Journal of Convergence for Information Technology (융합정보논문지)

Convergence Society for SMB (중소기업융합학회)
권호 표지
DOI QR코드

DOI QR Code

A study on Improving the Level of Introduction of Smart Factories Using the Extended Innovation Resistance Model

확장된 혁신저항모델을 활용한 스마트 팩토리 도입 수준 제고에 대한 연구

  • Park, Chan-Kwon (Institute of Construction Environment Energy Convergence Technology, Kyoungpook National University)
  • 박찬권 (경북대학교 건설환경에너지융합기술원)
  • Received : 2020.10.25
  • Accepted : 2021.03.20
  • Published : 2021.03.28
Download PDF
⟨ Previous Next ⟩

Abstract

This study is a study on the innovation resistance that may arise in connection with the introduction and use of smart factory-related technologies by SMEs. It is to study the effect of the leading factors of innovation resistance on innovation resistance and the effect of innovation resistance on use intention by using the extended innovation resistance model. A total of 176 survey data were used for the study, and the study was conducted using SPSS 25 and Smart PLS 2.0. Relative advantage, suitability, perceived risk, social impact, and organizational characteristics have a significant effect on innovation resistance, and innovation resistance was tested to have a significant effect on the intention to use. As an implication according to the research, a plan to improve the level of introduction and use of smart factories using the expanded innovative storage model was presented by dividing positive and negative factors, and factors that should be improved and factors that should be reduced are presented. It was specifically presented.

본 연구는 중소 제조 기업들의 스마트 팩토리 관련 기술의 도입 및 사용과 관련하여 발생할 수 있는 혁신저항에 대한 연구이다. 확장된 혁신저항모델을 활용하여 혁신저항 선행요인들이 혁신저항에 미치는 영향 및 혁신저항이 사용의 도에 미치는 영향을 연구하는 것이다. 총 176부의 설문데이터를 연구에 활용하였으며, SPSS 25와 Smart PLS 2.0을 활용하여 연구를 진행하였다. 상대적 이점, 적합성, 지각된 위험, 사회적 영향, 조직특성은 혁신저항에 유의한 영향을 미치며, 혁신저항은 사용의도에 유의한 영향을 미치는 것으로 검정되었다. 연구에 따른 시사점으로서 확장된 혁신저장모델을 활용하여 스마트 팩토리 도입 및 사용의 수준을 제고하기 위한 방안을 긍정적인 요인과 부정적인 요인을 구분하여 제시하였으며, 이를 통해 제고하여야 하는 요인과 감소시켜야 하는 요인들을 구체적으로 제시하였다.

