Increasingly, mobile banking (MB) has been growing phenomenally over the banking
sector and has become an integral banking channel alongside internet banking,
telebanking, and ATM (Lee et al., 2007). As an innovative banking channel, MB enables
customers to carry out financial transactions (i.e. balance enquiries, fund transfers,
payment of bills) using mobile devices, smartphones, or Personal Digital Assistants
24 hours a day, seven days a week (Zhou et al., 2010). The prevalence in MB could be
attributed to the ability of such technology to launch a variety of financial services over
a wider geographical area, especially where there is a problem regarding internet
connections, or where setting up branches is difficult and not feasible (Cruz et al., 2010;
Wessels and Drennan, 2010). Moreover, by introducing MB services, banks aim to
provide customers with a better service by means of more friendly and cost-effective
channels, thereby enhancing their satisfaction and loyalty (Alalwan et al., 2015;
Gu et al., 2009; Lee et al., 2014; Lin, 2013; Wessels and Drennan, 2010).In Jordan, mobile technology has evolved significantly over recent years; this is
evidenced by the increasing penetration rate of the mobile service which had climbed to
140 per cent by 2012 (The Jordan Times, 2013). Therefore, under intense competition, MB
has received particular attention from the Jordanian banks as about 15 banks out of
26 had implemented MB services by the end of 2012 (Migdadi, 2012). Nevertheless, in
both developed and developing countries, the evolution in MB services is not in line with
the boom in mobile technology, and the growth in the adoption rate of this technology is
still sluggish (Alalwan et al., 2015; Hanafizadeh et al., 2014; Lin, 2011; Püschel et al., 2010).
For instance, Cellular-News (2011) reported that the highest rate of adoption of MB
services were 25 and 22 per cent in China and USA, respectively. In the same way, these
rates go down dramatically in developing countries (Cellular-News, 2011).
The adoption of MB in Jordan is not on the desired level because Jordanian banking
customers are still sluggish in accepting these technologies (Awwad and Ghadi, 2010).
For instance, statistics provided by some of the largest banks in Jordan (Arab Bank and
HSBC) suggest that only 1.65 per cent of Jordanian bank customers have adopted MB
up to 2009 (Awwad and Ghadi, 2010). Hence, Jordanian banks have begun to express
concern regarding the low adoption rate of MB, as well as questioning the feasibility of
introducing such a channel, especially given the large amount of resources being
invested in this regard (Migdadi, 2012).
In effect, persuading customers to switch their behaviour from using traditional
banking channels to MB is not an easy process, especially as there is a lack of
understanding of this phenomenon from the customers’ perspective (Dwivedi and Irani,
2009). Thus, understanding the factors that might be responsible for the sluggish
adoption of MB could help the banks speed up the adoption rate of such technology.
However, as it is in the early stage of deployment and implementation, MB-related
issues are yet to be examined empirically in the Jordanian context. For that reason, this
study is motivated to fill this gap by empirically examining the main factors
influencing the adoption of MB from the Jordanian customers’ perspective.
The remaining sections of the paper are structured as follows: the next section
provides an overview of the relevant literature; a proposed conceptual model and
associated hypotheses follow in Section 3. Section 4 outlines the research method. The
results are then presented in Section 5 followed by a discussion in Section 6. Finally,
Section 7 outlines the key conclusions and briefly discusses the main research limitations
and future research directions.
2. Literature review
TheMB-related issues have recently been the focus of attention for many researchers (i.e.
Hanafizadeh et al., 2014; Lee et al., 2014; Lin, 2011; Purwanegara et al., 2014; Zhou
et al., 2010). However, examination of the usage patterns of MB (i.e. behavioural intention
(BI), usage behaviour, adoption, and continued intention to use) has received considerable
interest over prior literature of MB (e.g. Lin, 2011; Mishra and Bisht, 2013; Purwanegara
et al., 2014; Zhou et al., 2010; Zhou, 2011, 2012). Theoretically, in their endeavours to
provide an in-depth understanding of customer intention and adoption of MB,
researchers have formulated and integrated many theories and models from information
systems (ISs), information technologies, and disciplines relating to human behaviour
(Dwivedi and Irani, 2009). For instance, the Innovation Diffusion Theory (IDT) (Rogers,
2003) has been employed by along with perceived ease of use (PEOU) and trust (i.e. Lin,
2011; Hanafizadeh et al., 2014), and customer experience with cell-phone technology,
self-efficacy (SE), and facilitating conditions as proposed by Brown et al. (2003).
