Informatization Policy (정보화정책)

National Information Society Agency (한국지능정보사회진흥원)
권호 표지
DOI QR코드

DOI QR Code

Determinants of artificial intelligence adoption in firms: Evidence from Korean firm-level data

기업의 인공지능 기술 도입에 영향을 미치는 요인 분석: 국내 기업 데이터를 이용한 실증연구

  • Bong, Kang Ho (AI Policy Research Center, Software Policy and Research Institute)
  • Received : 2024.07.17
  • Accepted : 2024.08.13
  • Published : 2024.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

Artificial intelligence(AI) is regarded as a key tool that can significantly contribute to innovation and improve productivity as digital transformation continues to spread rapidly. Currently, however, there is lack of understanding and empirical research on the factors that influence the adoption of AI by companies. In particular, most studies have been conducted by foreign researchers analyzing data from foreign companies, and domestic studies have limitations in terms of objectivity and timeliness. This study employs econometric methods to identify the determinants of AI adoption at the firm level. To this end, we derive the technological, organizational, and environmental context factors from the perspective of the Technology-Organization-Environment(TOE) framework as a representative theory of technology adoption factors. We then conduct a logistic regression analysis using data from 11,601 Korean firms. This study not only expands the research literature by supplementing the limitations of previous studies in Korea but also provides timely evidence and implications through empirical analysis.

디지털 전환이 급속도로 확산되고 있는 가운데, 인공지능(AI) 기술은 혁신과 생산성 향상을 견인할 핵심 동력으로 인식되고 있다. 그러나 현재 기업의 AI 도입에 영향을 미치는 요인에 대한 이해와 실증적 연구가 부족한 실정이다. 특히 대다수의 연구는 해외 연구자가 해외 기업 데이터를 분석한 것이며, 국내 연구는 객관성 및 시의성 측면에서 한계를 가지고 있다. 본 연구에서는 계량경제학적 분석을 통해 기업 단위에서 AI 도입 영향요인을 규명한다. 이를 위해 신기술 도입 영향요인에 관한 대표적 이론인 TOE(Technology-Organization-Environment) 프레임워크 관점에서 기술적, 조직적, 환경적 맥락의 요인을 도출하고, 과학기술정보통신부·한국지능정보사회진흥원의 「2022년 정보화통계조사」를 활용하여 11,601개 국내 기업 데이터를 이용한 로지스틱 회귀분석을 실시한다. 본 연구는 국내 선행연구의 한계점을 보완함으로써 AI 및 신기술 도입 영향요인에 관한 연구 문헌을 확장하고, 실증분석을 통해 시의성있는 증거와 시사점을 제공한다는 점에서 의의를 가진다.

