Critical Success Factors of the Digital Payment Infrastructure for Developing Economies

  • Naveen Kumar SinghEmail author
  • G. P. Sahu
  • Nripendra P. RanaEmail author
  • Pushp P. PatilEmail author
  • Babita GuptaEmail author
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 533)


This paper studies the Critical Success Factors’ (CSFs) for the adoption of Digital Payment System in India. There are few studies about the literature on CSFs for the adoption of the digital payment system in the Indian context. This study is an attempt to cover this gap. In this study, we reviewed the theories for adoption model at the individual level used in Information System (IS) and discussed four technology model including “Technology Acceptance Model” (TAM). Ten factors have been identified with extensive literature review and review of selected models namely; Perceived Ease of Use, Perceived functional benefits, Awareness, Availability of Resources, Government as a policy maker, Performance Expectancy, Social Influence, Price Value, Experience & Habit, and Risk-taking ability. An expert from academic industry has been taken as a reviewer or consultant of the selected variables. The CSFs may ensure that they are the predictors and the important factors for adoption of digital payments system in India. The study mainly uses the deductive approach to consider the primary and secondary sources of data. The analyses of these models take into account through Interpretive Structural Modeling (ISM) methodology and develop a model for effective adoption of Digital Payment System in India. The paper also makes future recommendations for further research studies.


Technology Acceptance Model (TAM) Interpretive Structural Modeling (ISM) Digital Payment System Critical Success Factor (CSF) 


