Abstract
The meteoric rise of mobile banking technologies in Africa is a result of an increasing penetration of smartphones and internet. Although successful studies have covered a set of themes around mobile banking and recognized the great potential existing in Africa, very few of them have examined the motivations related to its adoption and its daily use by consumers in developing countries. To fill this research gap, this study investigates on the adoption of mobile banking by consumers in sub-Saharan Africa. It is based on several theoretical models such as TAM and DeLone and McLean IS success Model to better assess the acceptance of mobile banking on African consumers. The proposed research model was assessed and supported by a data collection from 479 mobile banking users. The last section of the paper focuses on the formulation of practical implications for future work and studies in mobile banking.
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References
Sharma, S.K.: Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: a SEM-neural network modeling. Inf. Syst. Front. 21, 815–827 (2019). https://doi.org/10.1007/s10796-017-9775-x
Priya, R., Gandhi, A.V., Shaikh, A.: Mobile banking adoption in an emerging economy: an empirical analysis of young Indian consumers. Benchmarking Int. J. 25, 743–762 (2018)
Sparks, D.L., Barnett, S.T.: The informal sector in Sub-Saharan Africa: out of the shadows to foster sustainable employment and equity? Int. Bus. Econ. Res. J. (IBER) 9 (2010)
Ondiege, P.: Mobile banking in Africa: taking the bank to the people. Afr. Econ. Brief 1, 1–16 (2010)
Chironga, M., Cunha, L., De Grandis, H.: Roaring to Life: Growth and Innovation in African Retail Banking. McKinsey & Company, New York (2018)
Demirguc-Kunt, A., Klapper, L., Singer, D., Ansar, S., Hess, J.: The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. The World Bank, Washington, D.C. (2018)
Demirguc-Kunt, A., Klapper, L., Singer, D., Van Oudheusden, P.: The Global Findex Database 2014: Measuring Financial Inclusion Around the World. The World Bank, Washington, D.C. (2015)
Pasti, F.: State of the Industry Report on Mobile Money: 2018 (2019)
Buku, M.W., Meredith, M.W.: Safaricom and M-PESA in Kenya: financial inclusion and financial integrity. Wash. J. Law Technol. Arts 8, 375 (2012)
Donovan, K.: Mobile money for financial inclusion. Inf. Commun. Dev. 61, 61–73 (2012)
Asongu, S., De Moor, L.: Recent advances in finance for inclusive development: a survey (2015)
Leon, N., Schneider, H., Daviaud, E.: Applying a framework for assessing the health system challenges to scaling up mHealth in South Africa. BMC Med. Inform. Decis. Mak. 12, 123 (2012)
Kliner, M., Knight, A., Mamvura, C., Wright, J., Walley, J.: Using no-cost mobile phone reminders to improve attendance for HIV test results: a pilot study in rural Swaziland. Infect. Dis. Poverty 2, 12 (2013)
Asongu, S.A., Kodila-Tedika, O.: Is poverty in the African DNA (Gene)? S. Afr. J. Econ. 85, 533–552 (2017)
Mishra, V., Bisht, S.S.: Mobile banking in a developing economy: a customer-centric model for policy formulation. Telecommun. Policy 37, 503–514 (2013)
Govender, I., Sihlali, W.: A study of mobile banking adoption among university students using an extended TAM. Mediterr. Ean J. Soc. Sci. 5, 451 (2014)
Boonsiritomachai, W., Pitchayadejanant, K.: Determinants affecting mobile banking adoption by generation Y based on the Unified Theory of Acceptance and Use of Technology Model modified by the Technology Acceptance Model concept. Kasetsart J. Soc. Sci. (2017). https://doi.org/10.1016/j.kjss.2017.10.005
Oluwatayo, I.: Banking the unbanked in rural southwest Nigeria: showcasing mobile phones as mobile banks among farming households. J. Financ. Serv. Mark. 18, 65–73 (2013)
Kimenyi, M., Ndung’u, N.: Brookings Institution. Expanding the Financial Services Frontier: Lessons from Mobile Phone Banking in Kenya. Brookings Institution, Washington, D.C. (2009)
Jack, W., Suri, T.: Risk sharing and transactions costs: evidence from Kenya’s mobile money revolution. Am. Econ. Rev. 104, 183–223 (2014)
Rosengard, J.K.: A quantum leap over high hurdles to financial inclusion: the mobile banking revolution in Kenya (2016)
Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: User acceptance of computer technology: a comparison of two theoretical models. Manag. Sci. 35, 982–1003 (1989)
Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46, 186–204 (2000)
Alsamydai, M.J.: Adaptation of the technology acceptance model (TAM) to the use of mobile banking services. Int. Rev. Manag. Bus. Res. 3, 2039 (2014)
Koenig-Lewis, N., Palmer, A., Moll, A.: Predicting young consumers’ take up of mobile banking services. Int. J. Bank Mark. 28, 410–432 (2010)
