한국IT서비스학회지 (Journal of Information Technology Services)

한국IT서비스학회 (Korea Society of IT Services)
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조직 내 빅데이터 시스템 확산에 영향을 주는 요인에 대한 연구

Factors for the Intra-organizational Diffusion of Big Data Systems

  • 박성관 (LGCNS Enterprise빅데이터담당 제조빅데이터1팀) ;
  • 김청 (한국공항공사 Smart Airport팀, 성균관대학교 경영학)
  • 투고 : 2019.05.03
  • 심사 : 2019.06.03
  • 발행 : 2019.06.30
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초록

In this paper, factors affecting intra-organizational diffusion of Big Data systems from the perspective of the Big Data system vendors have been analyzed. In particular, the theory of resistance against innovation that exists in some form before the adoption or rejection of innovation has been focused on. In order to do that, the resistance has been divided into three categories : postponement, rejection and opposition. The variables affecting each type are also divided into four independent variables : perceived risk, innovation characteristics, user attributes, and organizational attributes. As a result of the survey, it was confirmed that the influences of each variable are different according to the type of resistance. As the strength of the resistance was increased, the influence of the trialability was increased as well. As the strength of the resistance was decreased, the satisfaction with the existing system became more influential on the resistance. The time risk and the satisfaction with the existing system were found to affect all types of resistance. From the vendor's point of view, strategic implications are presented in terms of marketing or system development for diffusion, depending on the degree of resistance of the adopter.

키워드

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2017 Big Data Market Survey(NIA, 2018)

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2017 Market Size for Big Data(NIA, 2018)

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Big Data System Architecture(Proposal of Big Data Analytics System for Big Traffic Relieve, Ahn et al., 2016)

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Research Model

Demographic Information of Respondents

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Variables and Questions

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Variables and Questions(Continued)

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EFA Results

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EFA Results of Resistance

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Multiple Regression Analysis : Factors that Influence Postponement

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Multiple Regression Analysis : Factors that Influence Rejection

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Multiple Regression Analysis : Factors that Influence Opposition

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Relative Influence of Variables

