Understanding resistance to mobile banking adoption: Evidence from South Africa

Transcription

1 Understanding resistance to mobile banking adoption: Evidence from South Africa Introduction In the last decade, the convergence of the Internet, wireless technologies, and mobile devices has made possible mobile commerce (m-commerce), a new paradigm of an emerging information technology (IT) artefact (Luo, Li, Zhang, & Shim, 2010). Because banking activities are easily digitised and automated (Bradley & Stewart, 2002), banks have seized the m-commerce opportunity and have developed mobile banking applications that allows more flexibility for bank customers in terms of anywhere, anytime banking. Mobile banking is still in its infancy and internationally adoption rates remain low (Lin, 2011). Thus, the challenge for marketing managers of mobile banking services is to increase the adoption of mobile banking. Although previous studies have provided useful information on mobile banking adoption behaviour, research that focuses on why bank customers resist such a service and how this resistance influences behavioural intention is limited. This study aims to address the adoption challenge faced by marketing managers and the identified gap in literature by aiming to gain an understanding of what are the factors that negatively influence the formation of behavioural intention to adopt mobile banking of non-users of the self-service. The main objective of this study is therefore to identify the resistance factors that negatively influence the formation of behavioural intention of non-users (bank customers) of mobile banking. Literature review and conceptual model development Based on the seminal work of Ram and Sheth (1989) and other studies, a conceptual model was developed to test the influence of technology resistance factors on the formation of behavioural intention to adopt mobile banking. The conceptual model is presented in Figure 1. The theory underpinning the inclusion of each technology resistance factor will briefly be discussed, due to the page limitation. According to the Technology Acceptance Model (TAM) of Davis (1989) the two salient beliefs influencing behavioural intention to adopt a technology are Perceived usefulness and Perceived ease of use. TAM meta-analysis studies (see e.g. King and He (2006) and Ma and Liu (2004)) show that Perceived usefulness and Perceived ease of use influence Behavioural intention and that Perceived ease of use influences Perceived usefulness. Thus, in accordance with TAM theory and the results of the meta-analysis studies, it is hypothesised that the Perceived usefulness of mobile banking positively influences Behavioural intention to adopt mobile banking (H1), that the Perceived ease of use of mobile banking positively influences Behavioural intention (H2) and that Perceived ease of use positively influences Perceived usefulness of mobile banking (H3). The early work of Ram and Sheth (1989) identified two categories of technology resistance factors: functional s and psychological s (Ram & Sheth, 1989). Functional s relate to the Usage, Value and Risk ; whilst psychological s relate to the Tradition and Image (Ram & Sheth, 1989). According to Ram and Sheth (1989), the Usage occurs when a technology innovation does not fit with the user s workflows, habits and practices, as more effort will be required from the user to learn and utilise 1

2 the technological innovation. Two studies provide evidence of the significance of the Usage in the mobile banking context. Firstly, in Kuisma, Laukkanen, and Hiltunen (2007) it was reported that respondents who did not use mobile banking perceived mobile banking to be difficult to use for banking activities. Secondly, in Gerrard and Cunningham (2003) it was also reported that the complexity of mobile banking has caused customers to perceive such services as being difficult to use. Thus, based on the reviewed literature it is hypothesised in this study that the Usage negatively influences the Perceived ease of use of mobile banking (H4). Figure 1 Conceptual model Tradition Risk H8 - H7 - Value H12 + Information H6 - H11 - H10 - Perceived usefulness H3+ Perceived ease of use H1+ H2 + Behavioural intention H4 - H9 - H5 + Usage Image The second functional identified by Ram and Sheth (1989) is the Value. The Value occurs when a technological innovation does not offer a strong performance-toprice value compared with competing offers (Ram & Sheth, 1989). Kuisma et al. (2007) point out that customers who did not use mobile banking said that the benefits of mobile banking were not significant, since connection to the internet would be costly. Likewise, Laukkanen, Sinkkonen, Kivijarvi, and Laukkanen (2007) also reported that customers who did not use mobile banking believed it to be too expensive. In the context of this study, the Value can be defined as the extent to which a non-user of mobile banking perceives that the benefits associated with mobile banking do not justify the costs. Taking into consideration the definition of the Value in this study, it is reasonable to assert that the more non-users of mobile banking perceive a Value, the less they will perceive mobile banking as useful. Therefore, we hypothesise that the Value negatively influences the Perceived usefulness of mobile banking (H6). Furthermore, we also hypothesise that the Usage positively influences the Value (H5). This hypothesis (H5) is based on the argument that the more a technology requires effort to use (i.e., the Usage increases), the cost of using the technology 2

