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Factors Affecting Acceptance of Smart Farm Technology - Focusing on Mediating Effect of Trust and Moderating Effect of IT Level -

스마트 팜 기술수용에 영향을 미치는 요인 - 신뢰성의 매개효과 및 IT 수준의 조절효과를 중심으로 -

  • 강덕봉 (한국농수산대학교 특용작물학과) ;
  • 정병규 (남서울대학교 IPP 사업단) ;
  • 허철무 (호서대학교 벤처대학원 정보경영학과)
  • Received : 2020.04.27
  • Accepted : 2020.08.06
  • Published : 2020.08.31

Abstract

This study was conducted to analyze factors affecting acceptance of smart farm technology. Smart farm technology is rapidly being introduced to agriculture in accordance with the progress of the 4th Industrial Revolution, but research on this is still little. Therefore, in this study, based on the unified theory of acceptance and use of technology (UTAUT), a research model reflecting the characteristics of smart farm technology was constructed. To test this, empirical analysis was performed. A survey was conducted for students in smart farm technology education and adult male and female farmers who are currently planning to operate smart farms. Valid 204 sample were used for analysis. The hypothesis test was based on multiple regression analysis using SPSS 24 statistical package. For the mediating effect and moderating effect, Process Macro 3.4 based on the regression equation was used. The results of testing the hypothesis are as follows. First, in the causal hypothesis test, it was shown that performance expectancy, social influence and price value have a significant positive effect on the intention to use smart farm technology. On the other hand, effort expectancy, facilitating conditions were not tested for a significant influence on the use of smart farm technology. As a result of analyzing the mediating effect of trust, it was found that trust plays a mediating role between performance expectancy, effort expectancy, social influence, facilitating conditions, price value and intention to use smart farm technology. In particular, the effort expectancy has not been tested for a direct significant effect on intention to use smart farm technology, but it has been shown to have an impact through trust. Trust was found to be a full mediating between the effort expectancy and the intention to use the smart farm technology. The current IT level of prospective users has been shown to play a moderating role between performance expectancy, facilitating conditions and intention to use smart farm technology. In particular, the IT level was found to strengthen the relationship between performance expectancy and intention to use smart farm technology. Based on the results of these studies, academic and practical implications were suggested.

