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Growing Science » Decision Science Letters » Effective factors on the Fintech business models in the electronic payment: A DEMATEL-ISM-ANP approach

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Decision Science Letters
ISSN 1929-5812 (Online) - ISSN 1929-5804 (Print)
Quarterly Publication
Volume 14 Issue 2 pp. 515-530, 2025

Effective factors on the Fintech business models in the electronic payment: A DEMATEL-ISM-ANP approach Pages 515-530 PDF Download PDF

Authors: Nasser Safaie, Aida Eslami, Majid Mirzaee Ghazani

📋 Author Affiliations:
N. Safaie, A. Eslami, M.M. Ghazani ORCID
¹ Department of Industrial Engineering, K. N. Toosi University of Technology, Iran
doi 10.5267/j.dsl.2024.12.004
Crossref Source: CrossRef

🔑 Keywords: Fintech, Multi-criteria decision-making, Business model, Analytical Network Process, Interpretive Structural Modeling, DEMATEL

Abstract: In recent years, fintech has received much attention due to the introduction of new technologies in banking and electronic payment. For financial service providers to compete in the industries, they should apply the business model as a conceptual framework to improve performance. The current research is exploratory and tries to identify the factors influencing fintech design in electronic payment using the Osterwalder business model. This study aims to integrate three methods named DEMATEL, ISM, and ANP from MCDM techniques. To analyze the identified factors affecting the design of fintech in electronic payment, the indicators were examined in terms of influence and effectiveness by the DEMATEL method, then the levels of influence and effectiveness of the factors were investigated using the interpretive structural modeling method. Finally, the network analysis method was used to prioritize the factors. The findings showed that recognizing and identifying electronic payment customers is the most effective among the factors, and determining the type of relationship with customers is the most impressionable factor. In addition, after ranking the factors, the type of relationship with customers was the first rank, and the criteria of the company's cost structure and revenue streams were determined as the second and third, respectively.

How to cite this paper
APA: Safaie, N., Eslami, A & Ghazani, M. (2025). Effective factors on the Fintech business models in the electronic payment: A DEMATEL-ISM-ANP approach. Decision Science Letters, 14(2), 515-530.
Chicago/Turabian: Safaie, N., Eslami, A & Ghazani, M. 2025. "Effective factors on the Fintech business models in the electronic payment: A DEMATEL-ISM-ANP approach." Decision Science Letters 14, no. 2 (2025): 515-530.
AMA: Safaie, N., Eslami, A & Ghazani, M. Effective factors on the Fintech business models in the electronic payment: A DEMATEL-ISM-ANP approach. Decision Science Letters. 2025;14(2):515-530.

