Understanding the Factors Influencing Adoption of Digital Banking in Emerging Markets: The Role of Perception and Personality Antecedents

• Authors: Ntswaki Petunia Matlala

Abstracts

EN

The emergence of digital banking has presented the banking industry with benefits and challenges. Although digital banking services provide customers with increased convenience and accessibility around the clock, many still struggle to grasp their ever-changing nature. To address this, a study was conducted to identify the main factors influencing the adoption of digital banking in South Africa. The study used an e-readiness framework that combined the innovation diffusion theory and trust in technology with the technology readiness index to measure consumers’ adoption of digital banking channels. The researcher applied quantitative methodology to answer the research question. The snowball sample required respondents to answer the questionnaire and pass it on to others in the network with bank accounts and mobile phones; 338 responses were accepted. Structural equation modelling was employed to test the proposed hypotheses. This study discovered that the adoption of digital banking services is influenced positively by relative advantage, observability, optimism towards technology, innovativeness and insecurity. Therefore, banks should develop user-friendly platforms with online support to encourage the adoption of digital banking. Future research can use qualitative or mixed method approaches to investigate how customers’ perceptions and personalities influence the adoption of digital in emerging markets.

Keywords

EN

Digital Banking; Customer Behaviour; Innovation; Adoption; Emerging Markets

• Publisher: Uniwersytet Warszawski. Wydawnictwo Naukowe Wydziału Zarządzania
• Journal: Journal of Marketing and Consumer Behaviour in Emerging Markets
• Year: 2023
• Issue: 2(17)
• Pages: 32-45

