Essential Drivers of Payment Gateway Continuance Intention: The Moderating Role of Usage Rate
DOI:
https://doi.org/10.14414/jebav.v24i2.2631Keywords:
Usage rate, Subjective norm, Behavior control, Continuance intention, Payment gateway.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.
Bhattacherjee, A. & Premkumar, G. (2012). Theoretical Model and Longitudinal Test Article in Belief and Changes Understanding Information Attitude Toward Tech nology A Theoretical Usage: Model and Longitudinal. Management Information Systems, 28(2), 29–254.
Bickle, M. C. & Shim, S. (1993). Usage rate segmentation of the electronic shopper: Heavy versus non-heavy dollar volume purchasers. International Review of Retail, Distribution and Consumer Research, 3(1), 1-18.
Chang, I. C., Chou, P. C., Yeh, R. K. J., & Tseng, H. T. (2016). Factors influencing Chinese tourists’ intentions to use the Taiwan Medical Travel App. Telematics and Informatics, 33(2), 401-409.
Chen, M. F. & Tung, P. J. (2014). Developing an extended theory of planned behavior model to predict consumers’ intention to visit green hotels. International journal of hospitality management, 36, 221-230.
Chishti, S. (2016). Banking beyond banks and money, banking beyond banks and money. Springer.
Choi, H., Park, J., Kim, J., & Jung, Y. (2020). Consumer preferences of attributes of mobile payment services in South Korea. Telematics and Informatics, 51, 101397.
Cooper, D. R. & Schindler, P. S. (2014). Bussiness Research Methods. McGraw-Hill Irwin.
Dolarslan, E. S. (2014). Assessing the effects of satisfaction and value on customer loyalty behaviors in service environments. Management Research Review, 37(8), 706-727.
Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
Hajli, N. & Lin, X. (2016). Exploring the security of information sharing on social networking sites:The role of perceived control of information. Journal of Business Ethics, 133(1), 111-123.
Kelley, K., Hyde, J., & Bruwer, J. (2015). Usage rate segmentation: enriching the US wine market profile. International Journal of Wine Research, 7(2015), 49-61.
Kim, C., Mirusmonov, M., & Lee, I. (2018). An empirical examination of factors influencing the intention to use mobile payment. Computers in human behavior, 26(3), 310-322.
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach.
International Journal of e-Collaboration, 11(4), 1-10.
Koksal, M. H. (2016). The intentions of Lebanese consumers to adopt mobile banking. International Journal of Bank Marketing. 34(3), 327–346.
Lankton, N., McKnight, D. H., & Thatcher, J. B. (2014). Incorporating trust-in-technology into Expectation Disconfirmation Theory. The Journal of Strategic Information Systems, 23(2), 128-145.
Lee, M. C. (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, 8(3), 130-141.
Leong, K. & Sung, A. (2018). FinTech (Financial Technology): what is it and how to use technologies to create business value in fintech way?. International Journal of Innovation, Management and Technology, 9(2), 74-78.
Liao, G. Y., Huang, H. C., & Teng, C. I. (2016). When does frustration not reduce continuance intention of online gamers? The expectancy disconfirmation perspective. Journal of Electronic Commerce Research, 17(1), 65-79.
Lung-Guang, N. (2019). Decision-making determinants of students participating in MOOCs: Merging the theory of planned behavior and self-regulated learning model. Computers & Education, 134, 50-62.
Mahmoud, M. A., Hinson, R. E., & Anim, P. A. (2018). Service innovation and customer satisfaction: the role of customer value creation. European Journal of Innovation Management, 21(3), 402-422.
OJK. (2021). Laporan Triwulan I OJK: Momentum stabilitas pemulihan ekonomi nasional. Jakarta, Indonesia.
Okazaki, S. & Mendez, F. (2013). Exploring convenience in mobile commerce: Moderating effects of gender. Computers in Human Behavior, 29(3), 1234-1242.
Olaru, D., Purchase, S., & Peterson, N. (2008). From customer value to repurchase intentions and recommendations. Journal of Business and Industrial Marketing, 23(8), 554-565.
Raza, S. A., Umer, A., Qazi, W., & Makhdoom, M. (2018). The effects of attitudinal, normative, and control beliefs on m-learning adoption among the students of higher education in Pakistan.
Journal of Educational Computing Research, 56(4), 563-588.
Rouibah, K., Lowry, P. B., & Hwang, Y. (2016). The effects of perceived enjoyment and perceived risks on trust formation and intentions to use online payment systems: New perspectives from an Arab country. Electronic Commerce Research and Applications, 19, 33-43.
Ryu, H. S. (2018). What makes users willing or hesitant to use Fintech?: the moderating effect of user type. Industrial Management & Data Systems. 118(3), 541–569.
Shin, Y. H. & Hancer, M. (2016). The role of attitude, subjective norm, perceived behavioral control, and moral norm in the intention to purchase local food products. Journal of Foodservice Business Research, 19(4), 338-351.
Stocchi, L., Pourazad, N., Michaelidou, N., Tanusondjaja, A., & Harrigan, P. (2021). Marketing research on Mobile apps: past, present and future. Journal of the Academy of Marketing Science, 1-31.
Teoh, W. M. Y., Chong, S. C., Lin, B., & Chua, J. W. (2013). Factors affecting consumers' perception of electronic payment: an empirical analysis. Internet Research: Electronic Networking Applications and Policy, 23(4), 465-485.
Thakor, A. V. (2020). Fintech and banking: What do we know?. Journal of Financial Intermediation, 41, 100833.
Tussyadiah, I. P. (2016). Factors of satisfaction and intention to use peer-to-peer accommodation. International Journal of Hospitality Management, 55, 70-80.
Xie, Q., Song, W., Peng, X., & Shabbir, M. (2017). Predictors for e-government adoption: integrating TAM, TPB, trust and perceived risk. The Electronic Library, 35(1), 2-20.
Yang, H., Yu, J., Zo, H., & Choi, M. (2016). User acceptance of wearable devices: An extended perspective of perceived value. Telematics and Informatics, 33(2), 256-269.
Yang, H., Lee, H., & Zo, H. (2017). User acceptance of smart home services: an extension of the theory of planned behavior. Industrial Management & Data Systems. 117(1), 68-89.
Yang, S., Li, L., & Zhang, J. (2018). Understanding consumers’ sustainable consumption intention at china’s double-11 online shopping festival:An extended theory of planned behavior model.
Sustainability, 10(6), 1-19.
Zhao, Q., Chen, C. D., & Wang, J. L. (2016). The effects of psychological ownership and TAM on social media loyalty: An integrated model. Telematics and Informatics, 33(4), 959-972.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Yudi Sutarso
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
