Perceived key determinants of payment instrument usage: a fuzzy cognitive mapping-based approach

    Fabiana R. R. L. Santos Affiliation
    ; Fernando A. F. Ferreira Affiliation
    ; Ieva Meidutė-Kavaliauskienė Affiliation


The recent economic climate has had direct repercussions on people’s daily lives. This has occurred not only in how they use payment instruments, but is also evinced in new concerns adjacent to technological advances, people’s safety and the credibility of financial institutions. In this regard, the banking sector has had a crucial role in countries’ economic development, making it increasingly important to understand how the banking system operates and what payment instruments are available to users. Relying on specialized literature and the application of fuzzy cognitive mapping, this study aims to understand the cause-and-effect relationships between customers’ preference factors in using payment instruments. The results show that usability aspects and safety concerns constitute the factors which users pay more attention to. Strengths and limitations of our proposal are also discussed.

Keyword : payment instruments, customer usage preferences, decision aid, FCM

How to Cite
Santos, F. R. R. L., Ferreira, F. A. F., & Meidutė-Kavaliauskienė, I. (2018). Perceived key determinants of payment instrument usage: a fuzzy cognitive mapping-based approach. Technological and Economic Development of Economy, 24(3), 950-968.
Published in Issue
May 18, 2018
Abstract Views
PDF Downloads
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.


Ackermann, F.; Eden, C. 2001. SODA – Journey making and mapping in practice, in J. Rosenhead, J. Mingers (Eds.). Rational analysis for a problematic world revisited: problem structuring methods for complexity, uncertainty and conflict. 2nd ed. Chichester: John Wiley & Sons, 43–60.

Ahmadirezaei, H. 2011. The effect of information technology in Saderat banking system, Procedia – Social and Behavioral Science 30: 23–26.

Axelrod, R. 1976. Structure of decision the cognitive maps of political elites. New Jersey: Princeton University Press.

Bell, S.; Morse, S. 2013. Groups and facilitators within problem structuring processes, Journal of the Operational Research Society 64(7): 959–972.

Calais, G. 2008. Fuzzy cognitive maps theory: implications for interdisciplinary reading: national implications, Focus on Colleges, Universities, and Schools 2(1): 1–16.

Calisir, F.; Gumussoy, A. 2008. Internet banking versus other banking channels: young consumers’ view, International Journal of Information Management 28(3): 215–221.

Carlucci, D.; Schiuma, G.; Gavrilova, T.; Linzalone, R. 2013. A fuzzy cognitive map based approach to disclose value creation dynamics of ABIs, in Proceedings of the 8th International Forum on Knowledge Asset Dynamics (IFKAD-2013), 12–14 June 2013, Zagreb, Croatia, 207–219.

Dangolani, S. 2011. The impact of information technology in banking system: a case study in bank Keshavarzi Iran, Procedia – Social and Behavioral Sciences 30: 13–16.

Dauda, S.; Lee, J. 2015. Technology adoption: a conjoint analysis of consumers’ preference on future online banking services, Information Systems 53: 1–15.

Dick, A. 2008. Demand estimation and consumer welfare in the banking industry, Journal of Banking & Finance 32(8): 1661–1676.

Eden, C. 2004. Analyzing cognitive maps to help structure issues or problems, European Journal of Operational Research 159(3): 673–686.

Eden, C.; Ackermann, F. 2001. SODA – the principles, in J. Rosenhead, J. Mingers (Eds.). Rational analysis for a problematic world revisited: problem structuring methods for complexity, uncertainty and conflict. 2nd ed. Chichester: John Wiley & Sons, 21–41.

Ferreira, F. 2016. Are you pleased with your neighborhood? A fuzzy cognitive mapping-based approach for measuring residential neighborhood satisfaction in urban communities, International Journal of Strategic Property Management 20(2): 130–141.

Ferreira, F.; Jalali, M. 2015. Identifying key determinants of housing sales and time-on-the-market (TOM) using fuzzy cognitive mapping, International Journal of Strategic Property Management 19(3): 235–244.

