본문 바로가기
KERD
논문KCI 등재

생성형 AI 긍정 태도는 어떻게 형성될 수 있을까? 소비자 경험과 디지털 리터러시가 디지털 자아효능감을 통해 생성형 AI 긍정 태도에 미치는 영향

The Study of Consumer Experience and Digital Literacy Effects on Positive Attitudes toward Generative AI Mediated by Digital Self-efficacy

김범수|김미예|노환호|김민진
한국소비자학회 (Korean Society Of Consumer Studies)|2024.04|소비자학연구 (Journal of Consumer Studies)|제35권 제2호|pp. 143-163|DOI http://dx.doi.org/10.35736/JCS.35.2.7

0

조회

0

다운로드

4

인용

0

참고문헌

키워드

디지털 리터러시Digital Literacy태도Attitude생성형 AIGenerative AI소비자 경험Consumer experienceDigital self-efficacy디지털 자아효능감
주제분류경제학

초록

ChatGPT의 등장 이후 생성형 AI 사용 범위가 빠른 속도로 확대되면서 생성형 AI 활용에 있어 개인, 기업, 국가 간 격차가 예상된다. AI 활용의 확대는 추후 디지털 격차와 같이 AI로 인한 격차를 야기할 수 있기 때문에 생성형 AI 활용 증진을 위한 소비자 중심의 연구가 필요한 시점이다. 소비자들은 컴퓨터, 인터넷, 전자 상거래, 스마트폰 앱, AR/VR과 같은 기술의 발전을 늘 경험하며 이전의 경험을 바탕으로 새로운 기술에 적응해 나가고 있다. 본연구의 목적은 생성형 AI 서비스에 대한 긍정적인 태도 형성에 있어 선행요인으로 소비자 경험과 디지털 리터러시를 제시하고, 이 둘의 관계에서 디지털 자아효능감의 역할을 실증분석을 통해 확인한다. 연구 결과, 소비자 경험의하위 분류인 컴퓨터 경험과 모바일 경험은 모두 디지털 자아효능감에 긍정적인 영향을 주었다. 또한 디지털 자아효능감은 생성형 AI에 대해 긍정적인 영향을 미치고 있음을 확인했다. 이를 통해, 생성형 AI에 있어서 자아효능감이긍정 태도 형성에 중요한 역할을 하고 있음을 확인하였다. 하지만 모바일 리터러시의 경우 디지털 자아효능감에 유의미한 영향을 미치지 못하며, 디지털 자아효능감을 통해서도 생성형 AI 태도에 영향을 미치지 못했다. 이러한 차이는 생성형 AI가 가진 복잡성과 컴퓨터 인터페이스를 기반으로 한 개발의 특성 때문으로 보이며, 컴퓨터 리터러시가 모바일 리터러시보다 생성형 AI 사용에 요구되는 능력을 보다 명확하게 반영하고 있기 때문에 AI 수용태도에더 중요하게 작용할 수 있음을 보여준다. 본 연구는 디지털 환경속에서 기기 사용의 중요한 결정요인 중 하나로 설명되고 있는 자아효능감이 생성형 AI 태도를 결정하는데 있어서도 중요한 역할을 하고 있음을 실증 분석을 통해 확인하여 생성형 AI 인터페이스 운영과 AI 관련 소비자 교육 정책을 수립하는데 활용될 수 있을 것이다.

