$\require{mediawiki-texvc}$

연합인증

연합인증 가입 기관의 연구자들은 소속기관의 인증정보(ID와 암호)를 이용해 다른 대학, 연구기관, 서비스 공급자의 다양한 온라인 자원과 연구 데이터를 이용할 수 있습니다.

이는 여행자가 자국에서 발행 받은 여권으로 세계 각국을 자유롭게 여행할 수 있는 것과 같습니다.

연합인증으로 이용이 가능한 서비스는 NTIS, DataON, Edison, Kafe, Webinar 등이 있습니다.

한번의 인증절차만으로 연합인증 가입 서비스에 추가 로그인 없이 이용이 가능합니다.

다만, 연합인증을 위해서는 최초 1회만 인증 절차가 필요합니다. (회원이 아닐 경우 회원 가입이 필요합니다.)

연합인증 절차는 다음과 같습니다.

최초이용시에는
ScienceON에 로그인 → 연합인증 서비스 접속 → 로그인 (본인 확인 또는 회원가입) → 서비스 이용

그 이후에는
ScienceON 로그인 → 연합인증 서비스 접속 → 서비스 이용

연합인증을 활용하시면 KISTI가 제공하는 다양한 서비스를 편리하게 이용하실 수 있습니다.

The Factors Influencing the Use of Shared Economy-Based Mobility Services 원문보기

유통과학연구 = Journal of distribution science, v.18 no.1, 2020년, pp.107 - 121  

KIM, Hyeong-Min (Department of Entrepreneurship, Chungang University)

Abstract AI-Helper 아이콘AI-Helper

Purpose: Shared mobility services are the most notable in the shared economy; however, they have yet to be activated in Korea due to various regulations and conflicts amongst stakeholders. Nevertheless, shared mobility has become an irresistible trend of the times, as it can cause a great deal of ec...

주제어

표/그림 (14)

AI 본문요약
AI-Helper 아이콘 AI-Helper

문제 정의

  • 본 연구의 목적은 공유모빌리티 서비스에 대한 사용자의 이용의도와 이용행위에 미치는 영향요인을 구조적으로 분석하는 것이다. 영향요인은 시장조사 결과로 밝혀진 미참여 의견을 바탕으로 신뢰적, 기술적, 절차적 관점으로 분류하였다.

가설 설정

  • H1: 초기신뢰는 공유모빌리티의 이용의도에 정(+)의 영향을 미칠 것이다.
  • H2: 초기신뢰는 이용의도를 매개로 이용행위에 정(+)의 영향을 미칠 것이다.
  • H3-1: 기술특성은 과업기술적합도에 정(+)의 영향을 미칠 것이다.
  • H3-2: 과업특성은 과업기술적합도에 정(+)의 영향을 미칠 것이다.
  • H3-3: IT에 대한 자기효능감은 과업기술적합도에 정(+)의 영향을 미칠 것이다.
  • H4: 과업기술적합도는 이용의도를 매개로 이용행위에 정(+)의 영향을 미칠 것이다.
  • H5: 공유모빌리티 서비스의 이용의도는 이용행위에 정(+)의 영향을 미칠 것이다.
  • H6: 전환비용은 이용의도와 이용행위의 관계에서 부(-)의 조절효과를 보일 것이다.
본문요약 정보가 도움이 되었나요?

참고문헌 (57)

  1. Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun : Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694. 

  2. Ajzen, I., & Fisbbein, M. (1974). Factors influencing intentions and the intention-behavior relation. Human Relations, 27(1), 1-15. 

  3. Burnham, T. A., Frels, J. K., & Mahajan, V. (2003). Consumer switching costs -A typology, antecedents, and consequences. Journal of the Academy of Marketing Science, 31(2), 109-126. 

  4. Burton, J. J. F. (1986). The share economy -Conquering stagflation. Industrial and Labor Relations Review, 39(2), 285-291. 

  5. Chebat, J. C., Davidow, M., & Borges, A. (2011). More on the role of switching costs in service markets: A research note. Journal of Business Research, 64(8), 823-829. 

  6. Colgate, M., & Lang, B. (2001). Switching barriers in consumermakets -An investigation of the financial services industry. Journal of Consumer Marketing, 18(4), 332-347. 

  7. Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211. 

  8. Dishaw, M. T., & Strong, D. M. (1998). Assessing software maintenance tool utilization using task-technology fit and fitness-for-use models. Software Maintenance: Research and Practice, 10(3), 151-179. 

