디지털융복합연구 (Journal of Digital Convergence)

  • 제20권4호
  • /
  • Pages.225-234
  • /
  • 2022
  • /
  • 2713-6434(pISSN)
  • /
  • 2713-6442(eISSN)
한국디지털정책학회 (The Society of Digital Policy and Management)
권호 표지
DOI QR코드

DOI QR Code

비대면 음성 쇼핑의 인지된 가치, 지속이용의도에 미치는 영향 관계에 관한 연구

The Influence of Perceived Value on Continuance Use Intention in Voice Commerce Context

  • 김효정 (호서대학교 산업심리학과)
  • Kim, Hyo-Jung (Department of Industrial Psychology, Hoseo University)
  • 투고 : 2022.02.03
  • 심사 : 2022.04.20
  • 발행 : 2022.04.28
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

음성 쇼핑이 새로운 정보 탐색 및 구매 채널로 주목을 받고 있다. 본 논문은 비대면 음성 쇼핑의 지속이용의도에 영향을 미치는 요인들을 가치기반수용모델을 이용하여 살펴보았다. 음성 쇼핑 이용 경험이 있는 소비자들을 대상으로 온라인 조사를 실시하였으며, 총 470명의 응답자료가 최종 분석에 활용되었다. 음성 쇼핑 경험자는 음성 쇼핑으로 물품을 구매하였거나 음식 배달 서비스를 이용한 개인들로 한정하였다. SPSS 23.0과 Amos 23.0 프로그램을 이용하여 기술통계 분석, 상관관계 분석, 확인적 요인분석, 그리고 구조모형 분석을 실시하였다. 본 연구의 결과를 요약하면 다음과 같다. 첫째, 유용성과 응대 정확성이 음성 쇼핑의 인지된 가치를 증가시키는 것으로 확인되었다. 둘째, 기능적 위험이 음성 쇼핑의 인지된 가치를 감소시키는 것으로 확인되었다. 셋째, 인지된 가치가 음성 쇼핑의 지속이용의도를 향상시키는 것으로 나타났다. 본 연구 결과는 음성 쇼핑을 이용하는 소비자들의 특성을 이해하고, 음성 쇼핑이 이용자들에게 혜택을 제공하는 유용한 서비스로 자리매김하는데 기여할 수 있을 것이다.

Voice commerce has emerged as a key channel for consumer searches and purchases. This study examines the continuance use intention of voice commerce, applying value-based adoption model. An online survey was conducted with 470 consumers who has experienced with voice commerce. As participants were who buys and purchases goods; or a user who uses food delivery service in voice commerce context. This study used SPSS 23.0 and Amos 23.0 for descriptive analysis, correlation analysis, confirmatory factor analysis, and structul equation modeling analysis. These reaults are as follows. First, usefuleness and response accuracy were significantly influenced the perceived value of voice commerce. Second, functional risk was significantly influenced the the perceived value of voice commerce. Third, perceived value was significantly influenced the continuance use intention of voice commerce. These results enhance understanding of voice commerce users and provide insight into the service provider of voice commerce.

키워드

과제정보

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2021S1A5A8064298)

