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What Affects Consumers' Attitude and Usage Intention of O2O Apps?: Integration of TAM, TPB, and Transaction Cost Theory

  • Won In Lee (Department of Management Administaration, Tech University of Korea)
  • Received : 2022.08.12
  • Accepted : 2023.02.03
  • Published : 2023.06.30

Abstract

This study is about the attitudes and intentions of consumers considering the usage of O2O application (app) under the COVID-19 situation. By integrating TAM and TPB as a theoretical background, we selected VPC (various product choice) and PII (product information intensity) as new functional external variables that have a positive effect on new system called O2O commerce. We also applied the transaction cost theory to investigate the obstacle of O2O business. We conducted a survey of consumers in large cities in the Korean market. As a result of this study, it was found that the more O2O app users recognized the influence of SN (subject norms), the more useful O2O app was, the more it led to a change in attitude and usage intention was positively significant. In addition, as the O2O app was easy to use and useful, and the SN was recognized, the user's attitude was positive. On the other hand, it was also found that the transaction cost that consumers have to pay had a negative effect on usage intention. Additionally, VPC and PII have been shown to positively influence on usefulness of O2O apps.

Keywords

References

  1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
  2. Ajzen, I. (2002). Residual effects of past on later behavior: Habituation and reasoned action perspectives. Personality and Social Psychology Review, 6(2), 107-122. https://doi.org/10.1207/S15327957PSPR0602_02
  3. Alagoz, S. M., and Hekimoglu, H. (2012). A study on tam: analysis of customer attitudes in online food ordering system. Procedia-Social and Behavioral Sciences, 62, 1138-1143. https://doi.org/10.1016/j.sbspro.2012.09.195
  4. Alalwan, A. A. (2020). Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse. International Journal of Information Management, 50, 28-44. https://doi.org/0.1016/J.IJINFOMGT.2019.04.008 1016/J.IJINFOMGT.2019.04.008
  5. Bang, Y., Lee, D.-J., Han, K., Hwang, M., and Ahn, J.-H. (2013). Channel capabilities, product characteristics, and the impacts of mobile channel introduction. Journal of Management Information Systems, 30(2), 101-126. https://doi.org/10.2753/MIS0742-1222300204
  6. Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 351-370.
  7. Bucklin, L. P., and Sengupta, S. (1993). Organizing successful co-marketing alliances. Journal of Marketing, 57(2), 32-46. https://doi.org/10.307/1252025
  8. Che, T., Peng, Z., Lim, K. H., and Hua, Z. (2015). Antecedents of consumers' intention to revisit an online group-buying website: A transaction cost perspective. Information & Management, 52(5), 588-598. https://doi.org/10.1016/j.im.015.04.004
  9. Chen, S. H., and Lee, K. P. (2008). The role of personality traits and perceived values in persuasion: An elaboration likelihood model perspective on online shopping. Social Behavior and Personality: an international journal, 36(10), 1379-1399. https://doi.org/10.2224/sbp.200.36.10.1379
  10. Cheong, F., and Law, R. (2022). Will Macau's Restaurants Survive or Thrive after entering the O2O food delivery platform in the COVID-19 Pandemic? International Journal of Environmental Research and Public Health, 19(9), 5100. https://doi.org/10.3390/ijerph19095100
  11. Cho, M., Bonn, M. A., and Li, J. Justin. (2019). Differences in perceptions about food delivery apps between single-person and multi-person households. International Journal of Hospitality Management, 77, 108-116. https://doi.org/10.1016/j.ijhm.2018.06.019
  12. Cho, N., and Park, S. (2001). Development of electronic commerce user consumer satisfaction index (ECUSI) for Internet shopping. Industrial Management & Data Systems, 101(8), 400-406. https://doi.org/10.1108/EUM0000000006170
  13. Coase, R. H. (1937). The nature of the firm. Economica, 4(16), 386-405. https://doi.org/10.1111/j.1468-0335.1937.tb00002.x
  14. Davis, F. (1989). Technology acceptance model: origins. Working Papers on Information Systems, 35-59.
  15. Davis, F. D., Bagozzi, R. P., and Warshaw, 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
  16. Fornell, C., and 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/10.2307/3151312
  17. Gao, L., and Waechter, K. A. (2017). Examining the role of initial trust in user adoption of mobile payment services: an empirical investigation. Information Systems Frontiers, 19(3), 525-548. https://doi.org/10.1007/s10796-015-9611-0
  18. Hair, J. F., Risher, J. J., Sarstedt, M., and Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