Abstract

Since the advent of ChatGPT, the use of generative AI has seen rapid proliferation, concomitantly deepening disparities among consumers, businesses, and nations based on their adoption rates. The impact of generative AI on the digital divide highlights the need for research into the factors influencing consumers’ intentions and attitudes toward its use. However, there has been a lack of empirical and analytical research on the factors influencing attitudes towards generative AI. Therefore, this study focuses on consumer experiences with digital technologies and digital literacy to identify how such factors affect AI acceptance and how digital self- efficacy can act as a mediator between consumer experience, digital literacy, and AI attitude. With the rise of ChatGPT, the use of generative AI has quickly grown. At the same time, the differences between consumers, companies, and countries in how they use generative AI have grown. This situation has highlighted the need for research into the factors influencing consumers' intentions and attitudes towards using generative AI. However, there has been a lack of empirical and analytical research on the factors affecting attitudes towards the acceptance of generative AI. Therefore, this study aimed to explore how existing consumer experiences and digital literacy affect the attitude towards AI acceptance and how digital self-efficacy acts as a mediator between consumer experience, digital literacy, and AI acceptance attitude. The study found that consumers with high digital self-efficacy are more likely to have a positive attitude towards generative AI. This aligns with existing research that confidence in digital technology positively impacts the acceptance of new digital technologies. Moreover, consumer experiences, including computer and mobile experiences, were found to positively influence digital self-efficacy. Computer literacy had a significantly positive effect on digital self-efficacy, but mobile literacy did not. This difference is likely due to the complexity of generative AI and the nature of its computer-based development. This result proposes that this makes computer literacy more important to AI acceptance, as it more clearly reflects the skills required to use generative AI than mobile literacy, despite the widespread use of mobile devices.

참고문헌 (76)

