An Empirical Investigation of Mobile Banking Services Adoption in Pakistan
Commenced in January 2007
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Edition: International
Paper Count: 32799
An Empirical Investigation of Mobile Banking Services Adoption in Pakistan

Authors: Aijaz A. Shaikh, Richard Glavee-Geo, Heikki Karjaluoto

Abstract:

Adoption of Information Systems (IS) is receiving increasing attention such that its implications have been closely monitored and studied by the IS management community, industry and professional gatekeepers. Building on previous research regarding the adoption of technology, this paper develops and validates an integrated model of the adoption of mobile banking. The model originates from the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB). This paper intends to offer a preliminary scrutiny of the antecedents of the adoption of mobile banking services in the context of a developing country. Data was collected from Pakistan. The findings showed that an integrated TAM and TPB model greatly explains the adoption intention of mobile banking; and perceived behavioural control and its antecedents play a significant role in predicting adoption Theoretical and managerial implications of findings are presented and discussed.

Keywords: Developing country, mobile banking service adoption, technology acceptance model, theory of planned behaviour.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1109826

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[1] Adesina, A.A. and Ayo, C.K., “An empirical investigation of the level of users’ acceptance of e-banking in Nigeria”, Journal of Internet Banking & Commerce, Vol. 15, No. 1, pp.1–13, 2010.
[2] Ajzen, 1., “From intentions to actions: A theory of planned behavior”, In J. Kuhl and J. Beckmann (Eds.), Action-control: From cognition to behavior (pp. I 1-39). Heidelberg: Springer, 1985.
[3] Ajzen, I., “The theory of planned behavior”, Organizational Behavior and Human Decision Processes, Vol. 50, No. 2, pp. 179–211, 1991.
[4] Barclays, D., Thompson, R., and Higgins, C., “The partial least squares (PLS) approach to causal modeling: personal computer adoption and use as an illustration”, Technology Studies, Vol. 2, No. 2, pp. 285-309, 1995.
[5] Bauer, R.A., “Consumer behaviour as risk taking”, in Hancock, R.F. (Ed.), Proceedings of the 43rd Conference of the American Marketing Association, American Marketing Association, Chicago, IL, pp. 389-98, 1960.
[6] Bosnjak M, Obermeier D, and Tuten T.L., “Predicting and explaining the propensity to bid in online auctions: a comparison of two actiontheoretical models”, Journal of Consumer Behavior, Vol. 5, pp. 102–16, 2006.
[7] Chang, S. J., Van Witteloostuijn, A., and Eden, L., “From the editors: Common method variance in international business research”, Journal of International Business Studies, Vol. 41, No. 2, pp. 178-184, 2010.
[8] Chiu, C. M., Wang, E. T., Fang, Y. H., and Huang, H. Y., “Understanding customers' repeat purchase intentions in B2C ecommerce: the roles of utilitarian value, hedonic value and perceived risk”, Information Systems Journal, Vol. 24, No. 1, pp. 85-114, 2014.
[9] Cruz, P., Barretto Filgueiras Neto, L., Muñoz-Gallego, P., and Laukkanen, T., “Mobile banking rollout in emerging markets: evidence from Brazil”, International Journal of Bank Marketing, Vol. 28, No. 5, pp. 342-371, 2010.
[10] Davis, F.D., “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol. 13, pp. 318–339, 1989.
[11] Dinev, T., Goo, J., Hu, Q., and Nam, K., “User behaviour towards protective information technologies: the role of national cultural differences”, Information Systems Journal, Vol. 19, No. 4, pp. 391-412, 2009.
[12] Falk, R. F. and Miller, N. B., “A primer for soft modeling”, Ohio: The University of Akron Press, 1992.
[13] Fornell, C., and Larcker, D. F., “Evaluating structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, Vol. 18, No. 1, pp. 39−50, 1981.
