The Journal of the Korea institute of electronic communication sciences (한국전자통신학회논문지)

Korea Institute of Electronic Communication Science (한국전자통신학회)
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Exploring the Perceived Value of Generative AI and the Determinants of Continuous Use Intention

생성형 인공지능(Generative AI)에 대한 지각된 가치와 지속이용의도 결정요인 탐색

  • Su-Ji Moon (Dept. of Creative Writing & Contents Creation, Daejin University)
  • 문수지 (대진대학교 문예콘텐츠창작학과)
  • Received : 2024.06.30
  • Accepted : 2024.07.25
  • Published : 2024.08.31
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Abstract

By inputting consumer satisfaction as an exogenous variable into the value-based adoption model, this study explored the factors that influence the user's intention to continue using image-centered generative AI. Briefly presenting the main results, first, enjoyment did not significantly affect perceived value, but usefulness had a positive effect on perceived value. Second, Fee and technicality had a negative effect on perceived value. Third, perceived value had a positive effect on consumer satisfaction and continuous use intention. Fourth, consumer satisfaction had a positive effect on continuous use intention. Based on the above results, it is important to recognize the usefulness of image-centered generated AI and enjoyment in the process of use in order to increase the user's intention to continue using image-centered generated AI, and at the same time, it will be important to increase the user's perceived value and satisfaction by minimizing the reasonable fee and complexity in the method of use at the level acceptable to the users.

본 연구는 가치기반수용모델에 소비자 만족도를 추가하여 이미지 중심의 생성형 인공지능에 대한 사용자의 지속이용의도에 영향을 미치는 요인을 탐색하였다. 주요 결과를 간략하게 제시하면 첫째, 즐거움은 지각된 가치에 유의한 영향을 미치지 못하였으나, 유용성은 지각된 가치에 긍정적 영향을 미치는 것으로 나타났다. 둘째, 비용과 기술성은 지각된 가치에 부정적 영향을 미치는 것으로 나타났다. 셋째, 지각된 가치는 소비자 만족도와 지속이용의도에 긍정적 영향을 미치는 것으로 나타났다. 넷째, 소비자 만족도는 지속이용의도에 긍정적 영향을 미치는 것으로 나타났다. 이상의 결과에 근거하여 사용자의 이미지 중심 생성형 인공지능에 대한 지속이용의도를 높이기 위해서는 이미지 중심의 생성형 인공지능이 가지는 유용성과 이용과정에서의 즐거움을 인식시키는 것이 중요하며, 그와 동시에 사용자들이 수용 가능한 수준에서의 합리적 비용과 이용방법에서의 복잡성을 최소화함으로써 사용자의 지각된 가치와 만족도를 높이는 것이 중요할 것이다.

Keywords

Acknowledgement

이 논문은 2024년도 정부(교육부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 202400380001)