  1. 1.
    Achor, P.N., Robert, A.: Shifting policy paradigm from cash-based economy to cashless economy: The Nigeria experience. Afro-Asian J. Soc. Sci. 4(4) (2013)Google Scholar
  2. 2.
    Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50(2), 179–211 (1991)CrossRefGoogle Scholar
  3. 3.
    Ajzen, I.: Perceived behavioural control, self-efficacy, locus of control, and the theory of planned behaviour. J. Appl. Soc. Psychol. 32(4), 665–683 (2002)CrossRefGoogle Scholar
  4. 4.
    Ajzen, I., Fishbein, M.: Understanding attitudes and predicting social behavior (1980)Google Scholar
  5. 5.
    AlShihi, H.: E-government development and adoption dilemma: Oman case study. In: 6th International We-B (Working for e-Business) Conference (2005)Google Scholar
  6. 6.
    Baker, J.: The technology–organization–environment framework. In: Information Systems Theory, pp. 231–245. Springer, New York (2012)Google Scholar
  7. 7.
    Bandura, A.: Self-efficacy: toward a unifying theory of behavioural change. Psychol. Rev. 84, 191–215 (1977)CrossRefGoogle Scholar
  8. 8.
    Bihari, S.C.: Green banking-towards socially responsible banking in India. Int. J. Bus. Insights Transform. 4(1) (2010)Google Scholar
  9. 9.
    Böhle, K., Krueger, M., Herrmann, C., Carat, G., Maghiros, I.: Electronic payment system: strategic and technical issues (2000)Google Scholar
  10. 10.
    Bolanos, R., Fontela, E., Nenclares, A., Pastor, P.: Using interpretive structural modelling in strategic decision-making groups. Manag. Decis. 43(6), 877–895 (2005)CrossRefGoogle Scholar
  11. 11.
    Coffey, T., Saidha, P.: Non-repudiation with mandatory proof of receipt. ACM SIGCOMM Comput. Commun. Rev. 26(1), 6–17 (1996)CrossRefGoogle Scholar
  12. 12.
    Laurie Hughes, D., Dwivedi, Y.K., Rana, N.P., Simintiras, A.C.: Information systems project failure – analysis of causal links using interpretive structural modelling. Prod. Plan. Control. 27(16), 1313–1333 (2016)CrossRefGoogle Scholar
  13. 13.
    Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13, 319–340 (1989)CrossRefGoogle Scholar
  14. 14.
    Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: User acceptance of computer technology: a comparison of two theoretical models. Manage. Sci. 35(8), 982–1003 (1989)CrossRefGoogle Scholar
  15. 15.
    Dwivedi, Y.K., Wade, M.R., Schneberger, S.L.: Information Systems Theory: Explaining and Predicting Our Digital Society. Springer Science & Business Media, vol. 1 (2011)Google Scholar
  16. 16.
    Fishbein, M., Ajzen, I.: Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research Reading. Addison-Wesley, MA (1975)Google Scholar
  17. 17.
    Garrett, S., Skevington, P.: An introduction to e-commerce. BT Technol. J. 17(3), 11–16 (1999)CrossRefGoogle Scholar
  18. 18.
    Guriting, P., Oly Ndubisi, N.: Borneo online banking: evaluating customer perceptions and behavioural intention. Manag. Res. News 29(1/2), 6–15 (2006)CrossRefGoogle Scholar
  19. 19.
    Johnson, O.: e-Payment Options in Electronic Marketplaces, MSc Information Systems Dissertation, Leeds University (1999)Google Scholar
  20. 20.
    Johnson, O.E.: Payment Systems. Monetary Policy and the Role of the Central Bank, International monetary fund (1998)Google Scholar
  21. 21.
    Karahanna, E., Straub, D.W.: The psychological origins of perceived usefulness and ease-of-use. Inf. Manag. 35(4), 237–250 (1999)CrossRefGoogle Scholar
  22. 22.
    Kokkola, T.: The payment system. Payments, Securities and Derivatives, and the role of the eurosystem. Frankfurt am Main: ecB (2010)Google Scholar
  23. 23.
    Lau, S.M.: Strategies to motivate brokers adopting on-line trading in Hong Kong financial market. Rev. Pac. Basin Financ. Mark. Policies 5(4), 471–489 (2002)CrossRefGoogle Scholar
  24. 24.
    Mathieson, K.: Predicting user intentions: comparing the technology acceptance model with the theory of planned behaviour. Inf. Syst. Res. 2(3), 173–191 (1991)CrossRefGoogle Scholar
  25. 25.
    Moon, J.W., Kim, Y.G.: Extending the TAM for a World-Wide-Web context. Inf. Manag. 38(4), 217–230 (2001)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Norzaidi, M.D., Salwani, I.M.: Evaluating technology resistance and technology satisfaction on students’ performance. Campus Wide Inf. Syst. 26(4), 298–312 (2009)CrossRefGoogle Scholar
  27. 27.
    Ramayah, T., Jantan, M., Mohd Noor, M.N., Razak, R.C., Koay, P.L.: Receptiveness of internet banking by Malaysian consumers: the case of Penang. Asian Acad. Manag. J. 8(2), 1–29 (2003)Google Scholar
  28. 28.
    Rockart, J.F.: Chief executives define their own data needs. Harvard Bus. Rev. 57(2), 81–93 (1978)Google Scholar
  29. 29.
    Rogers, E.M.: Diffusion of Innovation. The Free Press of Glencoe, New York (1962)Google Scholar
  30. 30.
    Rogers, E.M.: Diffusion of innovations (1995)Google Scholar
  31. 31.
    Sahu, G.P., Singh, M.: Green information system adoption and sustainability: a case study of select Indian Banks. In: Conference on e-Business, e-Services and e-Society, pp. 292–304. Springer International Publishing (2016)Google Scholar
  32. 32.
    Sichel, D.E.: The productivity Slowdown: is a growing un-measurable sector the culprit? Rev. Econ. Stat. 79(3), 367–370 (1997)CrossRefGoogle Scholar
  33. 33.
    Taylor, S., Todd, P.: Assessing IT usage: the role of prior experience. MIS Q. 19(4), 561–570 (1995)CrossRefGoogle Scholar
  34. 34.
    Taylor, S., Todd, P.: Understanding information technology usage: a test of competing models. Inf. Syst. Res. 6(2), 144–176 (1995)CrossRefGoogle Scholar
  35. 35.
    Teo, T.S., Lim, V.K., Lai, R.Y.: Intrinsic and extrinsic motivation in Internet usage. Omega 27(1), 25–37 (1999)CrossRefGoogle Scholar
  36. 36.
    Titah, R., Barki, H.: E-government adoption and acceptance: a literature review. Int. J. Electron. Gov. Res. (IJEGR) 2(3), 23–57 (2006)CrossRefGoogle Scholar
  37. 37.
    Triandis, H.C.: Interpersonal behaviour. Brooks/Cole, Monterey (1977)Google Scholar
  38. 38.
    Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage. Sci. 46(2), 186–204 (2000)CrossRefGoogle Scholar
  39. 39.
    Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: Toward a unified view. MIS Q. 27, 425–478 (2003)CrossRefGoogle Scholar
  40. 40.
    Venkatesh, V., Morris, M.G., Sykes, T.A., Ackerman, P.L.: Individual reactions to new technologies in the workplace: the role of gender as a psychological constructs. J. Appl. Soc. Psychol. 34(3), 445–467 (2004)CrossRefGoogle Scholar
  41. 41.
    Venkatesh, V., Thong, J.Y., Xu, X.: Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology (2012)CrossRefGoogle Scholar
  42. 42.
    World Bank: Financial systems and development. World Bank Policy and Research Series No. 15., Washington, DC (1990)Google Scholar
  43. 43.
    Yu, H.C., His, K.H., Kou, P.J.: Electronic Payment Systems: an analysis and comparison of types. Technol. Soc. 24, 331–334 (2002)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.Motilal Nehru National Institute of Technology AllahabadAllahabadIndia
  2. 2.Emerging Markets Research Centre (EMaRC), School of ManagementSwansea University Bay CampusSwanseaUK
  3. 3.College of BusinessCalifornia State UniversityMonterey BayUSA

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