Adoption Dynamics of Digital Payments: An Urban Case Study on E-Money Using the Technology Acceptance Model
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Abstract
The utilization of e-money in Indonesia has surged, propelled by the expansion of digital payment platforms. Despite their growing prevalence, the dynamics of e-money acceptance within urban environments remain underexplored. This study innovatively extends the Technology Acceptance Model (TAM) by incorporating Perceived Security as a new variable, alongside traditional factors such as Perceived Usefulness, Perceived Ease of Use, Attitude Toward Using, Behavioral Intention to Use, and Facilitating Condition. The research focuses on Padang City, a representative urban landscape, where data was collected from 201 valid respondents through online platforms. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM). The integration of Perceived Security is a novel aspect of this study, reflecting its crucial role in the contemporary urban context of e-money utilization. Results reveal significant relationships among the studied variables, although the impacts of Facilitating Condition on Perceived Ease of Use and Perceived Usefulness on Behavioral Intention to Use were not supported. The findings underscore that positive attitude toward e-money significantly boost behavioral intentions to use it, primarily influenced by security perceptions and ease of use. These insights have substantial implications for policymakers and businesses focused on enhancing e-money adoption in urban settings. The study highlights the necessity of addressing user perceptions, particularly security, to foster broader acceptance. The limited influence of Facilitating Conditions suggests that improvements in infrastructure must be coupled with efforts to enhance user trust and ease of interaction with e-money platforms. This research contributes to the field by providing a deeper understanding of the factors driving e-money acceptance in urban areas, guiding targeted strategies for digital financial inclusion.
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[1]
R. G. Utomo, R. Yasirandi, and N. A. Suwastika, “Adoption Dynamics of Digital Payments: An Urban Case Study on E-Money Using the Technology Acceptance Model”, INFOTEL, vol. 16, no. 3, pp. 567–581, Sep. 2024.
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Informatics
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[26] M. Yang, A. Al Mamun, M. Mohiuddin, N. C. Nawi, and N. R. Zainol, “Cashless Transactions: A Study on Intention and Adoption of e-Wallets,” Sustainability, vol. 13, no. 2, pp. 1–18, Jan. 2021, doi: 10.3390/SU13020831.
[27] L. Chen and A. K. Aklikokou, “Determinants of E-government Adoption: Testing the Mediating Effects of Perceived Usefulness and Perceived Ease of Use,” International Journal of Public Administration, vol. 43, no. 10, pp. 850–865, Jul. 2020, doi: 10.1080/01900692.2019.1660989.
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[32] A. Farooq, F. Ahmad, N. Khadam, B. Lorenz, and J. Isoaho, “The Impact of Perceived Security on Intention to use E-Learning Among Students,” 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT), pp. 360–364, Jul. 2020, doi: 10.1109/ICALT49669.2020.00115.
[2] H. Brimantyo, A. Suwandaru, A. M. Ratri, G. I. K. Nugraha, and M. R. Firdaus, “The Role of E-money on Business Growth in Indonesia,” Jurnal Bisnis dan Manajemen, vol. 8, no. 2, pp. 405–411, Nov. 2021, doi: 10.26905/JBM.V8I2.7091.
[3] K.-Y. Kang, “E-money, Credit Cards, and Privacy,” SSRN Electronic Journal, May 2021, doi: 10.2139/SSRN.3838718.
[4] T. T. Le et al., “The impact of online identity theft on customers’ usage intention of e-banking transactions in uncertain context,” Journal of Governance and Regulation, vol. 12, no. 4, pp. 60–71, 2023, doi: 10.22495/JGRV12I4ART6.
[5] A. Y. Putra and A. H. Wijaya, “Analysis And Design Of E-Commerce (B2B) With The Technology Acceptance Model Method At PT. Global Pharma Indonesia,” Tech-E, vol. 4, no. 1, pp. 13–20, Sep. 2020, doi: 10.31253/TE.V4I1.404.