References

  1. Y. LeCun, Y. Bengio, and G. Hinton, "Deep learning," Nature, vol. 521, 2015, pp. 436-444. 
  2. R. Gupta, K. Nair, M. Mishra, B. Ibrahim, and S. Bhardwaj, "Adoption and impacts of generative artificial intelligence: Theoretical underpinnings and research agenda," Int. J. of Information Management Data Insights, vol. 4, April 2024, pp. 100232. https://doi.org/10.1016/j.jjimei.2024.100232 
  3. Y. K. Dwivedi, N. Kshetri, L. Hughes, E. L. Slade et al., "Opinion paper: So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy," Int. J. of Information Management, vol. 71, August 2023, pp. 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642 
  4. L. Tung, "ChatGPT can write code. Now researchers say it's good at fixing bugs, too," ZDNet, 2023. https://www.zdnet.com/article/chatgpt-can-write-code-now-researchers-say-its-good-at-fixing-bugs-too/ 
  5. S. Wang, H. Scells, G. Zuccon, & B. Koopman, "Can ChatGPT write a good boolean query for systematic review literature search?," arXIV, 2023, https://arxiv.org/abs/2302.03495 
  6. L. Avila-Chauvet, D. Mejia, and C. O. Acosta Quiroz, "Chatgpt as a support tool for online behavioral task programming," 2023, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4329020 
  7. O, Aydin, E. Karaarslan, and M. Damar, "Is ChatGPT leading generative AI? What is beyond expectations?," 2023, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4341500 
  8. J. C. Shin, "A study on generative artificial intelligence-based art in the genealogy of generative art: Diffusion model from a systematic perspective of generative art," J. of Humanities, vol. 15, 2023, pp. 235-265. 
  9. M. Chui, R. Roberts, and L. Yee, "Generative AI is here: How tools like ChatGPT could change your business," Quantum Black AI by McKinsey, 2022. https://www.mckinsey.com/capabilities/quantumblack/our-insights/generative-ai-is-here-how-tools-like-chatgpt-could-change-your-business 
  10. N. Dehouche, "Plagiarism in the age of m assive generative pre-trained transformers(GTP-3)," Ethics in Science and Environmental Politics, vol. 21 no. 3, 2021, pp. 17-23. 
  11. S. W. Choi, "Use of generative artificial intelligence for business college assignments: A quantitative and qualitative investigation on the students' perceptions of ethical justification," Korean Business Education Review, vol. 39 no. 1, February 2024, pp. 139-159. DOI : 10.23839/kabe.2024.39.1.139 
  12. A. K. Kar and A. K. Kushwaha, "Facilitators and barriers of artificial intelligence adoption in business: Insight from opinions using big data analytics," Information Systems Frontiers, vol. 25 no. 4, August 2023, pp. 1351-1374. https://doi.org/10.1007/s10796-021-10219-4 
  13. P. Shamsolmoali, M. Zareapoor, E. Granger, H. Zhou, R. Wang, M. E. Celebi, and J. Yang, "Image synthesis with adversarial networks: A comprehensive survey and case studies," Information Fusion, vol. 72, August 2021, pp. 126-146. https://doi.org/10.1016/j.inffus.2021.02.014 
  14. H. W. Kim, H. C. Chan, and S. Gupta, "Value-based adoption of mobile internet: An empirical investigation," Decision Support Systems, vol. 43, February 2007, pp. 111-126. https://doi.org/10.1016/j.dss.2005.05.009 
  15. T. C. Lin, S. Wu, J. S. C. Hsu, and Y. C. Chou, "The integration of value-based adoption and expectation-confirmation models: An example of IPTV continuance intention," Decision Support Systems, vol. 54, December 2012, pp. 63-57. https://doi.org/10.1016/j.dss.2012.04.004 
  16. D. H. Shin, "An empirical investigation of a modified technology acceptance model of IPTV," Behaviour and Information Technology, vol. 28, June 2009, pp. 361-372. https://doi.org/10.1080/01449290701814232 
  17. U. K. Lee, "Accessing the acceptance of the speech recognition based virtual assistant service; Applying UTAUT model," J. of Product Research, vol. 38 no 5, Octorber 2020, pp. 111-120. http://dx.doi.org/10.36345/kacst.2020.38.5.013 
  18. T. P. Liang, Y. L. Lin, and H. C. Hou, "What drives consumers to adopt a sharing platform: An integrated model of value-based and transaction cost theories," Information & Management, vol. 58 no. 4, June 2021, pp. 103471. https://doi.org/10.1016/j.im.2021.103471 
  19. T. P. Liang, R. Kohli, H. C. Huang, and Z. L. Li, "What drives the adoption of the blockchain technology? A fit-viability perspective," J. of Management Information Systems, vol. 38 no. 2, August 2021, pp. 314-337. https://doi.org/10.1080/07421222.2021.1912915 
  20. Y. F. Kuo, C. M. Wu, and W. J. Deng, "The relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile value-added services," Computers in Human Behavior, vol. 25, July 2009, pp. 887-896. https://doi.org/10.1016/j.chb.2009.03.003 
