Acceptance of mobile banking framework in Pakistan

https://doi.org/10.1016/j.tele.2015.09.005Get rights and content

Highlights

  • Tasks & technology characteristics are significant to facilitate task technology fit.

  • Initial trust is facilitated by structural assurance & familiarity with bank.

  • Intention is affected by task technology fit, initial trust & facilitating condition.

Abstract

Purpose

The purpose of this study is to analyze the untapped (behavioral, environmental and technological) dimensions of mobile banking acceptance by following a more comprehensive approach to address mobile banking intention adoption.

Design/methodology/approach

CFA and SEM analyses have been used to analyze the data collected from university students. The study strives to examine the role of technological and environmental variables in predicting behavioral intention of individuals to adopt mobile banking by integrating three pre-established frameworks of UTAUT, TTF and ITM.

Findings

The empirical findings established the significant contribution of task (TAC) and technology characteristics (TEC) in facilitating task technology fit (TTF). Initial trust is also found to be facilitated by structural assurance (SA) and familiarity with bank (FB). The statistical results also support the significant association of task technology fit (TTF), initial trust (IT) and facilitating condition (FC) with intention to adopt m-banking.

Originality/value

The present study provides an all-inclusive approach to understand the acceptance of mobile banking by incorporating three established theories of technology acceptance. The existing literature on mobile banking emphasizes greatly on the perception aspects of technology and hardly studies the impact of the task technology fit. The strength of present research lies in combining behavioral, technological and environmental aspects of mobile banking. This is evidenced by high explanatory power of our research model that depicted 60.1% of the behavioral intention to adopt m-banking compared to 31% by Kim et al. (2009) and 53% by Oliveira et al. (2014).

Introduction

Innovations and technological changes have come with great benefits to modern commerce. In order to get financial stability in firm’s maneuvers and greater competitive advantages, businesses from last few decades have diverted their focus on making information technology an integral part of their operations (Oliveira et al., 2014). Acknowledgment of this facet is followed by literatures’ supreme attention on IS related research.1 The analysis of some recent IS research also proposes to center their attention on coupling various theoretical models in predicting IT acceptance suggesting that a broad view in the context is needed (Williams et al., 2009, Oliveira et al., 2014). In this regard, a more recent interest of IS related research are diverted to the field of mobile banking (m-banking) emerging as the latest development of IS domain (Shih et al., 2010, Gu et al., 2009, Zhou et al., 2010, Al-Jabri and Sohail, 2012, Yu, 2012).

In today’s commerce, mobile banking has gained significant importance and the growth of the field is accelerating (Lin, 2011). M-banking is simply the usage of cell phone stations such as mobile and personal digital assistants (PDAs) to contact banking system through wireless application protocol (WAP). With the help of mobile banking, bank customers can avail banking facilities such as information inquiry, account managing, bill payment and money transfers etc. (Luarn and Lin, 2005). It also allows the users to use any portable computing device or smart phones to do banking task for example monitoring, find ATM locations and fund transfer.

Speculating growth in the acceptance of m-banking by an apparent segment of customers, financial institutions are including m-banking as part of their strategic directive (Nysveen et al., 2005). Complying with this recent fondness, the present study reaches out to provide the additional insights into the literature of mobile banking by providing an inclusive framework that seeks to explore (a) the degree to which mobile banking technology fits the tasks, (b) the domains of personal trust in mobile banking solutions and (c) how critical is the role of perceptions are in shaping the intentions of m-banking customer. The awareness resulting after such wider approach will assist banks not only in targeting bottlenecks that hinder user acceptance but also aids in finding the decision factors to perk up their services.

