The 2003 European Marketing Academy Conference

20 – 23 May in Glasgow, Scotland

 

Track: Marketing and Innovation

 

 

 

 

 

 

 

INBCT 4.1

 

 

 

 

 

 

Modelling Mobile Banking Adoption

 

 

 

 

 

 

 

 

 

 

 

 

Mari Suoranta

Researcher

University of Jyvaskyla

School of Business and Economics

 

 

 

 

 

 

 

 

Contact address: P.O.Box 35 (MaE), 40014 Jyvaskyla, Finland. Tel.: +358-40-5085552.

Fax: +358-14-2602968. E-mail: masuoran@cc.jyu.fi

 

 

Modelling Mobile Banking Adoption

 

 

Abstract

 

Innovation adoption literature suggests that perceived innovation attributes are the most important determinants of consumers’ adoption decision. This paper focuses on defining the factor influencing mobile banking adoption and aims at forming a model describing consumer behaviour pattern. Thus it also evaluates of the applicability of Rogers’ (1995) model in this context.  

 

In consequence we are able to state what are the drivers and inhibitors of using banking services via wireless delivery channel. A quantitative survey sheds more light on this researched issue. The data was collected in Finland during May-July 2002 and includes 1253 survey responses.

 

Keywords: Mobile banking, innovation adoption, modelling consumer behaviour

 

 

 

 

 

 

Introduction

 

Rapid changes in the financial services environment; increased competition by new players from non-banking sector, product innovations, globalization and technological advancement, have led to a market situation where battle of customers is intense. In order to rise to the challenges service provider are even more interested to enhance their understanding of consumer behaviour patterns. This paper examines factors influencing the adoption of mobile banking services.

 

Recent research in electronic delivery of financial services has largely been conducted in the context of Internet banking, the present study contributes to this research area by exploring wireless delivery channel and services used by mobile data terminal equipment. Marketing implications that can be drawn from the findings will assist service providers in understanding consumers better and making justified marketing decisions. Research findings make a contribution to the theoretical consumer behaviour modelling by extending a traditional theory to a new application area that may give new insights into the theory. Thus, the study contributes both to practice and theory. 

 

The paper is organised as follows: it begins with a brief literature review in order to provide theoretical background for the study. Thereafter, the methodology and data collection are described and the empirical implications of the survey explained. The paper concludes with a discussion of the findings and development of a model applicable to this case.

 

 

Theoretical background

 

The newly emerged mobile banking services represent an innovation where both intangible service and an innovative medium of service delivery employing high technology are present. Thus, concepts of innovation and diffusion of innovation are even more intricate as technology and service aspects have an effect on the characteristics of mobile banking services. (Mohr 2001). Traditionally research relating to the customer adoption of innovation has tended to concentrate on socio-demographic and psychographic attributes of potential adopters. Even though these kind of personal characteristics of a consumer have found to be predictors of adoption (e.g. Al-Ashban & Burney 2001), an increasing body of research has demonstrated that it is the perceived attributes of innovation itself rather than the personal characteristics that are the stronger predictors of the adoption decision. (Black et al. 2001, 391). In the search to understand consumers’ adoption of innovation, and where research has focused on the consumer perspective, Rogers’ diffusion model, which originally dates back to 1962, has often been employed. (Howcroft et al. 2002; Black et al. 2001). Within financial services innovation research i.a. Black et al. (2001), Polatoglu & Ekin (2001), Tan & Teo (2000) have applied Rogers’ model to Internet banking.

 

According to Rogers (1995) the perceived innovation characteristics are supposed to provide the framework how potential adopters perceive an innovation. Research that has investigated the product characteristics of innovation has generally endorsed evaluating the innovation along the product characteristics that involve five constructs; relative advantage, compatibility, complexity, trialability and observability. (Moore & Benbasat 1991). Concept of perceived risk is often included as augmented by Bauer (1960). Particularly in banking services the perceived risk associated with the financial product itself as well as with electronic delivery channel is higher than in basic consumer goods, and hence increasing the importance of this attribute of innovation. (Harrison 2000, 242). Ensuring security and confidentiality are the fundamental prerequisites before any banking activity involving sensitive information can take place. (Jayawardhena & Foley 2000). Relative advantage, compatibility, trialability and observability are positively related to adoption of an innovation and the remaining two, complexity and perceived risk, negatively related. (Rogers 1995). These innovation attributes and their influence on adoption of mobile banking services are detailed under empirical implications.    

 

Adoption of tele-banking (e.g. Al-Ashban & Burney 2001) as well as Internet banking (e.g. Bradley & Steward 2002) has received research attention in recent years. Much of the existing research in electronic banking services has adopted an organisational perspective (e.g. Daniel 1999) or a distribution channel perspective (e.g. Black, Lockett, Ennew, Winklhofer & McKechnie 2002), notwithstanding these slightly different approaches similar patterns have emerged within financial services innovations that include convenience, flexibility, access, security, control etc. (Black et al. 2001).      

