Hanif Adinugroho Widyanto, Kunthi Afrilinda Kusumawardani


The objective of this research was to analyze the predicting factors of Behavioral Intention to use a mobile payment service in an emerging country, namely Performance Expectancy, Effort Expectancy, Social Influence, Trust, and Perceived Security. The respondents in this study were limited to the users of LinkAja, one of the largest Indonesian mobile payment services, who lived in the Greater Jakarta (Jabodetabek) area. The data collected in this research (n=144) were examined using a quantitative method with structural equation modeling analysis using partial least squares (PLS-SEM) technique. In the end, there were seven out of ten hypotheses in the present study which was supported by the data. The results of this study also exhibited the strategic importance of trust as a mediating construct in this study. The adjusted coefficient of determination for Behavioral Intention was 67.7%, suggesting a moderate-to-substantial in-sample predictive power. This research also offered a few managerial implications for LinkAja and the mobile payment industry in Indonesia.


Keyword: Mobile Payment, Behavioral Intention, Performance Expectancy, Effort Expectancy, Social Influence

Full Text:



Aboobucker, I., & Bao, Y. (2018). What obstruct customer acceptance of internet banking? Security and privacy, risk, trust and website usability and the role of moderators. Journal of High Technology Management Research,

(1), 109–123.

Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile

banking by Jordanian bank customers: Extending UTAUT2 with trust.

International Journal of Information Management, 37(3), 99– 110.

Aydin, G.,& Burnaz, S (2016). Adoption of mobile payment systems : A study on mobile wallets.

Journal of Business, Economics and Finance, 5(1), 73–92.

Basari, M. T. (2019). Setahun, Jumlah Pengguna Internet Indonesia Bertambah 17 Juta – Teknologi internet- indonesia-bertambah-17-juta

Chaouali, W., Ben Yahia, I., & Souiden, N. (2016). The interplay of counter-conformity motivation, social influence, and trust in customers’ intention to adopt Internet banking services: The case of an emerging country. Journal of Retailing and Consumer Services, 28, 209–218.

Chellappa, R. K., & Pavlou, P. A. (2002). Perceived information security, financial liability and consumer trust in electronic commerce transactions. Logistics Information Management, 15(5/6), 358–368.

Chin, A. J., Azizi, S., Syed, W., Wafa, K., & Ooi, A.-Y. (2009). The Effect of Internet Trust and Social Influence towards Willingness to Purchase Online in Labuan, Malaysia (Vol. 2,Issue 2).

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340.

Gadabu, A., Sunguh, K., Arkorful, V. E., Uddin, M. M., & Lukman, S. (2019). Examining Trust as a Key Determinant of eHealth Adoption in Malawi. 1–25.

Garson,G.D.(2016). Partial Least Squares: Regression & Structural Equation Models. Statistical Associates Publishing.

Gupta,A.,&Dhami,A.(2015). Measuring the impact of security, trust and privacy in information sharing: A study on social networking sites. Journal of Direct, Data and Digital Marketing Practice, 17(1), 43–53.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. 11-2018-0203

Hwang, R. J., Shiau, S. H., & Jan, D. F. (2007). A new mobile payment scheme for roaming services. Electronic Commerce Research and Applications, 6(2), 184–191.

Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322.

KPMG Siddharta Advisory. (2017). Retail payments in Indonesia. indonesia.pdf

Lu, H. P., & Su, P. Y. J. (2009). Factors affecting purchase intention on mobile shopping web sites. Internet Research, 19(4), 442–458.

Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application.

International Journal of Information Management, 34(1), 1–13.

Miltgen, C. L., Popovič, A., & Oliveira, T. (2013). Determinants of end-user acceptance of biometrics: Integrating the “big 3” of technology acceptance with privacy context. Decision Support Systems, 56(1), 103–114.

Moraes,, & Meirelles,F.deS.(2017). User’s perspective of Eletronic Government adoption in Brazil. Journal of Technology Management and Innovation, 12(2), 1–10.

Multazam, M. (2019). Terlena Dompet Digital. Detik.Com. 4463578/terlena-dompet-digital

Namkung, Y., & Jang, S. C. (2007). Does Food Quality Really Matter in Restaurants? Its Impact On Customer Satisfaction and Behavioral Intentions. Journal of Hospitality and Tourism Research, 31(3), 387–409.

Oliveira,T.,Thomas,M.,Baptista,G.,& Campos,F.(2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Computers in Human Behavior, 61(2016), 404–414.