The branchless banking technology which starts from the Internet has now emerged as vastly innovative and updated mobile banking. M-banking has enormous potential as it chases the success of internet banking (Brown et al., 2003). The penetration of cellular banking in the advanced countries is elevated for obvious reasons; however, it is also gaining acceptance in the developing economies. Pakistan is a relevant setting based on its emerging growth of m-commerce. The results can easily be generalized to similar emerging economies. The emerging countries with greater segment of less educated and poorer individuals have higher potential for the widespread acceptance of m-banking based on the underlying concept that poor people likely to use m-banking more than the rich people (Ivatury and Mas, 2008). In such countries where there exists a less deployed infrastructure in the form of fewer banking branches, ATMs generally existed to minimize the need of bank branches and low broadband penetration. For majority of customers in these countries, the m-banking agents in principle could provide greater convenience advantage over its alternatives (travel and queuing at branches or cash-based savings). Hence, there are more reasons to believe that m-banking in developing countries can target more than a niche application and could be successful in becoming primary banking channel for large segments of the population.

The telecom industry in Pakistan has grown multifold and met the international levels of securities. It was initiated as a luxury and status symbol for the elite class, now it is suitably affordable for a common man. In the year 2014, among number of cellular users, Pakistan ranks eighth in the world with mobile users over 140 million and revenues of 322,683 million.2 By seeing the success of cellular networks, m-banking is introduced in the year 2009 in Pakistan. In the battle of registered users, the technology has already outpaced internet banking which was started in 2003 (1.4 million vs. 1.3 million). Due to the rising acceptance, m-banking has proved itself a preferable branchless banking segment (Khan and Khan, 2012, Muhammed et al., 2013) and therefore is attracted by both financial institutions and mobile service providers of the country.

M-banking supports traditional bank to enhance their service quality and decrease their service cost. This is the reason why many banks in Pakistan have introduced the technology of mobile banking to its customers. In order to increase the significance of mobile banking and to use it as a tool of financial inclusion, State Bank of Pakistan had already signed Memorandum of Understand (MoU) with Pakistan Telecommunication Authority (PTA) in 20123. The prime purpose of this MoU is to improve regulatory and technological framework to reinforce m-banking through the process of counseling. Moreover, this MoU is designed for an organized governing structure, in discussion with all investors and to support each other in attaining the mutual aim of giving the low cost mobile banking services.

Table 1.1 shows the trend of mobile banking in Pakistan’s economy, It shows that in 2009, the No. of m-banking transactions were 0.1 million and the total value of transaction was about 200 million rupees. Mobile banking was drastically increased in 2010 by 500% growth in No. of transaction i.e. 0.6 million and 1000% growth in the value of transaction i.e. 2200 million rupees. In the year 2013 and 2014, the growth in the number of transaction was stable with the increase of 35.48% (4.2 million) and 47.61% (6.2 million) respectively. Same with the value of transaction, the growth was increased by 125% (27,000 millions) to 149.62% (67,400 millions) respectively. The benefits of convenience, accessibility and personalization associated with m-banking have established the positive effects on the acceptance of m-banking of the country.

In the Pakistani context, the existing mobile banking literature utilized the simplistic approach in examining m-banking solutions4 and thus could not shed greater sights to the field. The uniqueness of our study lies in its aim to analyze behavioral, environmental and technological aspects of m-banking of the country. The high percentage of mobile phone usage, the accelerating growth in m-commerce and the preferred demand of customers for newer banking service distribution models makes Pakistan an ideal candidate for this study. In doing so, the study integrated the frameworks of UTAUT, TTF and ITM to explore behavioral intentions to adopt m-banking in Pakistan. Mainly, the aim is to examine the effect on the behavior of end customer on the basis of task-technology features and initial trust on mobile banking solutions. In addition it seeks to explain how the environmental and technological characteristics are critical to m-banking acceptance in the present scenario where the performance of the bank-led mobile banking models are often questionable for serving unbanked and under banked population of the country.

