Factors that influence customers’ decision of using food ordering application in Ho Chi Minh City

Tieu Van Trang1, Tran The Nam1
1 University of Finance - Marketing

Main Article Content

Abstract

Number of people who use food ordering app is increasing significantly. Analyzing antecedents that influence consumers’ decision of using food ordering app will help enterprises to have more solutions that attract customers to install app. Based on the technological acceptance model (TAM), through mix method research, authors analyzed antecedents of attitude and behavior toward online food ordering app of users in Hochiminh city. The structural equation model was employed to test the proposed hypotheses by analyzing the data of 602 users. Results of the study have both theoretical and practical implications. In theory, they support the technological acceptance model (TAM). In managerial view, enterprises should improve the convenience of food ordering app and build the trust of users. Moreover, companies need to build the community of users in order to share information of food ordering app.

Article Details

References

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.
Al-Debei, M. M., Akroush, M. N., & Ashouri, M. I. (2015). Consumer attitudes towards online shopping: The effects of trust, perceived benefits, and perceived web quality. Internet Research, 25(5), 707–733.
Alagoz, S. M., & 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/https://doi.org/10.1016/j.sbspro.2012.09.195.
Alreck, P., & Settle, R. (2002). The hurried consumer: Time-saving perceptions of Internet and catalogue shopping. Journal of Database Marketing & Customer Strategy Management, 10(1), 25–35. https://doi.org/10.1057/palgrave.jdm.3240091.
Anderson, R. E., & Srinivasan, S. S. (2003). E-satisfaction and e-loyalty: A contingency framework. Psychology & Marketing, 20(2), 123–138. https://doi.org/10.1002/mar.10063.
Bagozzi, R. P., Yi, Y., & Phillips, L. W. (1991). Assessing Construct Validity in Organizational Research. Administrative Science Quarterly, 36(3), 421–458. https://doi.org/10.2307/2393203.
Bhattacherjee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201–214. https://doi.org/10.1016/S0167-9236(01)00111-7.
Bhattacherjee, A., Perols, J., & Sanford, C. (2008). Information Technology Continuance: A Theoretic Extension and Empirical Test. Journal of Computer Information Systems, 49(1), 17–26. https://doi.org/10.1080/08874417.2008.11645302.
Bui, M., & Kemp, E. (2013). E-tail emotion regulation: Examining online hedonic product purchases. International Journal of Retail & Distribution Management, 41(2), 155–170. https://doi.org/10.1108/09590551311304338.
Chen, Y. L., Kuo, M. H., Wu, S. Y., & Tang, K. (2009). Discovering recency, frequency, and monetary (RFM) sequential patterns from customers’ purchasing data. Electronic Commerce Research and Applications, 8(5), 241–251. https://doi.org/10.1016/j.elerap.2009.03.002.
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. Lawrence Erlbaum Associates, Publishers.
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.
Escobar-Rodríguez, T., & Carvajal-Trujillo, E. (2013). Online drivers of consumer purchase of website airline tickets. Journal of Air Transport Management, 32, 58–64. https://doi.org/10.1016/j.jairtraman.2013.06.018.
Fishbein, M., & Ajzen, I. (1975). Chapter 2. Theories of Attitude (EVT). Belief, Attitude, Intention, and Behavior, An Introduction to Theory and Research. Addison-Wesley.
Flavián, C., & Guinalíu, M. (2006). Consumer trust, perceived security and privacy policy: Three basic elements of loyalty to a web site. Industrial Management & Data Systems, 106(5), 601–620. https://doi.org/10.1108/02635570610666403.
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly, 27(1), 51–90. https://doi.org/10.2307/30036519.
Gentry, L., & Calantone, R. (2002). A Comparison of Three Models to Explain Shop-Bot Use on the Web. Psychology and Marketing, 19(11), 945–956. https://doi.org/10.1002/mar.10045.
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., & Thiele, K. O. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). SAGE Publications.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8.
Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic consumption: Emerging concepts, methods and propositions. Journal of Marketing, 46(3), 92–101. https://econpapers.repec.org/RePEc:oup:jconrs:v:9:y:1982:i:2:p:132-40.
Hung, S. Y., Chang, C. M., & Yu, T. J. (2006). Determinants of user acceptance of the e-Government services: The case of online tax filing and payment system. Government Information Quarterly, 23(1), 97-122. https:// doi.org/https://doi.org/10.1016/j.giq.2005.11.005.
Jensen, R. (2012). Do labor market opportunities affect young women’s work and family decisions? Experimental evidence from India. The Quarterly Journal of Economics, 127(2), 753–792. https://doi.org/10.1093/qje/qjs002.
Jiang, L. A., Yang, Z., & Jun, M. (2013). Measuring consumer perceptions of online shopping convenience. Journal of Service Management, 24(2), 191–214. https://doi.org/10.1108/09564231311323962..
Kim, K., Park, J., & Kim, J. (2014). Consumer-brand relationship quality: When and how it helps brand extensions. Journal of Business Research, 67(4), 591–597. https://doi.org/10.1016/j.jbusres.2013.03.001.
Mokhtarian, P. L. (2004). A conceptual analysis of the transportation impacts of B2C e-commerce. Transportation, 31(3), 257–284. https://doi.org/10.1023/B:PORT.0000025428.64128.d3.
Park, C. H., & Kim, Y. G. (2003). Identifying key factors affecting consumer purchase behavior in an online shopping context. International Journal of Retail & Distribution Management, 31(1), 16–29. https://doi.org/10.1108/09590550310457818
Pavlou, P. (2001). Integrating Trust in Electronic Commerce with the Technology Acceptance Model: Model Development and Validation. Americas Conference on Information Systems, 816–822.
Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101–134. https://doi.org/10.1080/10864415.2003.11044275.
Rezaei, S., Shahijan, M. K., Amin, M., & 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.
Taylor, S., & Todd, P. A. (1995). Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6(2), 144–176. http://www.jstor.org/stable/23011007.
Thamizhvanan, A., & Xavier, M. J. (2013). Determinants of customers’ online purchase intention: An empirical study in India. Journal of Indian Business Research, 5(1), 17-32. https://doi.org/10.1108/17554191311303367.
Weisberg, J., Te’eni, D., & Arman, L. (2011). Past purchase and intention to purchase in e‐commerce: The mediation of social presence and trust. Internet Research, 21(1), 82-96. https://doi.org/10.1108/10662241111104893.
Yeo, V. C. S., Goh, S. K., & 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/https://doi.org/10.1016/j.jretconser.2016.12.013.