Purpose: Enterprise architecture (EA) aligns information systems with business processes to enable firms to reach their strategic objectives and, when effectively employed by organizations, can lead to enhanced levels of performance. However, while many firms may adopt EA, it is often not used extensively. The purpose of this paper is to examine how performance expectancy (PE) and training affect the degree to which organizations use EA. Design/methodology/approach: The paper employed a survey method to gather data from IT professionals, senior managers, and consultants who work within organizations that have adopted EA. Covariance-based structural equation modeling was used to analyze the research model and test the hypotheses. Findings: The paper found PE to be a significant predictor of EA use. In addition, training is also shown to enhance use of EA while also playing a mediating role within the relationship between PE and use of EA. Research limitations/implications: The study is limited by the focus only on training as an intervention. Other mediators and/or moderators such as top management support and organization culture may also play an important role and should be examined in future studies. Nonetheless, the study demonstrates the critical role that training can play in facilitating widespread use of EA within organizations. Practical implications: Widespread use is a critical success factor for organizations that want to gain the maximum possible benefit from EA. To achieve extensive use, the study suggests that organizations that adopt EA should consider implementing a formal and robust education and training program. Originality/value: This study extends the research on information technology training by examining the role of training as an intervention within the technology acceptance paradigm. The paper also contributes to the literature regarding post-adoption innovation diffusion by demonstrating the efficacy of organizational training in promoting widespread usage.
All Science Journal Classification (ASJC) codes
- Decision Sciences(all)
- Information Systems
- Management of Technology and Innovation