Pavlou, P. A. (2001). Integrating Trust in Electronic Commerce with the Technology Acceptance Model: Model Development and Validation. Seventh Americas Conference on Information Systems, 816–822.

Phonthanukitithaworn, C., Sellitto, C., & Fong, M. W. L. (2016). An investigation of mobile payment(m-payment) services in Thailand. Asia-Pacific Journal of Business Administration, 8(1), 37–54.


Popovska-Kamnar, N. (2014). The use of electronic money and its impact on monetary policy. Journal of Contemporary Economic and Business Issues, 1(2), 79–92.

Ramos, F. L., Ferreira, J. B., De Freitas, A. S., & Rodrigues, J. W. (2018). The effect of trust in the intention to use m-banking. Brazilian Business Review, 15(2), 175–191.

Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. SmartPLS GmbH.

Roca, J. C., García, J. J., & de la Vega, J. J. (2009). The importance of perceived trust, security and privacy in online trading systems. Information Management and Computer Security, 17(2), 96–113.

Saha, G. C., & Theingi. (2009). Service quality, satisfaction, and behavioural intentions: A study of low-cost airline carriers in Thailand. Managing Service Quality, 19(3), 350– 372.

Schierz,P.G., Schilke,O., & Wirtz,B.W.(2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9(3), 209–216.

Sekaran,U., & Bougie, R.(2016). Research methods for business: A skill building approach. John Wiley & Sons, Ltd.

Shah, M.H., Peikari,H.R., & Yasin,N.M.(2014). The determinants of individuals’ perceive de-security: Evidence from Malaysia. International Journal of Information Management,34(1), 48–57.

Sheikh, Z., Islam, T., Rana, S., Hameed, Z., & Saeed, U. (2017). Acceptance of social commerce framework in Saudi Arabia. Telematics and Informatics, 34(8), 1693–1708.

Shiau, H.C.

(2014). The impact of product innovation on behavior intention: The measurement of the mediating effect of the brand image of Japanesean imedolls. Anthropologist,17(3),777– 788.

Singh, A., Alryalat, M. A. A., Alzubi, J. A., & Sarma, H. K. D. (2017). Understanding jordanian consumers’ online purchase intentions: Integrating trust to the UTAUT2 framework. International Journal of Applied Engineering Research, 12(20), 10258– 10268.

Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015). Modeling Consumers’ AdoptionIntentionsofRemoteMobilePaymentsintheUnitedKingdom:ExtendingUTAU T with Innovativeness, Risk, and Trust. Psychology & Marketing, 32(8), 860–873.

Slade, E., Williams, M., & Dwivdei, Y. (2013). Extending UTAUT2 To Explore Consumer Adoption Of Mobile Payments. UK Academy for Information Systems Conferencem Proceedings, 36.

Sobti, N. (2019). Impact of demonetization on diffusion of mobile payment service in India: Antecedents of behavioral intention and adoption using extended UTAUT model. Journal of Advances in Management Research, 16(4), 472–497.

- 2018-0086

Syarizka,D.(2020). Bagaimana ShopeePay Unggul dari GoPay dan OVO Selama Pandemi. Tech In Asia.

Tarhini, A.,El-Masri, M.,Ali,M.,& Serrano, A.(2016). Extending the UTAUT model to understand the customers’ acceptance and use of internet banking in Lebanon. Information Technology & People, 29(4), 830–849.

Teo, T., & Milutinovic, V. (2015). Modelling the intention to use technology for teaching mathematics among pre-service teachers in Serbia. Australasian Journal of Educational Technology, 31(4), 363–380.

Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186–204.

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.

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157.

Voorhees, C.M., Brady, M.K., Calantone,R.,& Ramirez,E.(2016). Discriminant validity testing in marketing: ananalysis , causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44(1), 119–134.

Widyanto, H. A., Kusumawardani, K. A., & Septyawanda, A. (2020). Encouraging Behavioral Intention to Use Mobile Payment: An Extension of UTAUT2. Jurnal Muara Ilmu Ekonomi Dan Bisnis, 4(1), 87.

Widyastuti, K., Handayani, P. W., Pinem, A. A., & Wilarso, I. (2017). e-Money Implementation Barriers and Challenges: A Case of Indonesia Interbank Network Company. Journal of Engineering and Applied

Sciences, 12(12), 3281–3285.

Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services.

Decision Support Systems, 54(2), 1085–1091. Zhou,T.,Lu,Y.,&Wang,B.(2010).Integrating TTF and UTAUT to expla in mobile banking

user adoption. Computers in Human Behavior, 26(4), 760–767.


  • There are currently no refbacks.