What is it about?

The publication addresses the issue of acceptance of Computer-Aided Software Engineering (CASE) tools within IT professional's training and work. Experts and those involved in the teaching process report a number of issues and challenges regarding handling multiple modeling notations using different tools. Such challenges appear on a repetitive basis. Based on the research involving the Unified Theory of Acceptance and Use of Technology (UTAUT), authors propose two novel, domain-specific variables (i.e. Model Interchange and Professional Training Diffusion) that are hypothesized to have a relevant impact on the acceptance level of CASE tools. Through two-staged study (93+198 questionnaires), the former is indeed found to have a powerful influence on behavioral intention to use such tools, while the influence of the latter is indirect, as it significantly supports the facilitating conditions for using CASE tools. Naturally, the impact of classic UTAUT variables on behavioral intention to use CASE tools was re-evaluated as well. Aside from assessing the pertinence of question selection and proper formulation and the consistency of each question groups supporting individual variables with Cronbach’s Alpha coefficients, CMIN/DF, RMSEA, GFI and CFI fit indices of the target model were evaluated and found to meet the recommended threshold.

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Why is it important?

The variables proposed by the authors increase the explanation power of CASE tools acceptance studies and tailor the Unified Theory of Acceptance and Use of Technology to the demands and requirements of the Information Systems Development area. Therefore, potential users of CASE tools are provided with enhanced means of selecting optimal software for supporting their projects, while the vendors are endowed with improved reference models for developing and marketing their solutions.

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This page is a summary of: The Enriched UTAUT Model for the Acceptance of Software Engineering Tools in Academic Education, Information Systems Management, October 2016, Taylor & Francis,
DOI: 10.1080/10580530.2017.1254446.
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