References
Agarwal, S., & Zhang, J. (2020). FinTech, lending and payment innovation: A review. Asia‐Pacific Journal of Financial Studies, 49(3), 353-367.
Akyuz, E., & Celik, E. (2015). A fuzzy DEMATEL method to evaluate critical operational hazards during gas freeing process in crude oil tankers. Journal of Loss Prevention in the Process Industries, 38, 243-253.
Al-Debei, M. M., & Avison, D. (2010). Developing a unified framework of the business model concept. European journal of information systems, 19(3), 359-376.
Alkhazaleh, A. M. K., & Haddad, H. (2021). How does the Fintech services delivery affect customer satisfaction: A scenario of Jordanian banking sector. Strategic Change, 30(4), 405-413.
Arner, D. W., Barberis, J., & Buckley, R. P. (2015). The evolution of Fintech: A new post-crisis paradigm. Georgetown Journal of International Law, 47, 1271.
Arslan, A., Buchanan, B. G., Kamara, S., & Al Nabulsi, N. (2021). Fintech, base of the pyramid entrepreneurs and social value creation. Journal of Small Business and Enterprise Development, 29(3), 335-353.
Chishti, S., Craddock, T., Courtneidge, R., & Zachariadis, M. (Eds.). (2019). The PAYTECH Book: The Payment Technology Handbook for Investors, Entrepreneurs, and FinTech Visionaries. John Wiley & Sons.
DaSilva, C. M., & Trkman, P. (2014). Business model: What it is and what it is not. Long range planning, 47(6), 379-389.
Dijkman, R. M., Sprenkels, B., Peeters, T., & Janssen, A. (2015). Business models for the Internet of Things. International Journal of Information Management, 35(6), 672-678.
Feng, X., Li, E., Li, J., & Wei, C. (2023). Critical influencing factors of employees’ green behavior: three-stage hybrid fuzzy DEMATEL–ISM–MICMAC approach. Environment, development and sustainability, 1-29.
Feng, Y., Hong, Z., Zhang, Z., Zhang, Z., & Tan, J. (2017). Interval analysis and DEMATEL-based reliability apportionment for energy consumption optimization with energy Internet. IEEE Access, 5, 4769-4778.
Foss, N. J., & Saebi, T. (2017). Fifteen years of research on business model innovation: How far have we come, and where should we go?. Journal of management, 43(1), 200-227.
Gilsing, R., Türetken, O., Grefen, P., Ozkan, B., & Adali, O. E. (2022). Business model evaluation: a systematic review of methods. Pacific Asia Journal of the Association of Information Systems, 14(4), 26-61.
Globocnik, D., Faullant, R., & Parastuty, Z. (2020). Bridging strategic planning and business model management–A formal control framework to manage business model portfolios and dynamics. European Management Journal, 38(2), 231-243.
Gomber, P., Koch, J. A., & Siering, M. (2017). Digital Finance and FinTech: current research and future research directions. Journal of Business Economics, 87, 537-580.
Guo, P., & Zhang, C. (2023). The impact of bank FinTech on liquidity creation: Evidence from China. Research in International Business and Finance, 64, 101858.
Hashemkhani Zolfani, S., Görçün, Ö. F., & Küçükönder, H. (2023). Evaluation of the special warehouse handling equipment (turret trucks) using integrated fucom and waspas techniques based on intuitionistic fuzzy dombi aggregation operators. Arabian Journal for Science and Engineering, 48(11), 15561-15595.
Hill, J. (2018). Fintech and the remaking of financial institutions. Academic Press.
Kannan, G., & Haq, A. N. (2007). Analysis of interactions of criteria and sub-criteria for the selection of supplier in the built-in-order supply chain environment. International Journal of Production Research, 45(17), 3831-3852.
Le, L. T., Yarovaya, L., & Nasir, M. A. (2021). Did COVID-19 change spillover patterns between Fintech and other asset classes?. Research in international business and finance, 58, 101441.
Lee, E. (2020). The Global Financial Crisis Gave Birth to FinTech. What Will COVID-19 Recession Bring.
Liang, Y., Wang, H., & Zhao, X. (2022). Analysis of factors affecting economic operation of electric vehicle charging station based on DEMATEL-ISM. Computers & Industrial Engineering, 163, 107818.
Liu, J., Li, X., & Wang, S. (2020). What have we learnt from 10 years of fintech research? a scientometric analysis. Technological Forecasting and Social Change, 155, 120022.
Lv, P., & Xiong, H. (2022). Can FinTech improve corporate investment efficiency? Evidence from China. Research in International Business and Finance, 60, 101571.
Moro-Visconti, R., Cruz Rambaud, S., & López Pascual, J. (2020). Sustainability in FinTechs: An explanation through business model scalability and market valuation. Sustainability, 12(24), 10316.
Nalluri, V., & Chen, L. S. (2024). Modelling the FinTech adoption barriers in the context of emerging economies—An integrated Fuzzy hybrid approach. Technological Forecasting and Social Change, 199, 123049.
