10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 THE EFFECTS OF INNOVATION CHARACTERISTICS ON MOBILE BANKING ADOPTION ULUN AKTURAN Asst.Prof.Dr. Galatasaray University Faculty of Economics and Administrative Sciences Ciragan Cad. No: 36 Ortakoy/ISTANBUL Phone: 00 90 532 374 77 45, Fax: 00 90 212 258 22 83 E-mail: uakturan@yahoo.com NURAY TEZCAN Asst.Prof.Dr. Halic University Faculty of Management Emekyemez Mah. Okçu Musa Cad. Mektep Sok. No: 21 Sishane/İSTANBUL Phone: 00 90 532 700 81 46 , Fax: 00 90 212 297 31 44 E-mail: tezcan_nuray@yahoo.com October 15-16, 2010 Rome, Italy 1 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 THE EFFECTS OF INNOVATION CHARACTERISTICS ON MOBILE BANKING ADOPTION Asst.Prof.Dr. Ulun Akturan, Galatasaray University, Turkey Asst.Prof.Dr. Nuray Tezcan, Halic University, Turkey ABSTRACT This study aims to determine the effect of innovation characteristics on mobile banking adoption intention. In the study, the eight characteristics of innovation- relative advantage, compatibility, complexity, image, result demonstrability, visibility, trialability, and voluntariness- are portrayed and their combined effect on adoption intention was searched. The data was collected from 311 college students- who are described as young prospects- and the research hypothesis tested by SEM. The results provide support for the theoretical relationship between the relative advantage and compatibility, and mobile banking adoption. However, no relationship was found between image, result demonstrability, complexity, trialability, and adoption intention. INTRODUCTION The business of banking has changed by the developments in technology. The increasing use of information technologies enabled banking applications to be transformed to electronic and even mobile devices. Electronic banking has become very successful as a retail distribution channel for banks. Since the introduction of e-banking service in 1995, the number of consumers using e-banking has grown steadily. Gan et al. (2006) predicted that ebanking is necessary for banks to stay profitable in the future. Today, mobile banking is emerging as a new channel. The innovations in telecommunications have led the use of mobile devices in banking services (Suoranta and Mattila, 2004). Mobile banking is defined as the “a type of execution of financial services in the course of which- within an electronic procedure- the consumer uses mobile communication techniques in conjunction with mobile devices” (Pousttchi and Schurig, 2004: October 15-16, 2010 Rome, Italy 2 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 1). With their cell phone, consumers can access their accounts and check account balances, pay bills, and perform other banking transactions (Brown et al., 2003). Mobile banking is an important application of mobile commerce since it is an additional source of revenue to both banks and telecom services. In 2000s, mobile banking has been described as the most important distribution channel for retail banking. However, the adoption of mobile banking has not been as rapid as the new mobile devices. This slow start is partly resulted from the poor technology of the mobile handsets. But the new generation of mobile phones and the reduced costs accelerated its usage (Riivari, 2005). Therefore it is still growing and there are opportunities for mobile banking applications to expand. The worldwide number of users of mobile banking and related services is forecasted to grow from 55 million users in 2009 to reach 894 million users in 2015 (Berg Insight, 2010: Mobile Banking and Payments Report). Mobile banking services represent an innovation as an intangible service and a medium of service delivery employing high technology (Suoranta and Mattila, 2004). Since it is an innovative application, it is important to understand the perception of mobile banking as innovation. Besides in the literature it was revealed that the perception of innovation characteristics has an important influence on acceptance behavior (Agarwal and Prasad, 1997; Van Slyke et al., 2002; Moore and Benbasat, 1991). In the literature, the mobile banking usage intention was explained in relation with the TAM (Technology Acceptance Model) (Luarn and Lin, 2005), and trust and firm reputation (Kim et al., 2009). Brown et al. (2003) investigated the effects of some of the innovation characteristics (relative advantage, perceived compatibility, perceived complexity and trialability), along with experience, perceived risk, banking needs and self efficacy on the usage intention. October 15-16, 2010 Rome, Italy 3 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 This study aims is to determine the perceived characteristics of innovation (PCI) of mobile banking applications and its effect on the adoption intention. In the study, the combined effect of PCI was searched Mobile Banking Applications M-commerce embodies business transactions conducted thorough mobile communication networks or the internet (Kim et al., 2009). The distinctive values of mcommerce are convenience, ubiquity, flexibility and contextuality (Lee and Benbasat, 2003; Venkatesh et al., 2003). Mobile banking enables customers