The theoretical constructs pertinent to this study are consumer acceptance, adoption, and behavior prediction. Two of the classic adoption and intention models, Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT), can help develop a solid theoretical foundation for this study. TAM was designed to explain the determinants of user acceptance of a wide range of end-user computing technologies (Davis, 1986). The model posits that perceived usefulness (PU) and perceived ease of use (PEOU) are the primary determinants of system use. The model hypothesizes that actual system use is determined by users' behavioral intention to use (BI), which is in turn influenced by users' attitude toward using (A). Finally, A is directly affected by beliefs about the system, which consists of PU and PEOU. TAM theorizes this belief-attitude-intention-behavior relationship to predict user acceptance of technology.
Another well established theory for user adoption is IDT (Rogers, 1962, 1983, 1995). Rogers (1995) stated that an innovation's relative advantage, compatibility, complexity, trailability and observability were found to explain 49% to 87% of the variance in the rate of its adoption. Subsequent research projects including the meta-analysis of seventy-five diffusion articles conducted by Tornatzky and Klein (1982) found that only relative advantage, compatibility and complexity were consistently related to the rate of innovation adoption. The relative advantage construct in IDT is often viewed as the equivalent of PU construct in TAM, and the complexity construct in IDT is very similar to PEOU concept in TAM (Moore & Benbasat, 1991).
TAM and IDT are well versed to study EC and Internet application adoption. However, while TAM and IDT have been very successful in predicting the potential user acceptance, they provide little assistance in the design and development of systems with high level of acceptance. One remedy for this weakness is to identify the determinants of PU and PEOU to supply system designers with meaningful solutions (Venkatesh & Davis, 1996). Hence, the next step in this study is to identify a list of CSFs that virtual stores need to focus on.
The analyses of a large number of B-to-C EC literature and cases rendered five CSFs for virtual stores: product offerings, information richness, usability of storefront, perceived service quality, and perceived trust. We would like to point out that the list of CSFs presented here may not be exclusive. The sociotechnical perspective on B-to-C electronic commerce requires the investigation of a wide range of technical and behavior issues. While studying all these issues will not be possible and productive, this study chose to identify the most important CSFs that can explain and predict consumer acceptance substantially well. These five CSFs were chosen based on their high frequency of appearance in B-to-C literature. Some of the CSFs (i.e., product offerings, information richness, and usability) were the direct extensions of the PU and PEOU constructs in TAM, and the other CSFs (i.e., service quality and trust) were found to be crucial in forming positive consumer experience in literature.
Consumers' product perceptions are often found to be the primary determinant of shopping in a particular retailer. The efficacy of product offerings is often judged by three criteria: breadth of product selection, pricing strategies, and product retail channel fit. Product variety is an influential factor in retail store patronage (Woodside & Trappey, 1992). One study shows that a large percentage of people turn to the Internet to look for products that they cannot find from anywhere else (Machlis, 1999). As a result, consumers may expect virtual stores to offer a wider product variety than traditional retailers. Price has always been one of the salient, performative attributes that determine consumer store choice. Studies have found that online consumers are price sensitive (Rigdon, 1995). Jarvenpaa and Todd (1997) noted that many consumers expected lower prices due to the lower setup costs, lower cost per customer contact, and lower maintenance cost of virtual stores. The right kinds of products offered by a virtual store can create cost advantages and attract customers. Experts suggest that most online purchases will remain durable, standardized items requiring little customer service, for example, books and musical CDs (Scansaroli & Eng, 1997). Virtual stores must carefully evaluate the product retail channel fit and make adjustments to their product offerings accordingly.
Information richness plays a crucial role in shaping consumers' decision to purchase from a virtual store. According to the Information Richness Theory (IRT) (Daft & Lengel, 1986), information richness is defined as "the ability of information to change understanding within a time interval." Baty and Lee (1995) attribute the failures of early attempts of electronic shopping to limited product information and low product comparability. Therefore, the quality of product information and the extent of product comparison bear heavily on EC success. However, one of the primary difficulties in marketing products that are not dominated only by visual attributes on the Web is virtual stores' inability to satisfy consumers' need to touch, smell, or try on the product before purchasing. In order to predict their satisfaction with the products more accurately prior to the purchases, online consumers may expect rich product information and robust product comparison functions from virtual stores.
A poorly designed digital storefront has an adverse influence on the consumers' online shopping experience, hence interface issues related to navigation, search, and ordering process must be given special attention (Lohse & Spiller, 1998). Will consumers be able to effortlessly traverse in the virtual store? Will consumers easily and quickly find what they want in the virtual store? These are the two questions relevant to the usability of virtual stores that Web developers must ask themselves. Usability study has being widely used in evaluating the design of websites. It looks at website architecture, navigation, design and layout to predict how easy the website would be for users to navigate and find what they need. Experiences from virtual stores have shown that unusable websites are impeding consumers' performance and satisfaction when shopping online; therefore, usability of storefront is an important determinant of consumer acceptance of virtual stores.
Perceived service quality is a recurring research issue for both marketing and IS disciplines. With virtual stores being both marketing channels and information systems, service quality is crucial to their success. Perceived service quality is defined as the discrepancy between what customers expect and what customers get. High perceived service quality has always been associated with increased customer satisfaction and retention (Woodside & Trappey, 1992). Parasuraman et al. (1988) identified five dimensions which consumers use to evaluate service quality. They are tangibles, reliability, responsiveness, assurance, and empathy. These five dimensions are translated into the virtual store context as follows.
Tangibles: The physical facilities provided by a virtual store (the appearance of the virtual store, the existence of online and offline customer service facilities).
Reliability: A virtual store's ability to perform the promised action dependably and accurately (i.e., on time and accurate product delivery).
Responsiveness: A virtual store's willingness to offer help to its customer in a timely fashion (e.g., quick e-mail responses to customers' inquiries).
Assurance: A virtual store's ability to inspire trust and confidence.
Empathy: The caring and individualized attention given to its customers by a virtual store (e.g., personalized product suggestions).
The perceived service quality is believed to influence consumers' attitude toward using virtual stores.
A number of studies suggest that the reason why many people have not yet shopped online is due to the lack of trust in online businesses (e.g., Clark, 1999; Hoffman et al., 1999). Trust can be defined as feeling secure or insecure about relying on an entity. It has positive influence on the development of positive customer attitude, intention to purchase, and purchasing behaviors (Swan et al., 1999). In the context of online shopping, the influencing factors for consumers' lack of trust in virtual stores are found to be personal information privacy and data security concerns. Information exchange in a trustful environment is an essential part of B-to-C EC. Consumer trust can only be inspired if the risks associated with online purchases are reduced to a level that is tolerable to consumers.
By incorporating the variables from TAM and IDT with the five proposed CSFs, we developed the theoretical model for studying the determinants of consumer acceptance of virtual stores displayed in Figure 1.
Figure 1: Theoretical Model for Consumers' Acceptance of Virtual Stores.