Do socio-economic factors impede the engagement in online banking transactions? Evidence from Ghana
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DOIhttp://dx.doi.org/10.21511/bbs.15(4).2020.01
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Article InfoVolume 15 2020, Issue #4, pp. 1-14
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Researchers have long pondered on the online banking transaction adoption. Some of these studies focus primarily on the motivating factors that affect customers’ intention to adopt/accept these services (technologies). However, research into the constraining factors, in particular socio-economic factors, barely exist in the literature, especially in the context of sub-Saharan Africa. Against this background, the paper seeks to fill in this gap by: (1) assessing the socio-economic factors impeding the engagement of e-banking transactions among retail bank customers in Ghana, and (2) examining the moderating effect of ‘customer experience of Internet’ on the identified factors that inhibit the engagement in online banking in Ghana. The paper used a quantitative research approach to obtain data from two leading Ghanaian banks. Out of the 450 questionnaires distributed, 393 were valid for analysis. Data were analyzed with the aid of PLS-SEM (partial least squares and structural equation modeling). Findings revealed that perceived knowledge gap and the price of digital devices were directly important to the intention to disembark on e-banking transactions among Ghanaian bank customers. Whilst customer experience (frequent use of the Internet), as a moderator variable, has a significant effect on the interaction between perceived knowledge gap and the intent to disembark on e-banking transactions; and finance charges and the intent to disembark on e-banking transactions. Study implications and directions for future research are discussed in the paper.
Acknowledgment
This work was supported by the Internal Grant Agency of Tomas Bata University under the Projects no. IGA/FaME/2019/008 and IGA/FaME/2020/002. The authors would like to extend their appreciation to Prof. Boris Popesko (Vice-dean for Research and Business Liaison) at the Faculty of Management and Economics for facilitating the financial readiness of this project.
- Keywords
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JEL Classification (Paper profile tab)M01, M02, M21, O33
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References59
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Tables4
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Figures1
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- Figure 1. Research model
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- Table 1. Summary of socio-demographic characteristics of respondents
- Table 2. Cross-loadings and construct reliability and validity
- Table 3. Discriminant validity test – Fornell-Larcker criterion
- Table 4. Hypothetical path analysis
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- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
- Ali, M., & Langendoen, K. (2007). TinyPC: enabling low-cost internet access in developing regions. Proceedings of the 2007 Workshop on Networked Systems for Developing Regions (pp. 1-6).
- Ali, T. (2016). Extending the UTAUT model to understand the customers’ acceptance and use of internet banking in Lebanon: A structural equation modeling approach. Information Technology and People, 29(4), 830-849.
- Amegbe, H., & Osakwe, C. N. (2018). Towards achieving strong customer loyalty in the financial services industry: Ghanaian top banks’ customers as a test case. International Journal of Bank Marketing, 36(5), 988-1007.
- Awh, R. Y., & Waters, D. (1974). A discriminant analysis of economic, demographic, and attitudinal characteristics of bank charge-card holders: A case study. The Journal of Finance, 29(3), 973-980.
- Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.
- Boateng, H., Adam, D. R., Okoe, A. F., & Anning-Dorson, T. (2016). Assessing the determinants of internet banking adoption intentions: A social cognitive theory perspective. Computers in Human Behavior, 65, 468-478.
- Boateng, R., Heeks, R., Molla, A., & Hinson, R. (2008). E-commerce and socio-economic development: conceptualizing the link. Internet Research, 18(5), 562-594.
- Bozionelos, N. (2004). Socio-economic background and computer use: the role of computer anxiety and computer experience in their relationship. International Journal of Human-Computer Studies, 61(5), 725-746.
- Bradlow, E. T., Hoch, S. J., & Hutchinson, J. W. (2002). An assessment of basic computer proficiency among active internet users: Test construction, calibration, antecedents and consequences. Journal of Educational and Behavioral Statistics, 27(3), 237-253.
- Chen, X., Ran, L., Zhang, Y., Yang, J., Yao, H., Zhu, S., & Tan, X. (2019). Moderating role of job satisfaction on turnover intention and burnout among workers in primary care institutions: A cross-sectional study. BMC Public Health, 19(1), 1526.
- Denny, S. (1970). The electronic commerce challenge. The Journal of Internet Banking and Commerce, 3(3).
- Esteve, G., & Machin, A. (2007). Devices to access internet in developing countries. MobEA V-Mobile Web in the Developing World, Colocated with the International World Wide Web Conference.
- Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1-4.
- Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
- Garín-Muñoz, T., López, R., Pérez-Amaral, T., Herguera, I., & Valarezo, A. (2019). Models for individual adoption of eCommerce, eBanking and eGovernment in Spain. Telecommunications Policy, 43(1), 100-111.
- Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
- Hair, J. F., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26(2), 106-121.
- Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442-458.
- Hanafizadeh, P., Keating, B. W., & Khedmatgozar, H. R. (2014). A systematic review of Internet banking adoption. Telematics and Informatics, 31(3), 492-510.
- Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Industrial Management & Data Systems, 116(1), 2-20.
- 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(1), 115-135.
- Jibril, A. B., Kwarteng, M. A., Chovancova, M., & Pilik, M. (2019). The impact of social media on consumer-brand loyalty: A mediating role of online based-brand community. Cogent Business & Management, 6(1), 1673640.
- Jibril, A. B., Kwarteng, M. A., Pilik, M., Botha, E., & Osakwe, C. N. (2020). Towards Understanding the Initial Adoption of Online Retail Stores in a Low Internet Penetration Context: An Exploratory Work in Ghana. Sustainability, 12(3), 854.
- Kakar, A. K. (2020). Investigating factors that promote time banking for sustainable community based socio-economic growth and development. Computers in Human Behavior, 107, 105623.