Ferreira, F.; Jalali, M.; Ferreira, J. 2016a. Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables, Journal of Business Research 69(4): 1471–1478.

Ferreira, F.; Jalali, M.; Ferreira, J.; Stankevičienė, J.; Marques, C. 2016b. Understanding the dynamics behind bank branch service quality in Portugal: pursuing a holistic view using fuzzy cognitive mapping, Service Business 10(3): 469–487.

Ferreira, F.; Spahr, R.; Sunderman, M.; Banaitis, A.; Ferreira, J. 2017. A learning-oriented decision-making process for real estate brokerage service evaluation, Service Business 2016 11(3): 453–474 .

Fiol, C.; Huff, A. 1992. Maps for managers: where are we? Where do we go from here?, Journal of Management Studies 29(3): 266–285.

Frank, J.; Badre, D. 2015. How cognitive theory guides neuroscience, Cognition 135: 14–20.

Gavrilova, T.; Carlucci, D.; Schiuma, G. 2013. Art of visual thinking for smart business education, in Proceedings of the 8th international forum on knowledge asset dynamics (IFKAD-2013), 12–14 June 2013, Zagreb, Croatia, 1754–1751.

Gholami, R.; Al-Somali, S.; Clegg, B. 2009. An investigation into the acceptance of online banking in Saudi Arabia, Technovation 29(2): 130–141.

Glykas, M. 2010. Fuzzy cognitive maps: advances in theory, methodologies, tools and applications (studies in fuzziness and soft computing). Berlin: Springer Science & Business Media.

Gogoski, R. 2012. Payment systems in economy: present and future tendencies, Procedia – Social and Behavioral Sciences 44: 436–445.

Hancock, D.; Humphrey, D. 1997. Payment transactions, instruments, and systems: a survey, Journal of Banking & Finance 21(11/12): 1573–1624.

Jalali, M.; Ferreira, F.; Ferreira, J.; Meidutė-Kavaliauskienė, I. 2016. Integrating metacognitive and psychometric decision making approaches for bank customer loyalty measurement, International Journal of Information Technology and Decision Making 15(4): 815–837.

Jetter, A.; Kok, K. 2014. Fuzzy cognitive maps for futures studies: a methodological assessment of concepts and methods, Futures 61: 45–57.

Junadi, S. 2015. A model of factors influencing consumer’s intention to use e-payment system in Indonesia, Procedia – Computer Science 59: 214–220.

Kahn, C.; Roberds, W. 2009. Why pay? An introduction to payments economics, Journal of Financial Intermediation 18(1): 1–23.

Kang, B.; Deng, Y.; Sadiq, R.; Mahadevan, S. 2012. Evidential cognitive maps, Knowledge-Based Systems 35: 77–86.

Khare, A.; Khare, A.; Singh, S. 2010. Role of consumer personality in determining preference for online banking in India, Journal Database Marketing & Customer Strategy Management 17(3/4): 174–187.

Kim, H.; Lee, K. 1998. Fuzzy implications of fuzzy cognitive map with emphasis on fuzzy causal relationship and fuzzy partially causal relationship, Fuzzy Sets and Systems 97(3): 303–313.

Kitchin, R.; Freundschuh, S. 2000. Cognitive mapping past, present and future. London and New York: Routledge.

Klein, J.; Cooper, D. 1982. Cognitive maps of decision makers in a complex game, Journal of the Operational Research Society 33(1): 63–71.

Kok, K. 2009. The potential of fuzzy cognitive maps for semi-quantitative scenario development, with an example from Brazil, Global Environmental Change 19(1): 122–133.

Kokkola, T. 2010. The payment system. Frankfurt: AM Main.

Kosko, B. 1986. Fuzzy cognitive maps, International Journal of Man-Machine Studies 24(1): 65–75.