      

 

 

 

 

 

Methodology and data collection

 

The methodological approach in this study is descriptive, because purpose is to define and discuss factors influencing the adoption of mobile banking services. The phenomenon to be studied is comparatively new in the field of academic research and thereby study aims at modelling the current consumer behaviour pattern in mobile banking, these elements reflect the descriptive nature of the research design. (Churchill & Iacobucci 2002). The data was collected by means of a traditional postal survey. The questionnaire was sent to a gross section of 3,000 bank customers in Finland   This resulted to 1303 responses of which 1253 were usable i.e. usable response rate amounted to 41.8 percent, which was really satisfactory and above the 20-30 percent rate considered acceptable in economics research. The objective was to gather a geographically representative sample of Finnish bank customers. The survey sample consisted of three equal-sized segments that were selected in terms of mobile banking usage experience and density.  The non-users have not ever used permanently any form of mobile banking services, the occasional users had started to use some form of mobile services and the regular users had been using services for a longer period of time. The questionnaires were also partly tailored respectively. This data forms the basis of the whole research of which this paper is one part. Only the selected sections of the survey data will be used in the present paper. According to the chosen methodological research approach the quantitative data was analysed using statistical methods by SPSS-program.

 

Empirical implications

 

Relative advantage

Relative advantage is concerned with the degree to which an innovation is perceived as being better than the idea it supersedes. The degree of relative advantage is often expressed as economic profitability, social prestige, savings in time and effort, immediacy of the reward or as decrease of discomfort. (Rogers 1995, 212-216). The construct of relative advantage is highly domain specific and thus advantage can be seen differently in context of different innovations and on other hand of different consumer. In the case of mobile banking relative advantage is mainly formed across the mobile value of the new banking service delivery medium. Mobile value signifies the value arising from the mobility of the medium, i.e. making use of electronic services while on the move/road, mobility offers the creation of choice and new freedom.  (Anckar & D’Incau 2002, 47). As the major trigger for adopting mobile banking services regular users (85.4 %) and occasional users (77.8 %) named the accessibility and availability of services regardless of time and place. Over half of the regular users (52.1 %) and 43.8 % of occasional users mentioned also savings in time and effort as reasons to adopt as well as savings in financial costs of conducting banking (regular user 44.8 % and occasional user 44.5 %).   

 

Complexity

The perception of complexity involved when conducting financial transactions via mobile channel is often inversely related to a consumer’s experience with technology in general.   Adoption of complex products depends on adopter’s ability to develop new knowledge and new patterns of experience. This ability can be enhanced by the knowledge gained from related products. (Mahajan, Muller & Srivastava 1990, 45). In Finland usage of Internet banking has already diffused to masses of banking customers, it can be argued that Internet banking is sort of related service. Payments and account management products over mobile GSM phone as SMS have been available in Finland since 1992 too. (Mattila & Pento 2002). When respondents were asked about problem faced with mobile banking, all the response alternatives got rather low ratings. Regular users mentioned that malfunction of service (12.5 %) had caused some problems, whereas occasional users complained about insufficient guidance (14.6 %) to using mobile banking services.    

 

Compatibility

The degree to which an innovative channel such as a mobile device is compatible with the individual’s past experiences and values appears to have a significant impact on willingness to adopt. Respondents were asked about their attitudes towards technology-based products and services. Every target segment informed with positive mean scores (scale used ranged from -3 to 3) i.a. to mobile phone and services, Internet, personal computer, cable television, e-mail that they were pretty enthusiastic about using technology, except of electronic ID-card (mean scores  -0.2 - -0.09). Furthermore 82 % of the respondent had an Internet connection on use. In Finland mobile phone penetration exceeds 85 %, which certainly affect adoption of mobile banking services too. These results are consistent with Rogers’ suggestion and previous research (e.g. Tan & Teo 2000) that compatibility of an innovation with previously introduced idea can influence the adoption of the innovation as well as the development stage of infrastructure. Further, Hirschman (1980) has suggested that prior experience with the product class, which for example in this case is usage of Internet banking, may lead to greater acceptability of a new product. 

 

Observability

Observability of an innovation describes the extent to which an innovation is visible to other members of a social system, how easily the benefits can be observed and communicated. (Rogers 1995). The lack of physical domain in service products may present some problems, even though in this case the service delivery medium, mobile phone itself, may enhance physical evidence of the innovation. In this survey respondents mentioned they had gained information of mobile banking services from banks’ personnel (occasional users 46.7 %, non-users 19.5 %) via personal selling activities, and secondly from marketing communication activities, such as advertisements (occasional users 15.7 %, non-users 36.4 %) and mailings (occasional users 16.4 %, non-users 26.1 %).   

 

Trialability

Rogers argues that potential adopters who are allowed to experiment with an innovation will feel more comfortable with it and are more likely to adopt it. Consequently, if consumers are given the opportunity to try the innovation certain fears of unknown and inability to use can be reduced. In this survey 12.7 % of non-users had tested mobile banking services, but this did not lead to permanent use. However, this evidences that trial use of mobile banking services is possible.