Aboelmaged, M., Gebba, T.R.: Mobile banking adoption: an examination of technology acceptance model and theory of planned behavior. Int. J. Bus. Res. Dev. 2 (2013)
Gu, J.-C., Lee, S.-C., Suh, Y.-H.: Determinants of behavioral intention to mobile banking. Determ. Behav. Intent. Mob. Bank. 36, 11605–11616 (2009)
Yuan, S., Liu, Y., Yao, R., Liu, J.: An investigation of users’ continuance intention towards mobile banking in China. Inf. Dev. 32, 20–34 (2016)
Munoz-Leiva, F., Climent-Climent, S., Liébana-Cabanillas, F.: Determinants of intention to use the mobile banking apps: an extension of the classic TAM model. Span. J. Mark. ESIC 21, 25–38 (2017)
Crabbe, M., Standing, C., Standing, S., Karjaluoto, H.: An adoption model for mobile banking in Ghana. Int. J. Mob. Commun. 7, 515–543 (2009)
Luarn, P., Lin, H.-H.: Toward an understanding of the behavioral intention to use mobile banking. Comput. Hum. Behav. 21, 873–891 (2005)
Amin, H., Hamid, M.R.A., Lada, S., Anis, Z.: The adoption of mobile banking in Malaysia: the case of Bank Islam Malaysia Berhad (BIMB). Int. J. Bus. Soc. 9, 43 (2008)
Yu, C.-S.: Factors affecting individuals to adopt mobile banking: empirical evidence from the UTAUT model. J. Electron. Commer. Res. 13, 104 (2012)
Anderson, J.C., Gerbing, D.W.: Structural equation modeling in practice: a review and recommended two-step approach. Psychol. Bull. 103, 411 (1988)
Rauniar, R., Rawski, G., Jei, Y., Johnson, B.: Technology acceptance model (TAM) and social media usage: an empirical study on Facebook. J. Enterp. Inf. Manag. 27, 6–30 (2014). https://doi.org/10.1108/JEIM-04-2012-0011
Hsu, M.-W.: An analysis of intention to use in innovative product development model through TAM model. Eurasia J. Math. Sci. Technol. Educ. 12, 487–501 (2016). https://doi.org/10.12973/eurasia.2016.1229a
Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46, 186–204 (2000). https://doi.org/10.1287/mnsc.46.2.186.11926
Schneberger, S., Amoroso, D.L., Durfee, A.: Factors that influence the performance of computer-based assessments: an extension of the technology acceptance model. J. Comput. Inf. Syst. 48, 74–90 (2008). https://doi.org/10.1080/08874417.2008.11646011
Watat, K., Fosso Wamba, S., Kamdjoug, K., Robert, J.: Use and influence of social media on student performance in higher education institutions in Cameroon (2018)
Henseler, J., et al.: Common beliefs and reality about PLS: comments on Rönkkö and Evermann (2013). Organ. Res. Methods 17, 182–209 (2014)
Chin, W.W.: The partial least squares approach to structural equation modeling. Mod. Methods Bus. Res. 295, 295–336 (1998)
Chou, C.-P., Bentler, P.M.: Estimates and tests in structural equation modeling (1995)
Hair Jr., J.F., Sarstedt, M., Hopkins, L., Kuppelwieser, V.G.: Partial least squares structural equation modeling (PLS-SEM) an emerging tool in business research. Eur. Bus. Rev. 26, 106–121 (2014)
Tenenhaus, M.: L’approche PLS. Revue de statistique appliquée 47, 5–40 (1999)
Fornell, C., Larcker, D.F.: Structural equation models with unobservable variables and measurement error: algebra and statistics. J. Mark. Res. 18, 382–388 (1981). https://doi.org/10.1177/002224378101800313
Nunnally, J.C.: Psychometric Theory. McGraw-Hill, New York (1978)
Ab Hamid, M., Sami, W., Sidek, M.M.: Discriminant validity assessment: use of Fornell & Larcker criterion versus HTMT criterion. In: Proceedings of Journal of Physics: Conference Series, p. 012163 (2017)
Fornell, C., Larcker, D.F.: Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18, 39–50 (1981)
Valentini, F., Damásio, B.F.: Average variance extracted and composite reliability: reliability coefficients. Psicologia Teoria e Pesquisa 32 (2016)
Karjaluoto, H., Riquelme, H.E., Rios, R.E.: The moderating effect of gender in the adoption of mobile banking. Int. J. Bank Mark. 28, 328–341 (2010)
Püschel, J., Afonso Mazzon, J., Hernandez, J.M.C.: Mobile banking: proposition of an integrated adoption intention framework. Int. J. Bank Mark. 28, 389–409 (2010)
Akturan, U., Tezcan, N.: Mobile banking adoption of the youth market: perceptions and intentions. Mark. Intell. Plan. 30, 444–459 (2012)
Baabdullah, A.M., Alalwan, A.A., Rana, N.P., Kizgin, H., Patil, P.: Consumer use of mobile banking (M-Banking) in Saudi Arabia: towards an integrated model. Int. J. Inf. Manag. 44, 38–52 (2019)
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Watat, J.K., Madina, M. (2020). Towards an Integrated Theoretical Model for Assessing Mobile Banking Acceptance Among Consumers in Low Income African Economies. In: Themistocleous, M., Papadaki, M. (eds) Information Systems. EMCIS 2019. Lecture Notes in Business Information Processing, vol 381. Springer, Cham. https://doi.org/10.1007/978-3-030-44322-1_13
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