DOI QR코드

DOI QR Code

A Study on the User Acceptance of O2O Services : Mediating Effect of Customer Attitude

  • CHUNG, Ji Bok (Department of Retail Management, Kongju National University) ;
  • NAM, Sung Jip (Department of Business Administration, Hannam University)
  • Received : 2020.08.11
  • Accepted : 2020.09.09
  • Published : 2020.09.30

Abstract

Purpose - New technologies allow service providers to integrate all the customer information within and between contact channels so that they can offer individualized services. The availability of new mobile devices enables retailers to interact with customers through countless channels (Rigby, 2011). The objective of this research is to examine customers' attitudes toward O2O (on-line to off-line) services and their intention to use based on the Technology Acceptance Model (TAM). Research design, data, and methodology - Utilizing the TAM model, the mediating effect of the users' attitudes toward O2O services on the relationship among perceived ease of use, perceived usefulness, perceived risks and intention to use are to be investigated. Results - The result shows that the perceived ease of use, perceived usefulness, perceived risks have a significant effect on customers' attitudes toward O2O services. It is also revealed that the attitude toward O2O services has a mediating effect among perceived ease of use, perceived usefulness, perceived risks and intention to use. Conclusions - The boundary between on-line and off-line is eroding and various services based on the O2O platform are growing. The results of this study and managerial implications can be applied to O2O platform operators or enterprises planning to sharp on their competitiveness edge through offering variations of service channels.

Keywords

References

  1. Ajzen, I., & Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological Bulletin, 82(2). 261-277 https://doi.org/10.1037/h0076477
  2. Ajzen, I. (2011). The theory of planned behavior: reactions and reflections. Psychology and Health, 26(9), 1113-1127. https://doi.org/10.1080/08870446.2011.613995
  3. An, K. H., Lee, S. B., & Suh, Y. H. (2018). An effect of O2O service users' motivation on loyalty through expectation-confirmation and satisfaction. Journal of Korean Soc Qual Management, 46(4), 923-938. https://doi.org/10.7469/JKSQM.2018.46.4.923
  4. Ashraf, A. R., Thongpapanl, N., & Auh, S. (2014). The application of the technology acceptance model under different cultural context: the case of online shopping adoption. Journal of International Marketing, 22(3), 68-93. https://doi.org/10.1509/jim.14.0065
  5. Chi, Y. S., Kang, M. Y., Han, K. S., & Choi, J. I. (2016). A study on the discontinuance intention on O2O commerce: with a focus on the mediating effects of perceived risk and user resistance, International Journal of u-and e-Service, Science and Technology, 9(2), 207-218.
  6. Chuttur, M. (2009). Overview of the technology acceptance model: origins, developments and future directions. Indiana University, USA Sprouts. Working Papers on Information Systems, 9(37), 9-37
  7. Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information system: Theory and results. Boston, MA: Doctoral Dissertation. Massachusetts Institute of Technology.
  8. Davis, F. D. (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
  9. Davis, F. D., Bagozzi, R. P., & Warsaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models, Management Science, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982
  10. Fishbein, M., & Ajzen, I. (1970). The prediction of behavior from attitudinal and normative variables. Journal of Experimental Social Psychology, 6(1), 466-487. https://doi.org/10.1016/0022-1031(70)90057-0
  11. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
  12. Hayes, A. F. (2017). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-based Approach. Emeryville, CA: Guilford Press.
  13. Kim, N., & Lee. D. (2016). Differences in the consumers' intention to adopt in accordance with the characteristics of car O2O services. Innovation studies, 11(1), 71-96.
  14. Lee, Y. H., & Jeon, I. O. (2017). The effect of characteristics of ICT-based O2O service on user satisfaction - focusing on the mediating effect of user safety. Journal of Digital Convergence, 15(4), 157-169. https://doi.org/10.14400/JDC.2017.15.4.157
  15. Lee, O. J., & Yang, D. W. (2017). A study on the effect of O2O service quality on user satisfaction and intention of reuse. Journal of Digital Convergence, 15(6), 165-178. https://doi.org/10.14400/JDC.2017.15.6.165
  16. Maciejewski, G. (2011). The meaning of perceived risk in purchasing decisions of the Polish customers, scientific annals of the "Alexandru Ioan Cuza" University of Iasi. Economic Sciences, volume LVIII, 280-304.
  17. McCoy, S. Galletta, D. F., & King, W. R. (2007). Applying TAM across cultures: the need for caution. European Journal of Information Systems, 16(1), 81-90, https://doi.org/10.1057/palgrave.ejis.3000659
  18. Mitchell, V. W., Davies, F., Moutinho, L., & Vassos, V. (1999). Using neural networks to understand service risk in the holiday product. Journal of Business Research, 46(2), 167-180 https://doi.org/10.1016/S0148-2963(98)00020-4
  19. Oh, H. Y. (2016). Innovativeness or confidence? The effect of consumer innovativeness and self-efficacy on the acceptance and diffusion of innovative technology. International Journal of Software Engineering and Its Applications, 10(8), 117-126. https://doi.org/10.14257/ijseia.2016.10.8.11
  20. Rigby, D. K. (2011). The future of shopping. Harvard Business Review, 12(1),1-18.
  21. Spears, N., & Singh, S. N. (2004). Measuring attitude toward the brand and purchase intentions. Journal of Current Issues & Research in Advertising, 26(2), 53-66. https://doi.org/10.1080/10641734.2004.10505164
  22. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
  23. Verhoef, P. C., Kannan, P. K., & Inman, J. J. (2015). From multi-channel retailing to omni-channel retailing: Introduction to the special issue on multi-channel retailing. Journal of Retialing, 91(20), 174-181. https://doi.org/10.1016/j.jretai.2015.02.005
  24. Wenjie, Z. & Moon, T. (2019). The impact of O2O service influencing factors on repurchase intention in China. Proceeding of Korean MIS conference, 499-503.
  25. Wu, J., & Lu, X., (2013), Effects of extrinsic and intrinsic motivators on using utilitarian, hedonic, and dual-purposed information systems: a meta-analysis. Journal of the Association for Information Systems, 14(3), 153-191. https://doi.org/10.17705/1jais.00325
  26. Yim, D. S., & Han, S. S. (2016). Omnichannel's perceived ease of use and perceived usefulness effect on omnichannel use and customer-brand relationship. Journal of Distribution Science, 14(7), 83-90.
  27. You, J. H., & Park, C. A. (2010). A comprehensive review of technology acceptance model researches. Entrue Journal of Information Technology, 9(2), 31-50.
  28. Zhang, R. (2013). The development of O2O model enterprises. Logistics Engineering and management, 35(12), 127-129. https://doi.org/10.3969/j.issn.1674-4993.2013.12.051