  19. He, Z., Han, G., Cheng, T. C. E., Fan, B., and Dong, J. (2019). Evolutionary food quality and location strategies for restaurants in competitive online-to-offline food ordering and delivery markets: An agent-based approach. International Journal of Production Economics, 215, 61-72. https://doi.org/10.1016/j.ijpe.2018.05.008
  20. Humbani, M., and Wiese, M. (2019). An integrated framework for the adoption and continuance intention to use mobile payment apps. International Journal of Bank Marketing, 37(2), 646-664. https://doi.org/10.1108/IJBM-03-2018-0072
  21. Hung, M.-C., Yang, S.-T., and Hsieh, T.-C. (2012). An examination of the determinants of mobile shopping continuance. International Journal of Electronic Business Management, 10(1), 29.
  22. Kim, M., and Qu, H. (2014). Travelers' behavioral intention toward hotel self-service kiosks usage. International Journal of Contemporary Hospitality Management, 26(2), 225-245. https://doi.org/10.1108/IJCHM-09-2012-0165
  23. Lee, E.-Y., Lee, S.-B., and Jeon, Y. J. J. (2017). Factors influencing the behavioral intention to use food delivery apps. Social Behavior and Personality, 45(9), 1461-1474. https://doi.org/10.2224/sbp.6185
  24. Lee, M.-C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8(3), 130-141. https://doi.org/10.1016/j.elerap.2008.11.006
  25. Liang, T.-P., and Huang, J.-S. (1998). An empirical study on consumer acceptance of products in electronic markets: A transaction cost model. Decision Support Systems, 24(1), 29-43. https://doi.org/10.1016/S0167-9236(98)00061-X
  26. Liebana-Cabanillas, F., Marinkovic, V., and Kalinic, Z. (2017). A SEM-neural network approach for predicting antecedents of m-commerce acceptance. International Journal of Information Management, 37(2), 14-24. https://doi.org/10.1016/j.ijinfomgt.2016.10.008
  27. Lynch, B. M. Morgan. C. L. J. (2017). Morgan Stanley Bank of America Merrill Lynch Trust 2017-C33 - Appendix. https://www.fitchratings.com/research/structured-finance/morgan-stanley-bank-of-america-merrill-lynch-trust-2017-c33-appendix-26-04-2017
  28. Ornstein, S., and Dumas, C. (2015). Cleaning Up at DiningIn. com. Journal of Marketing Development and Competitiveness, 9(2), 47.
  29. Palmer, J. W., and Griffith, D. A. (1998). An emerging model of Web site design for marketing. Communications of the ACM, 41(3), 44-51. https://doi.org/10.1145/272287.272296
  30. Pelsmaeker, S., Schouteten, J. J., Gellynck, X., Delbaere, C., De Clercq, N., Hegyi, A., Kuti, T., Depypere, F., and Dewettinck, K. (2017). Do anticipated emotions influence behavioural intention and behaviour to consume filled chocolates? British Food Journal, 119(9), 1983-1998. https://doi.org/10.1108/BFJ-01-2016-0006
  31. Piroth, P., Ritter, M. S., and Rueger-Muck, E. (2020). Online grocery shopping adoption: do personality traits matter? British Food Journal, 122(3), 957-975. https://doi.org/10.1108/ BFJ-08-2019-0631
  32. Quevedo-Silva, F., Freire, O., de Oliveira Lima-Filho, D., Brandao, M. M., Isabella, G., and Moreira, L. B. (2016). Intentions to purchase food through the internet: Developing and testing a model. British Food Journal, 118(3), 572-587. https://doi.org/10.1108/BFJ-09-2015-0305
  33. Ray, A., Dhir, A., Bala, P. K., and Kaur, P. (2019). Why do people use food delivery apps (FDA)? A uses and gratification theory perspective. Journal of Retailing and Consumer Services, 51, 221-230. https://doi.org/10.1016/j.jretconser.2019.05.025
  34. Rezaei, S., Shahijan, M. K., Amin, M., and Ismail, W. K. W. (2016). Determinants of app stores continuance behavior: A PLS path modelling approach. Journal of Internet Commerce, 15(4), 408-440. https://doi.org/10.1080/15332861.2016.1256749
  35. Roh, M., and Park, K. (2019). Adoption of O2O food delivery services in South Korea: The moderating role of moral obligation in meal preparation. International Journal of Information Management, 47, 262-273. https://doi.org/10.1016/j.ijinfomgt.2018.09.017
  36. Sabherwal, R., and Vijayasarathy, L. (1994). An empirical investigation of the antecedents of telecommunication-based interorganizational systems. European Journal of Information Systems, 3(4), 268-284. https://doi.org/10.1057/ejis.1994.32
  37. Shah, A. M., Yan, X., and Qayyum, A. (2021). Adoption of mobile food ordering apps for O2O food delivery services during the COVID-19 outbreak. British Food Journal, 124(11), 3368-3395. https://doi.org/10.1108/BFJ -09-2020-0781
  38. Shareef, M. A., Baabdullah, A., Dutta, S., Kumar, V., and Dwivedi, Y. K. (2018). Consumer adoption of mobile banking services: An empirical examination of factors according to adoption stages. Journal of Retailing and Consumer Services, 43, 54-67. https://doi.org/10.1016/j.jretconser.2018.03.003
  39. Shareef, M. A., Dwivedi, Y. K., Kumar, V., and Kumar, U. (2017). Content design of advertisement for consumer exposure: Mobile marketing through short messaging service. International Journal of Information Management, 37(4), 257-268. https://doi.org/10.1016/j.ijinfomgt.2017.02.003