Dates

published

2023

Contributors

author

Ntswaki Petunia Matlala

• Department of Management and Entrepreneurship, University of Western Cape

• https://orcid.org/000000032447959X

References

• AbuAkel, S.A., & Ibrahim, M. (2023). The Effect of Relative Advantage, Top Management Support and IT Infrastructure on E-Filing Adoption. Journal of Risk and Financial Management, 16(6), 295. https://doi.org/10.3390/jrfm16060295
• Adiyarta, K., Napitupulu, D., Rahim, R., Abdullah, D., & Setiawan, M.I. (2018). Analysis of e-learning implementation readiness based on integrated our model. In Journal of Physics: Conference Series, vol. 1007, p. 012041. IOP Publishing. https://doi.org/10.1088/1742-6596/1007/1/012041
• Aguidissou, O.C., Shambare, R., & Rugimbana, R. (2017). Internet banking adoption in South Africa: The mediating role of consumer readiness. Journal of Economics and Behavioral Studies, 9(5), 6–17. https://doi.org/10.22610/jebs.v9i5(J).1905
• Alkhowaiter, W.A. (2020). Digital payment and banking adoption research in Gulf countries: A systematic literature review. International Journal of Information Management, 53(1), 102102. https://doi.org/10.1016/j.ijinfomgt.2020.102102
• Al-Rahmi, W.M., Yahaya, N., Aldraiweesh, A.A., Alamri, M.M., Aljarboa, N.A., Alturki, U., & Aljeraiwi, A.A. (2019). Integrating technology acceptance model with innovation diffusion theory: An empirical investigation on students’ intention to use E-learning systems. Ieee Access, 7, pp. 26797–26809. https://doi.org/10.1109/ACCESS.2019.2899368
• Anh, V.T. (2023). Mobile banking adoption in Vietnam: an empirical study. Economics, Finance and Management Review, (1), 60–67. https://doi.org/10.36690/2674-5208-2023-1-60
• Awada, A. (2023, June 6). How banks can tap into an $860 billion Metaverse market. EY. https://www.ey.com/en_gl/financial-services-emeia/the-metaverse-revolution-how-banks-can-tap-into-a-860-billion-dollar-market
• Bakr, A., Salahuddin, E., Chowdhury, I.A., Mahtab, H., & Khabir, L. (2017). Factors influencing the mobile banking adoption in the banking sector of Bangladesh. Australasian Journal of Business, Social Science and Information Technology, 3(3), 142–154.
• Bankole, F.O., Bankole, O.O., & Brown, I. (2017). Influences on cell phone banking adoption in South Africa: An updated perspective. Journal of Internet Banking and Commerce, 22(3), 1–16.
• Bentler, P.M., and Chih-Ping Chou. (1987). Practical Issues in Structural Modeling. Sociological Methods & Research 16: pp. 78–117. https://doi.org/10.1177/0049124187016001004
• Boomsma, A. (2000). Reporting analyses of covariance structures. Structural equation modeling, 7(3), 461–483. https://doi.org/10.1207/S15328007SEM0703_6
• Brown, I., Cajee, Z., Davies, D., & Stroebel, S. (2003). Cell phone banking: predictors of adoption in South Africa – an exploratory study. International Journal of Information Management, 23(2003), 381–394. https://doi.org/10.1016/S0268-4012(03)00065-3
• Chan, C.Y.T., & Petrikat, D. (2022). Self-Service Technology: Benefits and Challenges. Journal of Computer Science and Technology Studies, 4(2), pp. 118–127. https://doi.org/10.32996/jcsts.2022.4.2.14
• Cooper, D.R., & Schindler, P.S. (2018). Business research methods (13th ed.). McGraw-Hill/Irwin.
• Decyk, K. (2023). Innovative Activity of the Service Sector of the EU Member States. Journal of the Knowledge Economy, 1–26. https://doi.org/10.1007/s13132-023-01143-w
• De Jager, J.W., Wulandari, N., & Pham, Q.T. (2023). Digital Channel Distribution in Banking Services: A Customer Perspective from Three Developing Countries. Presented at: SIBR-Thammasat: Conference on Interdisciplinary Business and Economics Research, Bangkok, 1–20.
• Fariz, F. (2022). Strategies to increase user satisfaction in online shopping applications. Journal of Applied Management (JAM), 20(2), 438–444. https://doi.org/10.21776/ub.jam.2022.020.02.19
• Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18 (1), 39–50. https://doi.org/10.1177/002224378101800104
• Ghani, E.K., Ali, M.M., Musa, M.N.R., & Omonov, A.A. (2022). The Effect of Perceived Usefulness, Reliability, and COVID-19 Pandemic on Digital Banking Effectiveness: Analysis Using Technology Acceptance Model. Sustainability, 14(18), 11248. https://doi.org/10.3390/su141811248
