Assessing Performance Impact of Digital Transformation for Instructors in the Covid-19 Era

Abstract

Digital transformation has evolved as the main issue for higher education institutions (HEIs) across the globe due to the Covid-19 outbreak. The purpose of this study is to investigate the performance impacts of digital transformation for instructors of HEIs during the pandemic. The technology-to-performance chain (TPC) model pursues to predict the influence of an information system on the performance of an individual user. Hence, TPC model is used to evaluate the performance of instructors due to digital transformation in the institutions during the Covid-19 pandemic. The data is collected from instructors of higher educational institutions. Recently, partial least squares path modeling (PLS-PM) has found extensive application for causal information systems (IS) research. Hence, Smart-PLS is used to analyze the data. Five constructs (task-technology fit, social norms, facilitating conditions, utilization, and performance impacts) are used to develop the model. The results showed that task technology fit (TTF) has a significant effect on performance impacts whereas utilization does not have an influence on performance impacts. Facilitating conditions and TTF are found to have an influence on the utilization whereas subjective norms do not have influence. This study contributes to the knowledge on the factors that matter to instructors of HEI in improving their teaching productivity, communication, and co-ordination during the Covid-19 pandemic.