|
...businesses. model consumer adoption was developed and estimated via a two-step procedure. A significant sample selection bias was found with regard to access when estimating consumer adoption of a relatively new innovation, computer banking, but no such bias was found for a mature innovation, ATMs.
**********
Recent advances have introduced innovative ways of using electronic technologies to deliver services to consumers (Bitner, Brown, and Meuter 2000; White 1998). Consumers have increasing access to innovative financial services mediated by electronic banking technologies, ranging from automated teller machines (ATMs) to smart cards and computer banking. Using these innovative services, consumers can conduct fast and convenient financial transactions and obtain account information without visiting banks (Lee and Lee 2000; Lee, Lee, and Schumann 2002; White 1998).
The theory of diffusion of innovations (Rogers 1995) is a well-established theoretical framework (Gatignon and Robertson 1985) that explains how technological innovations spread across individuals within a social system. Diffusion research is currently at a relatively mature stage (Sultan, Farley, and Lehmann 1990). However, most studies have focused on organizational, rather than consumer, adoption of technological innovations (Frambach et al. 1998; Gauvin and Sinha 1993). With an exception of the self-service context (Bitner, Brown, and Meuter 2000; Meuter et al. 2000; Parasuraman 2000), it is not well recognized that an individual consumer's decision to adopt technology-based innovative services is often constrained by access.
For instance, a consumer may want to use computer banking, but if his or her bank does not offer such a service, the consumer cannot adopt it. In this case, the consumer's non-adoption of technological innovations stems from lack of access rather than from his or her reluctance to accept new technology. That is, adoption is observed only when consumers have access to the technology-based service. Therefore, it is necessary to use Heckman's (1979) two-step estimation approach, which adjusts for sample selection bias to estimate individuals' adoption correctly (Boyes, Hoffman, and Low 1989; Meng and Schmidt 1985).
Past research on consumers' adoption of innovations has identified isolating communication factors that can predict individuals' adoption (Lee, Lee, and Schumann 2002). Researchers (Kennickell and Kwast 1997; Lee and Lee 2000) have found that adopters of technology-based financial service innovations have distinct demographic characteristics, such as youth, affluence, and higher education levels. Furthermore, the diffusion literature and previous studies of consumers' use of self-service technology suggest that consumers' perceptions of innovation characteristics, such as complexity, trialability, and observability (Rogers 1995; Strutton, Lumpkin, and Vitell 1994); perceived benefits of technology (Davis 1989; Lee, Lee, and Schumann 2002); reliability (Parasuraman, Zeithaml, and Berry 1988); and security (Swaminathan, Lepkowska-White, and Rat 1999) are potential determinants of consumers' willingness to adopt technology-based service innovations.
The purpose of the current study is to investigate the factors affecting consumers' adoption of technology-based service innovations, while adjusting for sample selection bias associated with limited consumer accessibility to those innovations. The effects of perceived innovation characteristics and individual socioeconomic characteristics on consumers' adoption of technological innovations are estimated using a censored probit model that adjusts for sample selection bias. In order to examine the effect of limited accessibility on consumer adoption, two technology-based service innovations, ATMs and computer banking, were chosen. ATMs and computer banking both fall into the category of "electronic banking technologies"; however, they represent technologies at different stages of their diffusion processes. The ATM is at the mature stage of its diffusion process and is widely available to most consumers, whereas computer banking is a new technology at its early diffusion stage. Such wide variation in the diffusion stages between the ATM and computer banking allows a theoretical examination of the effect of the accessibility factor on consumer adoption (Rogers 1995).
This article is organized as follows. First, a conceptual model of consumer adoption of technology-based service innovations is presented. Based on the conceptual model, research hypotheses are generated regarding the effects of accessibility, perceived innovation characteristics, and individual socioeconomic characteristics on consumers' adoption of technology-based service innovations. Next, an empirical model that examines the effects of the isolating factors on consumer adoption of computer banking and ATMs using a two-step estimation approach is described. Finally, implications of the results of this study are discussed.
A CONCEPTUAL FRAMEWORK
In this section, a conceptual model of consumer adoption of technology-based service innovations drawing on the literature on diffusion of innovations and consumer use of self-service technologies is developed (see Figure). In this model, a consumer's adoption of technology-based service innovations is contingent upon his or her having access to the innovations (the first step). Given that the technology is available, adoption is determined by the individual's particular perception of the technology-based service innovation characteristics and socioeconomic characteristics (the second step).