참고문헌

  1. A. Mari & R. Algesheimer (2021, January). The Role of Trusting Beliefs in Voice Assistants during Voice Shopping. In Proceedings of the 54th Hawaii International Conference on System Sciences. (pp. 4073-4082). Howaii: HICSS.
  2. W. Jo, S. H. Ahn & D. H. Chung. (2020). Influence of User Innovativeness and Knowledge Base on Acceptance of Voice Shopping. Asia-Pacific Journal of Business Venturing and Entrepreneurship, 15(2), 153-169. DOI : 10.16972/apjbve.15.2.202004.153
  3. H. Y. Lee, D. B. Lee, J. S. Kim & Y. A. Kang. (2020. February). Voice User Interface Design Guidelines for Food Delivery Service. Proceedings of HCI Korea. (pp.537-544). Korea: HCI.
  4. P. Klaus & J. L. Zaichkowsky. (2022). The Convenience of shopping via voice AI: Introducing AIDM. Journal of Retailing and Consumer Services, 65, 1-7. https://doi.org/10.1016/j.jretconser.2021.102490
  5. R. E. Bawack, S. F. Wamba & K. D. A. Carillo. (2021). Adoption of Smart Speakers for Voice Shopping. In Exploring Innovation in a Digital World (pp. 21-35). Springer, Cham. https://doi.org/10.1007/978-3-030-87842-9_3
  6. P. Hu, Y. Lu, & B. Wang. (2022). Experiencing Power over AI: The Fit Effect of Perceived Power and Desire for Power on Consumers' Choice for Voice Shopping. Computers in Human Behavior, 128, 1-12. https://doi.org/10.1016/j.chb.2021.107091
  7. H. R. Lee & S. W. Lee. (2020). The Influence of the Attractiveness and Para-social Interaction of Intelligent Personal Assistant on the Product Attitude of Voice Shopping Users. Information Society & Media, 21(1), 55-82. DOI : 10.52558/ISM.2020.04.21.1.55
  8. S. H. Ahn, W. Jo & D. H. Jung. (2019). Factors Affecting Users to Adopt Voice Shopping: Empirical Evidence from the UTAUT Model, Journal of Technology Innovation, 27(4), 111-144. https://doi.org/10.14386/SIME.2019.27.4.111
  9. D. Y. Yoon & Y. Lee. (2021). Conversational AI Voice Shopping Service: MZ Generation vs. Baby Boom Generation, Journal of Consumer Studies, 32(3), 73-93. https://doi.org/10.35736/JCS.32.2.4
  10. H. W. Kim, H. C. Chan & S. Gupta (2007). Value-based Adoption of Mobile Internet: An Empirical Investigation. Decision Support Systems, 43(1), 111-126. https://doi.org/10.1016/j.dss.2005.05.009
  11. F. D. Davis. (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
  12. S. Moore, S. Bulmer & J. Elms. (2022). The Social Significance of AI in Retail on Customer Experience and Shopping Practices. Journal of Retailing and Consumer Services, 64, 1-8. https://doi.org/10.1016/j.jretconser.2021.102755
  13. C. Rzepka, B. Berger & T. Hess. (2020, January). Why Another Customer Channel? Consumers' Perceived Benefits and Costs of Voice Commerce. In Proceedings of the 53rd Hawaii International Conference on System Sciences. (pp. 4079-4088). Howaii: HICSS. DOI:10.24251/HICSS.2020.499
  14. N. K. Kim, K. H. Hwang & S. B. Yang. (2021). The Influence of Perceived Value of Fresh Food Early-Morning Delivery Services on Continuous Use Intention: Focusing on the Value-Based Adoption Model, The Journal of Internet Electronic Commerce Research, 21(3), 1-26. DOI : 10.37272/JIECR.2021.06.21.3.1
  15. S. Y. Lee, H. R. Yim & H. S. Kim. (2019). Study on Influence Relation of Membership User's Perceived Benefit, Sacrifice, Value and Continuous Use Intention by Using Theory of Value Based Adoption Model (VAM): Focused on 20's CJ Membership Service. Culinary Science & Hospitality Research, 25(6), 12-22. DOI : 10.20878/cshr.2019.25.6.002
  16. O. K. Kim & J. Y. Yun. (2019). A Convergence Study on the Chatbot(Voice-based/Messenger-based) in Mobile Shopping and User Experience in App Services. The Korean Society of Science & Art, 37(2), 47-59. DOI : 10.17548/ksaf.2019.03.30.47
  17. Y. Yin & Y. Nam. (2021). A Study on Factors Affecting Intention to Continue Using Mobile Audiobook Applications: Based on the Expectation Confirmation Model, Technology Acceptance Model and Value-based Adoption Model, The Journal of Internet Electronic Commerce Research, 21(3), 127-144. DOI : 10.37272/JIECR.2021.06.21.3.127
  18. E. H. Ki & H. M. Joen. (2020). Factors Influencing on Continuous Intention to Use of Accommodation App Using the Expended Value-based Adoption Model. Journal of Hospitality and Tourism Studies, 22(2), 214-228. DOI : 10.31667/jhts.2020.6.83.214
  19. H. A. Sung & A. J. Lee. (2020). A Study of Factors Affecting Intention to Continuous Use on Smart Order Service in Coffee Shop-Focused on Value-Based Adoption Model. FoodService Industry Journal, 16(1), 203-218. DOI : 10.22509/kfsa.2020.16.1.014
  20. H. A. Sung & A. J. Lee. (2020). A Study of Factors Affecting Intention to Continuous Use on Smart Order Service in Coffee Shop-Focused on Value-Based Adoption Model, FoodService Industry Journal, 16(1), 203-218. DOI : 10.22509/kfsa.2020.16.1.014
  21. J. H. Kim & J. H. Choi. (2018). Effect of Conversational Agent's Recommendation Strategy on Voice Shopping Experience: Focused on Initiative Strategies and Type of Goods, Journal of Cybercommunication Academic Society, 35(4), 5-35. DOI : 10.36494/JCAS.2018.12.35.4.5
  22. C. Rzepka, B. Berger & T. Hess. (2020, January). Why Another Customer Channel? Consumers' Perceived Benefits and Costs of Voice Commerce. In Proceedings of the 53rd Hawaii International Conference on System Sciences. (pp. 4079-4088). Howaii: HICSS.
  23. Y. H. Park, J. H. Song, D. H. Kwon & D. H. Chung. (2021). Factors Affecting Users Acceptance of Voice Assistant in Vehicles: Focusing on the Extended UTAUT Model. Innovation Studies, 16(3), 1-43. DOI:10.24251/HICSS.2020.499
  24. M. J. Kim & S. B. Lee. (2018). The Effect of the Perceived Benefit and Sacrifice of Delivery Application Service Users in the Food Industry on Perceived Value and Behavioral Intention: Using the Value-based Adoption Model(VAM), International Journal of Tourism and Hospitality Research, 32(2), 217-233. DOI : 10.21298/IJTHR.2018.02.32.2.217
  25. J. F. Hair, W. C. Black, B. J. Babin, R. E. Anderson R. L Tatham, Multivariate Data Analysis, Auflage, Upper Saddle River, 2006.