Information as a Barrier to Innovation Adoption. Tommi Laukkanen, Suvi Sinkkonen, Pekka Laukkanen, University of Kuopio, Kuopio, Finland.

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1 Information as a Barrier to Innovation Adoption Tommi Laukkanen, Suvi Sinkkonen, Pekka Laukkanen, University of Kuopio, Kuopio, Finland Abstract This paper is a preliminary exploration of the role of information as a to innovation adoption. Earlier literature has suggested five s namely Usage, Value, Risk, Tradition and Image s to explain consumer resistance to innovations. We will seek to ascertain if the information constitutes the sixth. The study was conducted in a mobile banking context representing an innovation with currently relatively low usage rates by consumers but with high future success expectations on the part of the service providers. An online questionnaire was developed and 1,540 responses among mobile banking non-users were collected. The results of the Principal Component Analysis suggest that information constitutes a distinct sixth factor explaining consumer resistance to innovations. Keywords: Consumer resistance, Information, Innovation, Adoption Introduction While adoption of innovations has received a lot of academic interest, innovation resistance has been neglected in this respect, with only few studies focusing on the subject. Most studies on innovations have focused on the rate of diffusion of innovations and the reasons why consumers have adopted them. Therefore, it is argued that the vast body of literature on innovations has suffered from pro-change bias (Sheth, 1981; Ram, 1987; Rogers, 2003), which assumes that all innovations are always good and should be adopted by everyone (Rogers, 2003). The premise of the assumption is that innovations are always improvements on existing product or service substitutes (Ram, 1987). However, Ram and Sheth (1989) note that organizations are faced with product failures and one of the major causes for the failures is the resistance the innovations encounter among consumers. Sheth (1981) further argues that since the vast majority of consumers have no a priori desire to change, we might actually learn more by concentrating on understanding the reasons for innovation resistance rather than on the reasons for adoption. Thus, the interest in studying consumer resistance to innovations is to identify the reasons that prevent consumers from adopting an innovation. Ram and Sheth (1989) explain consumer resistance to innovations through five s namely Usage, Value, Risk, Tradition and Image s. They suggest that the usage comes into operation when an innovation is not compatible with existing workflows, practices or habits, while the value is based on the monetary value of an innovation referring to an idea that if the innovation does not offer superior performance-to-price compared to its substitutes, it is not worthwhile for consumers to change their ways of performing their tasks. Indeed, Dunphy and Herbig (1995) note that an important reason for the failure of many products and services is the lack of acceptance by the "pragmatists", those who believe that the cost of learning the innovation far outweighs the benefits it may have offer them. The risk, for its part, refers to the degree of risks an innovation entails (Ram and Sheth, 1989). Uncertainty is inherent in innovations, and therefore, they always entail at least 3062

2 some degree of perceived risk. Further, the tradition mainly implies the change an innovation may cause in daily routines. If these routines are important to a consumer, the tradition will most likely be high. Moreover, behavior that is contrary to a consumer s social and family values and social norms will influence in the tradition (Ram and Sheth, 1989). Finally, the image comes into play since innovations attain a certain identity from their origins, such as the product category to which they belong, the country of origin or brand. Thus, the image originates from stereotyped thinking and hampers the adoption of an innovation (Ram and Sheth, 1989). Ram and Sheth (1989) argue that consumers primarily resist an innovation because it either conflicts with their prior beliefs or because it threatens to create changes in their wellestablished routines. However, it is argued that technological innovations, especially, as being knowledge intensive innovations, involve substantial learning effort and thus require the ability and willingness to learn and acquire knowledge (Saaksjarvi, 2003). Wilton and Pessemier (1981) have argued that limited offering of relevant information or possible misinformation will discourage innovation adoption. Therefore, we suggest that information, or lack of information, as a to innovation adoption should be discussed and explored more thoroughly. The interest of this paper is to make a tentative exploration to ascertain if the information forms a separate to innovation adoption. Mobile banking represents an innovation with currently relatively low usage rates by consumers but high future success expectations among service providers. The first applications of mobile banking were already introduced in the mid-nineties, enabling customers to make payments and request account balances via mobile phone as an SMS service. However, while Internet banking has been a successful innovation in many developed countries, mobile banking adoption rates have so far been rather low. Thus, mobile banking was used as a context in this study. The following section outlines the earlier literature on Internet and mobile banking seeking the resistance generating factors among consumers in the context. Thereafter, the questionnaire development, data and methods are explained. Finally, results are presented and conclusions with future research avenues discussed. Mobile Banking Barriers The usage is mostly related to the usability of the service and the changes it requires on the part of the consumers. Siau and Shen (2003) note that whilst mobile devices demonstrate a greater extent of mobility and flexibility compared to personal computers and laptops, the small screens of mobile terminals and tiny multifunction keypads are cumbersome to use further inhibiting data input and output. Earlier literature on mobile banking shows that smaller screens are adequate in information-based services but services requiring transactions call for bigger screen size (Laukkanen, 2007). For example, bill payment via mobile phone is perceived to be quite difficult and time-consuming by some consumers as the device enables only a limited amount of information processing and hence the whole bill is not visible on the display (Laukkanen and Lauronen, 2005). Moreover, in their qualitative study Laukkanen and Lauronen (2005) report that those mobile banking services that do not require PIN and TAN codes, such as request for account balance service, creates convenience, ease of use and efficiency to the service consumption. The value refers to performance-to-price value compared to substitutes. It has been argued that costs of mobile banking services can be a drawback to some consumers' mobile 3063