THE FIRST STEP: ACCESS TO TECHNOLOGY-BASED SERVICE INNOVATIONS
Access to electronic banking technologies is related to whether a consumer is affiliated with a bank that offers those services. In fact, lack of access is reported as the major reason that consumers do not adopt technological innovations, especially if the innovations have been introduced to the market only recently (Zeithaml and Gilly 1987). In practice, financial institutions use segmentation strategies for offering technology-based services based on customers' incomes (Burnett 1990; Hefter 1987; Raddon 1996), education (Hefter 1987), and age (Murphy and Rogers 1986; Raddon 1996; Stanley, Ford, and Richards 1985). Therefore, a consumer's likelihood of having access to technology-based financial service innovations is a function of these variables.
ACCESS = [f.sub.ACCESS] (income, education, age)
THE SECOND STEP: ADOPTION OF TECHNOLOGY-BASED SERVICE INNOVATIONS
Perceptions of innovation characteristics and socioeconomic characteristics have been proposed as determinants of consumers' adoption of technological innovations (Gatignon and Robertson 1985). Ostlund (1974) and Labby and Kinnear (1985) suggest that perceived innovation characteristics can be significant predictors of consumer adoption and that the predictive power of these variables is stronger than socioeconomic characteristics.
Perception of innovation characteristics relevant to technology-based service innovations includes perceived benefits of technology (Davis 1989; Lee, Lee, and Schumann 2002), reliability (Dabholkar 1996; Parasuraman, Zeithaml, and Berry 1988), security (Swaminathan, Lepkowska-White, and Rao 1999), complexity (Davis 1989; Rogers 1995), need for human interaction (Crosby, Evans, and Cowles 1990), trialability (Rogers 1995), and observability (Rogers 1995). Selected individual characteristics, such as age, education, and income (Rogers 1995), also affect consumer adoption of new technologies. Having a personal computer (PC) at home may also encourage consumer adoption of computer banking. Thus, given access, consumer adoption of electronic banking technologies can be modeled as follows.
ADOPT = [f.sub.ADOPTION][perceived benefits, reliability, security, complexity, triability, observability, income, education, age, PC at home for computer banking |ACCESS]
HYPOTHESES DEVELOPMENT
Perceived Innovation Characteristics
Perceived Benefits of Technology. Davis (1989) asserts that the decision to use a new technology is determined by the extent to which the consumer believes it is cost effective in providing goods or services compared to the current method. Perceived benefits of electronic banking are conceptually similar to Rogers' (1995) relative advantage, defined as "the degree to which an innovation is perceived better than the idea it supercedes" (p. 212). Past studies have found that relative advantage has a significant effect on consumers' adoption of many technological innovations (Tornatzky and Klein 1982).
Convenience and effective management of personal finances comprise two major advantages of using technology-based financial service innovations. Zeithaml and Gilly (1987) found that consumers who use ATMs and electronic funds transfer (EFT) give convenience as the reason for their adoption decision. Electronic banking also provides consumers with more flexibility in managing their finances and control over their accounts (US Banker 1997). For example, computer banking allows customers to know their exact daily balances and to pay or delay paying other bills accordingly. Therefore, if a consumer perceives a technology-based financial service innovation is convenient and helps to manage personal finances effectively, then he or she is more likely to adopt the technology-based service innovation.
Hypothesis 1: Perceived benefits of technology have a positive effect on consumer adoption of technology-based service innovations.
Reliability. Reliability refers to the degree to which a consumer believes a new technology will perform a job consistently and accurately. Reliability is considered to be critical to whether or not a consumer decides to adopt various technology-based services (Health Care Strategic Management 1997; Mohamed 1992; Simms 1999; Smith 1996; Takac and Singh 1992). Lewis (1989) applies the SERVQUAL scale to the bank-marketing context and confirms that reliability cannot be ignored in a consumer's evaluation process of technology-based financial services. If the potential adopter of technology-based service innovations perceives the new technology is not reliable and believes mistakes are likely to occur, then s/he is not likely to adopt (Dabholkar 1996). Therefore,
Hypothesis 2: Perceived reliability has a positive effect on consumer adoption...
NOTE: All illustrations and photos
have been removed from this article.
Looking for additional articles?
Search our database of over 3 million articles.
Looking for more in-depth information on this industry?
Search our complete database of Industry & Market reports by text, subject, publication
name or publication date.
About Goliath
Whether you're looking for sales prospects, competitive information, company
analysis or best practices in managing your organization,
Goliath can help you meet your business needs.
Our extensive business information databases empower business
professionals with both the breadth and depth of credible,
authoritative information they need to support their business
goals. Whether it be strategic planning, sales prospecting,
company research or defining management best practices -
Goliath is your leading source for accurate information.
|