- Kang, D., & Park, Y. (2014). based measurement of customer satisfaction in mobile service: Sentiment analysis and VIKOR approach. Expert Systems with Applications, 41(4), 1041-1050.
- Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods. Information Systems Journal, 28(1), 227-261.
- Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1-13.
- Mattila, A., & Wirtz, J. (2001). The Moderating Role of Expertise in Consumer Evaluations of Credence Goods. International Quarterly Journal of Marketing, 1, 281-292.
- Miniwatts Marketing Group. (2014). Internet Growth Statistics – the Global Village Online. Global Village Online.
- Nabareseh, S., Osakwe, C. N., Klímek, P., & Chovancová, M. (2014). A comparative study of consumers’ readiness for internet shopping in two African emerging economies: Some preliminary findings. Mediterranean Journal of Social Sciences, 5(23).
- Nasri, W. (2011). Factors influencing the adoption of internet banking in Tunisia. International Journal of Business and Management, 6(8), 143-160.
- Nwaiwu, F., Kwarteng, M. A., Jibril, A. B., Buřita, L., & Pilik, M. (2020). Impact of Security and Trust as Factors that influence the Adoption and Use of Digital Technologies that Generate, Collect and Transmit User Data. ICCWS 2020 15th International Conference on Cyber Warfare and Security (pp. 363-372).
- Nyangosi, R., Arora, J. S., & Singh, S. (2009). The evolution of e-banking: a study of Indian and Kenyan technology awareness. International Journal of Electronic Finance, 3(2), 149-165.
- Oertzen, A.-S., & Odekerken-Schröder, G. (2019). Achieving continued usage in online banking: a post-adoption study. International Journal of Bank Marketing, 37(6), 1394-1418.
- Ofori, K. S., Boateng, H., Okoe, A. F., & Gvozdanovic, I. (2017). Examining customers’ continuance intentions towards internet banking usage. Marketing Intelligence & Planning, 35(6), 756-773.
- Oliveira, T., Faria, M., Thomas, M. A., & Popovič, A. (2014). Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM. International Journal of Information Management, 34(5), 689-703.
- Page, K., & Uncles, M. (2004). Consumer knowledge of the World Wide Web: Conceptualization and measurement. Psychology & Marketing, 21(8), 573-591.
- Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903.
- Rahi, S., Ghani, M. A., & Ngah, A. H. (2019). Factors propelling the adoption of internet banking: the role of E-Customer service, Website design, brand image and customer satisfaction. International Journal of Business Information System, 33(4), 1-21.
- Saleem, A., & Higuchi, K. (2014). Globalization and ICT innovation policy: Absorption capacity in developing countries. 16th International Conference on Advanced Communication Technology, (pp. 409-417). IEEE.
- Sathye, M. (1999). Adoption of Internet banking by Australian consumers: an empirical investigation. International Journal of Bank Marketing, 17(7), 324-334.
- Shankar, V., & Meyer, J. (2009). The internet and international marketing. In M. Kotabe and K. Helsen (Eds.), The SAGE Handbook of International Marketing (Chapter 23).
- Sharma, H. (2011). Bankers’ perspectives on e-banking and its challenges: evidence from North India. IUP Journal of Bank Management, 10(4), 61-70.
- Sharma, R., Singh, G., & Sharma, S. (2020). Modelling internet banking adoption in Fiji: A developing country perspective. International Journal of Information Management, 53, 102116.
- Singh, B., & Malhotra, P. (1970). Adoption of Internet banking: An empirical investigation of Indian Banking Sector. The Journal of Internet Banking and Commerce, 9(2).
- Stein, D. S., Wanstreet, C. E., Calvin, J., Overtoom, C., & Wheaton, J. E. (2005). Bridging the transactional distance gap in online learning environments. The American Journal of Distance Education, 19(2), 105-118.
- Tarhini, A., El-Masri, M., Ali, M., & Serrano, A. (2016). Extending the UTAUT model to understand the customers’ acceptance and use of internet banking in Lebanon: A structural equation modeling approach. Information Technology & People, 29(4), 830-849.
- Thambiah, S., Eze, U. C., Tan, K. S., Nathan, R. J., & Lai, K. P. (2010). Conceptual framework for the adoption of Islamic retail banking services in Malaysia. Journal of Electronic Banking Systems, 2010(1), 1-10.
- Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365.
- Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
- Venkatesh, V., & Zhang, X. (2010). Unified theory of acceptance and use of technology: US vs. China. Journal of Global Information Technology Management, 13(1), 5-27.
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
- Wei, L., & Zhang, M. (2008). The impact of Internet knowledge on college students’ intention to continue to use the Internet. Information Research: An International Electronic Journal, 13(3).
- Wu, L.-Y., Chen, K.-Y., Chen, P.-Y., & Cheng, S.-L. (2014). Perceived value, transaction cost, and repurchase-intention in online shopping: A relational exchange perspective. Journal of Business Research, 67(1), 2768-2776.
- Yee-Loong Chong, A., Ooi, K.-B., Lin, B., & Tan, B.-I. (2010). Online banking adoption: an empirical analysis. International Journal of Bank Marketing, 28(4), 267-287.
- Yiu, C. S., Grant, K., & Edgar, D. (2007). Factors affecting the adoption of Internet Banking in Hong Kong implications for the banking sector. International Journal of Information Management, 27(5), 336-351.
- Yousafzai, S. Y., Pallister, J. G., & Foxall, G. R. (2003). A proposed model of e-trust for electronic banking. Technovation, 23(11), 847-860.
- Yu, C.-S. (2012). Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT model. Journal of Electronic Commerce Research, 13(2), 104.