Essential Drivers of Payment Gateway Continuance Intention: The Moderating Role of Usage Rate
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Keywords

Usage rate
Subjective norm
Behavior control
Continuance intention
Payment gateway.

How to Cite

Sutarso, Y. (2021). Essential Drivers of Payment Gateway Continuance Intention: The Moderating Role of Usage Rate. Journal of Economics, Business, and Accountancy Ventura, 24(2), 271-283. https://doi.org/10.14414/jebav.v24i2.2631
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Abstract

This study aims to analyze the effect of functional and economic benefit on the perceived value of payment gateway, elaborate the role of perceived value, subjective norm, and behavior control on continuance intention, and identify the moderating role of usage rate on the relationship. The study employed Partial Least Squares to test the proposed model and corresponding hypotheses. Using the purposive sampling technique, the data collection was from 460 survey samples of Fintech payment gateway users in Indonesia. Analysis data used Two-step SEM, inner model, and outer model analysis. The findings showed that functional and economic benefits influence the perceived value of payment gateway. Moreover, perceived value, subjective norm, and behavioral control effects continuance intention. This study shows the importance of the moderating role of usage level on the relationship of subjective norm and perceived behavior control with continuance intention on payment gateway. This study recommends payment getaway providers to manage customer value, promote sustainable intentions, and consider usage rates to encourage subjective norms and behavioral control. Therefore, this study enables a better understanding of the Theory of Plan Behavior (TPB) and Expectation Disconfirmation Theory (EDT) in the payment gateway context.

References

Achadinha, N. M. J., Jama, L. & Nel, P. (2014). The drivers of consumers’ intention to redeem a push mobile coupon. Behaviour and Information Technology, 33(12), 1306–1316.

Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

Alzahrani, A. I., Mahmud, I., Ramayah, T., Alfarraj, O., & Alalwan, N. (2017). Extending the theory of planned behavior (TPB) to explain online game playing among Malaysian undergraduate students. Telematics and Informatics, 34(4), 239–251.

Barkhordari, M., Nourollah, Z., Mashayekhi, H., Mashayekhi, Y., & Ahangar, M. S. (2017). Factors influencing adoption of e-payment systems: an empirical study on Iranian customers. Information systems and e-business management, 15(1), 89-116.

Benlian, A. & Hess, T. (2011). Opportunities and risks of software-as-a-service: Findings from a survey of IT executives. Decision support systems, 52(1), 232-246.