International Journal of Advanced Culture Technology

  • 제12권3호
  • /
  • Pages.345-354
  • /
  • 2024
  • /
  • 2288-7202(pISSN)
  • /
  • 2288-7318(eISSN)
국제문화기술진흥원 (The International Promotion Agency of Culture Technology)
권호 표지
DOI QR코드

DOI QR Code

Research on the Factors Influencing College Students' Wsillingness to sParticipate in Sports Online Competitions

  • Rui Liu (School of Physical Sciences, Lingnan Normal University) ;
  • Myeong-Cheol Choi (Department of Business, Gachon University)
  • 투고 : 2024.07.12
  • 심사 : 2024.09.01
  • 발행 : 2024.09.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

The sports cloud competition based on the network online platform breaks through the limitation of the time and space of traditional sports competition, changes the competitive environment and mode of sports competition, and is a new mode of sports competition. The detailed possibility model has been widely used in the study of information processing and attitude change. In order to better explore the sports cloud competition, we take 463 college students in Lingnan Normal University as the survey object based on the concept of detailed possibility model, and collects data through a pre-compiled questionnaire, so as to obtain the factors that affect the willingness of college students to participate in sports cloud competition, and explore the possibility of promoting sports cloud competition. Our results show that the convenience characteristics of the central path level are important factors for college students to participate in sports cloud competitions, and the credits, examinations and exercises at the edge path level can become important factors for college students to participate in sports cloud competitions, which play a positive role in promoting college students' participation in sports cloud competitions and are conducive to the promotion and application of sports cloud competitions.

키워드

과제정보

Project of Federation of University Sports of China (202203009)

