Determinants of FinTech Adoption: A Comparative Study of Individuals in Low- and High-Income Groups in Sindh, Pakistan.

Sadia Shaikh; Imam Uddin Khoso; Muhammad Faisal Sultan

doi:10.52633/erxdkn39

Authors

Sadia Shaikh Benazir Bhutto Shaheed University, Karachi. Author
Imam Uddin Khoso University of Sindh, Jamshoro, Pakistan. Author
Muhammad Faisal Sultan Khadim Ali Shah Bukhari Institute of Technology, KASBIT, Karachi Author

DOI:

https://doi.org/10.52633/erxdkn39

Keywords:

FinTech, FinTech Adoption, Small and Medium Enterprises (SMEs), Technology Acceptance Model (TAM), Consumer Attitude, Perceived Usefulness, Perceived Ease of Use

Abstract

FinTech, as a Digital Financial Service, is rapidly transforming the financial industry landscape, providing opportunities and posing challenges to financial service providers, consumers, and regulatory bodies alike. Pakistan’s consumer market, with the 5^th largest youth population in the world, ever-increasing smartphone penetration, and internet subscriptions, is ripe for launching innovative FinTech solutions to bring low- and high-income people into financial inclusion and lift low-income individuals out of poverty. The primary objective of this study is to empirically examine the factors that influence an individual’s decision to adopt and utilize FinTech. Applying a quantitative research approach, a structured survey questionnaire was developed and used for data collection. The main finding of this study revealed that perceived usefulness and perceived ease of use factors strongly influence attitude toward Fintech usage, which in turn, majorly determines behavioral intention to use FinTech. The results show that in terms of Fintech adoption, a gender gap exists in favor of males. Moreover, it was found that in Sindh Province, a lack of a positive mindset towards the use of digital finance has been the biggest limiting factor in the growth of Fintech businesses. The consumer's positive mindset is a prerequisite for the use of FinTech. With respect to Fintech adoption and growth, there should be collaborative networks connecting all the relevant stakeholders, including regulatory authorities, market participants, telecommunication companies, academicians, and others, to create a conducive environment in which the interests of service providers and end-users should be well safeguarded.

Author Biographies

Sadia Shaikh, Benazir Bhutto Shaheed University, Karachi.

Assistant Professor, Benazir School of Business, Benazir Bhutto Shaheed University, Karachi.
Imam Uddin Khoso, University of Sindh, Jamshoro, Pakistan.

Director, IBA, University of Sindh, Jamshoro, Pakistan.
Muhammad Faisal Sultan, Khadim Ali Shah Bukhari Institute of Technology, KASBIT, Karachi

Assistant Professor, Khadim Ali Shah Bukhari Institute of Technology, KASBIT, Karachi.

References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

Ajzen, I. (2002). Perceived behavioral control, self‐efficacy, locus of control, and the theory of planned behavior 1. Journal of Applied Social Psychology, 32(4), 665–683.

Alia, A. (2017). An investigation of the application of the Technology Acceptance Model (TAM) to evaluate instructors’ perspectives on E-Learning at Kuwait University (Dublin City University). Retrieved from http://doras.dcu.ie/21586/1/Alia_Ashkanani_Final_Dissertation.pdf

Ashrafi, D. M., Dovash, R. H., & Kabir, M. R. (2022). DETERMINANTS OF FINTECH SERVICE CONTINUANCE BEHAVIOR: MODERATING ROLE OF TRANSACTION SECURITY AND TRUST. Journal of Global Business & Technology, 18(2).

Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986.

Bankuoru Egala, S., Boateng, D., & Aboagye Mensah, S. (2021). To leave or retain? An interplay between quality digital banking services and customer satisfaction. International journal of bank marketing, 39(7), 1420-1445.

Bajunaied, K., Hussin, N., & Kamarudin, S. (2023). Behavioral intention to adopt FinTech services: An extension of the unified theory of acceptance and use of technology. Journal of Open Innovation: Technology, Market, and Complexity, 9(1), 100010.

Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly, 229–254.

Brown, C. (2011). Mobile Payment Security Concerns Put Breaks on M-commerce Market. Retrieved from https://www.nfcw.com/2011/03/17/36483/mobile-payment-security-concerns-put-brakes-on-m-commerce-market/

Burki, S. J. (2015). International migration and economic changes in South Asia: The emergence of the middle class. International Migration and Development in South Asia, 152-168.

