Main Article Content

Abstract

Cashless readiness reflects a society's preparedness to adopt digital payments over cash transactions. This study investigates key factors influencing cashless adoption in Batam, Indonesia, using the Technology Readiness Index 2.0 and the Technology Acceptance Model. A quantitative survey was conducted with 400 valid responses. Statistical analysis reveals that ease of use did not significantly impact readiness. However, usefulness, optimism, innovativeness, and lack of awareness significantly affected readiness. Additionally, readiness strongly influenced adoption. These findings suggest that addressing awareness barriers while promoting innovation and optimism can enhance cashless adoption. Policymakers should prioritize financial education programs, and service providers should improve accessibility and user experience to encourage digital payment use.

Keywords

Cashless Readiness Digital Payment Technology Acceptance Model Technology Readiness Index

Article Details

References

  1. Abbas, A. (2017). Literature review of a cashless society in Indonesia: Evaluating the progress. International Journal of Innovation, Management and Technology, 8, 193-196. https://doi.org/10.18178/ijimt.2017.8.3.727
  2. Al-Saedi, K., Al-Emran, M., Ramayah, T., & Abusham, E. (2020). Developing a general extended UTAUT model for M-payment adoption. Technol Soc, 62, 101293. https://doi.org/10.1016/j.techsoc.2020.101293
  3. AUD. (2022). BI: Transaksi Uang Elektronik Melesat 50,3 Persen pada April 2022. CNN Indonesia. Retrieved from https://www.cnnindonesia.com/ekonomi/20220524155517-78-800623/bi-transaksi-uang-elektronik-melesat-503-persen-pada-april-2022
  4. Balakrishnan, V., & Shuib, N. L. M. (2021). Drivers and inhibitors for digital payment adoption using the cashless society readiness-adoption model in Malaysia. Technol Soc, 65, 101554. https://doi.org/10.1016/j.techsoc.2021.101554
  5. Cruz-Cárdenas, J., Zabelina, E., Deyneka, O., Guadalupe-Lanas, J., & Velín-Fárez, M. (2019). Role of demographic factors, attitudes toward technology, and cultural values in the prediction of technology-based consumer behaviors: A study in developing and emerging countries. Technological Forecasting and Social Change, 149, 119768. https://doi.org/10.1016/j.techfore.2019.119768
  6. Daragmeh, A., Lentner, C., & Sági, J. (2021). FinTech payments in the era of COVID-19: Factors influencing behavioral intentions of “Generation X” in Hungary to use mobile payment. J Behav Exp Finance, 32, 100574. https://doi.org/10.1016/j.jbef.2021.100574
  7. Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems : theory and results. Massachusetts Institute of Technology, Retrieved from http://hdl.handle.net/1721.1/15192
  8. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
  9. Dinev, T., & Hu, Q. (2007). The centrality of awareness in the formation of user behavioral intention toward protective information technologies. J. AIS, 8. https://doi.org/10.17705/1jais.00133
  10. Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414-433. https://doi.org/10.1007/s11747-011-0261-6.
  11. Indonesia, B. (2022). Card-based payment instruments (APMK) and electronic money (UE) infrastructures. from Bank Indonesia https://www.bi.go.id/id/statistik/ekonomi-keuangan/spip/Documents/TABEL_5g.pdf
  12. Loh, X.-M., Lee, V.-H., Tan, G. W.-H., Ooi, K.-B., & Dwivedi, Y. K. (2021). Switching from cash to mobile payment: what's the hold-up? Internet Research, 31(1), 376-399. https://doi.org/10.1108/INTR-04-2020-0175.
  13. McLean, G., Osei-Frimpong, K., Al-Nabhani, K., & Marriott, H. (2020). Examining consumer attitudes towards retailers' m-commerce mobile applications – An initial adoption vs. continuous use perspective. Journal of Business Research, 106, 139-157.https:/doi.org/10.1016/j.jbusres.2019.08.032
  14. Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Comput Human Behav, 61, 404-414. https://doi.org/10.1016/j.chb.2016.03.030
  15. 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
  16. Parasuraman, A., & Colby, C. L. (2015). An Updated and Streamlined Technology Readiness Index:TRI 2.0. Journal of Service Research, 18(1), 59-74. https://doi.org/10.1177/1094670514539730
  17. Patil, P., Tamilmani, K., Rana, N. P., & Raghavan, V. (2020). Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal. International Journal of Information Management, 54, 102144. https://doi.org/10.1016/j.ijinfomgt.2020.102144
  18. Phonthanukitithaworn, C., Sellitto, C., & Fong, M. W. L. (2016). A comparative study of current and potential users of mobile payment services. SAGE Open, 6(4), 2158244016675397. https://doi.org/0.1177/2158244016675397
  19. Rahadi, R., Putri, N., Soekarno, S., Damayanti, S., Murtaqi, I., & Saputra, J. (2021). Analyzing cashless behavior among generation Z in Indonesia. International Journal of Data and Network Science, 5, 1-12. https://doi.org/10.5267/j.ijdns.2021.8.007
  20. Rahman, M., Ismail, I., & Bahri, S. (2020). Analysing consumer adoption of cashless payment in Malaysia. Digital Business, 1(1), 100004. https://doi.org/10.1016/j.digbus.2021.100004
  21. Sanchez, G. (2013). PLS path modeling with R. Berkeley: Trowchez Editions, 383(2013), 551. Retrieved from https://www.gastonsanchez.com/PLS_Path_Modeling_with_R.pdf.
  22. Singh, H., Singh, V., Singh, T., & Higueras-Castillo, E. (2023). Electric vehicle adoption intention in the Himalayan region using UTAUT2 – NAM model. Case Studies on Transport Policy, 11, 100946. https://doi.org/10.1016/j.cstp.2022.100946
  23. Sun, W., Shin, H. Y., Wu, H., & Chang, X. (2023). Extending UTAUT2 with knowledge to test Chinese consumers' adoption of imported spirits flash delivery applications. Heliyon, 9(5), e16346. https://doi.org/10.1016/j.heliyon.2023.e16346
  24. Thakur, R., & Srivastava, M. (2014). Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India. Internet Research, 24(3), 369-392. https://doi.org/10.1108/IntR-12-2012-0244.
  25. Trinugroho, I., Sawitri, H. S. R., Toro, M. J. S., Khoiriyah, S., & Santoso, A. B. (2017). How ready are people for cashless society? Jurnal Keuangan dan Perbankan, 21(1), 105-112. https://doi.org/10.26905/jkdp.v21i1.1231
  26. Wijoyo, H., Rakhmatulloh, A. R., Dewi, D. I. K., Haryati, D., Suryanti, Indrawan, I., Aprianto, I., Pranata, J., Lisnani, Firdaus, A. S., Mahdayeni, Marzuki, Mulyono, S., Sirikalimah, Mildawani, I., & Irzawati, I. (2021). Dampak pandemi terhadap kehidupan manusia (ditinjau dari berbagai aspek) (H. Wiyjoyo, D. Sunarsi, & I. Indrawan Eds.). Sumatera Barat: Insan Cendekia Mandiri.
  27. Yan, L.-Y., Tan, G. W.-H., Loh, X.-M., Hew, J.-J., & Ooi, K.-B. (2021). QR code and mobile payment: The disruptive forces in retail. Journal of Retailing and Consumer Services, 58, 102300. https://doi.org/10.1016/j.jretconser.2020.102300