Determining factors of intention to adopt internet banking services: A study on commercial bank users in Bangladesh
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DOIhttp://dx.doi.org/10.21511/bbs.17(1).2022.11
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Article InfoVolume 17 2022, Issue #1, pp. 125-136
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E-commerce and e-business are necessary components of today’s internet banking due to the developing global economy. Alternatively, in this technological era, the banking sector’s success is associated with creating bank users’ intention to adopt internet banking services. Therefore, the aim of this study is to determine the influencing factors of intention to adopt internet banking services of commercial bank users’ in the Bangladeshi context. A survey questionnaire was formulated based on past works of literature to find out the research objective. The convenience sampling method has been used in this study. For the data collection purpose, 250 bank users were asked request to participate in the research. As a fully completed survey, 180 responses were received where the response rate was 72% and the sample size was n = 180. For correlation analysis and hypotheses testing, SPSS version 26.0 was used. The results of the study show that Perceived Security Risk (PSR), Perceived Usefulness (PU), Perceived Ease of Use (PEU), Social Influence (SI), and Consumer Innovativeness (CI) have a statistical and significant impact on the intention to adopt internet banking services. It is concluded that the bank management committee should utilize PU, PEU, SI, and CI to amplify the level of willingness to adopt and embrace general banking services through internet platforms among bank users in their online banking transactions. For the future research study, this paper outlines several significant implications and offers some directions for the bank management committee of a commercial bank.
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JEL Classification (Paper profile tab)M15, M19
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References61
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Tables2
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Figures2
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- Figure 1. Research model of the study
- Figure 2. Regression analysis results
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- Table 1. Demographic information
- Table 2. Regression analysis
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- Abbasi, M. S., Chandio, F. H., Soomro, A. F., & Shah, F. (2011). Social influence, voluntariness, experience and the internet acceptance: An extension of technology acceptance model within a South-Asian country context. Journal of Enterprise Information Management, 24(1), 30-52.
- Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Algharabat, R. (2018). Examining factors influencing Jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk. Journal of Retailing and Consumer Services, 40, 125-138.
- Aldas-Manzano, J., Lassala-Navare, C., Ruiz-Mae, C., & Sanz-Blas, S. (2009). The role of consumer innovativeness and perceived risk in online banking usage. International Journal of Bank Marketing, 27(1), 53-75.
- Aldas-Manzano, J., Ruiz-Mafe, C., Sanz-Blas, S., & Lassala-Navarre, C. (2011). Internet banking loyalty: evaluating the role of trust, satisfaction, perceived risk and frequency of use. The Service Industries Journal, 31(7), 1165-1190.
- Appiahene, P., Missah, Y. M., & Najim, U. (2019). Evaluation of information technology impact on bank’s performance: The Ghanaian experience. International Journal of Engineering Business Management, 11, 1-10.
- Bashir, I., & Madhavaiah, C. (2014). Determinants of young consumers’ intention to use Internet banking services in India. Vision, 18(3), 153-163.
- Bhatnagar, A., & Ghose, S. (2004). Segmenting consumers based on the benefits and risks of Internet shopping. Journal of Business Research, 57(12), 1352-1360.
- Bhattacharjee, H., Hasan, M., & Ullah, K. T. (2015). Brand valuation of commercial banks in Bangladesh: An application of marketing profitability. Journal of Business Theory and Practice, 3(2), 159-177.
- 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(5), 381-394.
- Chang, L., & Kirk, A. (1999). Assessing the customer behavioral intentions on the Web: A research model. AMCIS 1999 Proceedings, 108.
- Changchit, C., Cutshall, R., Lonkani, R., Pholwan, K., & Pongwiritthon, R. (2019). Determinants of online shopping influencing Thai consumer’s buying choices. Journal of internet Commerce, 18(1), 1-23.
- Chong, A. Y. L., Ooi, K. B., Lin, B., & Tan, B. I. (2010). Online banking adoption: an empirical analysis. International Journal of Bank Marketing, 28(4), 267-287.
- Citrin, A. V., Sprott, D. E., Silverman, S. N., & Stem, D. E. (2000). Adoption of Internet shopping: the role of consumer innovativeness. Industrial Management & Data Systems, 100(7), 294-300.
- Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.
- Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Man-machine Studies, 38(3), 475-487.
- Durbin, J., & Watson, G. S. (1950). Testing for serial correlation in least squares regression I. Biometrika, 37(3-4), 409-428.
- Folake, N. P. (2014). The Impact of Trust Antecedents in Acceptance of Internet Banking in Nigeria. International Journal of Economic and Business Management, 2(2), 19-24.
- Fong, K. K. K., & Wong, S. K. S. (2015). Factors influencing the behavior intention of mobile commerce service users: An exploratory study in Hong Kong. International Journal of Business and Management, 10(7), 39.
- Forsythe, S., Liu, C., Shannon, D., & Gardner, L. C. (2006). Development of a scale to measure the perceived benefits and risks of online shopping. Journal of Interactive Marketing, 20(2), 55-75.
- Gheni, A. Y., Jusoh, Y. Y., Jabar, M. A., & Ali, N. M. (2016). Factors affecting global virtual teams’ performance in software projects. Journal of Theoretical and Applied Information Technology, 92(1), 90-97.
- Hammoud, J., Bizri, R. M., & El Baba, I. (2018). The impact of e-banking service quality on customer satisfaction: Evidence from the Lebanese banking sector. Sage Open, 8(3).
- Hirunyawipada, T., & Paswan, A. K. (2006). Consumer innovativeness and perceived risk: implications for high technology product adoption. Journal of Consumer Marketing, 23(4), 182-198.
- Hu, X., Chen, X., & Davison, R. M. (2019). Social support, source credibility, social influence, and impulsive purchase behavior in social commerce. International Journal of Electronic Commerce, 23(3), 297-327.
- Hussain, A., Abubakar, H. I., & Hashim, N. B. (2015). Evaluating mobile banking application: Usability dimensions and measurements. Proceedings of the 6th International Conference on Information Technology and Multimedia (pp. 136-140).
- Im, S., Mason, C. H., & Houston, M. B. (2007). Does innate consumer innovativeness relate to new products/service adoption behavior? The intervening role of social learning via vicarious innovativeness. Journal of the Academy of Marketing Science, 35, 63-75.
- Jahan, N., Ali, M. J., & Al Asheq, A. (2020). Examining the Key Determinants of Customer Satisfaction Internet Banking Services in Bangladesh. Academy of Strategic Management Journal, 19(1), 1-6.
- Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183-213.
- Karande, K., Merchant, A., & Sivakumar, K. (2011). Erratum to: Relationships Among Time Orientation, Consumer Innovativeness, and Innovative Behavior: The Moderating Role of Product Characteristics. Academy of Marketing Science Review, 1(2), 99-116.
- Kaur, A., & Malik, G. (2019). Examining factors influencing Indian customers’ intentions and adoption of Internet banking: Extending TAM with electronic service quality. Innovative Marketing, 15(2), 42-57.
- Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310-322.
- Koskosas, I. (2011). E-banking security: A communication perspective. Risk Management, 13(1), 81-99.
- Kutner, M. H., Kutner, M. H., Nachtsheim, C., & Neter, J. (2004). Student solutions manual for use with applied linear regression models. New York, USA: McGraw-Hill/Irwin.
- Lee, M. K., & Turban, E. (2001). A trust model for consumer internet shopping. International Journal of Electronic Commerce, 6(1), 75-91.
- Lee, M.-C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8(3), 130-141.
- Liang, C.-C., & Nguyen, N. L. (2018). Marketing strategy of internet-banking service based on perceptions of service quality in Vietnam. Electronic Commerce Research, 18(3), 629-646.
- Liao, Z., & Wong, W.-K. (2008). The determinants of customer interactions with internet-enabled E-banking services. Journal of the Operational Research Society, 59(9), 1201-1210.
- Lin, W. R., Wang, Y. H., & Hung, Y. M. (2020). Analyzing the factors influencing adoption intention of internet banking: Applying DEMATEL-ANP-SEM approach. Plos one, 15(2), e0227852.
- Ling, G. M., Fern, Y. S., Boon, L. K., & Huat, T. S. (2016). Understanding customer satisfaction of internet banking: A case study in Malacca. Procedia Economics and Finance, 37, 80-85.