  1. 고민환, "텍스트 마이닝 분석을 통한 한국 대중의 ChatGPT에 대한 인식 탐색에 대한 연구", 한국콘텐츠학회논문지, 23(4), pp.1~13 (2023)
  2. 김학실, "노인의 디지털 리터러시와 사회활동", 정책분석평가학회보, 30(2), pp.153~180 (2020)
  3. 박용완, "인공지능 기반 자동인식 기능이 탑재된 제품에 대한 소비자 태도 및 인식 연구", 한국마케팅관리학회, 27(3), pp.1~21 (2022)
  4. 신건권, "SmartPLS 3.0 구조방정식모델링" (2018), 청람
  5. 양지훈, "생성형 AI 서비스의 성공 요인에 대한 탐색적 연구: 텍스트 마이닝과 Chat GPT를 활용하여", 경영정보학연구, 25(2), pp.125~144 (2023)
  6. 이진명, "인공지능 스피커에 대한 소비자 인식과 수용의도 : 비수용자를 중심으로", 소비자학연구, 30(2), pp.193~213 (2019)
  7. 장은교, "인공지능 비서에 대한 소비자 양가성의 유형과 수준 및 수용의도에 미치는 영향", 소비자학연구, 31(2), pp.1~22 (2020)
  8. 한순미, "학습동기 변인들과 인지전략 및 학업성취간의 관계", 한국교육심리연구, 18(1), pp.329~350 (2004)
  9. "AI를 활용한 행정지원 서비스, 2024년부터 시범운용" (2023), 행정안전부[URL]
  10. Ala-Mutka, K., "Mapping digital competence:Towards a conceptual understanding" (2011), Institute for Prospective Technological Studies (IPTS), European Commission, Joint Research Centre
  11. "Digital literacy, libraries, and public policy" (2013)[URL]
  12. "Literacy in the digital age: From traditional to digital to mobile digital literacies" (2020)[URL]
  13. Bagozzi, R. P., "Assessing construct validity in organizational research", Administrative Science Quarterly, pp.421~458 (1991)
  14. Bandura, A., "Self-efficacy : Toward a unifying theory of behavioral change", Psychological Review, 84(2), pp.191~215 (1977)
  15. Bergner, A. S., "Machine talk : How verbal embodiment in conversational AI shapes consumer-brand relationships", Journal of Consumer Research, 50(4), pp.742~764 (2023)
  16. Brady, S. L., "Implementation of AI image reconstruction in CT—how is it validated and what dose reductions can be achieved", The British Journal of Radiology, 96(1150), pp.20220915~ (2023)
  17. Carter, L., "Exploring the intersection of the digital divide and artificial intelligence : A hermeneutic literature review", AIS Transactions on Human-Computer Interaction, 12(4), pp.253~275 (2020)
  18. CGS Survey, "2019 CGS Customer Service Chatbots & Channels Survey", ~ (2019)
  19. Chong, T., "AI-chatbots on the services frontline addressing the challenges and opportunities of agency", Journal of Retailing and Consumer Services, 63, pp.102735~ (2021)
  20. Choung, H., "Trust in AI and its role in the acceptance of AI technologies", International Journal of Human-Computer Interaction, 39(9), pp.1~13 (2022)
  21. Chung, M., "Chatbot e-service and customer satisfaction regarding luxury brands", Journal of Business Research, 117, pp.587~595 (2020)
  22. Clark, L. A., "Constructing validity: Basic issues in objective scale development" (2016)
  23. Compeau, D. R., "Computer self-efficacy: Development of a measure and initial test", MIS Quarterly, pp.189~211 (1995)
  24. Cosby, A., "Digital Literacy and Digital Self-Efficacy of Australian Technology Teachers", Education Sciences, 13(5), pp.530~ (2023)
  25. Cotter, K., "Practical knowledge of algorithms : The case of BreadTube", New Media & Society, pp.14614448221081802~ (2022)
  26. Crolic, C., "Blame the bot : anthropomorphism and anger in customer-chatbot interactions", Journal of Marketing, 86(1), pp.132~148 (2022)
  27. Durndell, A., "Computer selfefficacy, computer anxiety, attitudes towards the Internet and reported experience with the Internet, by gender, in an East European sample", Computers in Human Behavior, 18(5), pp.521~535 (2002)
  28. Falk, R. F., "A primer for soft modeling" (1992), University of Akron Press
  29. Frederickson, B. L., "The role of positive emotions in positive psychology : The broadenand-built theory of positive emotions", American Psychologist, 56, pp.218~226 (2001)
  30. Fornell, C., "Evaluating structural equation models with unobservable variables and measurement error", Journal of Marketing Research, 18(1), pp.39~50 (1981)
  31. Gao, J., "The impact of artificial intelligence technology stimuli on smart customer experience and the moderating effect of technology readiness", International Journal of Emerging Markets, 17(4), pp.1123~1142 (2022)
  32. Garvey, A. M., "Bad news? Send an AI. Good news? Send a human", Journal of Marketing, 87(1), pp.10~25 (2023)
  33. Getenet, S., "Students' digital technology attitude, literacy and self-efficacy and their effect on online learning engagement", International Journal of Educational Technology in Higher Education, 21(1), pp.3~ (2024)
  34. Gilster, P., "Digital literacy" (1997), Wiley Computer Pub
  35. Go, E., "Humanizing chatbots : The effects of visual, identity and convertsational cues on humanness perceptions", Computers in Human Behavior, 97, pp.304~316 (2019)
  36. Gray, H. M., "Dimensions of mind perception", Science, 315(5812), pp.619~619 (2007)
  37. Hair, J. F., "When to use and how to report the results of PLS-SEM", European Business Review, 31(1), pp.2~24 (2019)
  38. Hair Jr, J. F., "Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook", pp.91~113 (2021)
  39. Hammer, M., "New technology, new role of parents : How parents' beliefs and behavior affect students'digital media self-efficacy", Computers in Human Behavior, 116, pp.106642~ (2021)
  40. Henseler, J., "Goodness-offit indices for partial least squares path modeling", Computational Statistics, 28(2), pp.565~580 (2013)
  41. Holbrook, M. B., "Consumption experience, customer value, and subjective personal introspection : An illustrative photographic essay", Journal of Business Research, 59(6), pp.714~725 (2006)
  42. Hsieh, J. P. -A., "Understanding digital inequality : Comparing continued use behavioral models of the socioeconomically advantaged and disadvantaged", MIS Quarterly, 32(1), pp.97~126 (2008)