Section snippets

Conceptual framework

The literature of information systems (IS) is filled with a vast pool of theoretical models. The lack of grounded theory in the field of IS causes researchers to utilize the frameworks provided by intention models from social psychology as the foundations of their research (Harrison et al., 1997). In IS literature, mobile banking has received ample consideration by both academia and practice (Gu et al., 2009, Kim et al., 2009, Luarn and Lin, 2005, Zhou et al., 2010). Many of such studies

Sample and data collection

For present research, a sample of 198 responses was collected from the higher education students of three private universities of Karachi. The sample was collected in a period of eight weeks (April 2015 to May 2015) using online questionnaire written in English. The study utilized convenience sampling method. The method used is consistent with the approach adopted in many previous studies of technology adoption (e.g. Chen, 2008, Featherman and Pavlou, 2003, Luarn and Lin, 2005, Wu and Wang, 2005

Descriptive analysis

The data analysis was carried out through SPSS 21 and AMOS 21 software with sample size of N = 151. Displayed in Table 4.1 is the composition of the data used in present research.

Table 4.2 shows the means, standard deviations, and inter-correlation among the eleven variables of the present research. Data analysis was initiated before checking for the issue of multicollinearity. In order to deal with the problem of multicollinearity between predictors, Hair et al. (2010) established that the issue

Discussion

The present study investigated the factors of and their effects on the peoples’ intention to adopt mobile banking in Pakistan. In this regard, the research utilized a questionnaire survey in integrating the framework of UTAUT, ITM and TTF models. By incorporating these IS theories, the study strives to examine the role of technological and environmental variables in predicting behavioral intention of individuals to adopt mobile banking. The elucidation of the results based on the empirical

Theoretical and practical implications

The findings of the present research have contributed an inclusive awareness regarding the decision factors that affect the adoption intention of mobile banking. For researchers, the present study, instead of focusing on single theoretical framework, provides an all-inclusive approach by incorporating three established theories of technology acceptance. The existing literature on mobile banking emphasizes greatly on the perception aspects of technology and hardly studies the impact of the task

Conclusion

The present research put forward an integrative model to provide awareness regarding the decision factors affecting the adoption of mobile banking. The Research model of the present study is designed by the combinations of unified theory of acceptance and usage of technology (UTAUT) (Venkatesh et al., 2003) with initial trust model (ITM) (Kim et al., 2009), and task technology fit (TTF) (Goodhue and Thompson, 1995). The research findings suggested that our hypothesized proposed model not only

Limitations and future research

Our study also is not free from limitations. First of all, the present research is limited to the smaller sample size. The time available for the completion of this project was limited, thus the study proposes integration of similar framework with larger sample size. Second, the present research utilized urban data; a future recommendation can be to perform a comparative analysis of rural and urban behavioral and technological aspects in m-banking adoption.

Third, we did not analyze the effect

References (103)

  • C.C. Lee et al.

    An empirical study of mobile commerce in insurance industry: task-technology fit and individual differences

    Decis. Support Syst.

    (2007)
  • H.F. Lin

    An empirical investigation of mobile banking adoption: the effect of innovation attributes and knowledge-based trust

    Int. J. Inf. Manage.

    (2011)
  • P. Luarn et al.

    Toward an understanding of the behavioral intention to use mobile banking

    Comput. Hum. Behav.

    (2005)
  • X. Luo et al.

    Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: an empirical study of mobile banking services

    Decis. Support Syst.

    (2010)
  • N. Mallat

    Exploring consumer adoption of mobile payments – a qualitative study

    J. Strateg. Inf. Syst.

    (2007)
  • Q. Min et al.

    Mobile commerce user acceptance study in China: a revised UTAUT model

    Tsinghua Sci. Technol.

    (2008)
  • T. Oliveira et al.

    Extending the understanding of mobile banking adoption: when UTAUT meets TTF and ITM

    Int. J. Inf. Manage.

    (2014)
  • A.A. Shaikh et al.

    Mobile banking adoption: a literature review

    Telematics Inform.

    (2015)
  • J.H. Steiger

    Understanding the limitations of global fit assessment in structural equation modeling

    Pers. Indiv. Differ.

    (2007)
  • J.H. Wu et al.

    What drives mobile commerce? An empirical evaluation of the revised technology acceptance model

    Inf. Manage.

    (2005)
  • F.M. Abubakar et al.

    The moderating effect of technology awareness on the relationship between UTAUT constructs and behavioral intention to use technology: a conceptual paper

    Aust. J. Bus. Manage. Res.

