1.

IntroductionIncreasingly, mobile banking (MB) has been growing phenomenally over the bankingsector and has become an integral banking channel alongside internet banking,telebanking, and ATM (Lee et al., 2007). As an innovative banking channel, MB enablescustomers to carry out financial transactions (i.e. balance enquiries, fund transfers,payment of bills) using mobile devices, smartphones, or Personal Digital Assistants24 hours a day, seven days a week (Zhou et al., 2010). The prevalence in MB could beattributed to the ability of such technology to launch a variety of financial services overa wider geographical area, especially where there is a problem regarding internetconnections, 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 toprovide customers with a better service by means of more friendly and cost-effectivechannels, 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 isevidenced by the increasing penetration rate of the mobile service which had climbed to140 per cent by 2012 (The Jordan Times, 2013).

Therefore, under intense competition, MBhas received particular attention from the Jordanian banks as about 15 banks out of26 had implemented MB services by the end of 2012 (Migdadi, 2012). Nevertheless, inboth developed and developing countries, the evolution in MB services is not in line withthe boom in mobile technology, and the growth in the adoption rate of this technology isstill 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 MBservices were 25 and 22 per cent in China and USA, respectively. In the same way, theserates go down dramatically in developing countries (Cellular-News, 2011).

The adoption of MB in Jordan is not on the desired level because Jordanian bankingcustomers 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 andHSBC) suggest that only 1.65 per cent of Jordanian bank customers have adopted MBup to 2009 (Awwad and Ghadi, 2010).

Hence, Jordanian banks have begun to expressconcern regarding the low adoption rate of MB, as well as questioning the feasibility ofintroducing such a channel, especially given the large amount of resources beinginvested in this regard (Migdadi, 2012).In effect, persuading customers to switch their behaviour from using traditionalbanking channels to MB is not an easy process, especially as there is a lack ofunderstanding of this phenomenon from the customers’ perspective (Dwivedi and Irani,2009). Thus, understanding the factors that might be responsible for the sluggishadoption 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-relatedissues are yet to be examined empirically in the Jordanian context. For that reason, thisstudy is motivated to fill this gap by empirically examining the main factorsinfluencing the adoption of MB from the Jordanian customers’ perspective.The remaining sections of the paper are structured as follows: the next sectionprovides an overview of the relevant literature; a proposed conceptual model andassociated hypotheses follow in Section 3.

Section 4 outlines the research method. Theresults 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 limitationsand future research directions.2. Literature reviewTheMB-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; Zhouet 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 considerableinterest over prior literature of MB (e.g.

Lin, 2011; Mishra and Bisht, 2013; Purwanegaraet al., 2014; Zhou et al., 2010; Zhou, 2011, 2012). Theoretically, in their endeavours toprovide an in-depth understanding of customer intention and adoption of MB,researchers have formulated and integrated many theories and models from informationsystems (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).119Consumeradoption ofMB in JordanDownloaded by New York University At 01:34 05 February 2016 (PT)The Technology Acceptance Model (TAM) (Davis et al., 1989) has also been proposedbedside 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) modifiedtheir model based on factors extracted from the Decomposed Theory of PlannedBehaviour 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 oftrust to predict the actual adoption of MB as well.Nevertheless, there is a dearth of literature addressing BI and adoption of MB inJordan (Awwad and Ghadi, 2010; Khraim et al., 2011).

Based on simple regressionanalyses, both Khraim et al. (2011) and Awwad and Ghadi (2010) have found thatinnovation attributes – trialability, complexity, compatibility, relative advantages, andrisk – are the key predictors of Jordanian customer intention and adoption of MB. Eventhough these studies enriched the current understanding regarding the main predictorsof the adoption of MB in Jordan, there is still a necessity of selecting a theoreticalframework appropriate to the customers’ perspective as well as being able to capturethe most important aspects that could formulate the Jordanian customers’ intention toadopt MB. Therefore, this study is motivated to fill this gap by proposing a parsimonyconceptual model being able to provide a better understanding regarding the adoptionof MB from the perspective of Jordanian banking customers.3. Conceptual model and research hypothesesThe TAM was considered as an appropriate theoretical foundation for developing theconceptual model utilised in this study. Indeed, the TAM has been considered as one ofthe most popular and acceptable models within the IS field (Rana et al.

, 2013; Venkateshet al., 2003). For instance, according to a Google scholar report, 7,714 citations havebeen 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 theindividual’s intention and acceptance over the last two decades. It is worthwhile to notethat the TAM has been the most adopted theory to explain the customers’ intentionand 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 andWu, 2005; Curran and Meuter, 2007). By the same token, the TAM has successfullybeen used by different MB studies to predict the customer intention and adoptiontowards this technology (i.e.

Gu et al., 2009; Lee et al., 2007). Furthermore, this studyaims to propose a parsimonious model which is able to capture the most importantaspects that could shape the Jordanian customers’ intention and adoption of MB.Therefore, the TAM was found by the current study to be more suitable theoreticalfoundation to propose the conceptual model rather than the TAM2.Building on the theory of reasoned action (Fishbein and Ajzen, 1975), TAM wasproposed to examine the individual behaviour towards computer usage (Davis et al.

,1989). In accordance with the TAM, two main constructs – PEOU and perceivedusefulness (PU) – are identified as main predictors of the BI towards using the specifiedtechnology (Davis et al., 1989).

Therefore, both PEOU and PU were proposed in thecurrent study model as key factors influencing the Jordanian customers’ intention toadopt MB (see Figure 1). Nevertheless, PEOU and PU would not be able to provide aclear picture of explaining individual intention and behaviour-related technology120JEIM29,1Downloaded by