  43. Hu, L. T., "Cutoff criteria for fit indexes in covariance structure analysis:Conventional criteria versus new alternatives", Structural Equation Modeling : A Multidisciplinary Journal, 6(1), pp.1~55 (1999)
  44. Isman, A., "How Does Student Ability and Self-Efficacy Affect the Usage of Computer Technology?", Online Submission, 8(1) (2009)
  45. Jadil, Y., "A meta-analysis of the UTAUT model in the mobile banking literature : The moderating role of sample size and culture", Journal of Business Research, 132, pp.354~372 (2021)
  46. Jung, J., "Consumer experiences of virtual reality : Insights from VR luxury brand fashion shows", Journal of Business Research, 130, pp.517~524 (2021)
  47. Kim, J. K., "When Do You Trust AI? The Effect of Number Presentation Detail on Consumer Trust and Acceptance of AI Recommendations", Psychology & Marketing, 38(7), pp.1140~1155 (2021)
  48. Lim, W. M., "Alexa, what do we know about conversational commerce? Insights from a systematic literature review", Psychology &Marketing, 39(6), pp.1129~1155 (2022)
  49. Lim, E. M., "The effects of pre-service early childhood teachers’ digital literacy and selfefficacy on their perception of AI education for young children", Education and Information Technologies, 28(10), pp.12969~12995 (2023)
  50. Lokman, A. S., "Extension and prerequisite : An algorithm to enable relations between responses in chatbot technology", Journal of Computer Science, 6(10), pp.1212~ (2010)
  51. Meece, J. L., "Students' goal orientations and cognitive engagement in classroom activities", Journal of Educational Psychology, 80(4), pp.514~ (1988)
  52. Mustak, M., "Artificial intelligence in marketing : Topic modeling, scientometric analysis, and research agenda", Journal of Business Research, 124, pp.389~404 (2021)
  53. Nunnally, J. C., "Psychometric Theory, New York" (1994), McGraw-Hill
  54. "ChatGPT (August 3 version) Large language model" (2023)[URL]
  55. Pajares, F., "Self-efficacy beliefs in academic settings", Review of Educational Research, 66(4), pp.543~578 (1996)
  56. Parsakia, K., "The Effect of Chatbots and AI on The Self-Efficacy, Self-Esteem, Problem-Solving and Critical Thinking of Students", Health Nexus, 1(1), pp.71~76 (2023)
  57. Pumptow, M., "Students’ digital media self-efficacy and its importance for higher education institutions: development and validation of a survey instrument", Technology, Knowledge and Learning, 26(3), pp.555~575 (2021)
  58. Ram, S., "A Model of Innovation Resistance", Advances in Consumer Research, 14(1), pp.208~212 (1987)
  59. Rogers, E. M., "Diffusion of Innovations" (2003), Free Press
  60. Schunk, D. H., "Handbook of motivation at school", pp.35~53 (2009), Routledge
  61. Stumpf, S., "Selfefficacy expectations and coping with careerrelated events", Journal of Vocational Behavior, 31(1), pp.91~108 (1987)
  62. Taylor, S., "Assessing IT usage : The role of prior experience", Management Information Systems Quarterly, 19(4), pp.561~570 (1995)
  63. Tetri, B., "Self-efficacy, internet self-efficacy, and proxy efficacy as predictors of the use of digital social and health care services among mental health service users in Finland: A cross-sectional study", Psychology Research and Behavior Management, pp.291~303 (2022)
  64. Trivedi, J., "Examining the customer experience of using banking chatbots and its impact on brand love: The moderating role of perceived risk", Journal of Internet Commerce, 18(1), pp.91~111 (2019)
  65. Tsai, M. J., "Information searching strategies in web-based science learning: The role of Internet self-efficacy", Innovations in education and Teaching International, 40(1), pp.43~50 (2003)
  66. Ulfert-Blank, A. S., "Assessing digital self-efficacy : Review and scale development", Computers & Education, 191, pp.104626~ (2022)
  67. Van Dijk, J., "The deepening divide: Inequality in the information society" (2005), Sage Publications
  68. Venkatesh, V., "A theoretical extension of the technology acceptance model : Four longitudinal field studies", Management Science, 46(2), pp.186~204 (2000)
  69. Wang, B., "Measuring user competence in using artificial intelligence : validity and reliability of artificial intelligence literacy scale", Behaviour & Information Technology, 42(9), pp.1324~1337 (2023)
  70. Wang, C., "The artificial intelligence divide : Who is the most vulnerable?", New Media & Society, pp.14614448241232345~ (2024)
  71. Wang, S., "Effects of higher education institutes’ artificial intelligence capability on students' self-efficacy, creativity and learning performance", Education and Information Technologies, 28(5), pp.4919~4939 (2023)
  72. Xu, Y., "AI customer service : Task complexity, problem-solving ability, and usage intention", Australasian Marketing Journal, 28(4), pp.189~199 (2020)
  73. Yu, H., "ICT self-efficacy and ICT interest mediate the gender differences in digital reading : A multilevel serial mediation analysis", International Journal of Emerging Technologies in Learning(iJET), 17(5), pp.211~225 (2022)
  74. Zhu, Y., "AI is better when I'm sure : The influence of certainty of needs on consumers' acceptance of AI chatbots", Journal of Business Research, 150, pp.642~652 (2022)
  75. Zhou, Q., "Talking to a bot or a wall? How chatbots vs. human agents affect anticipated communication quality", Computers in Human Behavior, 143, pp.107674~ (2023)
  76. Zimmerman, B., "Self-efficacy : An essential motive to learn", Educational Psychology Review, 12(2), pp.117~144 (2000)