    (2012)
  • R. Agarwal et al.

    Are individual differences germane to the acceptance of new information technologies?

    Decis. Sci.

    (1999)
  • U. Akturan et al.

    Mobile banking adoption of the youth market: perceptions and intentions

    Market. Intell. Plan.

    (2012)
  • I.M. Al-Jabri et al.

    Mobile banking adoption: application of diffusion of innovation theory

    J. Electron. Commerce Res.

    (2012)
  • J.C. Anderson et al.

    The effect of sampling error on convergence, improper solutions, and goodness-of-fit indices for maximum likelihood confirmatory factor analysis

    Psychometrika

    (1984)
  • S. Anus et al.

    Trust and initial acceptance of mobile banking in Pakistan

    Int. J. Sci. Eng. Res.

    (2011)
  • A.A. Armenakis et al.

    Organizational change recipients’ beliefs scale development of an assessment instrument

    J. Appl. Behav. Sci.

    (2007)
  • N.M. Ashkanasy

    Editorial: submitting your manuscript

    J. Organiz. Behav.

    (2008)
  • R.P. Bagozzi et al.

    On the evaluation of structural equation models

    J. Acad. Mark. Sci.

    (1988)
  • R.P. Bagozzi et al.

    Multitrait-multimethod matrices in consumer research

    J. Consum. Res.

    (1991)
  • Barkus, E., Yavorsky, C., Foster, J., 2006. Understanding and Using Advanced Statistics. Faculty of Health &...
  • V. Bhatiasevi

    An extended UTAUT model to explain the adoption of mobile banking

    Inf. Dev.

    (2015)
  • B.M. Byrne

    Structural Equation Modeling with Mplus: Basic Concepts, Applications, and Programming

    (2012)
  • B.M. Byrne et al.

    Testing for the equivalence of factor covariance and mean structures: the issue of partial measurement invariance

    Psychol. Bull.

    (1989)
  • C.H. Chen

    Why do teachers not practice what they believe regarding technology integration?

    J. Educ. Res.

    (2008)
  • Y.H. Chen et al.

    Towards an understanding of the behavioral intention to use online news services: an exploratory study

    Internet Res.

    (2008)
  • Churchill, G.A., Iacobucci, D., 2010. Marketing Research: Methodological...
  • C. Craighead et al.

    Addressing common method variance: guidelines for survey research on information technology, operations, and supply chain management

    IEEE Trans. Eng. Manage.

    (2011)
  • S.L. Crowley et al.

    Structural equation modeling: basic concepts and applications in personality assessment research

    J. Pers. Assess.

    (1997)
  • F.D. Davis

    Perceived usefulness, perceived ease of use, and user acceptance of information technology

    MIS Q.

    (1989)
  • D.A. Dillman

    Mail and Telephone Surveys

    (1978)
  • M. Fishbein et al.

    Belief, Attitudes, Intention and Behavior: An Introduction to Theory and Research

    (1975)
  • J. Fisher et al.

    “Usability + usefulness = trust”: an exploratory study of Australian health web sites

    Internet Res.

    (2008)
  • C. Flavian et al.

    The influence of corporate image on consumer trust: a comparative analysis in traditional versus internet banking

    Internet Res.

    (2005)
  • Y.S. Foon et al.

    Internet banking adoption in Kuala Lumpur: an application of UTAUT model

    Int. J. Bus. Manage.

    (2011)
  • D. Gefen et al.

    Structural equation modelling and regression: guidelines for research practice

    Commun. Assoc. Inf. Syst.

    (2003)
  • D.L. Goodhue

    Understanding user evaluations of information systems

    Manage. Sci.

    (1995)
  • D.L. Goodhue et al.

    Task-technology fit and individual-performance

    MIS Q.

    (1995)
  • E. Guadagnoli et al.

    Relation to sample size to the stability of component patterns

    Psychol. Bull.

    (1988)
  • Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., 2010. Multivariate Data Analysis: A Global...
  • Cited by (0)

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