Technological readiness and its impact on mobile payment usage: A case study of go-pay

References

• Abrahão, R. D., Moriguchi, S. N., & Andrade, D. F. (2016). Intention of adoption of mobile payment: An analysis in the light of the Unified Theory of Acceptance and Use of Technology (UTAUT). RAI Revista De Administração E Inovação, 13(3), 221–23. https://doi.org/10.1016/j.rai.2016.06.003
   Google Scholar
• Alhassan, M. D., Kolog, E. A., & Boateng, R. (2020). Effect of gratification on user attitude and continuance use of mobile payment services: A developing country context. Journal of Systems and Information Technology. https://doi.org/10.1108/JSIT-01-2020-0010
   Google Scholar
• Bailey, A. A., Pentina, I., Mishra, A. S., & Ben Mimoun, M. S. (2017). Mobile payments adoption by US consumers: An extended TAM. International Journal of Retail and Distribution Management, 45(6), 626–640. https://doi.org/10.1108/IJRDM-08-2016-0144
   Web of Science ®Google Scholar
• Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418–430. https://doi.org/10.1016/j.chb.2015.04.024
   Web of Science ®Google Scholar
• Becker, J. M., Klein, K., & Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: Guidelines for using reflective-formative type models. Long Range Planning, 45(5–6), 359–394. https://doi.org/10.1016/j.lrp.2012.10.001
   Web of Science ®Google Scholar
• Cheng, T. C. E., Lam, D. Y. C., & Yeung, A. C. L. (2006). Adoption of internet banking: An empirical study in Hong Kong. Decision Support Systems, 42(3), 1558–1572. https://doi.org/10.1016/j.dss.2006.01.002
   Web of Science ®Google Scholar
• 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. https://doi.org/10.1016/j.tele.2020.101397
   Web of Science ®Google Scholar
• Cline, P. B. (2004). The merging of risk analysis and adventure education. Wilderness Risk Management, 5(1), 43–45.
   Google Scholar
• Cocosila, M., & Trabelsi, H. (2016). An integrated value-risk investigation of contactless mobile payments adoption. Electronic Commerce Research and Applications, 20, 159–170. https://doi.org/10.1016/j.elerap.2016.10.006
   Web of Science ®Google Scholar
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
   Web of Science ®Google Scholar
• Djauhari, M. J., Furqon, C., & Sultan, M. A. (2020). Integrating quality features into technology acceptance model for examining the acceptance of mobile payment go-pay. The International Journal of Business Review (The Jobs Review), 3(1), 29–36. https://doi.org/10.17509/tjr.v3i1.22511
   Google Scholar
• Erdoggmu, N., & Esen, M. (2011). An investigation of the effects of technology readiness on technology acceptance in e-HRM. Procedia - Social and Behavioral Sciences, 24, 487–495. https://doi.org/10.1016/j.sbspro.2011.09.131
   Google Scholar
• Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research 18(3), 382–388 https://doi.org/10.1177/002224378101800313.
   Web of Science ®Google Scholar
• Gai, K., Qiu, M., & Sun, X. (2018). A survey on FinTech. Journal of Network and Computer Applications, 103, 262–273. https://doi.org/10.1016/j.jnca.2017.10.011
   Web of Science ®Google Scholar
• Galloway, A. (2005). Non-probability sampling. Queen Margaret University College.
   Google Scholar
• Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: indeed a silver bullet. The Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202
   Google Scholar
• Huh, Y. E. & Kim, S. (2008). Do early adopters upgrade early? Role of post-adoption behavior in the purchase of next-generation products. Journal of Business Research, 61(1), 40–46. https://doi.org/10.1016/j.jbusres.2006.05.007
   Web of Science ®Google Scholar
• Im, I., Hong, S., & Kang, M. S. (2011). An international comparison of technology adoption. Information & Management, 48(1), 1–8. https://doi.org/10.1016/j.im.2010.09.001
   Web of Science ®Google Scholar
• Kailan, I., Aijaz, A., Boateng, H., & Robert, E. (2019). Perceived risk and trust in using mobile money services — An empirical study of Ghana. International Journal of E-Business Research, 15(1), 1–19. https://doi.org/10.4018/IJEBR.2019010101
   Web of Science ®Google Scholar
• Kaur, P., Dhir, A., Singh, N., Sahu, G., & Almotairi, M. (2020). An innovation resistance theory perspective on mobile payment solutions. Journal of Retailing and Consumer Services, 55, 102059. https://doi.org/10.1016/j.jretconser.2020.102059
   Web of Science ®Google Scholar
• Liébana-Cabanillas, F., Marinkovic, V., Ramos, D. L. I., & Kalinic, Z. (2018). Predicting the determinants of mobile payment acceptance: A hybrid SEM-neural network approach. Technological Forecasting and Social Change, 129, 117–130. https://doi.org/10.1016/j.techfore.2017.12.015
   Web of Science ®Google Scholar
• Liébana-Cabanillas, F., Molinillo, S., & Japutra, A. (2021). Exploring the determinants of intention to use P2P mobile payment in Spain. Information Systems Management, 38(2), 165–180. https://doi.org/10.1080/10580530.2020.1818897