to execute conventional and more advanced financial transactions and provide the wireless and mobile values of m-commerce. In order to use the service, a cell phone equipped with a built-in chipset or WAP (Wireless Access Protocol) and an activation of the banking service is needed. There are customer requirements to mobile banking applications that the banks should pay attention. These are grouped under four categories as technical, usability, design and security requirements (Pousttchi and Schurig, 2004: 3-4): As technically; the usage should be possible with both kinds of available mobile devices. The application should adapt to the conditions of the mobile device automatically. The usage must be possible for customers of any MNO. And the amount of transmitted data should be s small as possible. For the usability; it must be possible to work offline with the application. There should be a simplified method of data input. The application should allow the user to resume his usage and the information should be available with just a few “clicks”. For the design; the application should be personalized. The user should easily switch to a version of the application a wider range of functions. The application should provide push functionality. There should be a wide range of functionality, similar to the one in the electronic banking. For the security; the transmission of the data has to be encrypted. Before usage, access to the data must be authorized and the authorization has to be simple. October 15-16, 2010 Rome, Italy 4 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 Mobile banking application creates value not only for the customers but also for the banks. Mobile banking improves customer services, reduces costs, increase the reactivity of the company, increase market share and reinforce brand image (Riivari, 2005). Innovation Characteristics Innovation has been described as “an idea, material, or artifact perceived to be new by the relevant unit of adoption” (Agarwal and Prasad, 1997: 560). Innovation exists to the extent that the potential adopter finds it new or unlike any other products (Garcia and Calantone, 2002). Some innovations perceived as minor while some are perceived as great. The characteristics of an innovation influence the consumer’s impression of the product. Diffusion is “the process by which an innovation is communicated through certain channels over time among the members of a social system (Rogers, 1995: 5). The characteristics of an innovation affect the likelihood and speed of purchase (Holak and Lehmann, 1990). Rogers (1995: 15-16) defined five major innovation characteristics: Relative advantage, “is the degree to which an innovation is perceived as better than the idea it supersedes. The greater the perceived relative advantage, the more rapid its rate of adoption will be”. Compatibility, is the degree to which an innovation is perceived as being consistent with the existing values, past experiences, and needs of potential adopter. The adoption of an incompatible innovation requires the prior adoption of a new value system which is a relatively slow process”. Complexity, is the degree to which an innovation is perceived as difficult to understand and use. The innovations that are simpler to understand are adopted more rapidly than the innovations that require the adopter to develop new skills and understandings. October 15-16, 2010 Rome, Italy 5 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 Trialability, is the degree to which an innovation may be experimented with on a limited basis. An innovation that is trialable represents less uncertainty to the adopter”. Observability, “is the degree to which the results of an innovation are visible to others. The innovations that are relatively less observable diffuse more slowly”. Moore and Benbasat (1991: 195-203) identified three additional characteristics as: Image, “the degree to which use of an innovation is perceived to enhance one’s image or status in one’s special system. The desire to gain social status is an important motivation for someone to adopt an innovation”. Voluntariness of use, “the degree to which use of an innovation is perceived as being voluntary or of free will. When an innovation is mandatory, the freedom of choice of adoption. The behavior is influenced by the perception of voluntariness much more than the actual voluntariness”. Result demonstrability, “the tangible of the results of using an innovation. The greater the perceived result demonstrability, the more rapid its rate of adoption will be”. RESEARCH METHODOLOGY Research Model The research model of the study derived from the literature is given in Figure 1. Consistent with the theory, the model embodies eight PCI instruments and adoption intention of mobile banking. The main research hypothesis is stated as below: H1: The perceived characteristics of innovation in relation with mobile banking influence the adoption intention. <Figure 1> October 15-16, 2010 Rome, Italy 6 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 Measures and Data Collection The questionnaire was formed as including multi- item measures of the perceived characteristics