Main Article Content

Abstract

Go-Pay is one of the popular FinTech services in Indonesia. This research aims to identify the Go-Pay service's impact on net benefits influenced by perceived usefulness, perceived ease of use, comfort, information quality, security, trust, and internet connection quality. This research used a quantitative method to collect 220 data by distributing a questionnaire through Google Form and analyzing them using SmartPLS 3.3. The result shows that comfort, information quality, and perceived ease of use significantly impact the perceived usefulness. In contrast, internet connection quality, trust and security were proved to have no significant impact on the perceived usefulness. Comfort, information quality, trust, internet connection quality had a significant impact on the perceived ease of use. However, security had no significant impact on perceived ease of use. Perceived usefulness and perceived ease of use had a significant impact on net benefits. This research can use as a decision-making strategy for Go-Jek as a company concerning the success of Go-Pay service. 

Keywords

Net benefits the use of Go-Pay service TAM ISSM and SOR

Article Details

How to Cite
Nurherwening, A., Dari, A. W., Urumsah, D., & Wibowo, H. T. (2021). The success of go-pay financial technology service adoption. Journal of Contemporary Accounting, 3(2), 98–111. https://doi.org/10.20885/jca.vol3.iss2.art5

References

  1. Al-Maroof, R. S., Alfaisal, A. M., & Salloum, S. A. (2021). Google glass adoption in the educational environment: A case study in the Gulf area. Education and Information Technologies, 26, 2477–2500. https://doi.org/10.1007/s10639-020-10367-1
  2. Al-Somali, S. A., Gholami, R., & Clegg, B. (2009). An investigation into the acceptance of online banking in Saudi Arabia. Technovation, 29(2), 130–141. https://doi.org/10.1016/j.technovation.2008.07.004
  3. Alalwan, A. A., Baabdullah, A. M., Rana, N. P., Tamilmani, K., & Dwivedi, Y. K. (2018). Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust. Technology in Society, 55, 100–110. https://doi.org/10.1016/j.techsoc.2018.06.007
  4. Albayati, H., Kim, S. K., & Rho, J. J. (2020). Accepting financial transactions using blockchain technology and cryptocurrency: A customer perspective approach. Technology in Society, 62, 1–20. https://doi.org/10.1016/j.techsoc.2020.101320
  5. Anggreni, N. M. M., Ariyanto, D., Suprasto, H. B., & Dwirandra, A. A. N. B. (2020). Successful adoption of the village’s financial system. Accounting, 6(4), 1129–1138.
  6. Bailey, A. A., Pentina, I., Shankar, A., & Mimoun, M. S. Ben. (2019). Exploring factors influencing US millennial consumers’ use of tap-and-go payment technology. International Review of Retail, Distribution and Consumer Research, 13(2), 143–163.
  7. Bank Indonesia. (2021). Transaksi Uang Elektronik. https://www.bi.go.id/id/statistik/ekonomi-keuangan/ssp/uang-elektronik-transaksi.aspx
  8. Bhattarai, S., & Maharjan, S. (2020). Determining the factors affecting on digital learning adoption among the students in Kathmandu Valley: an application of technology acceptance model (TAM). International Journal of Engineering and Management Research, 10(3), 131–141. https://doi.org/10.31033/ijemr.10.3.20
  9. Chen, C. C., & Tsai, J. L. (2019). Determinants of behavioral intention to use the Personalized Location-based Mobile Tourism Application: An empirical study by integrating TAM with ISSM. Future Generation Computer Systems, 96, 628–638. https://doi.org/10.1016/j.future.2017.02.028
  10. Chen, N. H. (2019). Extending a TAM–TTF model with perceptions toward telematics adoption. Asia Pacific Journal of Marketing and Logistics, 31(1), 37–54. https://doi.org/10.1108/APJML-02-2018-0074
  11. Chi, T. (2018). Understanding Chinese consumer adoption of apparel mobile commerce: An extended TAM approach. Journal of Retailing and Consumer Services, 44, 274–284. https://doi.org/10.1016/j.jretconser.2018.07.019
  12. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates.
  13. Danuarta, G. L. N., & Darma, G. S. (2019). Determinants of using Go-pay and its impact on net benefits. International Journal of Innovative Science and Research Technology, 4(11), 173–182.
  14. Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems : Theory and results. Massachusetts Institute of Technology.
  15. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
  16. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.
  17. DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information System, 19(4), 3–30.