[14] Goodhue, D. L., and Thompson, R. L., “Task-technology fit and individual-performance”, MIS Quarterly, Vol. 19, pp. 213–236, 1995.
[15] Gu, J. C., Lee, S. C., and Suh, Y. H., “Determinants of behavioral intention to mobile banking”, Expert Systems with Applications, Vol. 36, No. 9, pp. 11605-11616, 2009.
[16] Hair, J. F., Anderson, R. E., Tatham, R. L. and Black, W. C., “Multivariate data analysis (5th ed.)”, London: Prentice Hall International, 1998.
[17] Hair, J. F., Hult, G. T. M., Ringle, C. M. and Sarstedt, M., “A primer on partial least squares structural equation modeling (PLS-SEM)”, Sage Publications, Inc, 2014.
[18] Hair, J. F., Ringle, C. M. and Sarstedt, M., “PLS-SEM: Indeed a silver bullet”, Journal of Marketing Theory and Practice, Vol. 19, pp. 139- 151, 2011.
[19] Hardin, A. M., Looney, C. A., and Fuller, M. A., “Self‐efficacy, learning method appropriation and software skills acquisition in learnercontrolled CSSTS environments”, Information Systems Journal, Vol. 24, No. 1, pp. 3-27. 2014.
[20] Henseler, J., Ringle, C. M., and Sinkovics, R. R., “The use of partial least squares path modeling in international marketing”. In R. R. Sinkovics, & P. N. Ghauri (Eds.), Advances in international marketing (pp. 277−320), 20. Bingley: Emerald, 2009.
[21] Hsu, M. H., Yen, C. H., Chiu, C. M., and Chang, C. M., “A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior”, International Journal of Human-Computer Studies, Vol. 64, No. 9, pp. 889-904, 2006.
[22] Jaruwachirathanakul, B., and Fink, D., “Internet banking adoption strategies for a developing country: the case of Thailand”, Internet research, Vol. 15, No. 3, pp. 295-311, 2005.
[23] Juniper Research (2012). Mobile Banking Handset & Tablet Market Strategies 2013-2017. Available at https://digitalpayments.files. wordpress.com/2013/03/mobile-banking-juniper -research.pdf. retrieved April 15, 2015.
[24] Laukkanen, T., “Internet vs mobile banking: comparing customer value perceptions”, Business Process Management Journal, Vol. 13, No. 6, pp. 788-797, 2007.
[25] Lee, K. C., and Chung, N., “Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean’s model perspective”, Interacting with computers, Vol. 21, No. 5, pp. 385-392, 2009.
[26] Lee, M. C., “Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit”, Electronic Commerce Research and Applications, Vol. 8, No. 3, pp. 130-141, 2009.
[27] Leng, G. S., Lada, S., Muhammad, M. Z., Ibrahim, A. A. H. A., and mboala, T., “An exploration of social networking sites (SNS) adoption in Malaysia using technology acceptance model (TAM), theory of planned behavior (TPB) and intrinsic motivation”, Journal of Internet Banking and Commerce, Vol. 16, No. 2, pp. 1-27, 2011.
[28] Liang, H., Saraf, N., Hu, Q., an d Xue, Y., “Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management”, MIS Quarterly, pp. 59-87, 2007.
[29] Lu, C. T., Huang, S. Y., and Lo, P. Y., “An empirical study of on-line tax filing acceptance model: Integrating TAM and TPB”, African Journal of Business Management, Vol. 4, No. 5, pp. 800-810l, 2010.
[30] Lu, H. P., Hsu, C. L., and Hsu, H. Y., “An empirical study of the effect of perceived risk upon intention to use online applications”, Information Management & Computer Security, Vol. 13, No. 2, pp. 106-120. 2005.
[31] Lu, Y., Zhou, T., & Wang, B., “Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory”, Computers in Human Behavior, Vol. 25, No. 1, pp. 29-39. 2009.