  40. Suhartanto, D., Helmi Ali, M., Tan, K.H., Sjahroeddin, F., and Kusdibyo, L. (2019). Loyalty toward online food delivery service: The role of e-service quality and food quality. Journal of Foodservice Business Reswarch, 22(1), 81-97. https://doi.org/10.1080/15378020.2018.1546076
  41. Talwar, S., Dhir, A., Scuotto, V., and Kaur, P. (2021). Barriers and paradoxical recommendation behaviour in online to offline (O2O) services. A convergent mixed-method study. Journal of Business Research, 131, 25-39. https://doi.org/10.1016/j.jbusres.2021.03.049
  42. Teo, T. S. H., and Yu, Y. (2005). Online buying behavior: A transaction cost economics perspective. Omega, 33(5), 451-465. https://doi.org/10.1016/j.omega.2004.06.002
  43. Teo, T. S. H., Wang, P., and Leong, C. H. (2004). Understanding online shopping behaviour using a transaction cost economics approach. International Journal of Internet Marketing and Advertising, 1(1), 62-84. https://doi.org/10.1504/IJIMA.2004.003690
  44. Teo, T., and Van Schalk, P. (2009). Understanding technology acceptance in pre-service teachers: A structural-equation modeling approach. Asia-Pacific Education Researcher, 18(1), 47-66. https://doi.org/10.3860/taper.v18i1. 1035
  45. Teo, T., Zhou, M., and Noyes, J. (2016). Teachers and technology: Development of an extended theory of planned behavior. Educational Technology Research and Development, 64(6), 1033-1052. https://doi.org/10.1007/s11423-016-9446-5
  46. Thompson, R. L., Higgins, C. A., and Howell, J. M. (1994). Influence of experience on personal computer utilization: Testing a conceptual model. Journal of Management Information Systems, 11(1), 167-187. https://doi.org/10.1080/07421222.1994.11518035
  47. Trotter. (2021). 25 top brands using O2O retail initiatives - Insider Trends. Trotter, Retrieved from https://www.insider-trends.com/25-brands-using-o2o-retail/
  48. Venkatesh, V., and Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
  49. Venkatesh, V., Morris, M. G., Davis, G. B., and 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
  50. Wang, O., and Somogyi, S. (2018). Consumer adoption of online food shopping in China. British Food Journal, 120(12), 2868-2884. https://doi.org/10.1108/BFJ-03-2018-0139
  51. Wigand, R. T. (1997). Electronic commerce: Definition, theory, and context. The Information Society, 13(1), 1-16. https://doi.org/10.1080/019722497129241
  52. Williamson, O. E. (1975). Markets and hierarchies: analysis and antitrust implications: A study in the economics of internal organization. Administrative Science Quarterly, 22(3), 540-544.
  53. Xu, X., and Huang, Y. (2019). Restaurant information cues, Diners' expectations, and need for cognition: experimental studies of online-to-offline mobile food ordering. Journal of Retailing and Consumer Services, 51, 231-241. https://doi.org/10.1016/j.jretconser.2019.06.010
  54. Yang, F. X., Li, X., Lau, V. M. C., and Zhu, V. Z. (2021). To survive or to thrive? China's luxury hotel restaurants entering O2O food delivery platforms amid the COVID-19 crisis. International Journal of Hospitality Management, 94, 102855. https://doi.org/10.1016/j.ijhm.2020.102855
  55. Yeo, V. C. S., Goh, S.-K., and Rezaei, S. (2017). Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services. Journal of Retailing and Consumer Services, 35, 150-162. https://doi.org/10.1016/j.jretconser.2016.12.013
  56. Zanetta, L. D. A., Hakim, M. P., Gastaldi, G. B., Seabra, L. M. A. J., Rolim, P. M., Nascimento, L. G. P., Medeiors, C. O., and da Cunha, D. T. (2021). The use of food delivery apps during the COVID-19 pandemic in Brazil: The role of solidarity, perceived risk, and regional aspects. Food Research International, 149, 110671. https://doi.org/10.1016/j.foodres.2021.110671
  57. Zhang, M., Luo, M., Nie, R., and Zhang, Y. (2017). Technical attributes, health attribute, consumer attributes and their roles in adoption intention of healthcare wearable technology. International Journal of Medical Informatics, 108, 97-109. https://doi.org/10.1016/j.ijmedinf.2017.09.016
  58. Zhao, Y., and Bacao, F. (2020). What factors determining customer continuingly using food delivery apps during 2019 novel coronavirus pandemic period?. International Journal of Hospitality Management, 91, 102683. https://doi.org/10.1016/j.ijhm.2020.102683
  59. Zugara.com. (2021). How Brands And Retailers Are Utilizing Pokemon Go, Retrieved from http://zugara.com/how-brands-and-retailers-are-utilizing-pokemon-go
  60. Zvarikova, K., Gajanova, L., and Higgins, M. (2022). Adoption of delivery apps during the COVID-19 crisis: consumer perceived value, behavioral choices, and purchase intentions. Journal of Self-Governance and Management Economics, 10(1), 69-81. https://doi.org/10.22381/jsme10120225.