The Role of Technology Readiness in Islamic Financial Technology Acceptance Among MSMEs: An Empirical Integration Analysis TPB and TAM Framework
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Published:
Jun 28, 2024
Keywords:
Islamic financial technology, MSMEs, TAM, technology readiness, TPB
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Abstract
Indonesia with the largest Muslim population in the world is expected to become the world's leading Islamic finance center. With a large Islamic economic base, Islamic FinTech has an important role in economic expansion in Indonesia. MSMEs as an instrument of economic growth in Indonesia, are expected to maximize the presence of Islamic financial technology for efficient and effective payments, expand market access, and facilitate access to finance and capital. On the other hand, the technology readiness of MSMEs is an important factor that needs to be investigated to see the acceptance of MSMEs towards the use of Islamic financial technology in Indonesia. This study analyzes the factors that influence MSMEs' intention to use Islamic FinTech services. This study involved 140 MSMEs from several regions in Indonesia as respondents. The analysis used partial least square structural equation modeling (SEM-PLS). By the objectives, four variables from TPB and TAM influence the intention to use Islamic financial technology, namely Islamic religiosity, ease of use, usefulness, and technology readiness. Finally, technology readiness is strongly correlated to the use of Islamic financial technology. The results of this study provide a comprehensive perspective for policymakers to improve the quality of applications so that it will also increase the intention of MSMEs to adopt Islamic FinTech. The results of this study can also be input, especially for the Financial Services Authority (OJK) to be able to promote Islamic FinTech and coordinate with Islamic FinTech to be able to provide the best service to users.
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References
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Alsmadi, A. A., Aalrawashdeh, N., Al-Gasaymeh, A., Al_hazimeh, A. M., & Alhawamdeh, L. (2023). Adoption of Islamic fintech in lending services through prediction of behavioural intention. Kybernetes.
Armitage, C. J. & Conner, M. (2001). Efficacy of the theory of planned behaviour: A meta-analytic review. British Journal of Social Psychology, 40(4), 471–499.
Asmy, M. T. T., Mohd, B., Thaker, T., Bin, A., Pitchay, A., Bin, H., & Thas, M. (2019). Factors influencing consumers’ adoption of Islamic mobile banking services in Malaysia. Journal of Islamic Marketing, 10(4), 1037–1056.
Astuti, N. C. & Nasution, R. A. (2014). Technology readiness and e-commerce adoption among entrepreneurs of SMEs in Bandung City, Indonesia. Gadjah Mada International Journal of Business, 16(1), 69–88.
Bley, J. & Kuehn, K. (2004). Conventional versus Islamic finance: Student knowledge and perception in the United Arab Emirates. International Journal of Islamic Financial Services, 5(4), 17–30.
Bukhari, S. N. Z., Isa, S. M. & Yen Nee, G. (2021). Halal vaccination purchase intention: A comparative study between Muslim consumers in Malaysia and Pakistan. Journal of Islamic Marketing, 12(4), 670–689.
Chin, W. W. & Todd, P. A. (1995). On the use, usefulness, and ease of use of structural equation modeling in MIS research: A note of caution. MIS Quarterly, 237–246.
Cohen, J. (2013). Statistical Power Analysis for the Behavioral Sciences. London (UK), Routledge.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319–340.
Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475–487.
Davis, F. D., & Venkatesh, V. (1996). A critical assessment of potential measurement biases in the technology acceptance model: Three experiments. International Journal of Human-Computer Studies, 45(1), 19–45.
Falk, R. F. & Miller, N. B. (1992). A Primer for Soft Modeling. Ohio (US), University of Akron Press.
Fianto, B. A., Hendratmi, A., & Aziz, P. F. (2020). Factors determining behavioral intentions to use Islamic financial technology: Three competing models. Journal of Islamic Marketing, 12(4), 794–812.
Firmansyah, I. A., Yasirandi, R. & Utomo, R. G. (2022). The influence of efficacy, credibility, and normative pressure to M-banking adoption level in Indonesia. Procedia Computer Science, 197, 51–60.
Gu, J.-C., Lee, S.-C., & Suh, Y.-H. (2009). Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36(9), 11605–11616.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24.
Hair Jr, J., 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). California (US), Sage publications.
Hamzah, H. & Mustafa, H. (2018). Exploring consumer boycott intelligence towards Israel-related companies in Malaysia: An integration of the theory of planned behaviour with transtheoretical stages of change. Journal of Islamic Marketing, 10(1), 208–226.
Hendratmi, A., Ryandono, M. N. H. & Sukmaningrum, P. S. (2020). Developing Islamic crowdfunding website platform for startup companies in Indonesia. Journal of Islamic Marketing, 11(5), 1041–1053.
Hosseini, S. M. P, Mirzaei, M., & Iranmanesh, M. (2020). Determinants of Muslims’ willingness to pay for halal certified food: Does religious commitment act as a moderator in the relationships? Journal of Islamic Marketing, 11(6), 1225–1243.
Huei, C. T., Cheng, L. S., Seong, L. C., Khin, A. A., & Bin, R. L. L. (2018). Preliminary study on consumer attitude towards fintech products and services in Malaysia. International Journal of Engineering & Technology, 7(2), 166–169.
Ibrahim, M. A., Fisol, W. N. M., & Haji-Othman, Y. (2017). Customer intention on Islamic home financing products: An application of theory of planned behavior (TPB). Mediterranean Journal of Social Sciences, 8(2), 77.
Khayruzzaman. (2016). Impact of religiosity on buying behavior of financial products: A literature review. International Journal of Finance and Banking Research, 2(1), 18-23.
Kock, N. (2020). WarpPLS user manual 7.0. ScriptWarp Systems, 94.