참고문헌

  1. J. Kitchen P, Kerr G and E. Schultz D, et al. The elaboration likelihood model: review, critique and research agenda. European Journal of marketing, 48(11/12): 2033-2050, 2014. https://doi.org/10.1108/EJM-12-2011-0776 
  2. Divine A, Watson P M and Baker S, et al. Facebook, relatedness and exercise motivation in university students: a mixed methods investigation. Computers in Human Behavior, 91: 138-150, 2019. https://doi.org/10.1016/j.chb.2018.09.037 
  3. He, W. and Jin, C. A study on the influence of the characteristics of key opinion leaders on consumers' purchase intention in live streaming commerce: based on dual-systems theory. Electronic Commerce Research, 1235-1265, 2022. https://doi.org/10.1007/s10660-022-09651-8 
  4. Chang H H, Lu Y Y and Lin S C. An elaboration likelihood model of consumer respond action to facebook second-hand marketplace: lmpulsiveness as a moderator. Information & Management, 57(2):103171, 2020. https://doi.org/10.1016/j.im.2019.103171 
  5. Urbonavicius S, Degutis M and Zimaitis I, et al. From social networking to willingness to disclose personal data when shopping online: Modelling in the context of social exchange theory. Journal of Business Research, 136:76-85, 2021. https://doi.org/10.1016/j.jbusres.2021.07.031 
  6. Wang L, Hu H H and Yan J, et al. Privacy calculus or heuristic cues? The dual process of privacy decision making on Chinese social media. Journal of Enterprise Information Management, 33(2):353-380, 2019. https://doi.org/10.1108/JEIM-05-2019-0121 
  7. Li K, Zhou C and Yu X. Exploring the differences of users' interaction behaviors on microblog: The moderating role of microblogger's effort. Telematics and Informatics, 59: 101553, 2021. https://doi.org/10.1016/j.tele.2020.101553 
  8. Ho S Y and Bodoff D. The effects of web personalization on user attitude and behavior: An integration of the elaboration likelihood model and consumer search theory. MIS Quarterly, 38(2):497-520, 2014. https://www.jstor.org/stable/26634936 
  9. Lin X, Wang X and Hajli N. Building e-commerce satisfaction and boosting sales: The role of social commerce trust and its antecedents. International journal of electronic commerce, 23(3): 328-363, 2019. https://doi.org/10.1080/10864415.2019.1619907 
  10. Choi W and Stvilia B. Web credibility assessment: Conceptualization, operationalization, variability, and models. Journal of the Association for Information Science and Technology, 66(12):2399-2414, 2015. https://doi.org/10.1002/asi.23543 
  11. Wongkitrungrueng A and Assarut N. The role of live streaming in building consumer trust and engagement with social commerce sellers. Journal of business research, 117: 543-556, 2020. https://doi.org/10.1016/j.jbusres.2018.08.032 
  12. Petty R E and Cacioppo J T, Schumann D. Central and peripheral routes to advertising effectiveness: The moderating role of involvement. Journal of consumer research, 10(2): 135-146, 1983. https://doi.org/10.1086/208954 
  13. Petty R.E. and Cacioppo J.T. The Elaboration Likelihood Model of Persuasion. Advances in Consumer Research, 19(4):123-205, 1984.
  14. Zeng Jianghong, Huang Xiangrong and Yang Yalan. Research on the Factors that Influence Brand Promotion Effect in Crowdfunding: Based on Elaboration Likelihood Model Perspective. Management Review, 34(9):170-180, 2022. 
  15. SEARS D O. Review of communication and persuasion:Central and peripheral routes to attitude change. Public Opinion Quarterly, 52:262-265, 1988. 
  16. Bhattacherjee A and Sanford C. Influence processes for information technology acceptance: An elaboration likelihood model. MIS quarterly, 30(4):805-825, 2006. https://doi.org/10.2307/25148755 
  17. Tang L R, Jang S S and Morrison A. Dual-route communication of destination websites. Tourism Management, 33(1):38-49, 2012. https://doi.org/10.1016/j.tourman.2011.01.021 
  18. Sussman S W and Siegal W S. Informational influence in organizations: An integrated approach to knowledge adoption. Information systems research, 14(1): 47-65, 2003. https://doi.org/10.1287/isre.14.1.47.14767 
  19. Petty R E, Brinol P and Tormala Z L. Thought confidence as a determinant of persuasion: the self-validation hypothesis. Journal of personality and social psychology, 82(5): 722, 2002. https://doi.org/10.1037/0022-3514.82.5.722 
  20. Jin X L, Yin M and Zhou Z, et al. The differential effects of trusting beliefs on social media users' willingness to adopt and share health knowledge. Information Processing & Management, 58(1):102413, 2021. https://doi.org/10.1016/j.ipm.2020.102413 
  21. Wu W Y, Qomariyah A and Sa N T T, et al. The integration between service value and service recovery in the hospitality industry: An application of QFD and ANP. International Journal of Hospitality Management, 75: 48-57, 2018. https://doi.org/10.1016/j.ijhm.2018.03.010 
  22. Kim M J, Lee C K and Jung T. Exploring consumer behavior in virtual reality tourism using an extended stimulus-organism-response model. Journal of travel research, 59(1): 69-89, 2020. https://doi.org/10.1177/0047287518818915 
  23. Fang Y H and Chiu C M. In justice we trust: Exploring knowledge-sharing continuance intentions in virtual communities of practice. Computers in human behavior, 26(2): 235-246, 2010. https://doi.org/10.1016/j.chb.2009.09.005 
  24. Kim, J. A Case Study of eSports' NFT utilization and Discussion of Activation Plan. The Journal of the Convergence on Culture Technology, 9(2): 493-502, 2023. https://doi.org/10.17703/JCCT.2023.9.2.493
  25. Chen R, Wang Y, Choi M, He Z and Li M. A Study on the Success Factors of Sinar Mas Group in Indonesia. International Journal of Advanced Culture Technology, 11(2): 118-124, 2023. https://doi.org/10.17703/IJACT.2023.11.2.118 
  26. Xia Y, Li M, Zhang J, Choi M and Kim H. The Competitiveness Analysis of Geely Automobile Group. International Journal of Advanced Culture Technology, 12(2), 402-408, 2024. https://doi.org/10.17703/IJACT.2024.12.2.402