Human-centered digital transformation: managing technostress and engaging neurodivergent employees
Owais Nazir et al.
Abstract
Purpose This study investigates how digital transformation influences technological self-efficacy, employee well-being, and engagement among neurodivergent employees, while also examining the moderating effect of technostress. Design/methodology/approach Data were collected through a structured survey administered to 322 neurodivergent employees working in digitally oriented organizations in Saudi Arabia. Partial Least Squares Structural Equation Modelling (PLS-SEM) using SmartPLS 4.0 was employed to test the hypothesized relationships and moderation effects. Findings Results reveal that digital transformation positively influences technological self-efficacy, well-being, and engagement. Technological self-efficacy and well-being also positively affect employee engagement. Results further reveal that technostress negatively moderates these relationships, weakening the positive impact of digital transformation on both well-being and engagement. Practical implications The findings highlight the importance of human-centered digital transformation strategies that prioritize accessibility, psychological safety, and inclusive technology design. Managers should proactively monitor technostress, provide digital training, and create peer support systems to ensure that technological change enhances rather than depletes employee resources. Originality/value This study integrates Conservation of Resources theory with the neurodiversity–digital transformation interface. By drawing on evidence from an underexplored Middle Eastern context, it advances understanding of how digital transformation operates as both a resource-enabling and resource-depleting force, offering a nuanced framework for managing inclusion, well-being, and engagement in digitally transforming workplaces.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.