Technostress and Productivity: Evidence from Business Process Outsourcing (BPO) Workers

Technostress in Kenya's Business Process Outsourcing sector significantly reduced productivity, increased turnover, and posed mental health challenges. This study examined primary factors contributing to technostress among BPO workers and their influence on employee productivity. The study was anchored on Job Demands-Resources (JD-R) Model and Transactional Model of Stress and Coping. The Job Demands-Resources (JD-R) Model. The study employed sequential explanatory mixed-methods design. Using Krejcie and Morgan's formula, 369 participants were selected through stratified random sampling from 8,000-10,000 BPO employees across 14 Nairobi service providers, with 15-20 purposively selected for qualitative phase. SPSS version 28 analyzed quantitative data through descriptive statistics, correlation and regression. The study found primary technostress factors negatively correlated with productivity at r = -0.403 and explained 16.2 percent variance with coefficient B = -0.435. The study concludes that primary factors contributing to technostress significantly and negatively influence employee productivity in Kenya's BPO sector. Technology insecurity emerged as the most severe stressor, with employees expressing substantial concerns about job displacement due to automation and AI integration, followed closely by technology overload manifesting through overwhelming digital task volumes and constant notification streams. Technology complexity, invasion, and uncertainty demonstrated moderate prevalence, indicating that BPO employees experience multiple simultaneous technostressors creating cumulative strain affecting work performance. The study recommends that BPO organizations in Kenya should implement comprehensive technostress mitigation strategies addressing all five primary stressor dimensions simultaneously rather than isolated interventions targeting single factors. Organizations should prioritize addressing technology insecurity concerns by providing transparent communication about automation implementation plans, offering clear career development pathways demonstrating how AI enhances rather than replaces human roles, and establishing job security assurances coupled with reskilling programs preparing employees for evolving technological landscapes.