 

Perceived risk

Security and trustworthiness of usage of service was mentioned to be the most important factor within every target segments when deciding on banking service delivery channel. Survey participants responded also positively (mean scores 1.4 – 0.1) to the argument “using mobile phone in banking is trustworthy”.

Discussion and model development

 

Based on the above discussed findings of the survey and the reviewed literature, a model of the factors influencing adoption of mobile banking services was formed (Figure 1). Rogers’ initial five constructs of innovation attributes augmented with perceived risk and external factors such as social system, communication channels, time and demographics of adopters are argued to be the dimensions of this model. The size of the attribute demonstrates also the importance of it. The most significant predictors of adoption in this case turned out to be relative advantage gained, compatibility of services with adopters existing values and perceived complexity of the services. The proposed model is not intended to be fully comprehensive or universally applicable, but rather it should be viewed as one of the first insights into this fairly unexamined and ‘unknown territory’ of mobile banking.    

 

 

FIGURE 1       A model of the factors affecting the adoption of mobile banking services

 

 

 

 

 

                                                                                                                     

 

                                                                                                                

Social  

                                                                                                                              System

                       

                                                                                    Communication

 

                                                                                                                       Time

                                                                                                                            

                                                                                                                                                      

Demographics                                                                                                                                            

 

                                                                          

 

                                                                                                                                         

               

 

 

 

 

 

 

 

REFERENCES

 

Al-Ashban, A. A. & Burney, M. A. 2001. Customer adoption of tele-banking technology:   the case of Saudi Arabia. International Journal of Bank Marketing. Vol. 19 (5), pp. 191-200.

 

Anckar, B & D’Incau, D. 2002. Value creation in mobile commerce: Findings from a consumer survey. Journal of Information Technology Theory & Application. Vol. 4 (1), pp. 43-64.

 

Bauer, R.A. 1960. Consumer behaviour as risk taking. Proceedings of the Educators Conference, American Marketing Association, pp. 389-398.

 

Black, N. J. & Lockett, A. & Winklhofer, H. & Ennew, C. 2001. The adoption of Internet financial services: a qualitative study. International Journal of Retail and Distribution Management. Vol. 29 (8), pp. 390-398.

 

Black, N. J. & Lockett, A. & Ennew, C. & Winklhofer, H. & McKechnie, S. 2002. Modelling consumer choice of distribution channels: an illustration from financial services. International Journal of Bank Marketing. Vol. 20 (4), pp. 161-173.

 

Bradley, L. & Steward, K. 2002. A Delphi study of the drivers and inhibitors of Internet banking. International Journal of Bank Marketing. Vol. 20 (6), pp. 250-260.

 

Churchill, G. & Iacobucci, D. 2002. Marketing research: Methodological foundations. 8^th edition. Orlando: Harcourt College Publishers.

 

Daniel, E. 1999. Provision of electronic banking in the UK and the Republic of Ireland. International Journal of Bank Marketing. Vol. 17 (2), pp. 72-82.

 

Harrison, T. 2000. Financial services marketing. Wiltshire: Prentice Hall.

 

Hirschman, E. C. 1980. Innovatiness, novelty seeking and consumer creativity. Journal of Consumer Research. Vol. 7, pp. 59-73.

 

Howcroft, B. & Hamilton, R. & Hewer, P. 2002. Consumer attitude and the usage and adoption of home-banking in the United Kingdom. International Journal of Bank Marketing. Vol. 20 (3), pp. 111-121.

 

Jayawardhena, C. & Foley, P. 2000. Changes in the banking sector – the case of Internet banking in the UK. Internet Research: Electronic Networking Applications and Policy. Vol. 10 (1), 19-30.

 

Mahajan, V. & Muller, E. & Srivastava, R. K. 1990. Determination of adopter categories by using innovation diffusion models. Journal of Marketing Research Vol. 27 (1), pp. 37-50.

 

Mattila, M. & Pento, T. 2002. Development of electronic distribution channels in Finland – M-banking usage and consumer profiles. Die Banking und Information Technologie. Vol. 2, pp. 41-49.

 

Mohr, J. 2001. Marketing of high-technology products and innovations. Upper Saddle River: Prentice Hall.

 

Moore, G. C. & Benbasat, I. 1991. Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research. Vol. 2 (3), pp. 192-222.

 

Polatoglu, V. N. & Ekin, S. 2001. An empirical investigation of the Turkish consumers’ acceptance of Internet banking services. International Journal of Bank Marketing. Vol. 19(4), pp. 156-165.

 

Rogers, E. M. 1995. Diffusion of innovations. 4^th edition. New York: Free Press.

 

Tan, M. & Teo, T. S. H. 2000. Factors influencing the adoption of Internet banking. Journal of the Association for Information Systems. Vol. 1 (5), pp. 1-42.