Revealing the Behavior Intention of Tech-Savvy Generation Z to Use Electronic Wallet Usage: A Theory of Planned Behavior Based Measurement

  • Satria Fadil Persada Institut Teknologi Sepuluh Nopember
  • Irfandy Dalimunte Institut Teknologi Sepuluh Nopember
  • Reny Nadlifatin Institut Teknologi Sepuluh Nopember
  • Bobby Ardiansyah Miraja Institut Teknologi Sepuluh Nopember
  • Anak Agung Ngurah Perwira Redi Bina Nusantara University
  • Yogi Tri Prasetyo Mapua University
  • Jacky Chin Mercu Buana University
  • Shu-Chiang Lin Texas Health and Science University
Keywords: E-wallet, online transaction, In-store transaction, TPB, Behavior Intention


Tech-savvy Generation Z will dominate the global population. Thus, in order to stay competitive, it is essential for a business that targets this demographic to understand this generation’s characteristics. The present research measured the behavioral nature of Generation Z in using the electronic wallet (e-wallet). Specifically, the present research highlighted online and in-store transactions. The measurement in this research was done by using the famous Theory of Planned Behavior (TPB) model. A multivariate analysis with Structural Equation Model (SEM) was conducted, and six hypotheses were proposed. A questionnaire was used as the instrument development to gather the data needed for the purpose of this study; 155 respondents participated. The result showed that the TPB model was appropriate in revealing the Generation Z intention on e-wallet’s usage. Statistical findings and practical perspectives were also discussed in this paper. E-wallet providers can use the result derived from this study to develops their marketing strategies.


Aboelmaged, M., & Gebba, T. R. (2013). Mobile banking adoption: an examination of technology acceptance model and theory of planned behavior. International Journal of Business Research and Development, 2(1).

Adam, A. M. (2020). Sample size determination in survey research. Journal of Scientific Research and Reports, 90-97.

Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.

Amoroso, D. L., & Ogawa, M. (2013). Comparing mobile and Internet adoption factors of loyalty and satisfaction with online shopping consumers. International Journal of E-Business Research (IJEBR), 9(2), 24-45.

Bacon, D. R., Sauer, P. L., & Young, M. (1995). Composite reliability in structural equations modeling. Educational and psychological measurement, 55(3), 394-406.

Bae, I.-H., & Zamrudi, M. F. Y. (2018). Challenge of Social Media Marketing & Effective Strategies to Engage More Customers: Selected Retailer Case Study. International Journal of Business & Society, 19(3).

Balaji, K., & Balaji, K. (2017). A study on demonetization and its impact on cashless transactions. International Journal of Advanced Scientific Research & Development, 4(3), 58-64.

Berkup, S. B. (2014). Working with generations X and Y in generation Z period: Management of different generations in business life. Mediterranean Journal of Social Sciences, 5(19), 218.

Bhatiasevi, V. (2016). An extended UTAUT model to explain the adoption of mobile banking. Information Development, 32(4), 799-814.

Chakraborty, R., Lee, J., Bagchi-Sen, S., Upadhyaya, S., & Rao, H. R. (2016). Online shopping intention in the context of data breach in online retail stores: An examination of older and younger adults. Decision Support Systems, 83, 47-56.

Chern, Y. X., Kong, S. Y., Lee, V. A., Lim, S. Y., & Ong, C. P. (2018). Moving into cashless society: factors affecting adoption of e-wallet. UTAR.

Cheung, M. F., & To, W.-M. (2017). The influence of the propensity to trust on mobile users' attitudes toward in-app advertisements: An extension of the theory of planned behavior. Computers in Human Behavior, 76, 102-111.

Dalimunte, I., Miraja, B. A., Persada, S. F., Prasetyo, Y. T., Belgiawan, P. F., & Redi, A. P. (2019). Comparing Generation Z’s Behavior Intention in Using Digital Wallet for Online and In-store Transaction: A Unified Theory of Acceptance and Use of Technology 2 Approach. Editorial Board, 660.

Deloitte Indonesia. (2019). Millennials in Industry 4.0: A Gift or a Threat to Indonesian Human Resources? Retrieved from Documents/about-deloitte/id-about-dip-edition-1-chapter-2-en-sep2019.pdf

Dewanti, P., & Indrajit, R. E. (2018). The effect of XYZ generation characteristics to e-commerce C-to-C: A review. IKRA-ITH INFORMATIKA: Jurnal Komputer dan Informatika, 2(2), 56-60.

Doan, N. (2014). Consumer adoption in mobile wallet: a study of consumers in Finland.

Gao, S., Mokhtarian, P. L., & Johnston, R. A. (2008). Nonnormality of data in structural equation models. Transportation Research Record, 2082(1), 116-124.

Gupta, A., Dogra, N., & George, B. (2018). What determines tourist adoption of smartphone apps? An analysis based on the UTAUT-2 framework. Journal of Hospitality and Tourism Technology, 9(1), 50-64.

Hair, J. F. (2006). Multivariate data analysis: Pearson Education India.

Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling: Guidelines for determining model fit. Articles, 2.

Hsieh, C. t. (2001). E‐commerce payment systems: critical issues and management strategies. Human Systems Management, 20(2), 131-138.