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Correlations

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Result of Fisher’s Z

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참고문헌

  1. Ahn, D., H. Kim, and S. Hong, "Proposal of Big Data Analytics System for Big Traffic Relieve", The Korean Institute of Communications and Information Sciences, 2016, 1103-1104
  2. Alavi, M., T.R. Kayworth, and D.E. Leidner, "An empirical examination of the influence of organizational culture on knowledge management practices", Journal of Management Information Systems, Vol.22, No.3, 2005, 191-224. https://doi.org/10.2753/MIS0742-1222220307
  3. Alexander, M.B., J. Elam, and C. Wasala, "Multiple theoretical perspectives for studying the assimilation of emerging information technologies", Proceedings of the Twenty-Fifth Hawaii International Conference at the System Sciences, 1992.
  4. Avlonitis, G.J. and N.G. Panagopoulos, "Antecedents and consequences of CRM technology acceptance in the sales force", Industrial Marketing Management, Vol.34, No.4, 2005, 355-368. https://doi.org/10.1016/j.indmarman.2004.09.021
  5. Bearden, W.O., R.G. Netemeyer, and J.E. Teel, "Measurement of consumer susceptibility to interpersonal influence", Journal of Consumer Research, Vol.15, No.4, 1989, 473-481. https://doi.org/10.1086/209186
  6. Brancheau, J.C. and J.C. Wetherbe, "The adoption of spreadsheet software : testing innovation diffusion theory in the context of enduser computing", Information Systems Research, Vol.1, No.2, 1990, 115-143. https://doi.org/10.1287/isre.1.2.115
  7. Dabholkar, P.A. and R.P. Bagozzi, "An attitudinal model of technology-based self-service : moderating effects of consumer traits and situational factors", Journal of the Academy of Marketing Science, Vol.30, No.3, 2002, 184-201. https://doi.org/10.1177/0092070302303001
  8. Cho, C., "SPSS. AMOS application structure equation model thesis statistical analysis", Chungram, 2014.
  9. Choi, S., Y. Kang, S. Choi, and S. Choi, "A Study of the Impact of Organizational Characteristics on Collaborationamong Multi-purposed Community Social Welfare Centers", Academy of Korean Social Welfare Administration, Vol.9, 2003, 87-112.
  10. Damanpour, F., "Organizational innovation : A meta-analysis of effects of determinants and moderators", Academy of Management Journal, Vol.34, No.3, 1991, 555-590. https://doi.org/10.2307/256406
  11. Davis, F.D., R.P. Bagozzi, and P.R. Warshaw, "User acceptance of computer technology : a comparison of two theoretical models", Management Science , Vol.35, No.8, 1989, 982-1003. https://doi.org/10.1287/mnsc.35.8.982
  12. Ellen, P.S., W.O. Bearden, and S. Sharma, "Resistance to technological innovations : an examination of the role of self-efficacy and performance satisfaction", Journal of the Academy of Marketing Science, Vol.19, No.4, 1991, 297-307. https://doi.org/10.1007/BF02726504
  13. Han, H., J. Seo, and H. Lee, "Big Data Industry Status and Prospects", KISTI Market Report, Special Issue, 2013.
  14. Harrington, S.J. and T. Guimaraes, "Corporate culture, absorptive capacity and IT success", Information and Organization, Vol.15, No.1, 2005, 39-63. https://doi.org/10.1016/j.infoandorg.2004.10.002
  15. Hirschheim, R. and M. Newman, "Information systems and user resistance theory and practice", The Computer Journal, Vol.31, No.5, 1988, 398-408. https://doi.org/10.1093/comjnl/31.5.398
  16. Hirschman, E.C., "Innovativeness, novelty seeking, and consumer creativity", Journal of Consumer Research, Vol.7, No.3, 1980, 283-295. https://doi.org/10.1086/208816
  17. Hollis, C., "IDC digital universe study : Big Data is here, now what" 2011, Available at https://chucksblog.typepad.com/chucks_blog/2011/06/2011-idc-digital-universe-study-big-datais-here-now-what.html)
  18. Hwang, S., "Meta-Analysis Using R", hakjisa, 2015.
  19. Jacoby, J. and L.B. Kaplan, "The components of perceived risk", ACR Special Volumes, 1972.
  20. Jang, D. and S. Cho, "Intraorganizational diffusion and innovation resistance of high technology products", Asia Marketing Journal, Vol.1, No.2, 1999, 100-115.
  21. Jang, D. and S. Cho, "Intraorganizational Innovation Resistance in High-Tech Products Purchase Situations-Focusing on Enterprise Resource Planning-", Korea Marketing Review, Vol.15, No.2, 2000, 75-97.
  22. Joen, S., "Expectations and Realities for Big Data", LG Business Insight, Vol.10, 2012, 17.
  23. Kim, S., "A Empirical Study on the User Resistance to Information Systems Innovation", Journal of the Korea Management Association, No.20, 1999, 317-342.
  24. Kleijnen, M., N. Lee, and M. Wetzels, "An exploration of consumer resistance to innovation and its antecedents", Journal of Economic Psychology, Vol.30, No.3, 2009, 344-357. https://doi.org/10.1016/j.joep.2009.02.004
