An Empirical Study of Computer Self-Efficacy and the Technology Acceptance Model in the Military: A Case of a U.S. Navy Combat Information System

An Empirical Study of Computer Self-Efficacy and the Technology Acceptance Model in the Military: A Case of a U.S. Navy Combat Information System

Yair Levy (Nova Southeastern University, USA) and Bruce D. Green (The GBS Group, USA)
Copyright: © 2011 |Pages: 22
DOI: 10.4018/978-1-60960-577-3.ch010


The U.S. Navy continues to be a major developer and procurer of information systems (ISs), yet very limited research has been done to determine the factors that influence technology acceptance by naval personnel. Literature suggests that efforts to embrace information technology in improving decision making and reducing workload depend heavily on the use of such systems. Moreover, previous research has shown the validity of the technology acceptance model (TAM) and computer self-efficacy (CSE) to model technology acceptance in numerous environments. However, very little research was done specifically addressing such technology acceptance with military combat ISs. Thus, this study examines the applicability of the extended TAM with a CSE construct model to the U.S. Navy’s combat ISs. A survey sample of 237 sailors from five different U.S. Navy aircraft carriers was used to assess such an extended model on a U.S. Navy’s combat IS. Results indicate that perceived ease of use, perceived usefulness, and CSE were valid antecedents of technology acceptance (as indicated by intention to use). Moreover, high Cronbach’s alpha was observed on all measures, indicating reliability of the measures in the context of military organizations.
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Understanding the factors that influence individual adoption and usage of information systems (ISs) continues to be a central interest for IS researchers (Thompson, Compeau, & Higgins, 2006, p. 25). Over the past two decades, a large body of research regarding technology acceptance of IS has been conducted (Chau, 1996; Chau & Hu, 2001; Davis, 1989; Hu, Chau, Sheng, & Tam, 1999; Legris, Ingham, & Collerette, 2003; Ma & Liu, 2004; Venkatesh, Morris, Davis, & Davis, 2003; King & He, 2006). One of the highly cited models is the technology acceptance model (TAM) introduced by Davis (1986). According to Compeau et al. (2006), it is the simplicity of TAM and its measures that made it fertile ground for the flourishing research stream that resulted.

Since the late 1980s, technology acceptance studies have been successfully replicated in many environments (Venkatesh et al., 2003). Such environments include a public hospital system (Chau & Hu, 2001), a construction-engineering environment (Lowry, 2002), technology adoption in Arab nations (Rose & Straub, 1998; Elbeltagi, McBride, & Hardaker, 2005), online gaming (Hsu & Lu, 2004), and a large corporation undergoing ERP implementation (Amoako-Gyampah & Salam, 2004). Moreover, many technology acceptance models and studies have been conducted in academic settings (Davis, 1989; McFarland & Hamilton, 2006; Taylor & Todd, 1995). Furthermore, others criticized most of the key TAM studies for the use of students as study participants and recommended that further validations are needed using other types of participants (Legris et al., 2003). However, researchers noted that it is important to study existing technology acceptance models in those IS contexts that “target highly specialized individual professionals” (Chau & Hu, 2001, p. 700).

Additionally, researchers have recommended replication of instruments and revalidation of technology acceptance models for unique environments (Amoako-Gyampah & Salam, 2004). Furthermore, others criticized previous TAM studies for the use of office-related applications as the IS and noted that research would benefit from the investigation of managerial or process-level applications, as well as other professional systems (Legris et al., 2003). Yet, despite the fertile work on technology acceptance in IS research, very little attention has been given to the investigation of technology acceptance in military environments (Briggs et al., 1999; Simon & Paper, 2007).

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