Computer Self-Efficacy (CSE) has been an important construct in information systems research for more than two decades. The authors review a recent study that meta-analyzed 102 empirical CSE studies and quantitatively affirmed significant correlations with 7 variables of frequent research interest, as well as several potential moderators of these CSE-correlate relationships. This chapter discusses the relationship between CSE and the technology acceptance model, and the authors suggest that the CSE construct merits continued research and practitioner attention for a variety of reasons. The findings also yield managerial and organizational implications and suggestions for future CSE research and practice.
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In an ideal world, all employees would view computer systems positively and embrace their use as a key to enhanced job performance. However, while computer use is pervasive in today’s society, many individuals continue to dislike computers, suffer from computer anxiety, and exhibit a variety of other characteristics and behaviors that inhibit effective computer use in the workplace (Compeau et al., 2006; Karsten et al., 2012; Marakas et al., 2007). Accordingly, there is considerable practical and research interest in seeking a better understanding of the determinants of computer systems use.
Two of the most popular research approaches in this regard have been the technology acceptance model (TAM) and the computer self-efficacy (CSE) construct. TAM (Davis, 1989) has emerged as a well-regarded and parsimonious framework to study and explain users’ behavioral intentions to use computer systems. TAM postulates that two primary predictors determine behavioral intentions: perceived usefulness and perceived ease of use. While TAM remains one of the most influential frameworks, its initial focus on the perceived characteristics of computer systems seemed to limit its usefulness to practitioners concerned about the role individual characteristics play in systems use. Realizing this as a significant concern, some scholars have attempted to modify TAM to include various individual difference factors (King & He, 2006; Venkatesh, 2000).
One such factor is computer self-efficacy. Over the last two decades, a growing body of research literature has supported the critical role CSE plays in influencing a variety of user-system outcomes (Compeau et al., 2006; Karsten et al., 2012; Marakas et al., 2007). CSE is defined as “an individual’s perception of efficacy in performing specific computer-related tasks within the domain of general computing” (Marakas et al., 1998, p. 128). CSE has its basis in the broader, well-researched concept of self-efficacy (Bandura, 1986, 1997). As defined by Wood and Bandura (1989, p. 408), “self-efficacy refers to beliefs in one’s capabilities to mobilize the motivation, cognitive resources, and courses of action needed to meet given situational demands.”
Correspondingly, CSE reflects individuals’ beliefs in their abilities to organize and execute the courses of action needed to complete computer specific tasks successfully in a variety of contexts (Compeau et al., 2006). For instance, researchers have consistently reported that CSE is significantly correlated with perceptions about computers, such as whether individuals see computers as being useful (e.g., Thompson et al., 2006) or easy to use (e.g., Hasan, 2006). CSE also is positively correlated to users’ attitudes toward computers (e.g., Compeau et al., 1999), intention to use computers (e.g., Klein, 2007), actual computer use (e.g., Ball & Levy, 2008), and computer skills (e.g., Marakas et al., 2007). On the other hand, CSE is negatively correlated with computer anxiety (e.g., Johnson & Marakas, 2000; Thatcher et al., 2008). CSE appears to have a significant and pervasive impact on a range of important, organizationally relevant factors that managers who are concerned about effective computer systems use would not want to ignore.