Watts, S. (2002). Donkeys Travel the World: Knowledge Management in Online Communities of Practice. AMCIS 2002.
  45. E. H. Kim, L Fan, S. C. Lee & Y. H. Suh. (2012). Continuous Usage Intention of Twitter's Informations Focus on Elaboration Likelihood Model Korea Society of IT Services, 11(3), 49-65.
  46. T. W. Park (2014). A study on the integrated model of eWOM effects through social network service. Master's degree dissertation. Kyung Hee University, Seoul
  47. B. J. Fogg, C. Soohoo, D. R. Danielson, L.. Marable, J. Stanford & E. R. Tauber. (2003, June). How do users evaluate the credibility of Websites?: a study with over 2,500 participants. Proceedings of the 2003 conference on designing for user experiences. (pp. 1-15).
  48. Wilson, E. j., & Sherril, E. L. (1993). Source effects in communication and persuasion research: A meta-analysis of effect size.Journal of the Academy of Marketing Science, 21(2), 101-112. DOI 10. 1007/BF02894421 https://doi.org/10.1007/BF02894421
  49. Wu, C., & Shaffer, D. R. (1987). Susceptibility to persuasive appeals as a function of source credibility and prior experience with the attitude object. Journal of personality and social psychology, 52(4), 677-688. https://doi.org/10.1037//0022-3514.52.4.677
  50. K. S. Hur, Y. H. Ji & J. W. Byun. (2012) This study is to understand the consumer"s change of brand attitude and behavior intention through the process of determining the large amount of information by SNS. Korean Journal of Tourism Reserch, 27(5), 619-635
  51. H. Choi. (2006). The impact of quality factors on satisfaction in mobile internet services: User's motivational orientation and use contexts. Doctoral dissertation, Yonsei University, Seoul.
  52. D. J. Kim. (2011). An empirical study on user satisfaction and the influencing factors for continuous usage of social network service. Doctoral dissertation, Chung-Ang University, Seoul
  53. S. I. Baek, S. H. Bae & Y. Y. Song. (2014). Exploring moderating effects of customer's previous knowledge and involvement on online word-of-mouth adoption in the application markets. Entrue Journal of Information Technology, 13(3), 21-34
  54. J. M. Lee. (2012). A Study on the Effect of Sociability, Ease of Use, Usefulness, Enjoyment on Acceptance Intention in e-Learning - A Perspective of the Extended Technology Acceptance Model. Journal of the korea contents association. 12(4), 417-425 https://doi.org/10.5392/JKCA.2012.12.04.417
  55. Y. C. Kim & H. M. Chung. (2007) The relationship analysis among influential factors to the effectiveness of on-line WOM at service industry. The korean journal of advertising. 18(4), 167-183
  56. Bhattacherjee, A., & Sanford, C. C.(2006). Influence processes for information technology acceptance. An elaboration likelihood model. MIS Quarterly, 30(4), 805-825. https://doi.org/10.2307/25148755
  57. Ohanian, R.. (1990). Construction and Validation of a scale to measure celebrity endorsers' perceived expertise, trustworthiness,
  58. S. Ha & j. Ahn. (2011). Why Are You Sharing Others' Tweets?: The Impact of Argument Quality and Source Credibility on Information Sharing Behavior. ICIS Proceedings, 1-11.
  59. Chen, C. D., & Ku, C. S.(2012). Building Member's Relationship Quality Toward Online Community From The Elaboration Likelihood Model Perspective. Proceedings of the Pacific Asia Conference on Information Systems (PACIS).
  60. Li, C. Y.(2013). Persuasive messages on information system acceptance: A theoretical extension of elaboration likelihood model and social influence theory. Computers in human behavior, 29(1), 264-275. https://doi.org/10.1016/j.chb.2012.09.003
  61. Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research Reading. Massachusetts: Addison-Wesley.
  62. Petty, R. E., & Cacioppo, J. T. (1981). Issue involvement as a moderator of the effects on attitude of advertising content and context. Advances in Consumer Research, 8(1), 20-24.