  18. Detiknet. (2021, February 17). Kecepatan Internet Indonesia Paling Bontot di ASEAN. Detik.Com. https://inet.detik.com/telecommunication/d-5372116/kecepatan-internet-indonesia-paling-bontot-di-asean
  19. Dumpit, D. Z., & Fernandez, C. J. (2017). Analysis of the use of social media in Higher Education Institutions (HEIs) using the Technology Acceptance Model. International Journal of Educational Technology in Higher Education, 14(5), 1–16.
  20. Gefen, D., Pavlou, P., Benbasat, I., McKnight, H., Stewart, K., & Straub, D. (2006). ICIS panel summary: Should institutional trust matter in information systems research? Communications of the Association for Information Systems, 17, 205–222.
  21. Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publications Ltd.
  22. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science Volume, 43, 115–135.
  23. Ke, P., & Su, F. (2018). Mediating effects of user experience usability: An empirical study on mobile library application in China. Electronic Library, 36(5), 892–909. https://doi.org/10.1108/EL-04-2017-0086
  24. Kementerian Keuangan Republik Indonesia. (2020). Keamanan Informasi: Sudah Saatnya Kita Peduli. Kementerian Keuangan Republik Indonesia. https://www.djkn.kemenkeu.go.id/kpknl-kisaran/baca-artikel/13113/Keamanan-Informasi-Sudah-Saatnya-Kita-Peduli.html
  25. Knight, E., & Wójcik, D. (2020). FinTech , economy and space : Introduction to the special issue. Environment and Planning A: Economy and Space, 52(8), 1490–1497.
  26. Kuo, R. Z., & Lee, G. G. (2009). KMS adoption: The effects of information quality. Management Decision, 47(10), 1633–1651. https://doi.org/10.1108/00251740911004727
  27. Lai, P. C. (2016). Design and Security impact on consumers’ intention to use single platform E-payment. Interdisciplinary Information Sciences, 22(1), 111–122.
  28. Lai, P. C. (2017). The literature review of technology adoption models and theories for the novelty technology. Journal of Information Systems and Technology Management, 4(1), 21–38.
  29. Lim, S. H., Kim, D. J., Hur, Y., & Park, K. (2019). An empirical study of the impacts of perceived security and knowledge on continuous intention to use mobile fintech payment services. International Journal of Human–Computer Interaction, 35(10), 886–898.
  30. Marselia, S., Sulistiowati, & Lemantara, J. (2018). Analisis kesuksesan website e-learning management system (EMS) dengan menggunakan model Delone dan McLean pada cabang primagama bumi citra fajar (BCF). Jurnal JSIKA, 7(1), 1–10.
  31. Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173–191.
  32. Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. The MIT Press.
  33. Mercurio, D. I., & Hernandez, A. A. (2020). Understanding user acceptance of information system for sweet potato variety and disease classification: An empirical examination with an extended technology acceptance model. 16th IEEE International Colloquium on Signal Processing and Its Applications, 272–277.
  34. Merdeka.com. (2020, November 9). Data BI: Pembayaran Melalui Fintech Lebih Tinggi Dibandingkan Perbankan. Merdeka.Com. https://www.merdeka.com/uang/data-bi-pembayaran-melalui-fintech-lebih-tinggi-dibandingkan-perbankan.html
  35. Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: An extension of the technology acceptance model. Internet Research, 14(3), 224–235. https://doi.org/10.1108/10662240410542652
  36. Pinem, R. J. (2020). Gopay as a practical payment tool for millennial generations in the digital era. Journal of Applied Business Administration, 4(2), 206–211.
  37. Pramanita, I. G. A. A. N. G., & Rasmini, N. K. (2020). Sistem e-filing dan kepatuhan wajib pajak orang pribadi: Studi D&M IS Success Model pada KPP Pratama Denpasar Timur. E-Jurnal Akuntansi, 30(11), 2825–2838.
  38. Safitri, T. A. (2020). The Development of Fintech in Indonesia. 1st Borobudur International Symposium on Humanities, Economics and Social Sciences, 666–670.
  39. Schueffel, P. (2016). Taming the Beast: A scientific definition of fintech. Journal of Innovation Management, 4(4), 32–54.
  40. Syahril, W. N., & Rikumahu, B. (2019). Penggunaan technology acceptance model (TAM) dalam analisis minat perilaku penggunaan e-money pada mahasiswa Universitas Telkom. Jurnal Mitra Manajemen, 3(2), 201–214.
  41. Talwar, S., Dhir, A., Khalil, A., Mohan, G., & Islam, A. K. M. N. (2020). Point of adoption and beyond. Initial trust and mobile-payment continuation intention. Journal of Retailing and Consumer Services, 55, 1–12. https://doi.org/10.1016/j.jretconser.2020.102086
  42. Venkatesh, V., & Davis, F. D. (2000). Theoretical acceptance extension model : Field four studies of the technology longitudinal. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926