Lopez, C.; Salmeron, J. 2013. Dynamic risks modelling in ERP maintenance projects with FCM, Information Sciences 256: 25–45.

Manrai, L.; Manrai, A. 2007. A field study of customers’ switching behavior for bank services, Journal of Retailing and Consumer Services 14(3): 208–215.

Masrek, M.; Mohamed, I.; Duad, N.; Omar, N. 2014. Technology trust and mobile banking satisfaction: a case of Malaysian consumers, Procedia – Social and Behavioral Sciences 129: 53–58.

Montazemi, A.; Qahri-Saremi, H. 2015. Factors affecting adoption of online banking: a meta-analytic structural equation modeling study, Information & Management 52(2): 210–226.

Papageorgiou, E.; Roo, J.; Huszka, C.; Colaert, D. 2012. Formalization of treatment guidelines using fuzzy cognitive maps and semantic web tools, Journal of Biomedical Informatics 45(1): 45–60.

Papageorgiou, E.; Salmeron, J. 2013. A review of fuzzy cognitive maps research during the last decade, IEEE Transactions on Fuzzy Systems 21(1): 66–79.

Peng, Z.; Wu, I.; Chen, Z. 2016. Research on steady states of fuzzy cognitive map and its application in three-rivers ecosystem, Sustainability 8: 1–10.

Pinto, S.; Ferreira, F. 2010. Technological dissemination in the Portuguese payments system: an empirical analysis to the region of Santarém, International Journal of Human Capital and Information Technology Professionals 1(4): 55–75.

Ramos, J.; Ferreira, F.; Monteiro-Barata, J. 2011. Banking services in Portugal: a preliminary analysis to the perception and expectations of front office employees, International Journal of Management and Enterprise Development 10(2/3): 188–207.

Reis, J.; Ferreira, F.; Monteiro-Barata, J. 2013. Technological innovation in banking services: an exploratory analysis to perceptions of the front office employee, Problems and Perspectives in Management 11(1): 34–49.

Salmeron, J. 2009. Augmented fuzzy cognitive maps for modelling LMS critical success factors, Knowledge-Based Systems 22(4): 275–278.

Salmeron, J.; Gutierrez, E. 2012. Fuzzy grey cognitive maps in reliability engineering, Applied Soft Computing 12(12): 3818–3824.

Salmeron, J.; Lopez, C. 2012. Forecasting risk impact on ERP maintenance with augmented fuzzy cognitive maps, IEEE Transactions on Software Engineering 38(2): 439–452.

Salmeron, J.; Vidal, R.; Mena, A. 2012. Ranking fuzzy cognitive maps based scenarios with TOPSIS, Expert Systems with Applications 39(3): 2443–2450.

Sohail, M.; Shanmugham, B. 2003. E-banking and customer preferences in Malaysia: an empirical investigation, Information Sciences 150(3/4): 207–217.

Sponarski, C.; Vaske, J.; Bath, A. 2015. The role of cognitions and emotions in human-coyote interactions, Human Dimensions of Wildlife 20: 238–254.

Tolman, E. 1948. Cognitive maps in rats and men, The Psychological Review 55(4): 189–208.

Trentin, E. 2001. Networks with trainable amplitude of activation functions, Neural Networks 14(4/5): 471–493.

Vidal, R.; Salmeron, J.; Mena, A.; Chulvi, V. 2015. Fuzzy cognitive map-based selection of TRIZ trends for eco-innovation of ceramic industry products, Journal of Cleaner Production 107: 202–214.

Wellman, M. 1994. Inference in cognitive maps, Mathematics and Computers in Simulation 34(2): 137–148.

Zavadskas, E.; Turskis, Z. 2011. Multiple criteria decision making (MCDM) methods in economics: an overview, Technological and Economic Development of Economy 17(2): 397–427.

Zavadskas, E.; Turskis, Z.; Kildienė, S. 2014. State of art surveys of overviews on MCDM/MADM methods, Technological and Economic Development of Economy 20(1): 165–179.