  21. S. Ho and M. H. Ryu, "A study on the perceived value, satisfaction and continuous usage intentions of Chinese consumers in live commerce: Focusing on value-based adoption model," J. of Consumption Culture, vol 25 no. 3, September 2022, pp. 111-135. DOI : 10.17053/jcc.2022.25.3.007 
  22. F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, "Extrinsic and intrinsic motivation to use computers in the workplace," J. of Applied Social Psychology, vol. 22 no 14, 1992, pp. 1111-1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x 
  23. K. T. Kim and J. S. Song, "A study of factors affecting consumers' intention to use A.I.-based mobile U.I. Design: Based on value-based adoption model," J. of the Korean Society of Design Culture, vol. 26 no. 2, June 2020, pp. 7-27. DOI : 10.18208/ksdc.2020.26.2.7 
  24. Y. D. Kim, J. Y. Kim, W. K. Jeong, and Y. T. Shin, "A study on the effect of perceived value and innovation resistance factors on adoption intention of artificial intelligence platform: Focused on drug discovery fields," KIPS Trans. on Computer and Communication Systems, vol. 10 no. 12, December 2021, pp. 329-342. https://doi.org/10.3745/KTSDE.2021.10.12.329 
  25. J. H. Kang, Y. J. Jeong, and J. S. Lee, "Application of value-based adoption model (VAM) to untact exercise and sport program users: Comparison between generation MZ and baby boomers," Korean J. of Sport Management, vol. 27 no. 2, April 2022, pp. 1-29. DOI : 10.31308/KSSM.27.2.1 
  26. M. Zhang and J. M. Lee, "The effect of consumers' perceived value and trust on adoption intention of artificial intelligent assistant," Consumer Policy and Education Review, vol. 17 no. 1, March 2021, pp. 17-40. http://dx.doi.org/10.15790/cope.2021.17.1.017 
  27. C. W. Kim and H. M. Cho, "A study on the intention to continue participation in K-Pop concert based on augmented reality: Focusing on value-based adoption model and satisfaction," The J. of the Korea Contents Association, vol. 23 no. 2, February 2023, pp. 439-449. http://dx.doi.org/10.5392/JKCA.2023.23.02.439 
  28. Z. Chen and A. J. Dubinsky, "A conceptual commerce: A preliminary investigation," Psychology & Marketing, vol. 20 no. 4, March 2003, pp. 323-347. https://doi.org/10.1002/mar.10076 
  29. S. H. Woo, "The effect of two-sided characteristics of artificial intelligence on perceived value and service use intention of fashion consumer," Doctoral dissertation, Konkuk University, 2023. 
  30. S. R. Wang, "Examining the impact of tourism information quality from ChatGPT on user's perceived value and satisfaction," J. of Hospitality & Tourism Studies, vol. 25 no. 11, November 2023, pp. 15-28. http://dx.doi.org/10.31667/jhts.2023.11.106.28 
  31. C. Sarfo, J. A. Zhang, C. O'Kane, and P. O'Kane, "Perceived value of microfinanance and SEM performance: The role of exploratory innovation," Int. J. of Innovation, vol. 8, June 2024, pp. 172-185. https://doi.org/10.1016/j.ijis.2024.02.003 
  32. L. Lalicic and C. Weismayer, "Consumers' reasons and perceived value co-creation of using artificial intelligence-enable travel service agents," J. of Business Research, vol. 129, May 2021, pp. 891-901. https://doi.org/10.1016/j.jbusres.2020.11.005 
  33. M. Zhang, "The effect of consumers' perceived value and trust on adoption intention of artificial intelligent assistant," Master's thesis, Chungnam National University, 2020. 
  34. S. J. Jun and H. I. Kim, "The effect of untact service experience value on customer satisfaction and reuse intention as the development of food tech," J. of Hospitality & Tourism Studies, vol. 22 no 4, December 2020, pp. 141-155. http://dx.doi.org/10.31667/jhts.2020.12.85.141 
  35. L. Jin and M. H. Ryu, "A study on the satisfaction and continuous use intention of Chinese consumers for delivery apps: Focusing on value-based adoption model," J. of Distribution and Management Research, vol. 25, October 2022, pp. 155-169. doI: 10.17961/jdmr.25.05.202210.155 
  36. H. M. Li, J. W. Han, and I. Y. Lee, "Predicting consumption behavior of sport O2O service in Korea and China: Applying value-based adoption model(VAM)," The Korean J. of Physical Education, vol. 61 no. 6, November 2022, pp. 1-17. http://dx.doi.org/10.23949/kjpe.2022.11.61.6.1 
  37. A. Poushneh, "Augmented reality in retail: A trade-off between user's control of access to personal information and augmentation quality," J. of Retailing and Consumer Services, vol. 41, March 2018, pp. 169-176. https://doi.org/10.1016/j.jretconser.2017.12.010 
  38. A. Bhattacherjee, "Understanding information systems continuance: An expectation-confirmation model," MIS Quarterly, vol. 25, September 2001, pp. 351-370. https://doi.org/10.2307/3250921