관련 논문AI추천

디지털 역량 수준이 생성형 AI 미래 인식에 미치는 영향김재남한국컴퓨터정보학회 · 한국컴퓨터정보학회논문지2025 · 제30권 제8호대학생들의 자기효능감, 사용경험 및 지각된 유용성이 AI 서비스 수용태도에 미치는 영향 연구강경란, 박철우한국창업학회 · 한국창업학회지2022 · 제17권 제4호생성형 AI의 특성이 사용자 만족과 신뢰에 미치는 영향: AI 리터러시의 조절효과김유진, 이형석한국컴퓨터정보학회 · 한국컴퓨터정보학회논문지2025 · 제30권 제12호생성형 AI 이용자 혁신성과 지속적 이용 의도 관계 : 사용 용이성, 지각된 유용성, 유희성의 병렬 삼중 매개효과를 중심으로김은희, 김화동한국융합학회 · 미래기술융합논문지2025 · 제4권 제5호생성형 AI 이용과 AI 역량 인식의 형성: 이용 동기와 이용 시간의 상호작용 효과를 중심으로배영, 이모란한국방송공사 · 방송문화연구2025 · 제37권 제2호생성형 AI 특성과 인공지능 리터러시가 자기효능감과 지속이용의도에 미치는 영향 - 관광계열 대학생을 중심으로 -김정은한국호텔리조트학회 · 호텔리조트연구2025 · 제24권 제6호

이 간행물의 다른 논문 (6건)

중․고령 소비자의 디지털 조력자 활용과 거래 행동: 모바일 거래환경을 중심으로구명진, 사지연pp. 1-25친환경 소비에 물질주의와 친환경 가치 인식이 미치는 영향: 소비자 혁신성의 조절 효과김나민, 이희정pp. 27-53건강기능식품 구매의도에 관한 연구: 한국과 중국 소비자 비교를 중심으로안가청, 남영운pp. 55-77소비자의 중고거래 동기, 거래, 소비자 행복의 관계: 지속가능 소비행태 관점의 탐색유재미pp. 79-98금융이해력 과신에서 과대평가와 우월평가의 관계 및 증권 투자 경험이윤호pp. 99-120
원문 보기