Purpose <p>The COVID-19 pandemic accelerated the widespread adoption of information and communication technologies (ICT), resulting in rapid digitalisation of higher education. Nevertheless, there is little empirical evidence post pandamic higher education context, focusing on academicians continued intention to use ICT Tools. Based on the Technology Acceptance Model (TAM), this research paper discusses the factors that affect the intention of academicians to use ICT by modifying TAM with the social influence and user expectancy.</p> Design/methodology/approach <p>A quantitative research design was employed using structured questionnaire and data was collected from academicians from private universities and higher education institutions. The analysis of the proposed research model was performed with the assistance of Partial Least Squares Structural Equation Modelling (PLS-SEM) and Smart PLS. Assessment of measurement models was done through internal consistency reliability, convergent validity and discriminant validity. Path coefficients, coefficient of determination (R<sup>2</sup>), effect size (f<sup>2</sup>) and collinearity diagnostics (VIF) were used to assess the structural model. Bootstrapping was used to test hypotheses with t-values and <i>p</i>-values used to calculate significance.</p> Findings <p>The results indicate that perceived usefulness has a strong and positive influence on intention to use ICT (β = 0.508, <i>p</i> &lt; 0.001), followed by perceived ease of use (β = 0.385, <i>p</i> = 0.016). User expectancy inferred a statistically significant but negative effect on intention to use ICT (β = − 0.226, <i>p</i> = 0.007), suggesting the presence of an expectation–performance misalignment. In contrast, social influence does not exhibit a significant effect on intention to use ICT (β = − 0.101, <i>p</i> = 0.479). The model explains 36.7% of the variance in intention to use ICT (R<sup>2</sup> = 0.367), indicating moderate explanatory power. Collinearity diagnostics reveal no multicollinearity concerns, as all VIF values remain below the recommended threshold.</p> Practical implications <p>The findings suggest that digital transformation in higher education requires institutions to focus on performance-driven ICT solutions, improve system usability, and proactively manage the expectations of academicians. Training programmes instigated within the institution and constant technological assistance play a crucial role in matching the ICT capacities with academic work demands in the post-pandemic environment.</p> Originality/value <p>This study contributes to ICT and technology acceptance literature by shifting the analytical focus from initial technology adoption to sustained post-pandemic usage in higher education. By suggesting the presence of an expectation–performance misalignment that negatively influences continued ICT use, the study extends traditional TAM applications and offers novel insight into the sustainability challenges of digital transformation in emerging economy contexts.</p>

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Transforming education sector with adoption of ICT tools and analysis with technology acceptance model (TAM)

  • Sachita Yadav,
  • Shubha Chandra,
  • Madhu Bala Kaushik,
  • Anadi Trikha,
  • Veenus Gehlot

摘要

Purpose

The COVID-19 pandemic accelerated the widespread adoption of information and communication technologies (ICT), resulting in rapid digitalisation of higher education. Nevertheless, there is little empirical evidence post pandamic higher education context, focusing on academicians continued intention to use ICT Tools. Based on the Technology Acceptance Model (TAM), this research paper discusses the factors that affect the intention of academicians to use ICT by modifying TAM with the social influence and user expectancy.

Design/methodology/approach

A quantitative research design was employed using structured questionnaire and data was collected from academicians from private universities and higher education institutions. The analysis of the proposed research model was performed with the assistance of Partial Least Squares Structural Equation Modelling (PLS-SEM) and Smart PLS. Assessment of measurement models was done through internal consistency reliability, convergent validity and discriminant validity. Path coefficients, coefficient of determination (R2), effect size (f2) and collinearity diagnostics (VIF) were used to assess the structural model. Bootstrapping was used to test hypotheses with t-values and p-values used to calculate significance.

Findings

The results indicate that perceived usefulness has a strong and positive influence on intention to use ICT (β = 0.508, p < 0.001), followed by perceived ease of use (β = 0.385, p = 0.016). User expectancy inferred a statistically significant but negative effect on intention to use ICT (β = − 0.226, p = 0.007), suggesting the presence of an expectation–performance misalignment. In contrast, social influence does not exhibit a significant effect on intention to use ICT (β = − 0.101, p = 0.479). The model explains 36.7% of the variance in intention to use ICT (R2 = 0.367), indicating moderate explanatory power. Collinearity diagnostics reveal no multicollinearity concerns, as all VIF values remain below the recommended threshold.

Practical implications

The findings suggest that digital transformation in higher education requires institutions to focus on performance-driven ICT solutions, improve system usability, and proactively manage the expectations of academicians. Training programmes instigated within the institution and constant technological assistance play a crucial role in matching the ICT capacities with academic work demands in the post-pandemic environment.

Originality/value

This study contributes to ICT and technology acceptance literature by shifting the analytical focus from initial technology adoption to sustained post-pandemic usage in higher education. By suggesting the presence of an expectation–performance misalignment that negatively influences continued ICT use, the study extends traditional TAM applications and offers novel insight into the sustainability challenges of digital transformation in emerging economy contexts.