Cao, W. (2016). FinTech acceptance research in Finland-Case company Plastc (School of Business | Aalto University). Retrieved from https://aaltodoc.aalto.fi/bitstream/handle/123456789/21518/hse_ethesis_14696.pdf?sequence=1

CB Insights. (2024). State of Fintech Q1 2024. Retrieved from https://www.cbinsights.com/research/report/fintech-trends-q1-2024

Cavalcanti, D. R., Oliveira, T., & de Oliveira Santini, F. (2022). Drivers of digital transformation adoption: A weight and meta-analysis. Heliyon, 8(2).

Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336.

Ching, A. T., & Hayashi, F. (2010). Payment card rewards programs and consumer payment choice. Journal of Banking & Finance, 34(8), 1773–1787.

Dadhich, M., Rathore, S., Gyamfi, B. A., Ajibade, S. S. M., & Agozie, D. Q. (2023). Quantifying the Dynamic Factors Influencing New‐Age Users’ Adoption of 5G Using TAM and UTAUT Models in an Emerging Country: A Multistage PLS‐SEM Approach. Education Research International, 2023(1), 5452563.

Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results [Dissertation]. Doctoral Dissertation, Massachusetts Institute of Technology. https://doi.org/10.1016/S0378-7206(01)00143-4

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319–340.

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.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace 1. Journal of Applied Social Psychology, 22(14), 1111–1132.

Durr-e-Nayab. (2011). Estimating the middle class in Pakistan. The Pakistan Development Review, 1–28.

Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information systems frontiers, 21, 719-734.

Elia, G., Stefanelli, V., & Ferilli, G. B. (2023). Investigating the role of Fintech in the banking industry: what do we know?. European Journal of Innovation Management, 26(5), 1365-1393.

FakhrHosseini, S., Chan, K., Lee, C., Jeon, M., Son, H., Rudnik, J., & Coughlin, J. (2024). User adoption of intelligent environments: A review of technology adoption models, challenges, and prospects. International Journal of Human–Computer Interaction, 40(4), 986-998.

Fishbein, M, & Ajzen, I. (1980). Understanding Attitudes and Social Behavior. Prentice Hall, Englewood Cliffs, NJ.

Fishbein, Martin, & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, Mass; Don Mills, Ontario: Addison-Wesley Pub. Co.

Gupta, S., & Xu, H. (2010). Examining the relative influence of risk and control on intention to adopt risky technologies. Journal of technology management & innovation, 5(4), 22-37.

Hair, J., Black, W., Babin, B., & Anderson, R. (2018). Multivariate Data Analysis: A Global Perspective. Vol 8th.

Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., Ray, S., ... & Ray, S. (2021). An introduction to structural equation modeling. Partial least squares structural equation modeling (PLS-SEM) using R: a workbook, 1-29.

Haritha, P. H. (2022). Mobile payment service adoption: understanding customers for an application of emerging financial technology. Information & Computer Security, 31(2), 145-171.

Hassan, M. S., Islam, M. A., Yusof, M. F., & Nasir, H. (2023). Users’ fintech services acceptance: A cross-sectional study on Malaysian Insurance & takaful industry. Heliyon, 9(11).

Jiakui, C., Abbas, J., Najam, H., Liu, J., & Abbas, J. (2023). Green technological innovation, green finance, and financial development and their role in green total factor productivity: Empirical insights from China. Journal of Cleaner Production, 382, 135131.

Khan, A. T., Kamran, R., Rehan, M. F., & Allahrakha, R. (2023). Factor Influencing Intention to Adopt Fintech in Pakistan: A Mediating Effect of Customer Attitude. Pakistan Journal of Humanities and Social Sciences, 11(2), 2354-2366.

Kowalewski, O., & Pisany, P. (2023). The rise of fintech: a cross-country perspective. Technovation, 122, 102642.

Marketing Journal, 29(2), 187-197.

Lee, M. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8(3), 130–141.

Lee, S. (2016). User Behavior of Mobile Enterprise Applications. KSII Transactions on Internet & Information Systems, 10(8).

Lomachynska, I. A., Kuzina, R., & Berezhniuk, I. (2020). Modernization of structure of financial systems with the development of FinTech. Scientific approaches to modernization of economic system: development trends, 363-382.

