한국문헌정보학회지 (Journal of the Korean Society for Library and Information Science)

한국문헌정보학회 (Korean Society For Library And Information Science)
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인공지능 기반 기술에 대한 공공도서관 사서의 사용의도 연구

A Study on the Intention of Public Library Librarians to Use Artificial Intelligence-Based Technology

  • 김지영 (인천광역시도서관발전진흥원)
  • 투고 : 2023.07.18
  • 심사 : 2023.08.11
  • 발행 : 2023.08.31
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초록

본 연구는 기술수용모델을 활용하여 기술준비도와 기술수용요인이 인공지능 기반 기술에 대한 공공도서관 사서의 사용의도에 미치는 영향을 분석하였다. 이를 위하여 공공도서관 사서를 대상으로 설문조사를 실시하였으며 총 202명의 설문 데이터를 통계 분석에 활용하였다. 가설검증 결과 첫째, 지각된 유용성에 낙관성은 유의한 정(+)의 영향을 미치는 것으로 나타났고 불편함은 유의한 부(-)의 영향을 미치는 것으로 나타났다. 지각된 용이성에 낙관성과 혁신성은 유의한 정(+)의 영향을 미치는 것으로 나타났으며 불편함은 유의한 부(-)의 영향을 미치는 것으로 나타났다. 둘째, 지각된 용이성은 지각된 유용성에 유의한 정(+)의 영향을 미치는 것으로 나타났으며 지각된 유용성과 지각된 용이성은 모두 사용의도에 유의한 정(+)의 영향을 미치는 것으로 나타났다. 셋째, 사용의도에 낙관성은 유의한 정(+)의 영향을 미치는 것으로 나타났으며, 불안감은 유의한 부(-)의 영향을 미치는 것으로 나타났다. 본 연구는 인공지능 기반 기술에 대한 공공도서관 사서의 인식을 실증적으로 분석하여 향후 인공지능 기술의 도서관 활용에 대한 기초적인 자료를 제공할 수 있을 것으로 기대한다.

This study analyzed the effect of technology preparation and technology acceptance factors on the intention of public library librarians to use artificial intelligence-based technology using the technology acceptance model. To this end, a survey was conducted on public library librarians, and a total of 202 survey data were used for statistical analysis. As a result of the hypothesis test, first, optimism has a significant positive (+) effect on perceived usefulness, and discomfort has a significant negative (-) effect. Optimism and innovation on perceived ease of use were found to have a significant positive (+) effect, and discomfort was found to have a significant negative (-) effect. Second, perceived ease of use was found to have a significant positive (+) effect on perceived usefulness, and both perceived usefulness and perceived ease of use had a significant positive (+) effect on the intention to use. Third, optimism was found to have a significant positive (+) effect on the intention to use, and anxiety was found to have a significant negative (-) effect. This study is expected to provide basic data on the use of artificial intelligence technology in the future by empirically analyzing public library librarians' perceptions of artificial intelligence-based technology.