Kumari, A. & Devi, N. C. (2023). Blockchain technology acceptance by investment professionals: A decomposed TPB model. Journal of Financial Reporting and Accounting, 21(1), 45–59.
Lim, W. M. (2022). Toward a theory of social influence in the new normal. Activities, Adaptation & Aging, 46(1), 1-8.
Lin, J.-S. C. & Hsieh, P. (2006). The role of technology readiness in customers’ perception and adoption of self-service technologies. International Journal of Service Industry Management, 17(5), 497–517.
Liu, N. & Ye, Z. (2021). Empirical research on the blockchain adoption–based on TAM. Applied Economics, 53(37), 4263–4275.
Lule, I., Omwansa, T. K. & Waema, T. M. (2012). Application of technology acceptance model (TAM) in m-banking adoption in Kenya. International Journal of Computing & ICT Research, 6(1).
Majid, R. & Mawaddah, H. (2022). FinTech and MSMEs: The role of product knowledge. Asian Journal of Islamic Management (AJIM), 15-24.
Majid, R. (2021). The role of religiosity in explaining the intention to use Islamic fintech among MSME actors. International Journal of Islamic Economics and Finance (IJIEF), 4(2), 207–232.
Mansori, S., Sambasivan, M. & Md-Sidin, S. (2015). Acceptance of novel products: The role of religiosity, ethnicity and values. Marketing Intelligence & Planning, 33(1), 39–66.
Marszk, A. & Lechman, E. (2019). New technologies and diffusion of innovative financial products: Evidence on exchange-traded funds in selected emerging and developed economies. Journal of Macroeconomics, 62, 103064.
Memon, M. A., Ting, H., Cheah, J. H., Thurasamy, R., Chuah, F., & Cham, T. H. (2020). Sample size for survey research: Review and recommendations. Journal of Applied Structural Equation Modeling, 4(2), 1-20.
Mukherjee, S., Baral, M. M., Lavanya, B. L., Nagariya, R., Singh Patel, B., & Chittipaka, V. (2023). Intentions to adopt the blockchain: Investigation of the retail supply chain. Management Decision, 61(5), 1320–1351.
Ninglasari, S. Y. (2021). Determinants of online zakat intention amongst Muslim millennials: An integration of technology acceptance model and theory of planned behavior. Shirkah: Journal of Economics and Business, 6(2), 227–245.
Nugroho, M. A., Susilo, A. Z., Fajar, M. A., & Rahmawati, D. (2017). Exploratory study of SMEs technology adoption readiness factors. Procedia Computer Science, 124, 329–336.
Ong, C.-S. & Lai, J.-Y. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816–829.
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.
Parasuraman, A. & Colby, C. L. (2015). An updated and streamlined technology readiness index: TRI 2.0. Journal of Service Research, 18(1), 59–74.
Pattansheti, M., Kamble, S. S., Dhume, S. M., & Raut, R. D. (2016). Development, measurement and validation of an integrated technology readiness acceptance and planned behaviour model for Indian mobile banking industry. International Journal of Business Information Systems, 22(3), 316–342.
Perwitasari, A.W., (2022). The effect of perceived usefulness and perceived easiness towards behavioral intention to use fintech by Indonesian MSMEs. The Winners, 23(1), 1–9.
Pew Research Center. (2020). Religious Landscape and Change [online]. [accessed 2024 Jun 27]. Retrieved from: https://www.pewresearch.org/religion/2023/09/12/religious-landscape-and-change/.
Purwantini, A. H., Athief, F. H. N., & Waharini, F. M. (2020). Indonesian consumers’ intention of adopting islamic financial technology services. Shirkah: Journal of Economics and Business, 5(2), 171-196.
Purwanto, E. & Loisa, J. (2020). The intention and use behaviour of the mobile banking system in Indonesia: UTAUT Model. Technology Reports of Kansai University, 62(06), 2757–2767.
Rajan, C. A. & Baral, R. (2015). Adoption of ERP system: An empirical study of factors influencing the usage of ERP and its impact on end user. IIMB Management Review, 27(2), 105–117.
Reuters, T. & Standard, D. (2018). State of the global Islamic economy report 2018/19. Dubai International Financial Centre, 112.
Riza, A. F. (2021). The potential of digital banking to handle the Covid-19 pandemic crisis: Modification of UTAUT model for Islamic finance industry. Jurnal Ekonomi & Keuangan Islam, 1–16.
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.
Setiawan, B., Nugraha, D. P., Irawan, A., Nathan, R. J., & Zoltan, Z. (2021). User innovativeness and fintech adoption in Indonesia. Journal of Open Innovation: Technology, Market, and Complexity, 7(3), 188.
Shaikh, I. M., Qureshi, M. A., Noordin, K., Shaikh, J. M., Khan, A., & Shahbaz, M. S. (2020). Acceptance of Islamic financial technology (FinTech) banking services by Malaysian users: An extension of technology acceptance model. Foresight, 22(3), 367–383.
Shih, B. Y., Chen, C. Y., & Chen, C. L. (2012). An enhanced acceptance model for exploring user intention towards virtual reality environment: Partial least squares (PLS) statistical method. International Journal of Physical Sciences, 7(5), 776-786.
Singh, S., Sahni, M. M., & Kovid, R. K. (2020). What drives FinTech adoption? A multi-method evaluation using an adapted technology acceptance model. Management Decision, 58(8), 1675–1697.
Siragusa, L. & Dixon, K. (2008). Planned behaviour: Student attitudes towards the use of ICT interactions in higher education. Hello! Where Are You in the Landscape of Educational Technology? Proceedings Ascilite Melbourne 2008, 942–953.
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