An Empirical Investigation of Mobile Banking Services Adoption in Pakistan
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.
[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.
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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
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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
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@article{"International Journal of Business, Human and Social Sciences:71295", author = "Aijaz A. Shaikh and Richard Glavee-Geo and Heikki Karjaluoto", title = "An Empirical Investigation of Mobile Banking Services Adoption in Pakistan", 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.", volume = "9", number = "11", pages = "3797-9", }