3 banking adoption (Scornavacca and Barnes, 2004; Luarn and Lin, 2005). Furthermore, the availability of substitutes can be seen as a key threat to the viability of mobile banking (Barnes and Corbitt, 2003). However, some of the mobile banking services appear to increase customers' feeling of control over their financial affairs (Laukkanen and Lauronen, 2005). The risk refers to the risks consumers encounter or perceive in innovations. Fain and Roberts (1997) point out that marketers should keep in mind that risk is rather a perception of a consumer than a characteristic of a product. Some customers, for example, are afraid that they may make mistakes when conducting their bank affairs using a mobile phone (Laukkanen and Lauronen, 2005). In mobile banking especially the data input and output mechanisms are argued to impede the banking process creating feelings of insecurity (Laukkanen and Lauronen, 2005). Mobile phones may also be limited in computational power, memory capacity and battery life limiting the usage of mobile services in complicated business environments (Siau and Shen, 2003). In addition, some studies state that security issues can have a major role in inhibiting consumer adoption of mobile banking services (Brown et al., 2003; Luarn and Lin, 2005), while some other studies (e.g. Laukkanen and Lauronen, 2005) argue the opposite. It may be that in mobile banking the tradition exists among those consumers who simply prefer to deal directly with the bank clerk instead of using arms-length technologies. Hence, not all customers may see the need for new, parallel channels. Finally, the image could be considered as the image of mobile banking services in general. In 1997 Fain and Roberts stated that the image in electronic banking emerges from the negative "hard-to-use" image of computers in general and the Internet channel in particular. This may also be the case today in mobile banking among some bank customers. Thus, it may be that some consumers perceive the technology to be too difficult to use, so they instantly form a negative image of the service related to the technology. It has further been suggested that for the adoption of online banking in general, it is necessary that banks make their customers aware of the availability of such a service and explain how it adds value relative to other ways of conducting banking services (Sathye, 1999). In their study Kuisma et al. (2007) found that some Internet banking non-users suffered from a lack of information and felt that they had not received enough information or help from the bank concerning Internet banking services resulting uncertainty toward the service. Jayawardhena and Foley, 2000) note that the information about the services provided should be detailed enough and easily available on the web pages. Indeed, in order to enable customers to perform transactions individually it has been found to be important that the information is available before but also during the usage of the service (Filotto et al., 1997). In their study, Kuisma et al. (2007) placed lack of information under the risk. However, in this study we aim to explore if the information forms a distinct in addition to the five s suggested by the earlier literature. Data and Methods An online survey was conducted. A questionnaire was designed based on the theory of innovation resistance and existing mobile banking literature. Altogether, a set of 17 variables examining the five different s to mobile banking resistance and, in addition, a set of three variables examining respondents' perceptions of the information about mobile banking services were selected for the study (Table 1). The respondents' reactions to the statements 3064