of innovation and adoption intention. All the scales were five-point Likert type scales. To measure perceived characteristics of innovation PCI scale adapted by Gounaris and Koritos (2008) and to measure adoption intention the scale developed by Kim et al. (2007) were used. Gounaris and Koritos (2008) adapted the PCI scale developed by Moore and Benbasat (1991) to the internet banking. The scales are given in the Appendix. The data used in the research was collected by face-to-face interviews. The subjects in this study are undergraduate and graduate students. The sample exhibits the characteristics of being a potential customer of mobile banking. Moreover, earlier adopters of technological innovations are often described as being relatively young, better educated, having higher income and having higher occupations (Suoranta and Mattila 2003). Therefore the sample consisted of future prospects for the mobile banking. Besides, the subjects in the sample were the non-user of the mobile banking applications. The soci-demographics of the sample is given in Table 1. <Table 1> RESEARCH FINDINGS In the study, to test the research hypothesis Structural Equation Modeling (SEM) was used. Before testing the hypothesis, because multi-item scales were used, reliability and validity analysis were executed. Table 2 displays the results of the validity and reliability analysis. To assure validity exploratory factor analysis was run, and to assure reliability Cronbach’s Alpha was used. <Table 2> October 15-16, 2010 Rome, Italy 7 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 As a result of the validity and reliability analysis eight variables eliminated from the PCI scale and five factor solution was reached, while no variables were deleted from the adoption intention scale. The innovation characteristics “relative advantage” and “compatibility” was found loaded on Factor 1, and “voluntariness” and “visibility” were found as having low Cronbach’s Alpha values (,617 and ,570) and deleted from the scale. These results are similar to the study of Agarwal and Prasad (1997). <Figure 2> After the reliability and validity analysis, the research hypothesis was tested by Structural Equation Modeling (SEM). In Figure 2 the structured model can be seen. The variables included in the model is displayed in Table 3. <Table 3> As it can be seen from the Table 3, the model includes 53 variables. 23 of them are observed variables and 30 of them are unobserved variables. The unobserved variables include 24 variables which are showing error and are identified as “e” and 6 latent variables. The evaluation criteria and values related with the fitness of the data and the model are given in Table 3 in details. <Table 4> As can be seen from Table 4, there are several criteria looked at while evaluating the goodness-of-fit between the model and the data. The first measure is the likelihood ratio chisquare statistics. This value has a statistical significance (p=0.000). And 2/sd ratio, which should be between 2 and 5, is 2.406. The other goodness of fit measures- GFI (0.878), NFI (0.871), RFI (0.848), IFI (0.920), TLI (0.905) and CFI (0.920)- should be close to 1.0 and in the study their values indicate the fitness between the model and the data. At last, in order to determine the required minimum sample Hoelter .05 and Hoelter .01 indexes were used. To test the hypothesis at %95 confidence interval level and 0.05 significance level, the required October 15-16, 2010 Rome, Italy 8 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 minimum sample size was determined as 150 and to test the hypothesis at %99 confidence interval level and 0.01 significance level, the required minimum sample size was determined as 160. The research sample (311) is much more than the minimum sample size. <Table 5> Table 5 displays the regression weights. As it is seen, only the “relative advantage & compatibility” has a significant effect on mobile banking adoption intention. The other innovation characteristics- trialability, image, result demonstrability and complexity- do not significantly affect the mobile banking adoption. Therefore the research hypothesis was partially accepted. In order to identify the explanatory power of the model, R2 values were used. R2 values represent the explanatory power of the dependent variables and the overall adequacy of the model and found in this study as 0,203. It means that relative advantage and compatibility explains 20 % of the adoption intention of mobile banking. This is not a high value but there are numerous other variables affecting mobile banking adoption intention and in this study just innovation characteristics were examined. Hence the R2 value can be acceptable. DISCUSSION Adoption is defined as “a decision to make full use of an innovation as the best course of action available. Rejection is a decision not to adopt an innovation” (Rogers, 2003: 117). Perceived attributes of an innovation is important in explaining the rate of adoption. This study examines the effect of innovation characteristics on the mobile banking adoption intention. From the underlying theory, the assumption was developed as there is a combined