• Gomber, P., Kauffman, R.J., Parker, C., & Weber, B.W. (2018). On the Fintech Revolution: Interpreting the Forces of Innovation, Disruption, and Transformation in Financial Services. Journal of Management Information Systems, 35, 220–265. https://doi.org/10.1080/07421222.2018.1440766
• Hanif, M.S., Yunfei, S., Hanif, M.I., & Afzal, F. (2022). Mobile shopping continuance intentions of expats in China: influence of structural assurance and the stay duration. International Journal of Mobile Communications, 20(5), 541–567. https://doi.org/10.1504/IJMC.2022.125421
• Hair, J.F., Black, W.C., Babin, B.J., & Andersen, R.E. (2014). Multivariate data analysis, Pearson, Essex.
• Hakimi, T.I., Jaafar, J.A., and Aziz, N.A.A. (2023). What factors influence the usage of mobile banking among digital natives? Journal of Financial Services Marketing, 1–16. https://doi.org/10.1057/s41264-023-00212-0
• Henseler, J., Ringle, C.M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling, Journal of the Academy of Marketing Science 43, 115–135. https://doi.org/10.1007/s11747-014-0403-8
• Hensen, J., & Kötting, B. (2022). From open banking to embedded finance: The essential factors for a successful digital transformation. Journal of Digital Banking, 6(4), 308–318.
• Ho, J.C., Wu, C.G., Lee, C.S., & Pham, T.T.T. (2020). Factors affecting the behavioural intention to adopt mobile banking: An international comparison. Technology in Society, 63, p.101360. https://doi.org/10.1016/j.techsoc.2020.101360
• Hu, L.T., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1–55.
• Humbani, M., & Wiese, M. (2018). A cashless society for all: Determining consumers’ readiness to adopt mobile payment services. Journal of African Business, 19(3), 409–429. https://doi.org/10.1080/15228916.2017.1396792
• Jarrar, Y., Awobamise, A., & Sellos, P. (2020). Technological Readiness Index (TRI) and the intention to use smartphone apps for tourism: A focus on in Dubai mobile tourism app. International Journal of Data and Network Science, 4(3), 297–304. https://doi.org/10.5267/j.ijdns.2020.6.003
• Jeník, I., Flaming, M., & Salman, A. (2020). Inclusive digital banking: Emerging markets case studies. Consultative Group to Assist the Poor Working Paper. Washington, DC.
• Jin, C.H. (2016). The effects of mental simulations, innovativeness on intention to adopt brand application. Computers in Human Behavior, 54, 682–690. https://doi.org/10.1016/j.chb.2015.08.013
• Kitsios, F., Giatsidis, I., & Kamariotou, M. (2021). Digital transformation and strategy in the banking sector: Evaluating the acceptance rate of e-services. Journal of Open Innovation: Technology, Market, and Complexity, 7(3), 204. https://doi.org/10.3390/joitmc7030204
• Kiliari, G., & Koesrindartoto, D.P. (2019). Proceeding Book of the 4th ICMEM 2019 and the 11th IICIES.
• Kumar, A., Dhingra, S., Batra, V., and Purohit, H. (2020). A framework of mobile banking adoption in India. Journal of Open Innovation: Technology, Market, and Complexity, 6(2), 40. https://doi.org/10.3390/joitmc6020040
• Kuo, K.M., Liu, C.F., & Ma, C.C., (2013). An investigation of the effect of nurses’ technology readiness on the acceptance of mobile electronic medical record systems. BMC medical informatics and decision making, 13, 1–14. https://doi.org/10.1186/1472-6947-13-88
• Kouladoum, J.C., Wirajing, M.A.K., & Nchofoung, T.N. (2022). Digital technologies and financial inclusion in Sub-Saharan Africa. Telecommunications Policy, 102387. https://doi.org/10.1016/j.telpol.2022.102387
• Lai, Y.L., & Lee, J. (2020). Integration of Technology Readiness Index (TRI) Into the Technology Acceptance Model (TAM) for Explaining Behavior in Adoption of BIM. Asian Education Studies, 5(2), 10. https://doi.org/10.20849/aes.v5i2.816
• Lee, J.C., & Chen, X. (2022). Exploring users &; adoption intentions in the evolution of artificial. Intelligence mobile banking applications: the intelligent and anthropomorphic perspectives. International Journal of Bank Marketing, 40(4), 631–658.
• Louw, C., & Nieuwenhuizen, C. (2019). Online, community-driven E-commerce platforms and the rise of lifestyle commerce: A conceptual study. In Seventh annual winter global business conference, 12(4), 1–8.