3 increases. Consequently, the value of using the technology decreases (i.e., the Value increases). The Risk, the third functional identified by Ram and Sheth (1989), explains the degree of risk associated with a technological innovation. Generally speaking, the perceived risk in using an e-service could be an important to consumer acceptance of electronic services (Featherman & Pavlou, 2003). Previous studies such as Lu, Hsu, and Hsu (2005) and Gefen, Karahanna, and Straub (2003) provide empirical evidence that if consumers perceive some risk in using an electronic service, it will reduce the usefulness of the service. Therefore, the hypothesis is included in the conceptual model stating that the Risk of mobile banking negatively influences the Perceived usefulness of mobile banking (H7). The Tradition is one of the two psychological s identified by Ram and Sheth (1989). The Tradition originates when a technology innovation poses a change in customers established traditions and is particularly contrary to the values that are important to the customer (Ram & Sheth, 1989). Mobile banking is just one of the many channels that banks offer to customers. The Tradition may be highly relevant in the context of mobile banking adoption for various reasons. For example, for some bank customers, mobile banking is a channel they are not accustomed to (Fain & Roberts, 1997). Indeed, Gerrard, Cunningham, and Devlin (2006) report that some bank customers do not find it necessary to utilise mobile banking, because they prefer their current way of handling their banking activities. Thus, the Tradition could be a major determinant exerting a negative influence on the Perceived usefulness of mobile banking (H8). An Image (the second psychological ) occurs when customers embrace stereotyped thinking concerning the relevant technological innovation and hence hinder its adoption (Ram & Sheth, 1989). In the case of mobile banking, such thinking can be caused by the product s category (Laukkanen & Kiviniemi, 2010). According to Fain and Roberts (1997) the Image in the online banking context emerges from a negative hard-to-use image of computers and the internet. Laukkanen and Kiviniemi (2010) argue that this may also be the case in terms of mobile banking - consumers may perceive the mobile technology to be too difficult to use and therefore instantly form a negative image of the service. Given that the Image relates to the hard-to-use aspect of a technology, it is hypothesised in this study that the Image negatively influences the Perceived ease of use of mobile banking (H9). The final considered in this study is the Information. The significance of the Information lies in the logical arguments that when bank customers do not have knowledge about mobile banking, they may not know or understand the benefits of mobile banking, nor will they know how they should use the service. Wilton and Pessemier (1981) demonstrated that when relevant information about a technology innovation is limited to the bank customers, then bank customers will be inclined to resist adoption. Moreover, Sathye (1999) also points out that it is important for banks to explain how self-service technologies add value compared to other means of banking which offer the same benefit. Therefore, it is hypothesised that the Information negatively influences the Perceived usefulness and Perceived ease of use of mobile banking, whilst it positively influence the Value (H11, H10 and H12 respectively). 3

