Purpose – The purpose of this paper is to examine the claim that the application of human factors (HF) knowledge can improve both human well-being and operations system (OS) performance. Design/methodology/approach – A systematic review was conducted using a general and two specialist databases to identify empirical studies addressing both human and OS effects in examining manufacturing OS design aspects. Findings – A total of 45 empirical studies were found, addressing both the human and system effects of OS (re)design. Of those studies providing clear directional effects, 95 percent showed a convergence between human effects and system effects (þ, þ or 2, 2 ), 5 percent showed a divergence of human and system effects (þ, 2 or 2, þ ). System effects included quality, productivity, implementation performance of new technologies, and also more “intangible” effects in terms of improved communication and co-operation. Human effects included employee health, attitudes, physical workload, and “quality of working life”. Research limitations/implications – Future research should attend to both human and system outcomes in trying to determine optimal configurations for OSs as this appears to be a complex relationship with potential long-term impact on operational performance. Practical implications – The application of HF in OS design can support improvement in both employee well-being and system performance in a number of manufacturing domains. Originality/value – The paper outlines and documents a research and practice gap between the fields of HF and operations management research that has not been previously discussed in the management literature. This gap may be inhibiting the design of OSs with superior long-term performance.

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doi.org/10.1108/01443571011075056, hdl.handle.net/1765/20443
ERIM Top-Core Articles
International Journal of Operations and Production Management
Erasmus Research Institute of Management

Neumann, W.P, & Dul, J. (2010). Human factors: spanning the gap between OM and HRM. International Journal of Operations and Production Management, 30(9), 923–950. doi:10.1108/01443571011075056