• Louw, C., & Nieuwenhuizen, C. (2020). Digitalisation strategies in a South African banking context: A consumer services analysis. South African Journal of Information Management, 22(1), 1–8. https://doi.org/10.4102/sajim.v22i1.1153
• Magotra, I., Sharma, J., & Sharma, S.K. (2019). Adoption of self-service technologies among banking customers: a revisit. International Journal of Applied Management and Technology, 18(1), 67–72. https://doi.org/10.5590/IJAMT.2019.18.1.05
• Martínez-Navalón, J.G., Fernández-Fernández, M., & Alberto, F.P. (2023). Does privacy and ease of use influence user trust in digital banking applications in Spain and Portugal? International Entrepreneurship and Management Journal, 19(2), 781–803. https://doi.org/10.1007/s11365-023-00839-4
• Matlala, N.P. (2022, June 28). Digital readiness and the adoption of self-service banking technologies in South Africa. University of the Western Cape. https://etd.uwc.ac.za/handle/11394/9842
• McKnight, D.H., Carter, M., Thatcher, J.B., & Clay, P.F. (2011). Trust in a specific technology: an investigation of its components and measures. Transactions on Management Information Systems, Vol. 2, No. 2, pp. 1–15. https://doi.org/10.1145/1985347.1985353
• Melnychenko, S., Volosovych, S., & Baraniuk, Y. (2020). Dominant ideas of financial technologies in digital banking. Baltic Journal of Economic Studies, 6(1), 92–99. https://doi.org/10.30525/2256-0742/2020-6-1-92-99
• Merhi, M., Hone, K., Tarhini, A., & Ameen, N. (2020). An empirical examination of the moderating role of age and gender in consumer mobile banking use: a cross-national, quantitative study. Journal of Enterprise Information Management. https://doi.org/10.1108/JEIM-03-2020-0092
• Moore, G.C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, 2(3), 192–222. https://doi.org/10.1287/isre.2.3.192
• Mtwecu, K. (2019, June 30). Consumer Adoption of ATM Banking (master’s Dissertation). University of Johannesburg. https://hdl.handle.net/10210/452103
• Mombeuil, C., & Uhde, H. (2021). Relative convenience, relative advantage, perceived security, perceived privacy, and continuous use intention of China’s WeChat Pay: A mixed-method two-phase design study. Journal of Retailing and Consumer Services, 59, 102384. https://doi.org/10.1016/j.jretconser.2020.102384
• Musyaffi, A.M., Sari, D.A.P., Amal, M.I., Deswanto, V., Nuryati, T., & Rismawati. (2021). Attitude Toward of Public Hospital Information System: The Role of Technology Readiness. Quality – Access to Success, 22(185), 136–141. https://doi.org/10.47750/QAS/22.185.18
• Nassr, R.M., Aldossary, A.A., & Nasir, H. (2021). Students’ Intention to Use Emotion-Aware Virtual Learning Environment: Does a Lecturer’s Interaction Make a Difference? Malaysian Journal of Learning and Instruction, 18(1), 183–218. https://doi.org/10.32890/mjli2021.18.1.8
• Omoge, A.P., Gala, P., & Horky, A. (2022). Disruptive technology and AI in the banking industry of an emerging market. International Journal of Bank Marketing, 40(6), 1217–1247. https://doi.org/10.1108/IJBM-09-2021-0403
• Omotayo, F.O., & Adekunle, O.A. (2021). Adoption and use of electronic voting system as an option towards credible elections in Nigeria. International Journal of Development Issues, 20(1), 38–61. https://doi.org/10.1108/IJDI-03-2020-0035
• OECD. (2021, June 30). Artificial Intelligence, Machine Learning and Big Data in Finance: Opportunities, Challenges, and Implications for Policy Makers. OECD. https://www.oecd.org/finance/artificial-intelligence- machine-learningbig-data-in-finance.htm
• Parasuraman, A. (2000). Technology Readiness Index (TRI) is a multiple-item scale to measure readiness to embrace new technologies. Journal of service research, 2(4), 307–320. https://doi.org/10.1177/109467050024001
• Ragnvald, S. (2001). Self-Service Banking: Value Creation Models and Information Exchange. Informing Science: The International Journal of an Emerging Trans discipline, 4(4), 139–148. https://doi.org/10.28945/568
• Rogers, E.M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.
• Sardana, V., & Singhania, S. (2018). Digital technology in the realm of banking: A review of the literature. International Journal of Research in Finance and Management, 1(2), 28–32. https://doi.org/10.33545/26175754.2018.v1.i2a.12