Keywords

References

  1. Alalwan, A. A., Y. K. Dwive, and N. P. Rana. 2017. Factors Influencing Adoption of Mobile Banking by Jordanian Bank Customers : Extending UTAUT2 with Trust. International Journal of Information Management. 37(3): 99-110. https://doi.org/10.1016/j.ijinfomgt.2017.01.002
  2. An, M. Y. 2018. A Study on the Effects of Technical Characteristics of Smart Farm on the Acceptance Intention : Focusing on the Mediating Effect of Effort Expectation. Department of Information Management, The Graduate School of Venture, Hoseo University Seoul, Korea.
  3. Bhatiasevi, V. 2015. An Extended UTAUT Model to Explain the Adoption of Mobile Banking. Information Development. 32(4): 799-814. https://doi.org/10.1177/0266666915570764
  4. Chang, K. CH. 2017. Smart Farm Enters the Fourth Industrial Revolution, The Society Of Air-Conditioning and Refrigerating Engineers of Korea. Magazine of th SAREK. 46(8): 11-11.
  5. Choi, Y. C. and I. H. Jang. 2019. Smart Farm in the Fourth Industrial Revolution, The Journal of The Korean Institute of Communication Sciences. 36(3): 9-16.
  6. Chun, Seong Chan, Kim, Hyun Joo, Youn, Ji Young. 2019. An Analysis of Domestic and Foreign Fashion Platform Business Success cases and Growth Factors. Korean Society of Basic Design & Art. 20(4): 455-474.
  7. Dillon, A. and Morris, M. G. 1996. User acceptance of information technology: Theories and model, Annual Review of Information Science and Technology. 31: 3-32.
  8. Jang, Y. J. and T. W. Kim. 2019. Smart Farm Spread and Distribution Project Status and Challenges. NARS.
  9. Jeon, H. Mo, and H. M. Choi. 2017. Consumer’s Acceptance on Mobile Delivery App Service ; Focused on UTATU2. Food Service Industry Journal. 13(1): 67-82.
  10. Chung, B. G. and D. B. Kang. 2020. Factors Affecting Acceptance of Smart Farming Technology : A Comparative Analysis of Return and Native Farmers. Academic Society of Global Business Administration. 17(2): 54-80. https://doi.org/10.38115/asgba.2020.17.2.54
  11. Kang, D. B., K. J. Chang, Y. K. Lee, and M. U. Jeong, 2020. A Study on the Effects of Changes in Smart Farm Introduction Conditions on Willingness to Accept Agriculture. Korean Journal of Organic Agriculture. 28(2): 119-138. https://doi.org/10.11625/KJOA.2020.28.2.119
  12. Kang, S. H. 2016. A Study on the User's Acceptance and Use of Easy Payment Service based on UTAUT. Department of Business Administration. Pukyong National University.
  13. Kim, J. S. 2017. A Study on Factors Affecting the Intention to Accept Blockchain Technology. Graduate School of Soongsil University.
  14. Kim, K. B. and I. O. Jeon. 2018. Influential Factors of Intention to Use Drone Technology : An Applicaion of Extended UTAUT Model. Journal of Distribution and Management Research. 21(3): 161-173. https://doi.org/10.17961/jdmr.21.3.201806.161
  15. Kim, S. D. and I. O. Kim. 2017. Influencing Factors on the Acceptance for Crowd Funding : Focusing on Unified Theory of Acceptance and Use of Technology. Journal of Korean Institute of Intelligent Systems. 27(2): 150-156. https://doi.org/10.5391/JKIIS.2017.27.2.150
  16. Kim, Y. J., J. Y. Park, and Y. G. Park. 2016. An Analysis of the Current Status and Success Factors of Smart Farms, Korea Rural Economic Institue. 74: 1-74.
  17. Lee, T. Y. 2019. A Study on the Effect of Acceptance Factors of ICT Convergence Technology Using UTAUT on Smart Farm Startup Intention. Department of Information Management, The Graduate School of Venture, Hoseo University Seoul, Korea.
  18. Lee, J. E. and D. K. Sung. 2017. The Study on the Factors Influencing on the Behavioral Intention of Free Mobile Video Service: Focusing on the UTAUT2. Institute of Communication Research. 54(1): 258-313. https://doi.org/10.22174/jcr.2017.54.1.258
  19. Malaquias, R. F. and Y. Hwang. 2018. Understanding the Deterninants of Mobile Banking Adoption : A Longitudianl Study in Brazil. Electronic Commerce Research and Applications. 30: 1-7. https://doi.org/10.1016/j.elerap.2018.05.002
  20. Nam, S. T., C. Y. Jin, and J. S. Sim. 2014. A Meta-analysis of the Relationship between Mediator Factors and Purchasing Intention in E-commerce Studies. Journal of Information and Communication Convergence Engineering. 12(4): 257-262. https://doi.org/10.6109/jicce.2014.12.4.257
  21. Nisreen, A., W. Robert, H. Sh. Mahmood. 2018. An examination of the gender gap in smartphone adoption and use in Arab countries: A cross-national study. Computers in Human Behavior. 89: 148-162. https://doi.org/10.1016/j.chb.2018.07.045
  22. Venkatesh, V., M. G. Morris, G. B. Davis, and F. D. Davis. 2003. User Acceptance of Information Technology : Toward a Unified View. MIS Quarterly. 27(3): 425-478. https://doi.org/10.2307/30036540
  23. Venkatesh, V., J. Y. L. Thong, and X. Xu. 2012. Consumer Acceptance and Use of Information Technology : Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly. 36(1): 157-178. https://doi.org/10.2307/41410412
  24. Venkatesh, V., J. Y. L. Thong, and X. Xu. 2016. Unified Theory of Acceptance and Use of Technology : A Synthesis and the Road Ahead. Journal of the Association for Information Systems. 17(5): 328-376. https://doi.org/10.17705/1jais.00428
  25. Yang, S. H., Y. S. Hwang, and J. K. Park. 2016. A Study on the Use of Fintech Payment Services Based on the UTAUT Model. Journal of Vocational Rehabilitation. 38(1): 183-209.
  26. Yeo, U. H., I. B. Lee, K. S. Kwon, T. H. Ha, S. J. Park, R.W. Kim, and S. Y. Lee. 2016. Analysis of Research Trend and Core Technologies Based on IT to Materialize Smart-farm, Protected Horticulture and Plant Factory. 25(1): 30-41. https://doi.org/10.12791/KSBEC.2016.25.1.30
  27. Zhao, J. W. 2019. A Study on Acceptance Attitude and Acceptance Intention of Omni Channel Using Unified Theory of Acceptance and Use of Technology. Department of Consumer Information Science, Graduate School of Konkuk University.