effect of innovation characteristics. However it was found that not all innovation characteristics emerged as predictor but relative advantage and compatibility. Relative advantage is the perception of innovation as a better idea. It is cited as a remarkable variable in the adoption intention and most commonly found significant. October 15-16, 2010 Rome, Italy 9 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 Perception of relative advantage is the outcome of the comparison made by the potential adopters between the existing technology and the new technology. This study bring out that when the prospects perceive that using mobile banking speeds up banking, improves the quality of banking, makes banking easier, gives greater control in banking and enhances banking activities their usage intention increases. Compatibility, is the perception of innovation as being consistent with the existing values, past experiences, and needs of potential adopter. It is related with how well the innovation fits into the adopters’ existing social structure. When an innovation perceived as compatible, it is perceived as consistent with an individual’s life situation. In this study compatible was found as an important innovation characteristic that has a significant effect on adoption intention. When the prospects perceive that using mobile banking is compatible with all aspects of banking, is completely compatible with their current ways of banking and fits well with the way they like to do banking, they tend to adopt it. Moreover, it was found that image, trialability, result demonstrability and complexity do not influence the adoption intention of mobile banking. Therefore the banks should focus on communicating information that emphasizes the relative advantage of mobile banking compared to other banking channels and its compatibility with the existing values, past experiences and needs of the prospects. As a further research the adoption intention of mobile banking should be investigated through other underlying variables and a more comprehensive model should be developed. REFERENCES Agarwal, R. & Prasad, J. (1997). The Role of Innovation Characteristics and Perceived Voluntariness in The Acceptance of Information Technologies. Decision Sciences, Vol:28, No:3, pp.557-582. Brown, I., Zaheda, C., Davies, D. & Strobel, S. (2003). Cell Phone Banking: Predictors of Adoption in South Africa- an Exploratory Study. International Journal of Information Management, Vol:23, pp.381-394. Gan, C., Clemens, M., Limsombunchai, V. & Weng, A. (2006). A logit analysis of electronic banking in New Zealand. International Journal of Bank Marketing, Vol. 24 No. 6, pp. 360-83. October 15-16, 2010 Rome, Italy 10 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 Garcia R. & Calantone R. (2002). A Critical Look at Technological Innovation Typology and Innovativeness Terminology: A Literature Review. Journal of Product Innovation Management, Vol:19, pp.110–132. Gounaris, S. & Koritos, C. (2008). Investigating the Drivers of Internat Banking Adoption Decision A Comparison of Three Alternative Frameworks. International Journal of Bank Marketing, Vol:26, No:5, pp.282-304. Holak, S.L. & Lehmann, D.R. (1990). Purchase Intentions and the Dimensions of Innovation: An Exploratory Model. Journal of Product Innovation Management, Vol:7, pp.59–73. Kim, G., Shin, B. & Lee, H.G. (2009). Understanding Dynamics Between Initial Trust and Usage Intentions of Mobile Banking. Information Systems Journal, Vol:19, pp.283-311. Kim, H.W., Chan, H.C. & Gupta Sumeet (2007). Value-based Adption of Mobile Internet: An Empirical Investigation. Decision Support Systems, Vol:43, pp.111-126. Lee, Y. & Benbasat, I. (2003) Interface Design for Mobile Commerce. Communications of the ACM, Vol: 46, pp.49–52. Luarn, P. & Lin, H.H. (2005). Toward an Understanding of The Behavioral Intention to Use Mobile Banking. Computers in Human Behavior, Vol:21, pp.873-891. Moore, G.C. & Benbasat, I. (1991). Development of an Instrument To Measure The Perceptions of Adopting an Information Technology Innovation. Information Systems Research, Vol:21, No:3, pp.192-222. Pousttchi, K. & Schurig, M. (2004). Assessments of Today’s Mobile Banking Applications From the View of Customer Requirements. Proceedings of the Hawai’I International Conference on System Sciences, January 5-8. Riivari, J. (2005). Mobile Banking: A Powerful New Marketing and CRM Tool for Financial Services Companies All Over Europe. Journal of Financial Services Marketing, Vol:20, No:1, pp.11-20. Rogers, E.M. (1995). The Diffusion of Innovations. 4th Edition, The Free Press, New York. Rogers, E.M. (2003). The Diffusion of Innovations. 