Keywords

References

  1. W. J. Jang, S. I. Cho, S. S. Kim & G. Y. Gim. (2018). A Study on the Implementation of Big Data Infrastructure in Smart Factory. Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology. 8(10), 11-23. DOI : 10.21742/AJMAHS.2018.10.07
  2. Smart Manufacturing Innovation Promotion Team. (2020). Smart Factory Business Management System.
  3. Ministry of SMEs and Startups. (2020). Statistics.
  4. M. K. Lee, R. Verma & A. Roth. (2015). Understanding Customer Value in Technology-Enabled Service: A Numerical Taxonomy Based on Usage and Utility. Service Science, 7(3), 227-248. DOI : 10.1287/serv.2015.0105
  5. E. M. Rogers. (2003). Diffusion of Innovation 5rd Ed. New York : The Free Press.
  6. M. Kleijnen, N. Lee & M. Wetzels. (2009). An Exploration of Consumer Resistance to Innovation and Its Antecedents. Journal of Economic Psychology, 30(3), 344-357. DOI : 10.1016/j.joep.2009.02.004
  7. J. R. Kim & S. J. Lee. (2020). Factors Affecting Technology Acceptance of Smart Factory. Journal of Information Technology Applications & Management, 27(1), 75-95. DOI : 10.21219/jitam.2020.27.1.075
  8. H. J. Kim, H. Huh, J. W. Kang & J. M. Boo. (2019). A Study on Factors Influencing the Introduction of Smart Factory : Focusing on Small and Medium-sized Enterprises in Korea. Journal of Society of Korea Industrial and Systems Engineering. 42(3), 252-261. DOI : 10.11627/jkise.2019.42.3.252
  9. J. H. Oh, J. H. Seo & J. D. Kim. (2019). The Effect of Both Employees' Attitude toward Technology Acceptance and Ease of Technology Use on Smart Factory Technology Introduction level and Manufacturing Performance. Journal of Information Technology Applications & Management, 26(2), 13-26. DOI : 10.21219/jitam.2019.26.2.013
  10. M. H. Chang & Y. M. Kim. (2019). A Study on the Innovation Resistance Caused by Blockchain to the Shipping and Port Industry. Journal of Korea Port Economic Association, 35(4), 121-146. DOI : 10.38121/kpea.2019.12.35.4.121
  11. J. Sheth. (1981). Psychology of Innovation Resistance: The less Developed Concept(LDC) in Diffusion Research. Research In marketing, 4, 273-282.
  12. S. Ram. (1987). A Model of Innovation Resistance. Advances in Consumer Research, 14, 208-212.
  13. S. Ram. (1989). Successful Innovation Using Strategies to Reduce Resistance: An Empirical Test. Journal of Product Innovation Management, 6(1), 20-34. DOI : 10.1016/0737-6782(89)90011-8
  14. S. Ram & J. N. Sheth. (1989). Consumer Resistance to Innovation: The marketing Problem and Its Solutions. Journal of Consumer Marketing, 6(2), 5-14. DOI : 10.1108/EUM0000000002542
  15. S. U. Yun. (2013). A Study on the Innovation Resistance on Social Network Service : Focusing on Facebook Non-Users on their 20's University Students. Journal of Communication Science, 13(3), 331-360. DOI : G704-001590.2013.13.3.005
  16. M. L. Katz & C. Shapiro. (1994). Systems Competition and Network Effects. Journal of Economic Perspectives, 8(2), 93-115. DOI : 10.1257/jep.8.2.93
  17. J. J. Oh & S. J. Choi. (2017). Development of PLC-based Fieldbus Educational Equipment and Curriculum for Building Smart Factory. Journal of Practical Engineering Education, 9(1), 49-56. DOI : 10.14702/JPEE.2017.049
  18. S. J. Lee, B. G. Lim, G. R. Park & J. C. Park. (2018). (Leading the People-Centered 4th Industrial Revolution) Smart Factory Operation and Strategy. Hanol Publishing House.
  19. Y. S. Yang & C. H. Shin. (2010). Innovation Resistance of Consumer in Accepting New Technology -With Emphasis on Mobile Phone Touch Interface Technology-. Archives of Design Research, 23(3), 37-52. DOI : G704-000241.2010.23.3.013
  20. B. H. Lee. (2017). A Study on Factors Affecting Innovation Resistance and Intention of Use of Social TV Non-Users: Focused on Innovation Diffusion Theory and Innovation Resistance Model. Journal of Internet Computing and Services, 18(6), 101-112. DOI : 10.7472/jksii.2017.18.6.101
  21. J. Y. Chu & D. H. Lee. (2018). Influence of Smart Factor's Implementing Energy Management System on Innovation Resistance and Performance. Journal of Digital Convergence, 16(1), 103-116. DOI : 10.14400/JDC.2018.16.1.103
  22. Y. H. Kim & Y. Choi. (2009). Determinants of Psychological Resistance against IPTV-Modification of Innovation Resistance Model. Journal of Broadcasting and Telecommunications Research, 69, 163-191. DOI : G704-SER000000521.2009..69.002
  23. H. S. Song & K. C. Kim. (2006). Resistance to Mobile Commerce Services. The Journal of Society for e-Business Studies, 11(2), 111-134.
  24. M. S. Suh, J. W. Ahn, E. K. Lee & D. Y. Oh. (2009). Purchasing Avoidance of Digital Convergence Products: Focusing on the Customer's Psychological Factors and the Innovation Resistance. The Journal of the Korea Contents Association, 9(1), 270-284. DOI : 10.5392/JKCA.2009.9.1.270
  25. J. S. Hyun & J. S. Hyun. (2000). A Structural Model of Network Externalities and Switching Costs in High Technology Markets: Consumer Perspective. Korean Management Review, 29(1), 63-87.
  26. J. M. Lee. (2005). Information and Communication Media Convergence, Choice, and Change of Use Factors: Focusing on Internet and Mobile. Paju : Kstudy.
  27. G. J. Lee & Y. G. Kim. (2018). A Study on the Development of Internet(IoT) Model and Platform For Building Smart Logistics Information System. Korean Entrepreneur Association Winter Conference Presentation, 1-15.
  28. B. J. Ahn & K. H. Kwon. (2005). A Study on Factors affecting the Perceived Usefulness and Perceived Ease of Use of ERP System. Korea International Accounting Review, 13, 139-163. DOI : G704-001756.2005..13.008
  29. W. H. Delone & E. R. McLean. (2003). The Delone and McLean Model of Information Systems Success: A Ten-Years Update. Journal of Management Information Systems, 19(4), 9-30. DOI : 10.1080/07421222.2003.11045748
  30. S. Kitchell. (1995). Corporate Culture, Environmental Adaptation, and Innovation Adoption: A Qualitative/Quantitative Approach. Journal of the Academy of Marketing Science, 23(3), 195-205. DOI : 10.1177/0092070395233004
  31. Y. Weber & N. Pliskin. (1996). The Effects of Information Systems Integration and Organizational Culture on a Firm's Effectiveness. Information and Management, 30(2), 81-90. DOI : 10.1016/0378-7206(95)00046-1
  32. H. J. Kim, H. G. Choi, S. T. Kim, M. S. An & Y. M. Lee. (2012). A Study of Innovation Resistance among Social Media Non - Users. Korean Journal of Journalism & Communication Studies, 56(4), 439-464. DOI : G704-000203.2012.56.4.004
  33. Y. H. Chang & J. G. Park. (2011). Adoption Model of Microblog: An Integrated Approach to Media Adoption Studies. Korean Journal of Journalism & Communication Studies, 54(5), 32-58.
  34. K. D. Kim & T. W. Nam. (2019). Public Officials' Acceptance of Technology and Innovation Resistance of the 4th Industrial Revolution: Using PLS-SEM. Korean Society for Policy Studies Spring Academic Papers, 1-23.
  35. J. F. Hair, G. T. M. Hult, C. M. Ringle & M. Sarstedt. (2014). A Primer on Partial Least Squares Structural Equation Modeling(PLS-SEM). Sage Publication.
  36. H. S. Lee & J. H. Lim (2019). SPSS New UI Manual. Jibhyeonjae.
  37. J. C. Nunally & I. H. Bernstein (1994). Psychometric Theory 3rd ed. New York, McGraw-Hill.
  38. J. Henseler, C. M. Ringle & R. R. Sinkovics. (2009). The use of Partial least Path Modeling in International Marketing. In R. R. Sinkovics and P. N. Ghauri(eds). New Challenges to International Marketing, Emerald Group Publishing Limited.
  39. C. Fornell & D. F. Larcker. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39-50. DOI : 10.2307/3151312