   Web of Science ®Google Scholar
• Lin, J. C., Chang, H., & Fisk, R. P. (2011). The role of technology readiness in self‐service technology acceptance. Managing Service Quality: An International Journal, 21(4), 424–444. https://doi.org/10.1108/09604521111146289
   Google Scholar
• Luarn, P., & Lin, H. H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873–891. https://doi.org/10.1016/j.chb.2004.03.003
   Web of Science ®Google Scholar
• Lu, Y., Yang, S., Chau, P. Y. K., & Cao, Y. (2011). Dynamics between the trust transfer process and intention to use mobile payment services: A cross- environment perspective. Information and Management, 48(8), 393–403. https://doi.org/10.1016/j.im.2011.09.006
   Web of Science ®Google Scholar
• Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370–396. https://doi.org/10.1037/h0054346
   Web of Science ®Google Scholar
• Miltgen, C. L., Popovicˇ, 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, 103–114. https://doi.org/10.1016/j.dss.2013.05.010
   Web of Science ®Google Scholar
• OJK. (2021). Penyelenggara Fintech Lending Terdaftar dan Berizin di OJK per 10 Juni 2021.: https://www.ojk.go.id/id/kanal/iknb/financial-technology/Pages/Penyelenggara-Fintech-Lending-Terdaftar-dan-Berizin-di-OJK-per-10-Juni-2021.aspx (accessed on 10 June 2021)
   Google Scholar
• 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, 404–414. https://doi.org/10.1016/j.chb.2016.03.030
   Web of Science ®Google Scholar
• Ozturk, A. B., Bilgihan, A., Salehi-Esfahani, S., & Hua, N. (2017). Understanding the mobile payment technology acceptance based on valence theory: A case of restaurant transactions. International Journal of Contemporary Hospitality Management, 29(8), 2027–2049. https://doi.org/10.1108/IJCHM-04-2016-0192iv
   Web of Science ®Google Scholar
• Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307–320. https://doi.org/10.1177/109467050024001
   Google Scholar
• Roca, J. C., García, J. J., & Vega, J. J. D. L. (2009). The importance of perceived trust, security and privacy in online trading systems. Information Management & Computer Security, 17(2), 96–113. https://doi.org/10.1108/09685220910963983
   Google Scholar
• Ryu, H.-S. (2018). Understanding benefit and risk framework of fintech adoption: Comparison of early adopters and late adopters. Proceedings of the 51st Hawaii International Conference on System Sciences, 3864–3873.
   Google Scholar
• Senyo, P. K., & Osabutey, E. L. (2020). Unearthing antecedents to financial inclusion through FinTech innovations. Technovation, 98, 102155. https://doi.org/10.1016/j.technovation.2020.102155
   Web of Science ®Google Scholar
• Shao, Z., Zhang, L., Li, X., & Guo, Y. (2019, December). Antecedents of trust and continuance intention in mobile payment platforms: The moderating effect of gender. Electronic Commerce Research and Applications, 33, 100823. https://doi.org/10.1016/j.elerap.2018.100823
   Web of Science ®Google Scholar
• Son, M., & Han, K. (2011). Beyond the technology adoption: Technology readiness effects on post-adoption behavior. Journal of Business Research, 64(11), 1178–1182. https://doi.org/10.1016/j.jbusres.2011.06.019
   Web of Science ®Google Scholar
• Teo, T. (2011). Factors influencing teachers’ intention to use technology: Model development and test. Computers and Education, 57(4), 2432–2440. https://doi.org/10.1016/j.compedu.2011.06.008
   Web of Science ®Google Scholar
• Venkatesh, V., Thong, J., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36 (1): 157–178. http://papers.ssrn.com/sol3/papers.cfm?Abstract_id=2002388
   Web of Science ®Google Scholar
• Yang, Y., Liu, Y., Li, H., & Yu, B. (2015). Understanding perceived risks in mobile payment acceptance. Industrial Management and Data Systems, 115(2), 253–269. https://doi.org/10.1108/IMDS-08-2014-0243
   Web of Science ®Google Scholar
• Yang, S., Lu, Y., Gupta, S., Cao, Y., & Zhang, R. (2012). Mobile payment services adoption across time: An empirical study of the effects of behavioral beliefs, social influences, and personal traits. Computers in Human Behavior, 28(1), 129–142. https://doi.org/10.1016/j.chb.2011.08.019
   Web of Science ®Google Scholar
• Yu, C. (2012). Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT model. Journal of Electronic Commerce Research, 13(2), 104–121. http://www.jecr.org/node/48
   Web of Science ®Google Scholar
• Zhang, L., Zhu, J., & Liu, Q. (2012). A meta-analysis of mobile commerce adoption and the moderating effect of culture. Computers in Human Behavior, 28(5), 1902–1911. https://doi.org/10.1016/j.chb.2012.05.008
   Web of Science ®Google Scholar
• Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26 (4),760–767. http://doi.org/10.1016/j.chb.2010.01.013
   Web of Science ®Google Scholar