  9. Divis, 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. 

  10. Farrell, D., Greig, F., & Hamoudi, A. (2018). The Online Platform Economy in 2018: Drivers, Workers, Sellers, andLessors. New York, NJ: JP Morgan Chase & Co. 

  11. Foye, L. (2017). Sharing Economy: 3 Industries Ripe For Disruption. Hampshire, UK: Juniper Research. 

  12. Furneaux, B. (2012). Task-technology fit theory: A survey and synopsis of the literature. In: Y. Dwivedi, M. Wade & S. Schneberger (Eds.), Information Systems Theory Integrated Series in Information Systems (pp. 87-106), New York, NJ: Springer. 

  13. Fuentes-Blasco, M., Saura, I. G., Berenguer-Contri, G., & Moliner-Velazquez, B. (2010). Measuring the antecedents of e-loyalty and the effect of switching costs on website. Service Industries Journal, 30(11), 1837-1852. 

  14. Goodhue, D. L. (1995). Understanding user evaluation of information systems. Management Science, 41(12), 1827-1844. 

  15. Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213-236. 

  16. Han, H. S., & Joung, S. K. (2011). Exploring the technology fit of digital media on product shopping task. Jounal of Society for e-Business Studies, 16(4), 283-299. 

  17. Hsieh, J. K., Hsieh, Y. C., Chiu, H. C., & Feng, Y. C. (2012). Post-adoption switching behavior for online service substitutes: A perspective of the push-pull-mooring framework. Computers in Human Behavior, 28(5), 1912-1920. 

  18. Jang, S. H. (2016). The Influence of task-technology fit on usage intention of SNS: Focused on social enterprise. Asia-Pacific Journal of Business Venturing and Entrepreneurship, 11(6), 61-69. 

  19. Jarupathirun, S., & Zahedi, F. M. (2007). Exploring the influence of perceptual factors in the success of web-based spatial DSS. Decision Support Systems, 43(3), 933-951. 

  20. Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2002). Why customers stay-measuring the underlying dimensions of services switching costs and managing their differential strategic outcomes. Journal of Business Research, 55(6), 441-450. 

  21. Ju, N. Y., Kim, J. W., & Kim, E. J. (2017). An empirical study on the factors influencing on the customer satisfaction in case of switching from mobile banking to fintech service. Journal of Information Systems, 26(4), 203-225. 

  22. Junglas, I., Abraham, C., & Ives, B. (2009). Mobile technology at the frontlines of patient care: Understanding fit and human drives in utilization decisions and performance. Decision Support Systems, 46(3), 634-647. 

  23. Kang, M., Gao, Y., Wang, T., & Wang, M. (2015). The role of switching costs in O2O platforms: Antecedents and consequences. International Journal of Smart Home, 9(3), 135-150. 

  24. Kim, G., Kim, W. W., & Lee, H. G. (2005). Investigation of factors influencing consumer initial trust and intention to use mobile banking services. Korean Management Science Review, 22(2), 13-34. 

  25. Kim, G., Shin, B., & Lee, H. G. (2009). Understanding dynamics between initial trust and usage intentions of mobile banking. Information Systems Journal, 19(3), 283-311. 

  26. Kim, H., & Cho, Y. (2018). Analysis of the bicycle-sharing economy: Strategic issues for sustainable development of society. Journal of Distribution Science, 16(7), 5-16. 

  27. Kim, K., & Prabhakar, B. (2004). Initial trust and the adoption of B2C e-commerce - The case of Internet banking. Data Base for Advances in Information Systems, 35(2), 50-64. 

  28. Kim, M., Kang, S., & Yang, H. (2008). The effect of task-technology fit on groupware usage and performance. Korean Management Review, 37(1), 67-96. 

  29. Kim, S., Lim, J., & Yang, S. (2016). An empirical study on influencing factors of untention to use third-party mobile payment services: Applying the task-technology fit model. Journal of Information Technology Services, 15(2), 185-201. 

  30. Kim, S. H. (2013). Moderating effects of switching cost on the IT service switching intention. Journal of the Korea Contents Association, 13(10), 452-460. 

  31. Kim, Y. (2015). The impact of brand awareness, perceived switching cost, user loyalty on purchase intention: Moderator as a purchase experience. Journal of Internet Electronic Commerce Resarch, 15(1), 75-94. 

  32. Klaus, T., Gyires, T., & Wen, H. J. (2003). Theuse of Web-based information systems for non-work activities - An empirical study. Human Systems Management, 22(3), 105-114. 