J.P.Morgan. (2019). E-commerce Payments Trends: Indonesia. Retrieved from https://www.

Kengatharan, N. (2020). Home Is Where the Heart Is: Factors Determining Family Demand and Its Implications for Hrm Practices. International Journal of Business and Society, 21(1), 153-167.

Lee, C. M. (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, 130-141.

Liao, C., Chen, J.-L., & Yen, D. C. (2007). Theory of planning behavior (TPB) and customer satisfaction in the continued use of e-service: An integrated model. Computers in Human Behavior, 23(6), 2804-2822.

Lingga, M. A. (2019). Ada 37 Uang Elektronik yang Ada di Indonesia, Apa Saja? Retrieved from

Lu, L. (2018). Decoding Alipay: mobile payments, a cashless society and regulatory challenges. Butterworths Journal of International Banking and Financial Law, 40-43.

Mathieson, K. (1991). Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Information systems research, 2(3), 173-191.

Nasri, W., & Charfeddine, L. (2012). Factors affecting the adoption of Internet banking in Tunisia: An integration theory of acceptance model and theory of planned behavior. The Journal of High Technology Management Research, 23(1), 1-14.

Oyelami, L. O., Adebiyi, S. O., & Adekunle, B. S. (2020). Electronic payment adoption and consumers’ spending growth: empirical evidence from Nigeria. Future Business Journal, 6(1), 1-14.

Persada, S. F., Ivanovski, J., Miraja, B. A., Nadlifatin, R., Mufidah, I., Chin, J., & Redi, A. A. N. P. (2020). Investigating Generation Z’Intention to Use Learners’ Generated Content for Learning Activity: A Theory of Planned Behavior Approach. International Journal of Emerging Technologies in Learning (iJET), 15(04), 179-194.

Persada, S. F., Miraja, B. A., & Nadlifatin, R. (2019). Understanding the Generation Z Behavior on D-Learning: A Unified Theory of Acceptance and Use of Technology (UTAUT) Approach. International Journal of Emerging Technologies in Learning, 14(5).

Qin, Z., Sun, J., Wahaballa, A., Zheng, W., Xiong, H., & Qin, Z. (2017). A secure and privacy-preserving mobile wallet with outsourced verification in cloud computing. Computer Standards & Interfaces, 54, 55-60.

Rathore, H. S. (2016). Adoption of digital wallet by consumers. BVIMSR’s Journal of Management Research, 8(1), 69.

Sharma, M., & Sharma, S. K. (2019). Theoretical Framework for Digital Payments in Rural India: Integrating UTAUT and Empowerment Theory. Paper presented at the International Working Conference on Transfer and Diffusion of IT.

Shin, D.-H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior, 25(6), 1343-1354.

Singh, M., & Matsui, Y. (2018). How long tail and trust affect online shopping behavior: An extension to UTAUT2 framework. Pacific Asia Journal of the Association for Information Systems, 9(4).

Sivathanu, B. (2019). Adoption of digital payment systems in the era of demonetization in India: an empirical study. Journal of Science and Technology Policy Management, 10(1), 143-171.

Skinner, H., Sarpong, D., & White, G. R. (2018). Meeting the needs of the Millennials and Generation Z: gamification in tourism through geocaching. Journal of Tourism Futures.

Slade, E. L., Williams, M. D., & Dwivedi, Y. (2013). Extending UTAUT2 To Explore Consumer Adoption Of Mobile Payments. UKAIS, 36.

Tan, E., & Lau, J. L. (2016). Behavioural intention to adopt mobile banking among the millennial generation. Young Consumers.

Timones, L. (2019). Total e-wallet size in Indonesia likely to hit $15 billion by 2020. The Asian Banker. Retrieved from

Turner, A. (2015). Generation Z: Technology and social interest. The Journal of Individual Psychology, 71(2), 103-113.

Uddin, M. S., & Akhi, A. Y. (2014). E-wallet system for Bangladesh an electronic payment system. International Journal of Modeling and Optimization, 4(3), 216.

Upadhayaya, A. (2012). Electronic Commerce and E-wallet. International Journal of Recent Research and Review, 1, 37-41.

Varsha, R., & Thulasiram, M. (2016). Acceptance of e-wallet services: A study of consumer behavior. International Journal of Innovative Research in Management Studies, 1(4), 2455-7188.

Yang, K., & Forney, J. C. (2013). The moderating role of consumer technology anxiety in mobile shopping adoption: differential effects of facilitating conditions and social influences. Journal of Electronic Commerce Research, 14(4), 334.

Yu, C.-Y. (2002). Evaluating cutoff criteria of model fit indices for latent variable models with binary and continuous outcomes (Vol. 30): University of California, Los Angeles Los Angeles.

How to Cite
Satria Fadil Persada, Irfandy Dalimunte, Reny Nadlifatin, Bobby Ardiansyah Miraja, Anak Agung Ngurah Perwira Redi, Yogi Tri Prasetyo, Jacky Chin, & Shu-Chiang Lin. (2021). Revealing the Behavior Intention of Tech-Savvy Generation Z to Use Electronic Wallet Usage: A Theory of Planned Behavior Based Measurement. International Journal of Business and Society, 22(1), 213-226.