[6] F. Filona and M. Misdiyono, “FACTORS AFFECTING THE ADOPTION OF ELECTRONIC MONEY USING TECHNOLOGY ACCEPTANCE MODEL AND THEORY OF PLANNED BEHAVIOR,” Journal of Business Economics, vol. 24, no. 1, pp. 100–113, 2019, doi: 10.35760/EB.2019.V24I1.1858.
[7] M. A. Camilleri, “The online users’ perceptions toward electronic government services,” J. Inf. Commun. Ethics Soc., vol. 18, no. 2, pp. 221–235, Apr. 2020, doi: 10.1108/JICES-09-2019-0102.
[8] A. Ghodratnama, M. Sabet, and O. Jabari, “The acceptance model of e-learning during the coronavirus pandemic,” Journal of Modern Medical Information Sciences, vol. 7, no. 4, pp. 24–32, Jan. 2022, doi: 10.52547/JMIS.7.4.24.
[9] S. Purwanto, S. Hartini, and G. C. Premananto, “The Development and Testing of Technology Acceptance Models for Consumers towards the Intention to Use E-Wallet,” Proceedings of the International Conference on Innovation in Research (ICIIR 2018) – Section: Economics and Management Science, Aug. 2019, doi: 10.2991/ICIIR-18.2019.11.
[10] J. T. Zielonka and F. Rothlauf, “Techno-Eustress: The Impact of Perceived Usefulness and Perceived Ease of Use on the Perception of Work-Related Stressors,” Proceedings of the Annual Hawaii International Conference on System Sciences, vol. 2020-January, pp. 1–10, 2021, doi: 10.24251/HICSS.2021.780.
[11] M. T. Nuseir, A. I. Aljumah, and G. A. El Refae, “Trust in Adoption of Internet of Things: Role of Perceived Ease of Use and Security,” 2022 International Arab Conference on Information Technology (ACIT), pp. 1–7, 2022, doi: 10.1109/ACIT57182.2022.9994207.
[12] N. Muliati, “Pengaruh Perceived Usefulness, Perceived Ease Of Use, Attitude Toward Using Dan Behavior Intention To Use Terhadap Actual System Use Dalam Implementasi Teknologi Enterprise Resource Planning (ERP) System (Studi Pada End User ERP System Di PT Semen Gresik),” Jurnal Manajemen dan Inovasi (MANOVA), vol. 2, no. 2, pp. 31–46, Dec. 2019, doi: 10.15642/MANOVA.V2I2.191.
[13] I. A. Ambalov, “Decomposition of perceived usefulness: A theoretical perspective and empirical test,” Technol Soc, vol. 64, Feb. 2021, doi: 10.1016/J.TECHSOC.2020.101520.
[14] M. Sheppard and C. Vibert, “Re-examining the relationship between ease of use and usefulness for the net generation,” Educ Inf Technol (Dordr), vol. 24, no. 5, pp. 3205–3218, Sep. 2019, doi: 10.1007/S10639-019-09916-0.
[15] S. Park and J.-E. Lee, “The Influence of Theory of Planned Behavior (TPB) on the Perceived Ease of Use and Perceived Usefulness in Accounting Information Users,” Korean Association Of Computers And Accounting, vol. 20, no. 2, pp. 23–45, Aug. 2022, doi: 10.32956/KAOCA.2022.20.2.23.
[16] A. M. Adam, “Sample Size Determination in Survey Research,” J Sci Res Rep, pp. 90–97, Jun. 2020, doi: 10.9734/JSRR/2020/V26I530263.
[17] R. W. Emerson, “Convenience Sampling Revisited: Embracing Its Limitations Through Thoughtful Study Design,” J Vis Impair Blind, vol. 115, no. 1, pp. 76–77, Jan. 2021, doi: 10.1177/0145482X20987707.
[18] S. S. Zabukovšek, S. Bobek, U. Zabukovšek, Z. K. Kalini´c, and P. Tominc, “Enhancing PLS-SEM-Enabled Research with ANN and IPMA: Research Study of Enterprise Resource Planning (ERP) Systems’ Acceptance Based on the Technology Acceptance Model (TAM),” Mathematics 2022, Vol. 10, Page 1379, vol. 10, no. 9, p. 1379, Apr. 2022, doi: 10.3390/MATH10091379.