MB in Jordan
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The Technology Acceptance Model (TAM) (Davis et al., 1989) has also been proposed
bedside system quality and social influences by Gu et al. (2009), Hanafizadeh et al. (2014),
and Akturan and Tezcan (2012) to predict the customer intention and acceptance of MB.
The Theory of Planned Behaviour (Ajzen, 1991) was formulated by Luarn and Lin (2005)
accompanied by perceived credibility in one single model. Püschel et al. (2010) modified
their model based on factors extracted from the Decomposed Theory of Planned
Behaviour and the IDT. The Unified Theory of Acceptance and Use of Technology
(UTAUT) (Venkatesh et al., 2003) has been used by Zhou et al. (2010) in the company of
trust to predict the actual adoption of MB as well.
Nevertheless, there is a dearth of literature addressing BI and adoption of MB in
Jordan (Awwad and Ghadi, 2010; Khraim et al., 2011). Based on simple regression
analyses, both Khraim et al. (2011) and Awwad and Ghadi (2010) have found that
innovation attributes – trialability, complexity, compatibility, relative advantages, and
risk – are the key predictors of Jordanian customer intention and adoption of MB. Even
though these studies enriched the current understanding regarding the main predictors
of the adoption of MB in Jordan, there is still a necessity of selecting a theoretical
framework appropriate to the customers’ perspective as well as being able to capture
the most important aspects that could formulate the Jordanian customers’ intention to
adopt MB. Therefore, this study is motivated to fill this gap by proposing a parsimony
conceptual model being able to provide a better understanding regarding the adoption
of MB from the perspective of Jordanian banking customers.
3. Conceptual model and research hypotheses
The TAM was considered as an appropriate theoretical foundation for developing the
conceptual model utilised in this study. Indeed, the TAM has been considered as one of
the most popular and acceptable models within the IS field (Rana et al., 2013; Venkatesh
et al., 2003). For instance, according to a Google scholar report, 7,714 citations have
been recorded for the original study of Davis et al. (1989) by the end of June 2010
(Bradley, 2012). Further, as reported by Rana et al. (2013), Venkatesh and Davis (2000),
and Irani et al. (2009), the TAM is one of the strongest and rational models to predict the
individual’s intention and acceptance over the last two decades. It is worthwhile to note
that the TAM has been the most adopted theory to explain the customers’ intention
and usage of different kinds of electronic banking channels such as internet banking
(i.e. Al-Somali et al., 2009; Curran and Meuter, 2005) and telebanking (Sundarraj and
Wu, 2005; Curran and Meuter, 2007). By the same token, the TAM has successfully
been used by different MB studies to predict the customer intention and adoption
towards this technology (i.e. Gu et al., 2009; Lee et al., 2007). Furthermore, this study
aims to propose a parsimonious model which is able to capture the most important
aspects that could shape the Jordanian customers’ intention and adoption of MB.
Therefore, the TAM was found by the current study to be more suitable theoretical
foundation to propose the conceptual model rather than the TAM2.
Building on the theory of reasoned action (Fishbein and Ajzen, 1975), TAM was
proposed to examine the individual behaviour towards computer usage (Davis et al.,
1989). In accordance with the TAM, two main constructs – PEOU and perceived
usefulness (PU) – are identified as main predictors of the BI towards using the specified
technology (Davis et al., 1989). Therefore, both PEOU and PU were proposed in the
current study model as key factors influencing the Jordanian customers’ intention to
adopt MB (see Figure 1). Nevertheless, PEOU and PU would not be able to provide a
clear picture of explaining individual intention and behaviour-related technology