  33. Laudon, K. C., & Laudon, J. P. (2004). Management Information Systems: Managing the Digital Firm (8th ed.). Upper Saddle River, New Jersey: Prentice-Hall. 

  34. Lee, M. K. O., & Turnan, E. (2001). A trust model for consumer Internet shopping. International Journal of Electronic Commerce, 6(1), 75-91. 

  35. Lessig, L. (2008). REMIX: Making Art and Commerce Thrive in the Hybrid Economy. London, UK: The Penguin Press. 

  36. Li, Q. Z., & Lee, J. H. (2017). The influential relations on sharing economy and consumer traits. International Journal of Industrial Distribution & Business, 8(6), 75-86. 

  37. Lin, T. C., & Huang, C. C. (2008). Understanding knowledge management system usage antecedents: An integration of social cognitive theory and task technology fit. Information & Management, 45(6), 410-417. 

  38. Lippert, S. K., & Forman, H. (2006). A supply chain study of technology trust and antecedents to technology internalization consequences. International Journal of Physical Distribution & Logistics Management, 36(4), 271-288. 

  39. Mathieson, K., & Keil, M. (1998). Beyond the interface - Ease of use and task/technology fit. Information & Management, 34(4), 221-230. 

  40. McKnight, D. H., & Chervany, N. L. (2001). What trust means in e-commerce customer relationships -An interdisciplinary conceptual typology. International Journal of Electronic Commerce, 6(2), 35-59. 

  41. McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site: A trust building model. Journal of Strategic Information Systems, 11(3), 297-323. 

  42. McKnight, D. H., Cummings, L. L., & Chervany, N. L. (1998). Initial trust formation in new organizational relationships. Academy of Management Review, 23(3), 473-490. 

  43. Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222. 

  44. Park, H., & Noh, M. (2011). The influence of product attribute of smart clothing on initial trust and purchase intention: Focused on sensor - based smart clothing. Journal of the Korean Home Economics Association, 49(6), 13-22. 

  45. Park, K., Park, S., &Jang, H. (2014). Study on the sse of SNS(social network service) for tasks: Focus on the task-media fit. Journal of Digital Convergence, 12(2), 577-586. 

  46. Park, S. J., & Hwang, K. T. (2016). A study on the repurchase intention of customers in the foreign direct sales Internet shopping mall - Focused on the Japanese customers. Journal of Digital Convergence, 14(6), 199-218 

  47. Pendharkar, P. C., Khosrowpour, M., & Rodger, J. A. (2001). Development and testing of an instrument for measuring the user evaluations ofinformation technology in health care. Journal of Computer Information Systems, 41(4), 84-89. 

  48. Stephany, A. (2015). The Business of Sharing. Seoul, Korea: Hansmedia. 

  49. Sundararajan, A. (2016). The Sharing Economy. Seoul, Korea: Kyobobook. 

  50. Tian, X. F., Lee, J., & Wu, R. (2017). Use intention of chauffeured car services by O2O and sharing economy. Journal of Distribution Science, 15(12), 73-84. 

  51. Venkatesh, V., Morris, M. G., Divis, G. B., & Divis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. 

  52. Wang, L., & Kim, M. J. (2017). A Study on the customer continuance intention of O2O e-commerce mobile platform. e-Business Studies, 18(3), 187-199. 

  53. Wang, S., Beatty, S. E., & Foxx, W. (2004). Signaling the trustworthiness of small online retailers. Journal of Interactive Marketing, 18(1), 53-69. 

  54. Wu, J. H., Chen, Y. C., & Lin, L. M. (2007). Empirical evaluation of the revised end user computing acceptance model. Computers in Human Behavior, 23(1), 162-174. 

  55. Wu, R., & Lee, J. H. (2017a). The use intention of mobile travel apps by Korea-visiting Chinese tourists. Journal of Distribution Science, 12(5), 53-64. 

  56. Wu, R., &Lee, J. H. (2017b). The comparative study on third party mobile payment between UTAUT2 and TTF. Journal of Distribution Science, 15(11), 5-19. 

  57. Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760-767. 

관련 콘텐츠

오픈액세스(OA) 유형

GOLD

오픈액세스 학술지에 출판된 논문

저작권 관리 안내
섹션별 컨텐츠 바로가기

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

AI-Helper 아이콘
AI-Helper
안녕하세요, AI-Helper입니다. 좌측 "선택된 텍스트"에서 텍스트를 선택하여 요약, 번역, 용어설명을 실행하세요.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.

선택된 텍스트

맨위로