4 were measured using a seven-point Likert scale ranging from totally disagree (1) to totally agree (7). The questionnaire was placed on the log-out page of a large Scandinavian bank s online service in Finland, thereby only reaching users of online banking services. The questionnaire was open for 72 hours from noon to noon between November 6th and 9th This yielded 2,060 responses in total, of which 1,540 (74.8 %) respondents did not have experience and 520 (25.2 %) had experience of using a mobile phone for banking transactions. The interest of this paper is in those bank customers not having experience of using mobile banking services. Principal Component Analysis with Varimax rotation was used in order to identify the underlying structure of relationships between the measured items. Table 1: Measure Items Barrier Usage Value Risk Tradition Image Information *Inverted variables Variables V1: In my opinion, mobile banking services are easy to use* V2: In my opinion, the use of mobile banking services is convenient* V3: In my opinion, mobile banking services are fast to use* V4: In my opinion, progress in mobile banking services is clear* V5: The use of changing PIN codes in mobile banking services is convenient* V6: The use of mobile banking services is economical* V7: In my opinion, mobile banking does not offer any advantage compared to handling my financial matters in other ways V8: In my opinion, the use of mobile banking services increases my ability to control my financial matters by myself* V9: I am afraid that while I am paying a bill by mobile phone, I might make mistakes since the correctness of the inputted information is difficult to check from the screen V10: I am afraid that while I am using mobile banking services, the battery of the mobile phone will run out or the connection will otherwise be lost V11: I fear that while I am using a mobile banking service, I might tap out the information of the bill wrongly V12: I am afraid that the list of PIN codes may be lost and end up in the wrong hands V13: I trust that while I am using mobile banking services, third parties are not able to use my account or see my account information* V14: Visiting the bank branch and chatting with the teller is a nice occasion on a weekday V15: I find self-service alternatives more pleasant than personal customer service* V16: In my opinion, new technology is often too complicated to be useful V17: I have such an image that mobile banking services are difficult to use V18: In my opinion, there is enough information available about mobile banking services V19: I feel that the bank has guided me enough related to mobile banking services V20: I feel that when needed, I will get enough guidance from the bank related to mobile banking services Results First the items measuring the five s presented by the theory were analyzed. Even though there existed an underlying structure based on the theory in the set of selected variables the number of factors was not predetermined. The Principal Component Analysis correctly suggested five factors examining the resistance (Table 2: figures in brackets). Out of the selected variables, variable V6 was the only one that did not load correctly, as it loaded under the usage instead of the value. However, the difference between the correlations of the variable with the usage and the value were not remarkable. Thereafter, we included the set of three items measuring the respondents' perceptions on the information about mobile banking services. The Principal Component Analysis suggested six 3065

5 factors examining the resistance (Table 2), indicating that the three added variables about information represented a distinct factor. The analysis with the three added variables yielded even better loadings as the variable V6 loaded correctly under the value. Table 2: Factor Loadings for the Variables V1-V17 and V1-V20 Variables Factor 1 (Usage Factor 2 (Value Factor 3 (Risk Factor 4 (Tradition Factor 5 (Image Factor 6 (Information V1 (0.857) V2 (0.884) V3 (0.857) V4 (0.889) V5 (0.727) V6 (0.437) (0.378) V7 (0.764) V8 (0.708) V9 (0.820) V10 (0.838) V11 (0.865) V12 (0.721) V13 (0.427) V14 (0.780) V15 (0.839) V16 (0.780) V17 (0.733) V V V Conclusions and Future Research Innovations have been, and will continue to be, a major subject in marketing management and consumer behavior. While the majority of the studies on innovations have focused on successful innovations and their adoption, resistance to innovations has been neglected in this respect. There are very few studies in the earlier literature focusing on consumer resistance to innovations. One of the fundamental studies in the field by Ram and Sheth (1989) categorizes consumer resistance to innovations into five resistance s namely Usage, Value, Risk, Tradition and Image s. However, technological innovations, especially, involve substantial learning effort and thus require the ability and willingness to learn and acquire knowledge among consumers (Saaksjarvi, 2003). It is further argued that a limited supply of relevant information or possible misinformation will discourage innovation adoption (Wilton and Pessemier, 1981). Therefore, we suggested that information, or lack of information, might constitute a to the adoption of a technological innovation. As a tentative exploration we used Principal Component Analysis and showed that information constitutes a distinct sixth to innovation adoption. Future research should pay more attention to the role of information in consumer resistance to innovations. For example, confirmatory factor analysis and Structural Equation Modeling could be used to test the resistance model with and without the suggested Information. 3066

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