[32] Luarn, P. & Lin, H. H., “Toward an understanding of the behavioral intention to use mobile banking”, Computers in Human Behavior, Vol. 21, pp. 873-891, 2005.
[33] Manstead, A. S., and Eekelen, S. A., “Distinguishing between perceived behavioral control and self‐efficacy in the domain of academic achievement intentions and behaviors”, Journal of Applied Social Psychology, Vol. 28, No. 15, pp. 1375-1392, 1998.
[34] Mathieson, K., Peacock, E. & Chin, W. W. Extending the technology acceptance model: the influence of perceived user resources. DATA BASE for Advances in Information Systems, 32, 86-112. (2001).
[35] Montazemi, A. R. & Qahri-Saremi, H., “Factors affecting adoption of online banking: A meta-analystic structural equation modeling study”, Information and Management, Vol. 52, pp. 210-226, 2015.
[36] Moser, F., “Mobile Banking: A fashionable concept or an institutionalized channel in future retail banking? Analyzing patterns in the practical and academic mobile banking literature”, International Journal of Bank Marketing, Vol. 33, No. 2, pp. 162-177, 2015.
[37] Mun, Y. Y., and Hwang, Y., “Predicting the use of web-based information systems: self -efficacy, enjoyment, learning goal orientation, and the technology acceptance model”, International journal of humancomputer studies, Vol. 59, No. 4, pp. 431-449, 2003.
[38] Nasri, W., and Charfeddine, L., “Factors affecting the adoption of Internet banking in Tunisia: An integration theory of acceptance model and theory of planned behavior”, The Journal of High Technology Management Research, Vol. 23, No. 1, pp. 1-14, 2012.
[39] Nyeko, J. S., Moya, M., Kabaale, E., and Odongo, J., “Factors Influencing the Short Message Service (SMS) Mobile Banking Adoption: A Users’ Perspective in the West Nile Region in Uganda”, European Journal of Business and Management, Vol. 6, No. 5, pp. 34- 45, 2014.
[40] Oliveira, T., Faria, M., Thomas, M. A., and Popovič, A., “Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM”, International Journal of Information Management, Vol. 34, No. 5, pp. 689-703, 2014.
[41] Park, E., and Kim, K. J., “An Integrated Adoption Model of Mobile Cloud Services: Exploration of Key Determinants and Extension of Technology Acceptance Model”, Telematics and Informatics, Vol. 31, No. 3, pp. 376-385, 2014.
[42] Park, K. C., Shin, J. W., and Lee, B. G., “Analysis of Authentication Methods for Smartphone Banking Service using ANP”, KSII Transactions on Internet and Information Systems (TIIS), Vol. 8, No. 6, pp. 2087-2103, 2014a.
[43] Park, N., Rhoads, M., Hou, J., & Lee, K. M., “Understanding the acceptance of teleconferencing systems among employees: An extension of the technology acceptance model”, Computers in Human Behavior, Vol. 39, pp. 118-127, 2014b.
[44] Pavlou, P. A., “Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model”, International journal of electronic commerce, Vol. 7, No. 3, pp. 101- 134, 2003.
[45] PEW Research (2014). Retrieved from http://www.pewglobal.org/search/Cellphone+ownership+in+Pakistan/. Accessed on April 20, 2015.
[46] Preacher, K. J., and Hayes, A. F., “Asymptotic and resampling strategies for assessing and comparing indirect effects in simple and multiple mediator models”, Behavior Research Methods, Vol. 40, No. 3, pp. 879−891, 2008.
[47] Püschel, J., Mazzon, J. A., and Hernandez, J. M. C., “Mobile banking: proposition of an integrated adoption intention framework”, International Journal of Bank Marketing, Vol. 28, No. 5, pp. 389-409. 2010.
[48] Raina, K. and Harsh, A., “Mcommerce security”. Osborne, New York, N.Y, USA, 2002.