[19] D. Russo and K. J. Stol, “PLS-SEM for Software Engineering Research,” ACM Computing Surveys (CSUR), vol. 54, no. 4, pp. 1–38, Jul. 2021, doi: 10.1145/3447580.
[20] A. Afthanorhan, Z. Awang, and N. Aimran, “An extensive comparison of CB-SEM and PLS-SEM for reliability and validity,” International Journal of Data and Network Science, vol. 4, no. 4, pp. 357–364, 2020, doi: 10.5267/J.IJDNS.2020.9.003.
[21] G. Dash and J. Paul, “CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting,” Technol Forecast Soc Change, vol. 173, p. 121092, Dec. 2021, doi: 10.1016/J.TECHFORE.2021.121092.
[22] S. Panahi, A. Bazrafshani, and A. Mirzaie, “Development and validation of a modified LibQUAL scale in health sciences libraries: application of Structural Equation Modeling,” Journal of the Medical Library Association, vol. 111, no. 4, pp. 792–801, Oct. 2023, doi: 10.5195/JMLA.2023.1348.
[23] J. F. Hair, J. J. Risher, M. Sarstedt, and C. M. Ringle, “When to use and how to report the results of PLS-SEM,” European Business Review, vol. 31, no. 1, pp. 2–24, Jan. 2019, doi: 10.1108/EBR-11-2018-0203.
[24] G. Shmueli et al., “Predictive model assessment in PLS-SEM: guidelines for using PLSpredict,” Eur J Mark, vol. 53, no. 11, pp. 2322–2347, Sep. 2019, doi: 10.1108/EJM-02-2019-0189.
[25] H. Djajadikerta and M. Susan, “Determinants of e-money adoption: an empirical study,” International Journal of Trade and Global Markets, vol. 13, no. 1, p. 1, 2020, doi: 10.1504/IJTGM.2020.10021935.
[26] M. Yang, A. Al Mamun, M. Mohiuddin, N. C. Nawi, and N. R. Zainol, “Cashless Transactions: A Study on Intention and Adoption of e-Wallets,” Sustainability, vol. 13, no. 2, pp. 1–18, Jan. 2021, doi: 10.3390/SU13020831.
[27] L. Chen and A. K. Aklikokou, “Determinants of E-government Adoption: Testing the Mediating Effects of Perceived Usefulness and Perceived Ease of Use,” International Journal of Public Administration, vol. 43, no. 10, pp. 850–865, Jul. 2020, doi: 10.1080/01900692.2019.1660989.
[28] M. G. Salimon, S. Sanuri, and M. M. Yusr, “E-Banking as a Financial Supply Chain System: Can e-TAM improve Trust and the Rate of Adoption?,” International Journal of Supply Chain Management, 2020.
[29] K. Keni, H. Tjoe, N. Wilson, and E. S. Negara, “The Effect of Perceived Security, Ease of Use and Perceived Usefulness on Intention to Use Towards Mobile Payment Services in Indonesia,” Proceedings of the 2nd Tarumanagara International Conference on the Applications of Social Sciences and Humanities (TICASH 2020), Dec. 2020, doi: 10.2991/ASSEHR.K.201209.010.
[30] D. Sugandini, M. I. Effendi, and Y. Istanto, “The Effect of Ease of Use, Usefulness, Trust, Self-efficacy, and Security on Adoption Technology,” Proceedings of the International Conference of Business, Economy, Entrepreneurship and Management, pp. 89–93, Sep. 2020, doi: 10.5220/0009964400890093.
[31] F. Nurhidayat, “INFLUENCED FACTORS OF E-MONEY ADOPTION,” JRAK: Jurnal Riset Akuntansi dan Komputerisasi Akuntansi, vol. 9, no. 2, pp. 222–233, Aug. 2018, doi: 10.33558/JRAK.V9I2.1589.
[32] A. Farooq, F. Ahmad, N. Khadam, B. Lorenz, and J. Isoaho, “The Impact of Perceived Security on Intention to use E-Learning Among Students,” 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT), pp. 360–364, Jul. 2020, doi: 10.1109/ICALT49669.2020.00115.