Primary Technostress Factors and Employee Productivity in AI Business Process Outsourcing: Evidence from Kenya
DOI:
https://doi.org/10.59413/ajocs/v7.i5.19Keywords:
Technostress, Employee Productivity, Business Process Outsourcing, Task-Technology Fit, Job Demands-Resources, KenyaAbstract
Business Process Outsourcing (BPO) firms in developing economies have adopted artificial intelligence (AI) and digital platforms at a pace that has outrun the organisational and human resources needed to absorb them, producing technostress – stress arising from the use of information and communication technologies. This study examined the effect of three primary technostress factors – technology factors, organisational factors and individual response factors – on employee productivity among BPO workers in Kenya. A sequential explanatory mixed-methods design was used. Quantitative data were collected from 368 employees (99.7% response rate) across 14 BPO providers in Nairobi using a validated, piloted questionnaire, and analysed with multiple linear regression in SPSS; qualitative data were collected through semi-structured interviews and focus group discussions with 15–20 purposively selected employees and analysed thematically in NVivo. The three factors jointly explained 4.5% of the variance in productivity (R² = .045), F(3, 364) = 5.685, p = .001. Organisational factors (β = 0.137, p = .010) and individual response factors (β = 0.172, p = .001) were significant positive predictors, whereas technology factors alone were not (β = -0.046, p = .390). Interview participants described technology overload and unexplained system changes as stressful but attributed their effect on productivity to the presence or absence of training, technical support and employee involvement. The findings support the Job Demands-Resources model and Task-Technology Fit theory and suggest that BPO managers seeking to protect productivity under AI-driven digitalisation should prioritise organisational support and employee coping resources rather than technology alone.
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Copyright (c) 2026 Fredrick Michael Ogore, Prof. Patrick Wamuyu Kanyi, Prof. Gerald Chegee (Author)
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