- Malaquias, R. F., & Hwang, Y. (2016). An empirical study on trust in mobile banking: A developing country perspective. Computers in Human Behavior, 54, 453-461.
- Marakarkandy, B., Yajnik, N., & Dasgupta, C. (2017). Enabling internet banking adoption: An empirical examination with an augmented technology acceptance model (TAM). Journal of Enterprise Information Management, 30(2), 263-294.
- Martins, C., Oliveira, T., & Popovic, 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.
- Mondal, K., & Saha, A. K. (2013). Client satisfaction of internet banking service in Bangladesh: An exploratory study. ASA University Review, 7(1), 131-141.
- Nazaritehrani, A., & Mashali, B. (2020). Development of E-banking channels and market share in developing countries. Financial Innovation, 6(1), 1-19.
- Oruç, Ö. E., & Tatar, Ç. (2017). An investigation of factors that affect internet banking usage based on structural equation modeling. Computers in Human Behavior, 66, 232-235.
- Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: an extension of the technology acceptance model. Internet Research, 14(3), 224-235.
- Rahaman, M. A., Ali, M. J., Mamoon, Z. R., & Asheq, A. A. (2020). Understanding the Entrepreneurial Intention in the Light of Contextual Factors: Gender Analysis. Journal of Asian Finance, Economics and Business, 7(9), 639-647.
- Rahi, S., Ghani, M. A., & Ngah, A. H. (2020). 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 Systems, 33(4), 549-569.
- Rahman, M., Islam, R., Ahmed, S., & Asheq, A. A. (2021). Determinants of service quality and its effect on customer satisfaction and loyalty: an empirical study of private banking sector. The TQM Journal, 33(6), 1163-1182.
- Riffai, M., Grant, K., & Edgar, D. (2012). Big tam in Oman: Exploring the promise of on-line banking, its adoption by customers and the challenges of banking in Oman. International Journal of Information Management, 32(3), 239-250.
- Sanchez-Prieto, J. C., Olmos-Miguelanez, S., & Garcia-Penalvo, F. J. (2017). Learning and pre-service teachers: An assessment of the behavioral intention using an expanded TAM model. Computers in Human Behavior, 72, 644-654.
- Sathiyavany, N., & Shivany, S. (2018). E-banking service qualities, e-customer satisfaction, and e-loyalty: a conceptual model. The International Journal of Social Sciences and Humanities Invention, 5(6), 4808-4819.
- 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.
- Utami, C. W. (2017). Attitude, subjective norm, perceived behavior, entrepreneurship education and self-efficacy toward entrepreneurial intention university student in Indonesia. European Research Studies Journal, 20(2), 475-495.
- Venkatesh, V., Morris, M. G., Davis, F. D., & Davis, G. B. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
- Venkatraman, M. P., & Price, L. L. (1990). Differentiating between cognitive and sensory innovativeness: Concepts, measurement, and implications. Journal of Business Research, 20(4), 293-315.
- Vukovic, M., Pivac, S., & Kundid, D. (2019). Technology acceptance model for the Internet banking acceptance in split. Business Systems Research, 10(2), 124-140.
- Wang, Y.-S., Wang, Y.-M., Lin, H.-H., & Tang, T.-I. (2003). Determinants of user acceptance of internet banking: An empirical study. International Journal of Service Industry Management, 14(5), 501-519.
- Wazid, M., Zeadally, S., & Das, A. K. (2019). Mobile banking: evolution and threats: malware threats and security solutions. IEEE Consumer Electronics Magazine, 8(2), 56-60.
- Wibowo, H. A., Wahid, F., & Nafiudin, N. (2019). The influences of website design on formation of E-Trust, E-Satisfaction and E-Loyalty of Bukalapak.com consumers: Relationship marketing revisited. Proceedings of the 2019 International Conference on Organizational Innovation (ICOI 2019) (pp. 365-369).
- Yoon, H. S., & Steege, L. M. B. (2013). Development of a quantitative model of the impact of customers’ personality and perceptions on internet banking use. Computers in Human Behavior, 29(3), 1133-1141.
- Zhang, F., Sun, S., Liu, C., & Chang, V. (2020). Consumer innovativeness, product innovation and smart toys. Electronic Commerce Research and Applications, 41, 100974.