  63. Wilkie, W. L. (1990). Consumer Behavior. NY: Wiley
  64. Chaiken, S., and Maheswaran, D. (1994). Heuristic Processing can Bias systematic Processing: Effects of Source Credibility, Argument Ambiguity, and Task Importance on attitude Judgment. Journal of personality and Social Psychology, 66(3), 460-473. https://doi.org/10.1037/0022-3514.66.3.460
  65. Reimer, A., & Kuehn, R. (2005). The impact of servicescape on quality perception. European Journal of Marketing, 39(7/8), 785-808. https://doi.org/10.1108/03090560510601761
  66. I. S. Lee. (2018). A Study on the Causal Relationship Between the Information-Processing and Visiting Intention of Fine Dining Consumers Under Multi-Channel Environment: The Perspective of Elaboration Likelihood Model (ELM) Doctoral dissertation, Kyung Hee University, Seoul.
  67. K. P. Lee & S. M. Kwon. (2020). Consumer Awareness and Visit Intention of Instagram Majib Information. Journal of Tourism and Leisure Research, 32(1), 255-273. https://doi.org/10.31336/jtlr.2020.1.32.1.255
  68. H. J. Lee. (2012). A Study on Interction affecting factor and information sharing and creation intention in Social Network Services. Doctoral dissertation, Seoul National University, Seoul.
  69. S. M. Jung. & Y. H. Kim. (2015). A Study on the Effects of SNS Information Characteristics and SNS Site Characteristics on the Intention to Visit a Restaurant. Culinary Science & Hospitality Research, 21(1), 159-173. https://doi.org/10.20878/cshr.2015.21.1.012012012
  70. S. J. Kim. & J. H. Yoon. (2016). The Effects of Information Attributes and Reputation of Travel Power blog on Travellers Information Acceptance : An Elaboration Likelihood Model. Korean Journal of Hospitality & Tourism, 25(2), 145-160.
  71. D. H. Cheon. & H. J. Lee. (2012). A Study of effect on trust, acceptance and spread of word-of-mouth and purchase intention by characteristics of electronic word-of-mouth on travel industry. .The Academy of Customer Satisfaction Management, 14(1), 83-100.
  72. E. H. Cho. & J. S. Han. (2018). The effect of video User Created Content tourism information quality on user's satisfaction, visit intention and information sharing intention. .Korean Journal of Hospitality & Tourism, 27(2), 163-179. https://doi.org/10.24992/kjht.2018.02.27.02.163.
  73. Davis, F. D. (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
  74. David L. Loudon & Albert J. Della Bitta. (1984). Consumer Behavior, Concepts and Applications, 2nd ed., N.Y.: Mcgraw-Hill Book Company.
  75. S. K. Kang. (2014). The Influence of Virtual Experiential Marketing on Customer Attutude and Purchase Intention. Doctoral dissertation, Gachon University, Seongnam-City.
  76. D. H. Kim. (2008). AMOS A to Z. : Hakhyunsa.
  77. Y. H. Ji, K. S. Hur & J. W. Byun. (2013) A Study of The Structural Relationship between The Information of SNS and The Impulsive Buying. Korean Journal of Hospitality & Tourism, 22(3), 119-134.
  78. S. J. Kim & S. M. Jung. (2014) The Effect of SNS Users Characteristics and Informational Values on the Information Acceptance Intention. The Journal of Internet Electronic Commerce Research, 14(6), 127-146.
  79. K. Y. Kim & S. B. Kyung. (2018) The Effect of social network service(SNS)-based food content information quality on user satisfaction, intention to use, and information sharing intention. International Journal of Tourism and Hospitality Research, 32(8), 177-192. https://doi.org/10.21298/ijthr.2018.08.32.8.177
  80. J. S. Kim & S. B. Yang. (2019) The Effect of Content Quality and Creator Attributes on the Satisfaction and Behavioral Intention on Personal Broadcasting Muckbang Channels: Based on the Elaboration Likelihood Model. The Journal of Internet Electronic Commerce Research, 19(5), 257-281.
  81. S. J. Kim & C. B. Kim. (2017) A Study on the Relationships among SNS Information Characteristics, the Characteristics of Information Provider and the Intention to Visit the Restaurants: Focused on Millennials Generation. Korean Association Of Business Education, 32(4), 279-299. https://doi.org/10.23839/kabe.2017.32.4.279