Transforming traditions: how training shapes employee acceptance of digital transformation in a large legacy government workforce

Abstract

Governments worldwide are leveraging digital technologies to provide better citizen services and operational capabilities. This phenomenon, known as Digital Government Transformation (DGT), has begun to fundamentally transform government-citizen interaction and has great potential to enhance citizens’ wellbeing. While researchers have studied DGT from the citizen perspective, very few studies have focused on the employee perspective. To address this gap, this empirical study examines how training influences government employees’ acceptance and adoption of new technologies in a large DGT project impacting around 2.4 million personnel of the Indian Railways. This study employed a quantitative survey method using a modified Unified Model of Electronic Government Adoption (UMEGA). Data from 349 Indian Railways officials were analyzed through Structural Equation Modelling (SEM) with AMOS/SPSS. Validating UMEGA and its modification with the inclusion of training as an antecedent factor, this study revealed that training plays a critical role in shaping employees’ acceptance and usage intention of DGT by impacting other antecedent factors. It also provides deeper insights into technology adoption and suggests new research avenues, such as exploring training as a key factor with potential subcomponents, mediating and moderating effects, and establishing training as an efficacy-enhancing intervention for practitioners.

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