Keywords

References

  1. Agarwal, P., Swami, S. & Malhotra, S. K. (2024). "Artificial Intelligence Adoption in the Post COVID-19 New-Normal and Role of Smart Technologies in Transforming Business: a Review." Journal of Science and Technology Policy Management, 15(3), 506-529. 
  2. Agrawal, K. P. (2023). "Towards Adoption of Generative AI in Organizational Settings." Journal of Computer Information Systems, inpress, https://doi.org/10.1080/08874417.2023.2240744. 
  3. Baek, S. I., Lim, G. G. & Yu, D. S. (2016). "Exploring Social Impact of AI." Informatization Policy, 23(4), 3-23. 
  4. Barney, J. (1991). "Firm Resources and Sustained Competitive Advantage." Journal of Management, 17(1), 99-120. 
  5. Bong, K. H., An, M. & Kim, J. (2023). An analysis and implications on the status of Korean companies adopting AI. Seongnam: Software Policy and Research Institute. 
  6. Chatterjee, S., Chaudhuri, R., Kamble, S., Gupta, S. & Sivarajah, U. (2023). "Adoption of Artificial Intelligence and Cutting-Edge Technologies for Production System Sustainability: A Moderator-Mediation Analysis." Information Systems Frontiers, 25, 1779-1794. 
  7. Chatterjee, S., Rana, N. P., Dwivedi, Y. K. & Baabdullah, A. M. (2021). "Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model." Technological Forecasting and Social Change, 170, 120880. 
  8. Chen, H., Li, L. & Chen, Y. (2021). "Explore success factors that impact artificial intelligence adoption on telecom industry in China." Journal of Management Analytics, 8(1), 36-68. 
  9. Chen, J. & Tajdini, S. (2024). "A moderated model of artificial intelligence adoption in firms and its effects on their performance." Information Technology and Management, in-press, https://doi.org/10.1007/s10799-024-00422-5. 
  10. Cho, J., DeStefano, T., Kim, H., Kim, I. & Paik, J. H. (2023). "What's driving the diffusion of next-generation digital technologies?" Technovation, 119, 102477. 
  11. Czarnitzki, D., Fernandez, G. P. & Rammer, C. (2023). "Artificial intelligence and firm-level productivity." Journal of Economic Behavior & Organization, 211, 188-205. 
  12. Das, S. D. & Bala, P. K. (2024). "What drives MLOps adoption? An analysis using the TOE framework." Journal of Decision Systems, 33(3), 376-412. 
  13. Davis, F. D. (1989). "Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology." MIS Quarterly, 13(3), 319-340. 
  14. Hitt, L. M. & Brynjolfsson, E. (1997). "Information Technology and Internal Firm Organization: An Exploratory Analysis." Journal of Management Information Systems, 14(2), 81-101. 
  15. Min, B. (2018). "Korean Informartization Policy." http://www.nca.or.kr/0101.html, (Retrieved on August 15). 
  16. IBM (2024). "IBM Global AI Adoption Index." https://www.multivu.com/players/English/9240059-ibm-2023-global-ai-adoption-index-report, (Retrieved on July 15). 
  17. Jiang, L., Chen, J., Bao, Y. & Zou, F. (2022). "Exploring the patterns of international technology diffusion in AI from the perspective of patent citations." Scientometrics, 127, 5307-5323. 
  18. Johnk, J., Weissert, M. & Wyrtki, K. (2021). "Ready or Not, AI Comes: An Interview Study of Organizational AI Readiness Factors." Business & Information Systems Engineering, 63(1), 5-20. 
  19. Jung, H. & Whang, U. (2024). "The Impact of Introducing and Utilizing Digital Transformation Technologies on a Firm's Performance." Journal of Corporation and Innovation, 47(1), 21-35. 
  20. Kim, K. H., Cho, H. & Lim, S. (2020). "An Exploratory Study on the Core Technology of the Fourth Industrial Revolution and Information Security Organization: Focusing on Firm Performance." Knowledge Management Research, 21(1), 41-59. 
  21. Khan, A. N., Jabeen, F., Mehmood, K., Soomro, M. A. & Bresciani, S. (2023). "Paving the way for technological innovation through adoption of artificial intelligence in conservative industries." Journal of Business Research, 165, 114019. 
  22. Knez, K. (2023). "Technology diffusion and uneven development." Journal of Evolutionary Economics, 33(4), 1171-1195. 
  23. Korea Foundation for the Advancement of Science & Creativity (2022). Report on the Science and Technology Public Awareness Survey. Seoul: Korea Foundation for the Advancement of Science & Creativity. 
  24. Lee, H. S., Qiao, X., Shin, S. Y., Kim, G. R. & Oh, S. H. (2022). "Analysis of Korea's Artificial Intelligence Competitiveness Based on Patent Data: Focusing on Patent Index and Topic Modeling." Informatization Policy, 29(4), 43-66. 
  25. Lee, Y. S., Kim, T., Choi, S. & Kim, W. (2022). "When does AI pay off? AI-adoption intensity, complementary investments, and R&D strategy." Technovation, 118, 102590. 
  26. Lee, Z. K. & Nam, H. (2022). "A Literature Review Study in the Field of Artificial Intelligence(AI) Aplications, AI-Related Management, and AI Application Risk." Informatization Policy, 29(2), 3-36. 
  27. McElheran, K., Li, J. F., Brynjolfsson, E., Kroff, Z., Dinlersoz, E., Foster, L. & Zolas, N. (2024). "AI adoption in America: Who, what, and where." Journal of Economics & Management Strategy, 33(2), 375-415. 
  28. Merhi, M. I. & Harfouche, A. (2024). "Enablers of artificial intelligence adoption and implementation in production systems." International Journal of Production Research, 62(15), 5457-5471. 
  29. Ministry of Science and ICT & National Information Society Agency (2022). 2022 Yearbook of Information Society Statistics. Sejong & Daegu: Ministry of Science and ICT & National Information Society Agency. 
  30. Nam, C. (2024). "Factors influencing the introduction of new technologies related to the Fourth Industrial Revolution by Korean companies." KOSTAT Statistics Plus, 27(Spring), 4-17. 
  31. Oh, Y. & Kang, T. (2023). "Adoption Strategy of New Technology in Manufacturing firms: Focusing on Smart Factory." Innovation studies, 18(1), 97-119. 
  32. Rogers, E. M. (2003). Diffusion of Innovations. 5th edition, New York, NY: Free Press. 
  33. Scott, W. R. (1995). Institutions and Organizations. Thousand Oaks, CA: Sage. 
  34. Solaimani, S. & Swaak, L. (2023). "Critical Success Factors in a multi-stage adoption of Artificial Intelligence: A Necessary Condition Analysis." Journal of Engineering and Technology Management, 69, 101760. 
  35. Tornatzky, L. G. & Fleischer, M. (1990). The Processes of Technological Innovation. Lexington, MA: Lexington Books. 
  36. Yang, C. (2022). "How Artificial Intelligence Technology Affects Productivity and Employment: Firm-level Evidence from Taiwan." Research Policy, 51(6), 104536. 
  37. Yang, J., Blount, Y. & Amrollahi, A. (2024). "Artificial intelligence adoption in a professional service industry: A multiple case study." Technological Forecasting and Social Change, 201, 123251. 
  38. Zhu, K. & Kraemer, K. L. (2005). "Post-Adoption Variations in Usage and Value of E-Business by Organizations: Cross-Country Evidence from the Retail Industry." Information Systems Research, 16(1), 61-84.