Nasfi, N., Yunimar, Y., & Prawira, A. (2022). The role of Fintech in Sharia rural bank West Sumatra. International Journal of Social and Management Studies, 3(2), 13-19.
Navaretti, G. B., Calzolari, G., Mansilla-Fernandez, J. M., & Pozzolo, A. F. (2018). Fintech and banking. Friends or foes?. Friends or Foes.
Osterwalder, A., & Pigneur, Y. (2010). Business model generation: a handbook for visionaries, game changers, and challengers (Vol. 1). John Wiley & Sons.
Panahifar, F., Byrne, P. J., & Heavey, C. (2014). ISM analysis of CPFR implementation barriers. International Journal of Production Research, 52(18), 5255-5272.
Peng, Z., & Ke, J. (2022).Spillover effect of the interaction between fintech and the real economy based on tail risk dependent structure analysis. Sustainability, 14(13), 7818.
Polasik, M., Huterska, A., Iftikhar, R., & Mikula, Š. (2020). The impact of Payment Services Directive 2 on the PayTech sector development in Europe. Journal of Economic Behavior & Organization, 178, 385-401.
Priem, R. L., Wenzel, M., & Koch, J. (2018). Demand-side strategy and business models: Putting value creation for consumers center stage. Long range planning, 51(1), 22-31.
Siddiqui, Z., & Rivera, C. A. (2022). Fintech and fintech ecosystem: A review of literature. Risk Governance & Control: Financial Markets & Institutions, 12(1).
Sironi, P. (2016). FinTech innovation: from robo-advisors to goal based investing and gamification. John Wiley & Sons.
Slozko, O., & Pelo, A. (2015).Problems and risks of digital technologies introduction into e-payments. Transformations in Business & Economics, 14(1).
Snihur, Y., & Bocken, N. (2022). A call for action: The impact of business model innovation on business ecosystems, society and planet. Long Range Planning, 55(6), 102182.
Thakkar, J. J., Thanki, S., & Guru, S. (2023). A quantitative framework for health‐care service quality assessment in India. Journal of Modelling in Management, 18(4), 1064-1092.
Trivedi, P., Vansjalia, R., Erra, S., Narayanan, S., & Nagaraju, D. (2023). A fuzzy CRITIC and fuzzy WASPAS-based integrated approach for wire arc additive manufacturing (WAAM) technique selection. Arabian Journal for Science and Engineering, 48(3), 3269-3288.
Tut, D. (2020). FinTech and the COVID-19 Pandemic: Evidence from Electronic Payment Systems.
Valmohammadi, C., & Dashti, S. (2016). Using interpretive structural modeling and fuzzy analytical process to identify and prioritize the interactive barriers of e-commerce implementation. Information & Management, 53(2), 157-168.
Viet, D. D. T., Thanh, L. N., & Hoai, A. N. D. (2021). Extending UTAUT2 in Mobile money adoption and actual use behavior: An empirical research in Vietnam during the Covid-19. Industrielle Beziehungen. Zeitschrift Für Arbeit, Organisation Und Management, 10(4).
Voelpel, S. C., Leibold, M., & Tekie, E. B. (2004). The wheel of business model reinvention: how to reshape your business model to leapfrog competitors. Journal of change management, 4(3), 259-276.
Wang, D., Wang, Y., Huang, Z., & Cui, R. (2020). Understanding the resilience of coal industry ecosystem to economic shocks: Influencing factors, dynamic evolution and policy suggestions. Resources Policy, 67, 101682.
Wang, Y., Xiuping, S., & Zhang, Q. (2021). Can fintech improve the efficiency of commercial banks?—An analysis based on big data. Research in international business and finance, 55, 101338.
Wirtz, B. W. (2020). Business Model Management: Design-Process-Instruments. Springer Nature.
Wirtz, B. W., Pistoia, A., Ullrich, S., & Göttel, V. (2016). Business models: Origin, development and future research perspectives. Long range planning, 49(1), 36-54.
Wonglimpiyarat, J. (2017). FinTech banking industry: a systemic approach. foresight, 19(6), 590-603.
Yadav, S., Luthra, S., & Garg, D. (2022). Internet of things (IoT) based coordination system in Agri-food supply chain: development of an efficient framework using DEMATEL-ISM. Operations management research, 15(1), 1-27.
Zeng, S., Hu, Y., Balezentis, T., & Streimikiene, D. (2020). A multi‐criteria sustainable supplier selection framework based on neutrosophic fuzzy data and entropy weighting. Sustainable Development, 28(5), 1431-1440.
Zhao, J., Li, X., Yu, C. H., Chen, S., & Lee, C. C. (2022). Riding the FinTech innovation wave: FinTech, patents and bank performance. Journal of International Money and Finance, 122, 102552.
Zrobek, S., Kovalyshyn, O., Renigier‐Biłozor, M., Kovalyshyn, S., & Kovalyshyn, O. (2020). Fuzzy logic method of valuation supporting sustainable development of the agricultural land market. Sustainable Development, 28(5), 1094-1105.
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📚 Journal: Decision Science Letters | 📅 Year: 2025 | 📖 Volume: 14 | 📄 Issue: 2 | 👁️ Views: 471 | 📊 Crossref:

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