• Sarkar, S., Chauhan, S., & Khare, A. (2020). A meta-analysis of antecedents and consequences of trust in mobile commerce. International Journal of Information Management, 50, 286–301. https://doi.org/10.1016/j.ijinfomgt.2019.08.008
• Saunders, M.N.K., Lewis, P., & Thornhill, A. (2019). Research Methods for Business Students. 8th Edition, Pearson, New York.
• Saxena, N., Gera, N., & Taneja, M. (2022). An empirical study on facilitators and inhibitors of adoption of mobile banking in India. Electronic Commerce Research, 1–32. https://doi.org/10.1007/s10660-022-09556-6
• Shahid, S., Jamid, U.l., Islam, J., Malik S., & Hasan U. (2022). Examining consumer experience in using m-banking apps: A study of its antecedents and outcomes. Journal of Retailing and Consumer Services, 65(102870). https://doi.org/10.1016/j.jretconser.2021.102870
• Shambare, R. (2012). Predicting consumer preference for Remote Banking Services in South Africa and Zimbabwe: The role of consumer perspectives versus personality variables (D.Tech Thesis). Tshwane University of Technology. SA.
• Shambare, R. (2011) Cell phone banking adoption in South Africa. Business and economic research, 1(1). https://doi.org/10.5296/ber.v1i1.1144
• Shi, X., Liu, J., & Sirkeci, I. (2016). Psychological Determinants of Brand Loyalty: The case of Apple and Samsung. 1–19.
• Shrestha, N. (2021). Factor Analysis as a Tool for Survey Analysis. American Journal of Applied Mathematics and Statistics, 9(1), 4–11. https://doi.org/10.12691/ajams-9-1-2
• Shim, H.S., Han, S.L., & Ha, J. (2020). The effects of consumer readiness on the adoption of self-service technology: Moderating effects of consumer traits and situational factors. Sustainability, 13(1), 95. https://doi.org/10.3390/su13010095
• Shua, T.M., Siangb, P.Y., & Chuanc, T.C. (2018). Confirmatory Factor Analysis on Factors Influencing M-commerce Adoption among Generation Y in East Malaysia. Proceedings of the International Social Science Conference Challenge on Law and Business, Melaka, Malaysia.
• Sibanda, W., Ndiweni, E., Boulkeroua, M., Echchabi, A., and Ndlovu, T. (2020). Digital technology disruption on bank business models. International Journal of Business Performance Management, 21(1–2), 184–213. https://doi.org/10.1504/IJBPM.2020.106121
• Simarmata, M.T., and Hia, I.J. (2020). The role of personal innovativeness on behavioral intention of Information Technology. Journal of Economics and Business, 1(2), 18–29. https://doi.org/10.36655/jeb.v1i2.169
• Sohaib, O., Hussain, W., Asif, M., Ahmad, M., & Mazzara, M. (2019). A PLS-SEM neural network approach for understanding cryptocurrency adoption. Ieee Access, 8, 13138–13150. https://doi.org/10.1109/ACCESS.2019.2960083
• Taber, K.S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in science education, 48(1), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
• Thusi, P., & Maduku, D.K. (2020). South African millennials’ acceptance and use of retail mobile banking apps: An integrated perspective. Computers in Human Behavior, 111, p. 106405. https://doi.org/10.1016/j.chb.2020.106405
• van der Vaart, L. (2021).The performance measurement conundrum: Construct validity of the individual work performance questionnaire in South Africa. South African Journal of Economic and Management Sciences, 24(1), 3581. https://doi.org/10.4102/sajems.v24i1.3581
• Wiese, M., & Humbani, M. (2020). Exploring technology readiness for mobile payment app users. The International Review of Retail, Distribution and Consumer Research, 30(2), 23–142. https://doi.org/10.1080/09593969.2019.1626260
• Windasari, N.A., Kusumawati, N., Larasati, N., & Amelia, R.P. (2022). Digital-only banking experience: Insights from gen Y and gen Z. Journal of Innovation & Knowledge, 7(2), p. 100170. https://doi.org/10.1016/j.jik.2022.100170
• Wingreen, S.C., Mazey, N.C., Baglione, S.L., & Storholm, G.R. (2019). Transfer of electronic commerce trust between physical and virtual environments: experimental effects of structural assurance and situational normality. Electronic Commerce Research, 19, 339–371. https://doi.org/10.1007/s10660-018-9305-z

Identifiers

DOI

10.7172/2449-6634.jmcbem.2023.2.3

Biblioteka Nauki

32315242