Gen Z Consumers’ Online Shopping Motives, Attitude, and Shopping Intention

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Khomson Tunsakul


The Internet’s explosive growth has facilitated e-commerce and online retailing development. Consumers also benefit from product and service customization, ease of transactions, and real time interactive communications. Gen Z consumers were the main target respondents in this study due to their growing number and dominance in global markets, including Thailand. This study aimed to investigate whether Gen Z’s online shopping intention would be influenced by such independent variables as hedonic motive, simplicity motive, and usefulness motive. In addition, attitude towards online shopping was hypothesized to mediate the relationship between the independent variables and online shopping intention. The research results were statistically analyzed using Structural Equation Modeling. The analysis revealed that hedonic and usefulness motives had a significant impact on attitude towards online shopping. Furthermore, attitude towards online shopping had a significant impact on online shopping intention. However, simplicity motive did not have a significant impact on attitude towards online shopping. The findings have considerably contributed to marketing practices in the digitally connected world.


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Abdul-Munmin, A. (2010). Repeat purchase intentions in online shopping: The role of satisfaction, attitude, and online retailers’ performance. Journal of International Consumer Marketing, 23(1), 5–20.

Ajzen, I. (2012). Attitudes and persuasion. In K. Deaux & M. Snyder (eds.). The Oxford handbook of personality and social psychology (pp. 367-393). Oxford University Press.

Alavi, S., Rezaei, S., Valaei, N., & Ismail, W. (2016). Examining shopping mall consumer decision-making styles, satisfaction and purchase intention. The International Review of Retail Distribution and Consumer Research, 26(3), 272–303.

Bassiouni, D., & Hackley, C. (2014). Generation Z' children's adaptation to digital consumer culture: A critical literature review. Journal of Customer Behaviour, 13(2), 113–133.

Berenson, M., & Levine, D. (1999). Basic business: Concepts and applications (7th ed.). Pearson Education.

Bilgihan, A. (2016). Gen Y customer loyalty in online shopping: An integrated model of trust, user experience and branding. Computer in Human Behavior, 61, 103–113.

Brown, M. (2017). AdReaction: Engaging Gen X, Y, and Z. (2017, January 10). https://www.

Chang, M., Cheung, W., & Lai, V. (2012). Literature derived reference models for the adoption of online shopping. Information and Management, 42(4), 543–559.

Childers, T., Carr, C., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77(4), 511–535.

Chu, C., & Lu, H. (2007). Factors influencing online music purchase intention in Taiwan: An empirical study based on the value-intention framework. Internet Research, 17(2), 139–155.

Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly. 13(3), 319–340.

Escobar-Rodriguez, T., & Carvajal-Trujillo, E. (2013). Online drivers of consumer purchase of website airline tickets. Journal of Air Transport Management, 32, 58–64.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intentions, and behavior: An introduction to theory and research. Addison-Wesley.

Hair, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate Data Analysis (6th ed.). Pearson Prentice Hall.

Ho, R. (2006). Handbook of univariate and multivariate data analysis and interpretation with SPSS. Taylor & Francis Group.

Ingham, J., Cadieux, J., & Berrada, A. M. (2015). E-shopping acceptance: qualitative and meta-analytic review. Information and Management, 52(1), 44–60.

Jaafar, S., Lalp, P., & Naba, M. (2011). Consumers’ perceptions, attitudes and purchase intention towards private label food products in Malaysia. Asian Journal of Business and Management Sciences, 2(8), 73–90.

Ku, E. (2011). Recommendations from a virtual community as a catalytic agent of travel decisions. Internet Research, 21(3), 282–303.

Kuo, Y., & Yen, S. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computer in Human Behavior, 25(1), 103–110.

Malhotra, N. (2007). Marketing research: An applied orientation (5th ed.). New Jersey: Pearson Prentices Hall.

Mort, G., & Rose, T. (2004). The effect of product type on value linkages in the means-end chain implications for the theory and method. Journal of Consumer Behavior, 3(3), 221–234.

Park, E., & Kim, K. (2013). User acceptance of long-term evolution (LTE) services: An application of extended technology acceptance model. Program Electronic Library and Information Systems, 47(2), 188–205.

Priporas, C., Stylos, N., & Fotiadis, A. (2017). Generation Z consumers’ expectations of interactions in smart retailing: A future agenda. Computers in Human Behavior, 77, 374–381.

Rezaei, S., Shahijan, M., Amin, M., & Ismail, W. (2016). Determinants of app stores continuance behavior: A PLS path modeling approach. Journal of Internet Commerce, 15(4), 408–440.

Tunsakul, K. (2018). Generation Z’s perception of servicescape, their satisfaction and their retail shopping behavioral outcomes. Human Behavior, Development and Society, 19(1), 123–133.

Wood, S. (2013). Generation Z as consumers: Trends and Innovation. Institute for Emerging Issues: NC State University.

Yang, T., & Lai, H. (2006). Comparison of product bundling strategies on different online shopping behaviors. Electronic Commerce Research and Application, 5(4), 295–304.

Zeithaml, V., Bitner, M., & Gremler, D. (2016). Services marketing: Integrating customer focus across the firm (6th ed.). McGraw-Hill Education.