4 Research design and method The target population consisted of 288 bank customers who are non-users of mobile banking. Given that a sampling frame was not available, judgement sampling was used. The first section of the questionnaire measured the demographic information, and the second section measured the six s to technology acceptance, as well as Perceived usefulness, Perceived ease of use and Behavioural intention as discussed in the literature review. A seven-point Likert-type scale was used, where 1 = strongly disagree, 2 = disagree, 3 = slightly disagree, 4 = undecided, 5 = slightly agree, 6 = agree and 7 = strongly agree. The scales used to measure resistance factors were adopted from previous studies and pre-tested with 200 respondents. The females comprised 50.3% of the sample, while the males comprised 49.3% of the sample. The age groups were distributed as follows: (26.1%), (24.3%), (19.7%), (9.9%), (9.2%) and 45 and above (10.9%). Assessment of the measurement model and structural model A confirmatory factor analysis (CFA) (using EQS 6.1) based on the measurement scales showed acceptable fit. The values for the fit indices for the CFA were well below the recommended cutoff values for acceptable fit as indicated in Hair, Black, Babin, Anderson, and Tatham (2006). The results of the CFA also provided sufficient evidence of construct validity and construct reliability. The S-Bχ 2 /df ratio of the structural model was 1.419; the CFI and the RMSEA were Considering the guidelines set by Hair et al. (2006) for model fit indices, the hypothesised model fits acceptably with the observed data. The standardised path coefficients of the proposed research model are shown in Figure 1. Figure 1 EQS 6.1 analysis results of the research model Tradition Risk H7: ß=.096 H8: ß=-.174* Value R 2 =.604 H12: ß=.277* Information H6: ß=-.325* H11: ß=-.120 H10: ß=-.480* Perceived usefulness R 2 =.644 H3: ß=.492* Perceived ease of use R 2 =.499 H1: ß=.425* H2: ß=.435* Behavioural intention R 2 =.637 H4: ß=-.322* H9: ß=-.082 H5: ß=.605* Usage Image * ρ<.05 4

5 Discussion The results of the study provide empirical support for nine of the 12 hypotheses. More importantly, the results provide empirical support that the Tradition and the Value negatively influence the Perceived usefulness of mobile banking. The results also show that the Information and the Usage negatively influence the Perceived ease of use of mobile banking. The that exerted the strongest influence on the Perceived usefulness of mobile banking is the Value. Almost 60% of the variance in the Value is explained by the Usage and the Information. In the tested model the strongest predictor of Perceived ease of use is the Information. Overall, the conceptual model explains 64% of the variance in Perceived usefulness, about 50% of the variance in the Perceived ease of use and almost 64% of Behavioural intention. Managerial implications The provision of adequate information to non-users of mobile banking should be well supported by different types of marketing communications. For example, advertisements should not only focus on creating awareness, but also on educating non-users about the benefits of mobile banking and how easy it is to use mobile banking. This will have two positive effects that are important considering the results of the study. Firstly, the Value may decrease among non-users which will have a positive influence on Perceived usefulness. Secondly, by providing information on how to use mobile banking (i.e., addressing the Information with regards to the use of mobile banking) the Perceived ease of use of mobile banking may increase. Furthermore, banks should continuously experiment with different designs of mobile banking applications. The focus of the experimentation must be to refine the design and/or be innovative in the design of different mobile banking applications in order to present reduced effort in learning how to use the application. Moreover, banks must make use of strategies such as bundling of services to overcome the Tradition. Limitations of the study and future research The main limitation of the study is that the study was conducted in a developing country. Thus, it may be incorrect to assume that the findings of the study apply equally well to non-users of mobile banking in developed countries. Therefore, it is of importance that researchers with an interest in mobile banking re-test the conceptual model in developed countries to validate the findings. Future studies can also include Attitude, which plays a critical role in influencing behavioural intention. Furthermore, previous research demonstrated that technology adoption behaviour is moderated by variables such as age, income and gender. Future studies can also consider these moderators. Conclusion The results confirmed that technology resistance factors do indeed play a strong role in the formation of intention to use mobile banking. Considering the results of the study, it is imperative for marketing managers to take cognisance of these factors and develop appropriate marketing strategies to minimise their impact. 5

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