[49] Ratten, V., “Technological innovations in the m-commerce industry: A conceptual model of WAP banking intentions”, The Journal of High Technology Management Research, Vol. 18, No. 2, pp. 111-117, 2008.
[50] Reid, M., and Levy, Y., “Integrating trust and computer self-efficacy with TAM: An empirical assessment of customers’ acceptance of banking information systems (BIS) in Jamaica”, Journal of Internet Banking and Commerce, Vol. 12, No. 3, pp. 2008-12, 2008.
[51] Ringle, C. M., Wende, S., and Becker, J-M. (2014). SmartPLS 3. Hamburg: SmartPLS. Retrieved from http://www.smartpls.com
[52] Rucker, D. D., Preacher, K. J., Tormala, Z. L. and Petty, R. E., “Mediation analysis in social psychology: Current practices and new recommendations”, Social and Personality Psychology Compass, Vol. 5/6, pp. 359-371, 2011.
[53] Schepers, J., and Wetzels, M., “A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects”, Information & Management, Vol. 44, No. 1, pp. 90-103, 2007.
[54] Shaikh, A.A. and Karjaluoto, H., “Mobile banking adoption: A literature review”, Telematics and Informatics, Vol. 32, 1, pp. 129–142, 2015.
[55] Sobel, M., “Assymptotic confidence intervals for indirect effects on structural regression models”, In S. Leinhardt (Ed.), Sociological Methodology (pp.290-312). Jossy-Bass, 1982.
[56] Sohail, M. S., and Al-Jabri, I. M., “Attitudes towards mobile banking: are there any differences between users and non-users?”, Behaviour & Information Technology, Vol. 33, No. 4, pp. 335-344, 2014.
[57] State Bank of Pakistan (2014), quarterly branchless banking newsletter, Jan-Mar-2014, http://www.sbp.org.pk/publications /acd / Branchless Banking-Jan-Mar-2014.pdf. Accessed on September 25, 2014.
[58] State Bank of Pakistan (2014), quarterly Payment systems review, Jan- Mar-2014, http://www.sbp.org.pk/psd/pdf/2014/PS-3rd-Qrtly-FY14. pdf. Accessed on April 20, 2015.
[59] Straub, D., Boudreau, M.-C., and Gefen, D., “Validation guidelines for IS positivist research”, Communications of AIS, Vol. 13, pp. 380–427, 2004.
[60] Tan, M., and Teo, T. S., “Factors influencing the adoption of Internet banking”, Journal of the AIS, Vol. 1, No. 5, pp. 1-42, 2000.
[61] Thakur, R., “What keeps mobile banking customers loyal?”, International Journal of Bank Marketing, Vol. 32, No. 7, pp. 628-646, 2014.
[62] UNICEF (2015). Retrieved from http://www.unicef.org/infobycountry /pakistan _ pakistan _ statistics.html#117. Accessed on April 17, 2015.
[63] Venkatesh, V., and Davis, F. D., “A theoretical extension of the technology acceptance model: four longitudinal field studies”, Management science, Vol. 46, No. 2, pp. 186-204, 2000.
[64] Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D., “User acceptance of information technology: Toward a unified view”, MIS Quarterly, pp. 425-478, 2003.
[65] Wallace, L. G., and Sheetz, S. D., “The adoption of software measures: A technology acceptance model (TAM) perspective”, Information & Management, Vol. 51, No. 2, pp. 249-259, 2014.
[66] Wang, Y. S., Lin, H. H., and Luarn, P., “Predicting consumer intention to use mobile service”, Information Systems Journal, Vol. 16, No. 2, pp. 157-179, 2006.
[67] Yousafzai, S. Y., Foxall, G. R., and Pallister, J. G., “Explaining internet banking behavior: Theory of reasoned action, theory of planned behavior, or technology acceptance model?”, Journal of Applied Social Psychology, Vol. 40, No. 5, pp. 1172-1202, 2010.