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참고문헌

  1. Chung, In Goo (2020). A Study on the Effect of Integrated Technology Acceptance Theory (UTAUT) and Technology Readiness (TRI) on the Customer's Intention to Accept the Innovative Products: Focused on the mediating role of the Value-Based Acceptance Model (VAM). Ph.D. Diss. Graduate School Kyonggi University.
  2. Kang, Ho Chul, Yun, Seung Ho, & Lim, Jong Sik (2013). The study on ethical management on the workers' job satisfaction and organizational citizenship behavior. Kyung Young Non Chong, 34(-), 1-19. 
  3. Kim, Tae-Young, Gang, Ju-Yeon, Kim, Geon, & Oh, Hyo-Jung (2018). A study on the current status and application strategies for intelligent archival information services. Journal of Korean Society of Archives and Records Management, 18(4), 149-182. 
  4. Kwak, Woojung & Noh, Younghee (2021). A study on the current state of the library's AI service and the service provision plan. Journal of Korean Library and Information Science Society, 52(1), 155-178.  https://doi.org/10.16981/KLISS.52.1.202103.155
  5. Noh, Younghee & Shin, Youngji (2021). A study on the library activation plan using autonomous objects. Journal of Korean Library and Information Science Society, 52(1), 27-54.  https://doi.org/10.16981/KLISS.52.1.202103.27
  6. Noh, Younghee (2014). A study suggesting the development direction of the next generation digital library. Journal of the Korean Society for Information Management, 31(2), 7-40.  https://doi.org/10.3743/KOSIM.2014.31.2.007
  7. Park, Jinpyo & Kim, Jae Young (2010). Study on response of consumers for mobile advertisement: based on TAM. Journal of Outdoor Advertising Research, 7(4), 71-103. 
  8. Seo, Jae-Yeon, Kim, Song-I, & Jeong, Chul (2018). Effects of technology readiness on usage intention of smart-phone tourism applications: an application of the technology readiness and acceptance model. Journal of Tourism Sciences, 42(8), 109-127.  https://doi.org/10.17086/JTS.2018.42.8.109.127
  9. Sun, ZhaoQ (2021). An Empirical Study on the Intention to Adopt the IoT-Based Innovative Products: Focused on the mediating role of Trust and Perceived Risk. Ph.D. Diss. Graduate School Kyonggi University.
  10. Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: a replication. MIS Quarterly, 16(2), 227-247. https://doi.org/10.2307/249577 
  11. Agarwal, R. & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204-215.  https://doi.org/10.1287/isre.9.2.204
  12. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.  https://doi.org/10.1016/0749-5978(91)90020-T
  13. Andrews, J. E., Ward, H., & Yoon, J. W. (2021). UTAUT as a model for understanding intention to adopt AI and related technologies among librarians. The Journal of Academic Librarianship, 47(6). 
  14. Basgoze, P. (2015). Integration of technology readiness(TR) into the technology acceptance model (TAM) for m-shopping. International Journal of Scientific Research and Innovative Technology, 2(3), 26-35. 
  15. Cave, S. & Dihal, K. (2019). Hopes and fears for intelligent machines in fiction and reality. Nature Machine Intelligence, 1(2), 74-78. https://doi.org/10.1038/s42256-019-0020-9 
  16. Chau, P. Y. (1996). An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems, 13(2), 185-204. https://doi.org/10.1080/07421222.1996.11518128 
  17. Chen, S. C., Chen, H. H., & Chen, M. F. (2009). Determinants of satisfaction and continuance intention towards self-service technologies. Industrial Management & Data Systems, 109(9). 1248-1263. https://doi.org/10.1108/02635570911002306 
  18. Chris Lin, J. S. & Chang, H. C. (2011). The role of technology readiness in self-service technology acceptance. Managing Service Quality: An International Journal, 21(4), 424-444. https://doi.org/10.1108/09604521111146289 
  19. Colby, C. & Thibodeaux, C. (2000). Ready or not? What consumer really think about technology. 2000 International CES, Jan, 6-9, Las Vegas, Nevada, USA. 
  20. 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 
  21. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R.(1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982-1003.  https://doi.org/10.1287/mnsc.35.8.982
  22. DeLone, W. & McLean, E. (1992). Information systems success: the quest for the dependent variable, Information Systems Research, 3(1), 60-95. https://doi.org/10.1109/HICSS.2002.994345 
  23. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: an integrated model. MIS Quarterly, 27(1), 51-90. https://doi.org/10.2307/30036519 
  24. Hong, W., Thong, J. Y. L., Wong, W.-M., & Tam, K.-Y. (2002). Determinants of user acceptance of digital libraries: an empirical examination of individual differences and system characteristics. Journal of Management Information Systems, 18(3), 97-124. https://doi.org/10.1080/07421222.2002.11045692 
  25. Igbaria, M. & Iivari, J. (1995). The effects of self-efficacy on computer usage. Omega, 23(6), 587-605. https://doi.org/10.1016/0305-0483(95)00035-6 
  26. Igbaria, M., Guimaraes, T., & Davis, G. B. (1995). Testing the determinants and of microcomputer usage via a structural equation model. Journal of Management Information Systems, 11(4), 87-114. https://doi.org/10.1080/07421222.1995.11518061 
  27. Lin, C. H., Shih, H. Y., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance: the TRAM model. Psychology & Marketing, 24(7), 641-657. https://doi.org/10.1002/mar.20177 
  28. Lin, J. S. C. & Hsieh, P. L. (2006). The role of technology readiness in customers' perception and adoption of self-service technologies. International Journal of Service Industry Management, 17(5), 497-517. https://doi.org/10.1108/09564230610689795 
  29. Lund, B., Omame, I., Tijani, S., & Agbaji, D. (2020). Perceptions toward artificial intelligence among academic library employees and alignment with the diffusion of innovations' adopter categories. College & Research Libraries, 81(5), 865-882. https://doi.org/10.5860/crl.81.5.865 
  30. Oh, J. C., Yoon S. J., & Jung N. H. (2014). The role of technology readiness in consumers' adoption of mobile internet services between South Korea and China. International Journal of Mobile Communications, 12(3), 229-248. https://doi.org/10.1504/IJMC.2014.061460 
  31. Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of service research, 2(4), 307-320. https://doi.org/10.1177/109467050024001 
  32. Park, Namkee, Roman, Raul, Lee, Seungyoon, & Chung, Jae Eun (2009). User acceptance of a digital library system in developing countries: an application of the Technology Acceptance Model, International Journal of Information Management, 29(3), 196-209. https://doi.org/10.1016/j.ijinfomgt.2008.07.001 
  33. Rogers, E. M. (1995). Lessons for guidelines from the diffusion of innovations. Joint Commission Journal on Quality and Patient Safety, 21(7), 324-328. https://doi.org/10.1016/s1070-3241(16)30155-9 
  34. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.
  35. Taylor, S. & Toddy, P. A. (1995). Understanding information technology usage: a test competing models, Information Systems Research, 6(2), 144-176.  https://doi.org/10.1287/isre.6.2.144
  36. Thong, J. Y. L., Hong, W., & Tam, K.-Y. (2002). Understanding user acceptance of digital libraries: what are the roles of interface characteristics, organizational context, and individual differences? International Journal of Human-Computer Studies, 57, 215-242. https://doi.org/10.1016/S1071-5819(02)91024-4 
  37. Venkatesh, V. & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: development and test. Decision Sciences, 27(3), 451-481.  https://doi.org/10.1111/j.1540-5915.1996.tb01822.x
  38. Venkatesh, V. & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926 
  39. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540 
  40. Walczuch, R., Lemmink, J., & Streukens, S. (2007). The effect of service employees' technology readiness on technology acceptance. Information & Management, 44(2), 206-215. https://doi.org/10.1016/j.im.2006.12.005 
  41. Wood, Barbara A. & Evans, David J. (2018). Librarians' perceptions of artificial intelligence and its potential impact on the profession. Computers in Libraries, 38(1), 26-30.
  42. Zhang, B. & Dafoe, A. (2019). Artificial Intelligence: American Attitudes and Trends. Available: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3312874