  25. KOREA Data Agency, "2017 BIG DATA Market Status Research", 2018.
  26. KOREA Data Agency, "2016 BIG DATA Market Status Reserch", 2017.
  27. KOREA Data Agency, "2017 Data Industry White Paper", 2017.
  28. Kuisma, T., T. Laukkanen, and M. Hiltunen, "Mapping the reasons for resistance to Internet banking : A means-end approach", International Journal of Information Management, Vol.27, No.2, 2007, 75-85. https://doi.org/10.1016/j.ijinfomgt.2006.08.006
  29. Kwahk, K. and S. Im, "The Determinants of IT Assimilation and Its Effect on Organizational Performance : An Innovation Diffusion Theory Perspective", Journal of the Korean Operations Research and Management Science Society, Vol.33, No.1, 2008, 149-168.
  30. Lee, S. and H. Lee, "A Study on an Integrative Model for Big Data System Adoption : Based on TOE, DOI and UTAUT", Journal of Information Technology Applications and Management, Vol.21, No.4, 2014, 463-483.
  31. Lewis, W., R. Agarwal, and V. Sambamurthy, "Sources of influence on beliefs about information technology use : An empirical study of knowledge workers", MIS Quarterly, 2003, 657-678.
  32. Lim, J. and J. Oh, "Study on the Effect of the Characteristics of Cloud Computing Services on Perceived Expectancy Performance and Intention to Use-Focusing on the Innovation Diffusion Theory", Asia Pacific Journal of Information Systems, Vol.22, No.3, 2012, 99-124.)
  33. Manyika, J., M. Chui, B. Brown, J. Bughin, R. Dobbs, C. Roxburgh, and A.H. Byers, "Big Data : The next frontier for innovation, competition, and productivity", 2011.
  34. Martinko, M.J., R.W. Zmud, and J.W. Henry, "An attributional explanation of individual resistance to the introduction of information technologies in the workplace", Behaviour and Information Technology, Vol.15, No.5, 1996, 313-330. https://doi.org/10.1080/014492996120085a
  35. Moore, G.A., "Crossing the chasm", 2002.
  36. Moore, G.C. and I. Benbasat, "Development of an instrument to measure the perceptions of adopting an information technology innovation", Information Systems Research, Vol. 2, No.3, 1991, 192-222. https://doi.org/10.1287/isre.2.3.192
  37. Park, C., L. Liang, and A. Cho, "A Study on the Factors Influencing on the Salesperson's Resistance to SFA", Journal of Information Technology Service, Vol.15, No.3, 2016, 15-31. https://doi.org/10.9716/KITS.2016.15.3.015
  38. Park, S. and K. Lee, "Big Data Analytics Case Study from the Marketing Perspective : Emphasis on Banking Industry", Journal of Information Technology Service, Vol.17, No.2, 2018, 207-218. https://doi.org/10.9716/KITS.2018.17.2.207
  39. Piccoli, G. and B. Ives, "IT-dependent strategic initiatives and sustained competitive advantage : a review and synthesis of the literature", MIS Quarterly, Vol.29, No.4, 2005, 747-776. https://doi.org/10.2307/25148708
  40. Ram, S., "A model of innovation resistance", ACR North American Advances, 1987.
  41. Ram, S., "Successful innovation using strategies to reduce consumer resistance : An empirical test", Journal of Product Innovation Management, Vol.6, No.1, 1989, 20-34. https://doi.org/10.1111/1540-5885.610020
  42. Ram, S. and H.-S. Jung, "The conceptualization and measurement of product usage", Journal of the Academy of Marketing Science, 1990, Vol.18, No.1, 67-76. https://doi.org/10.1007/BF02729763
  43. Ranganathan, C., J.S. Dhaliwal, and T.S. Teo, "Assimilation and diffusion of web technologies in supply-chain management : an examination of key drivers and performance impacts", International Journal of Electronic Commerce , Vol.9, No.1, 2004, 127-161. https://doi.org/10.1080/10864415.2004.11044319
  44. Rogers, E.M., "Diffusion of innovations", 1995.
  45. Roselius, T., "Consumer rankings of risk reduction methods", The Journal of Marketing, 1971, 56-61.
  46. Sheth, J.N., "Psychology of innovation resistance : The less developed concept in diffusion research", 1981.
  47. Song, H., J. Jung, and Y. Kim, "Factors affecting postponement, rejection, and opposition to 3DTV adoption", Media Economics and Culture, Vol.11, No.2, 2013, 7-50.
  48. Song, H., J. Jung, and J. Jung, "Factors Affecting Web Developers' Resistance to HTML5 Adoption", Korea Business Review, Vol.45, No.3, 2016, 933.
  49. Stone, R.N. and K. Gronhaug, "Perceived risk : Further considerations for the marketing discipline", European Journal of Marketing, Vol.27, No.3, 1993, 39-50. https://doi.org/10.1108/03090569310026637
  50. Szmigin, I. and G. Foxall, "Three forms of innovation resistance : the case of retail payment methods", Technovation, Vol.18, No. 6-7, 1998, 459-468. https://doi.org/10.1016/S0166-4972(98)00030-3
  51. Verdegem, P. and L. De Marez, "Rethinking determinants of ICT acceptance : Towards an integrated and comprehensive overview", Technovation, Vol.31, No.8, 2011, 411-423. https://doi.org/10.1016/j.technovation.2011.02.004