Factors Affecting Adoption Intention of Productivity Software Applications Among Teachers: A Structural Equation Modeling Investigation

Teachers play a central role in achieving the mission, vision, and goals of educational institutions. However, the multitude of responsibilities and obligations they must fulfill demands a high level of productivity. Consequently, productivity software is increasingly becoming a necessity for teachers to lessen their day-to-day work pressure and instead focus on offering quality education. Despite their popularity, the key antecedents and precursors affecting the intention to use productivity software have yet to be investigated. Therefore, the goal of this study was to determine what factors contribute to the adoption of productivity software by applying the theoretical lens of the Technology Acceptance Model (TAM). A total of 947 responses from basic and higher education teachers were analyzed using a structural equation modeling approach. Results show that the usefulness and ease of use of productivity software are key in predicting behavioral intention. It is also indirectly affected by external variables such as subjective norms, professional reputation, job relevance, and output quality through perceived usefulness as well as facilitating conditions and self-efficacy through perceived ease of use. Overall, the findings of this study support the applicability of the specific TAM version as well as its employment in the context of productivity software.

Automated summary

Teachers play a crucial role in educational institutions and productivity software is essential for them to reduce work pressure and focus on quality education. This study aimed to determine the factors influencing the adoption of productivity software by teachers using the Technology Acceptance Model (TAM). The results showed that perceived usefulness and ease of use of the software are key predictors of behavioral intention, influenced by external variables such as subjective norms, professional reputation, job relevance, output quality, facilitating conditions, and self-efficacy. The findings support the applicability of TAM in the context of productivity software.