ChatGPT 품질과 활용만족이 지속적 이용의도에 미치는 영향

A Study on the impact of ChatGPT Quality and Satisfaction on Intention to Continuous Use

  • 박철우 (부산가톨릭대학교 소프트웨어학과) ;
  • 강경란 (부산대학교 융합학부 과학기술혁신전공 )
  • Park Cheol Woo (Catholic University of Pusan, Department of Software) ;
  • Kang Gyung Lan (Pusan National University, Science and Technology Acceleration for Resign Academy)
  • 투고 : 2023.11.02
  • 심사 : 2023.12.28
  • 발행 : 2023.12.31

초록

최근 생성형 AI 기반인 ChatGPT는 상업적·교육적 활용 가능성과 높은 효용가치 기대로 급격히 발전함과 동시에 여러 가지 우려와 문제점도 대두되고 있다. 본 연구는 ChatGpt의 품질이 사용자의 활용만족과 지속적 이용의도에 미치는 영향을 분석하는데 목적이 있다. 이를 위하여 부산경남지역 대학생들을 대상으로 설문조사를 실시하였으며 총 155명의 응답을 표본으로 SPSS 28.0 프로그램을 이용하여 검증하였다. 연구 결과, ChatGPT 품질 요소 중 신뢰성과 안정성은 활용만족과 지속적 이용의도에 긍정적인 영향을 미치는 것으로 나타났다. ChatGPT의 활용만족은 지속적 이용의도에 긍정적인 영향을 미치는 것으로 나타났다. ChatGPT의 신뢰성과 안정성, 지속적 이용의도간에에 활용만족은 긍정적인 매개효과가 있는 것으로 나타났다. 본 연구 결과로 ChatGPT의 품질요소 중 사용자의 지속적 이용의도에 영향을 미치는 요인을 제시함으로서 ChatGPT의 이용 촉진에 필요한 교육적·정책적 방향 제시에 기여고자 한다.

The purpose of this study is to examine the impact of ChatGpt's quality on users' satisfaction and intention to continuous use it. For this purpose, a survey was conducted targeting college students in the Busan and Gyeongnam regions, and responses from a total of 155 people were verified using the SPSS 28.0 program. As a result of the study, reliability and stability among ChatGPT quality factors were found to have a positive effect on satisfaction with use and intention to continuous use. Satisfaction with the use of ChatGPT was found to have a positive effect on intention to continuous use.. Satisfaction with use was found to have a positive mediating effect between the reliability and stability of ChatGPT quality and intention to continous use it. As a result of this study, we aim to contribute to suggesting educational and policy directions necessary to promote the use of ChatGPT by presenting factors that affect users' intention to continuous use ChatGPT among the qualities of ChatGPT.

키워드

과제정보

이 논문은 2023학년도 부산가톨릭대학교 학술연구비 지원에 의한 논문임

참고문헌

  1. Ajzen, I., & Fishbein, M.(1980). Understanding attitude sand predicting social behavior. Englewood Cliffs.
  2. Baron, R. M., & Kenny, D. A.(1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of personality and social psychology, 51(6), 1173. https://doi.org/10.1037/0022-3514.51.6.1173
  3. Bhattacherjee, A.(2001a). An Empirical Analysis of the Antecedents of Electronic Commerce Service Continuance. Decision Support Systems, 32(2), 201-214. https://doi.org/10.1016/S0167-9236(01)00111-7
  4. Bhattacherjee, A(2001b). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 351-370.
  5. Han, B., S.(2018). An Empirical Study on the Effects of Store IT Management Service and System Quality on Intention to Continuous Use. Doctoral Dissertation, Soongsil University.
  6. Kang, M., H.(2019). A Study on the Factors Affecting the Intention to Continuous Use of POS System, Department of Service Management. Master's thesis, Graduate School of Soongsil University.
  7. Kim, H., J.(2023). A Study on the Intentions of ChatGPT Users Using the Extended UTAUT Model. Journal of Digital Contents Society, 24(7), 1465-1473. https://doi.org/10.9728/dcs.2023.24.7.1465
  8. Kim, H. J., & Oh, S. N.(2023). Analysis of the Intention to Use ChatGPT in College Students' Assignment Performance: Focusing on the Moderating Effects of Personal Innovativeness. Culture and Convergence, 45(6), 203-214.
  9. Lo, C. K.(2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), 410. https://doi.org/10.3390/educsci13040410
  10. Davis, F. D.(1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
  11. DeLone, W. H., & McLean, E. R.(1992). Information systems success: The quest for the dependent variable. Information systems research, 3(1), 60-95. https://doi.org/10.1287/isre.3.1.60
  12. DeLone, W. H., & McLean, E. R.(2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4), 9-30.
  13. Jiang, J. J., Klein, G., & Carr, C. L.(2002). Measuring information system service quality: SERVQUAL from the other side. MIS quarterly, 145-166.
  14. Oliver, R. L.(1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions. Journal of Marketing Research, 17(4), 460-469. https://doi.org/10.1177/002224378001700405
  15. Roca, J. C., Chiu, C., & Martinez, F. J.(2006). Understanding E-Learning Continuance Intention: An Extension of the Technology Acceptance Model. International Journal of Human-Computer Studies, 64(8), 683-696. https://doi.org/10.1016/j.ijhcs.2006.01.003
  16. SamgJong KPMG(2023). Big tech platform innovation created by ChatGPT and generative AI. Issue Monitor, No.159. Sep.2023. Retrieved from https://assets.kpmg.com/content/dam/kpmg/kr/pdf/2023/issue-monitor/kpmg-korea-ai-platform-20230921.pdf.
  17. Seddon, P. B.(1997). A respecification and extension of the DeLone and McLean model of IS success. Information systems research, 8(3), 240-253. https://doi.org/10.1287/isre.8.3.240
  18. Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B.(2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10(1), 15. https://doi.org/10.1186/s40561-023-00237-x
  19. Van Dis, E. A., Bollen, J., Zuidema, W., van Rooij, R., & Bockting, C. L.(2023). ChatGPT: five priorities for research. Nature, 614(7947), 224-226. https://doi.org/10.1038/d41586-023-00288-7
  20. Van Dyke, T. P., Kappelman, L. A., & Prybutok, V. R. (1997). Measuring information systems service quality: concerns on the use of the SERVQUAL questionnaire. MIS quarterly, 195-208.