Literature Review

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Collectively, the literature suggests that a variety of external factors significantly influence the extent of IT innovation and diffusion. The IT diffusion of innovation (DOI) process may be viewed within the context of Innovation Decision Process theory (Rogers, 1995) which posits that potential adopters of a technology must learn about the innovation (knowledge); become persuaded of the value of the innovation (persuasion); decide to adopt it (decision); implement the innovation (implementation); and finally reaffirm or reject the innovation (confirmation). Researchers often employ Davis' (1986) Technology Acceptance Model (TAM) as a theoretical framework to examine external variables, conceivably because of its goal to "provide an explanation of the determinants of computer acceptance that is general, capable of examining user behavior across a broad range of end-user computing technologies and user populations" (Davis et al., 1989). The model, grounded in social psychology, reflects Fishbein and Ajzen's Theory of Reasoned Action (TRA), which theorizes that behavior is determined by intentions that are in part influenced by attitude (Fishbein and Ajzen, 1975). Attitude, or the "predisposition to respond favorably or unfavorably to a computer system, application, system staff member, or a process related to the use of that system or application" (Melone, 1990, pp. 81), has a strong theoretical background and previous research has conclusively proven that attitude is an accurate predictor of use. TAM postulates that actual behavior is influenced by attitudes that are shaped by external variables as well as perceptions regarding the usefulness and ease of use of the technology under study. In fact, a key premise in TAM is that a user's attitude toward using information technology is a major determinant of whether the person actually uses the technology. Several extensions or modifications to the TAM have incorporated theoretical perspectives or constructs that reflect the salience of beliefs and attitudes, social or normative influences, and end-user characteristics on acceptance and adoption. Other research augments the TAM with individual, organizational, and system characteristics; many of which have received empirical support as moderators of IT acceptance (Igbaria et al., 1997; Mathieson et al., 2001; Jackson et al.; 1997, Agarwal and Prasad, 1999; Davis, 1993).

The research model for this chapter examines environmental, organizational, and personal factors as antecedents to perceptions of eCommerce. Bharaadwaj et al.'s (1999) multi-stage research framework, which was developed to conceptualize factors that govern a firm's IT capability, provides some justification for focusing on these external variables. With the assistance of Delphi panels and focus groups, the researchers identified 30 IT capabilities that were distributed among the following six categories: IT business partnerships, external IT linkages, business IT strategic thinking, IT business process integration, IT management, and IT infrastructure. The authors concluded that an enterprise-wide IT capability embodies both organizational and technological capabilities which, in turn, reflect the firm's ability to sustain IT innovation and respond to changing market conditions.

Several researchers (Devaraj et al., 2002; Gefen and Straub, 2000; Jiang et al., 2000; Moon and Young-Gul, 2001; Lederer et al., 2000) have employed the TAM to examine a variety of external variables related to eCommerce. Collectively, the findings suggest that TAM is a suitable theoretical framework for eCommerce-based studies. In studying user acceptance of digital libraries, Hong et al. (2002) employed the TAM to examine individual differences (self efficacy and knowledge of search domain) and system characteristics (relevance, terminology, and screen design) within the context of user acceptance of digital libraries. The researchers concluded that results strongly supported the utilization of TAM in predicting users' intention to adopt digital libraries. Venkatesh and Davis' (2000) TAM2 examined user acceptance through social influence (subjective norm, voluntariness, and image) and cognitive instrumental processes (job relevance, output quality, result demonstrability, and perceived ease of use) while Mathieson et al. (2001) augmented the TAM with a perceived resources construct as a means to examine the influence of organizational infrastructure on use. In each case, TAM proved to be a parsimonious model for predicting user acceptance.

The role of perceptions in predicting acceptance and usage decisions has also received considerable attention (Moore and Benbasat, 1991; Davis, 1993; Gefen and Straub, 1997; Morris and Dillon, 1997; Venkatesh, 1999; Agarwal, 2000; Mathieson et al., 2001). Notably, both Agarwal (2000) and Moore and Benbasat (1991) examined the influence of perceptions on IT acceptance and adoption while Mathieson et al. (2001) emphasized the need to more fully explore perceptions of real world artifacts such as technology. Possibly in response to TAM and DOI's effectiveness in explaining the propensity to use an IT, Agarwal and Prasad (1997) merged the two theories. After examining the diffusion constructs within the context of Internet usage, the researchers concluded that visibility, compatibility, and trialability influenced current levels of usage, while perceived usefulness and result demonstrability influenced continued use decisions.

In a recent editorial, Chin and Marcolin (2001) emphasized the continued need to develop "deep usage" models as well as "conceptualizations of usage as they lead to individual and performance outcomes." Clearly, then, a review of the literature establishes a precedent for developing models that are derived from the constructs originally presented by Davis.

The purpose of this study is to develop a descriptive profile of Chinese business managers' perceptions and attitudes regarding eCommerce. As such, this study should not be construed as an attempt to offer yet another extension of TAM nor to validate previous findings. Instead, the research model incorporates key TAM constructs in an effort to present a comprehensive profile that represents the triangulation of external variables, perceptions, and attitudes. The theoretical foundation for the model is derived from human behavior theory, which posits that behavior is largely a function of attitudes; attitudes are formed from individual perceptions; and individual perceptions are influenced by external variables.

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