Long, L. (2008). Why do people use or not use an information technology: an interpretive investigation on the adoption and use of an electronic medical records system (Virginia Commonwealth University). Retrieved from http://scholarscompass.vcu.edu/etd/1745

Malhotra, H., & Chauhan, M. K. (2008). Consumers’ Behaviour towards Online Purchases. International Journal of English Language, Literature and Humanities, 2(9), 387–401.

Marikyan, D., & Papagiannidis, S. (2023). Technology acceptance model. TheoryHub Book. Retrieved June, 6, 2023.

Na, S., Heo, S., Han, S., Shin, Y., & Roh, Y. (2022). Acceptance model of artificial intelligence (AI)-based technologies in construction firms: Applying the Technology Acceptance Model (TAM) in combination with the Technology–Organisation–Environment (TOE) framework. Buildings, 12(2), 90.

OECD. (2017). Technology and Innovation in the insurance Sector 2017. Shiyan Shengwu Xuebao, 1–41.

PWC Fintech Survey. (2023). "FinTech Insights - July 2023". PwC India. Retrieved from https://www.pwc.in/industries/financial-services/fintech/point-of-view/fintech-insights-july-2023.html

Rah, J. H., Hasler, C. M., Painter, J. E., & Chapman-Novakofski, K. M. (2014). Applying the theory of planned behavior to women’s behavioral attitudes on and consumption of soy products. Journal of Nutrition Education and Behavior, 36(5), 238–244.

Rogers Everett, M. (1995). Diffusion of innovations. New York, 12.

Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In Handbook of market research (pp. 587-632). Cham: Springer International Publishing.

Sarwar, A., Khan, M. A., Sarwar, Z., & Khan, W. (2021). Financial development, human capital and its impact on economic growth of emerging countries. Asian Journal of Economics and Banking, 5(1), 86-100.

Subhani, W., Tahir, A., Naz, M. A., Nazir, M. U., & Chaudhry, N. E. (2024). Understanding Sustainable Fintech Adoption Across Generations in Pakistan. Journal of Asian Development Studies, 13(1), 1089-1100.

Sundjaja, A. M., & Tina, A. (2019). The factors of the intention to use P2P lending financial technology (Fintech) website at Jadetabek intervening by perceived value. International Journal of Recent Technology and Engineering, 8(3), 3102-3107.

Sullivan, R. J. (2010). The Changing Nature of US Card Payment Fraud: Industry and Public Policy Options. Economic Review, Second Quarter. Retrieved from https://pdfs.semanticscholar.org/8e53/0664dd6cf425ed2db792f6fdd3794ed1e0ec.pdf

Taylor, S., & Todd, P. (1995a). Assessing IT usage: The role of prior experience. MIS Quarterly, 561–570.

Taylor, S., & Todd, P. A. (1995b). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176.

Teeroovengadum, V., Heeraman, N., & Jugurnath, B. (2017). Examining the antecedents of ICT adoption in education using an extended technology acceptance model (TAM). International Journal of Education and Development Using ICT, 13(3).

Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: toward a conceptual model of utilization. MIS Quarterly, 125–143.

Vahdat, A., Alizadeh, A., Quach, S., & Hamelin, N. (2021). Would you like to shop via mobile app technology? The technology acceptance model, social factors and purchase intention. Australasian

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315.

Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451–481.

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.

Venkatesh, V., Thong, J. Y. L., & 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.

World Bank Digital Finance Report (2022). World Development Report 2022. Finance for sn Equitable Recovery. Retrieved from: https://www.worldbank.org/en/publication/wdr2022

Wang, G., Tan, G. W. H., Yuan, Y., Ooi, K. B., & Dwivedi, Y. K. (2022). Revisiting TAM2 in behavioral targeting advertising: a deep learning-based dual-stage SEM-ANN analysis. Technological Forecasting and Social Change, 175, 121345.

Warsame, M. H., & Ireri, E. M. (2022). FinTech’ Future in Kenya: Does Social Influence Matter?. Journal of African Business, 23(4), 1067-1087.

Wiprayoga, P., Gede, S., & Suasana, G. A. K. G. (2023). The role of attitude toward using mediates the influence of perceived usefulness and perceived ease of use on behavioral intention to use. Russian Journal of Agricultural and Socio-Economic Sciences, 140(8), 53-68.

Zhong, J., Dhir, A., Nieminen, M., Hämäläinen, M., & Laine, J. (2013). Exploring consumer adoption of mobile payments in China. Proceedings of International Conference on Making Sense of Converging Media, 318. ACM.