5th Edition, The Free Press, New York Suoranta, M. & Mattila, M. (2004). Mobile Banking and Consumer Behaviour: New Insights into the Diffusion Pattern. Journal of Financial Services Marketing. Vol:8, No:4, pp.354-366. Van Slyke, C., Lou, H. & Day, J. (2002). The Impact of Perceived Innovation Characteristics on Intention to use Groupware, Information Resources Management Journal, Vol:15, No:1, pp. 5–12. Venkatesh, V., Ramesh, V. & Massey, A.P. (2003) Understanding Usability in Mobile Commerce. Communications of the ACM, Vol:46, pp.53–36. Acknowledgments The authors would like to thank to Galatasaray University Scientific Research Projects Commission for the support provided (Research Project No. 09.102.009). October 15-16, 2010 Rome, Italy 11 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 TABLES AND FIGURES Perceived Characteristics of Innovation- PCI - relative advantage - compatibility - image - ease of use - result demonstrability - visibility - trialability - voluntariness ADOTION INTENTION Figure 1: The Research Model Table 1: The Demographic Characteristics of The Sample Age 18 19 20 21 22 23 24 25 Total Family Income (USD) 2.000 USD or below 1.001-3.500 USD 3.501 USD and above Total October 15-16, 2010 Rome, Italy n % 8 34 76 52 57 37 29 18 311 2.6 10.9 24.4 16.8 18.3 11.9 9.3 5,8 100.0 n 137 72 102 311 % 44 23.1 32.8 100.0 Monthly Expenditure (USD) n % 375 USD and below 376-750 USD 751-1.125 USD 1.126- 1.500 USD 1.501 USD and above 25 57 162 50 17 8 18.3 52.1 16.1 5.5 Total 311 100.0 Gender n % Female Male 173 138 55.6 44.4 Total 311 100.0 12 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 Table 2: Results of Reliability and Validity Analysis No.of Cronbach’s Scales Items Alpha F1: Relative Advantage & Compatibility 8 ,869 F2: Trialability 3 ,856 F3: Image 3 ,839 F4: Result Demonstrability 3 ,813 F5: Complexity 3 ,738 ADI: Adoption Intention 3 ,941 1 Total Variance Explained ,528 ,782 ,756 ,726 ,657 ,894 v21 e8 1 v22 e7 1 v23 e6 1 v24 e5 1 F1 v25 e4 1 v26 e3 1 1 v27 e2 1 v28 e1 1 v42 e11 1 v43 e10 1 e28 1 1 F2 v44 e9 ADI 1 v49 v50 v51 1 v29 e14 1 e13 1 e12 1 e17 1 e16 1 e15 1 e20 1 e19 1 e18 v30 1 F3 v31 v35 v36 1 F4 v37 v32 v33 1 F5 v34 Figure 2: The Structured Research Model October 15-16, 2010 Rome, Italy 13 1 e25 1 e26 1 e27 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 Table 3: The Variables in The Research Model Number of variables in the model 53 Number of observed variables 23 Number of unobserved variables 30 Number of exogenous variables 29 Number of endogenous variables 24 Table 4: Goodness of Fit Fit Measure Discrepancy (2) Degrees of freedom P Discrepancy / df (2/sd) Goodness of Fit Adjusted Goodness of Fit Normed fit index Relative fit index Incremental fit index Tucker-Lewis index Comparative fit index RMSEA Hoelter ,05 index Hoelter ,01 index Default model 517,221 215 ,000 2,406 ,878 ,843 ,871 ,848 ,920 ,905 ,920 ,067 150 160 Saturated 0.000 0 1.000 1.000 1.000 0,05<RMSEA<0,08 Abbreviations CMIN DF P CMINDF GFI AGFI NFI RFI IFI TLI CFI RMSEA HFIVE HONE Table 5: Regression Weights Estimate Adoption Intention <-Adoption Intention Adoption Intention Adoption Intention Adoption Intention R2: ,203 <-<-<-<-- Relative Adv.& Compatibility Trialability Image Result Demonstrability Complexity S.E. ,178 4,241 *** -,048 ,071 ,168 ,021 ,096 -,494 ,073 ,965 ,116 1,453 ,074 ,287 ,621 ,335 ,146 ,774 Perceived Characteristics of the Innovation (PCI; Gounaris and Koritos, 2008- adapted from Moore and Benbasat, 1991) Relative advantage . Using mobile banking speeds up banking. . Using mobile banking improves the quality of banking. . Using mobile banking makes banking easier. . Using mobile banking gives me greater control in banking. . Using mobile banking enhances banking. October 15-16, 2010 Rome, Italy 14 Sig. ,754 Appendix Complexity (Ease of use) . Overall, I believe that mobile banking is easy to use. . Learning to operate mobile banking is easy for me. t 10th Global Conference on Business & Economics ISBN : 978-0-9830452-1-2 . I believe that it is easy to get mobile banking to do what I want it to do. Compatibility . Using mobile banking is compatible with all aspects of banking. . Using mobile banking is completely compatible with my current ways of banking. . I think that using mobile banking fits well with the way I like to do banking. Image . People who use mobile banking have a high profile. . People who use a mobile banking have more prestige than those who do not. . Using mobile banking is a status symbol. Result demonstrability . I would have no difficulty telling others about the results of using mobile banking. . I would have difficulty explaining why using mobile banking may or may not be beneficial. . The results of using mobile banking are apparent to me. Visibility . I have not seen many others using mobile banking. . I have seen what others do using mobile banking. . It is easy for me to observe others using mobile banking. Trialability . Before deciding whether to use mobile banking, I can properly try it out. . Mobile banking is available to me to adequately try it. . It is permitted to use mobile banking on a trial basis long enough to see what it can do. . I don’t really have adequate opportunities to try out different things on mobile banking. Voluntariness . My bank does not require me to use mobile banking. . Although it was suggested by my bank, using mobile banking is certainly not compulsory. . My use of mobile banking is voluntary. Adoption Intention (Kim et al., 2007) . I plan to use mobile banking in the future. . I intend to use mobile banking in the future. . I predict I would use mobile banking in the future. October 15-16, 2010 Rome, Italy 15