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Open AccessArticle

Predicting Students’ Behavioral Intention to Use Open Source Software: A Combined View of the Technology Acceptance Model and Self-Determination Theory

Department of Management and Marketing, Universidad Pablo de Olavide, 41013 Seville, Spain
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Appl. Sci. 2020, 10(8), 2711; https://doi.org/10.3390/app10082711
Received: 26 February 2020 / Revised: 9 April 2020 / Accepted: 10 April 2020 / Published: 14 April 2020
This study focuses on students’ behavioral intention to use Open Source Software (OSS). The article examines how students, who were trained in OSS, are motivated to continue using it. A conceptual model based on Self-Determination Theory and the Technological Acceptance Model (TAM) was defined in order to test the behavioral intention to use OSS, comprising six constructs: (1) autonomy, (2) competence, (3) relatedness, (4) perceived ease of use, (5) perceived usefulness and (6) behavioral intention to use. A survey was designed for data collection. The participants were recent secondary school graduates, and all of them had received mandatory OSS training. A total of 352 valid responses were used to test the proposed structural model, which was performed using the Lisrel software. The results clearly confirmed the positive influence of the intrinsic motivations; autonomy and relatedness, to improve perceptions regarding the usefulness and ease of use of OSS, and; therefore, on behavioral intention to use OSS. In addition, the implications and limitations of this study are considered. View Full-Text
Keywords: Open Source Software (OSS); Technology Acceptance Model (TAM); Self-Determination Theory (SDT); behavioral intention to use; student; secondary school Open Source Software (OSS); Technology Acceptance Model (TAM); Self-Determination Theory (SDT); behavioral intention to use; student; secondary school
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Racero, F.J.; Bueno, S.; Gallego, M.D. Predicting Students’ Behavioral Intention to Use Open Source Software: A Combined View of the Technology Acceptance Model and Self-Determination Theory. Appl. Sci. 2020, 10, 2711.

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