Performance optimization of unique resilient human resource management system in a coal mine industry

Ali Azadeh, Delaram Heydarian (), Keivan Nemati and Reza Yazdanparast
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Ali Azadeh: University of Tehran
Delaram Heydarian: University of Tehran
Keivan Nemati: École Nationale Supérieure d’Arts et Métiers (ENSAM)
Reza Yazdanparast: University of Tehran

International Journal of System Assurance Engineering and Management, 2018, vol. 9, issue 5, No 17, 1178-1197

Abstract: Abstract Coal mine industry is recognized as a highly risk-oriented environment. Integrated resilience engineering can be employed to minimize the damages and hazards caused by sudden changes in such systems. It can be used to shift human resource management (HRM) to normal state in case of emergencies and unexpected events. Resilient HRM (RHRM) is composed of cognitive, behavioral, and contextual elements of organizational resilience. Moreover, this study presents and evaluates a new concept of RHRM in a real coal industry. An integrated algorithm composed of mathematical programming and statistical techniques is presented to assess and optimize RHRM. Data are obtained by standard questionnaire in a real mining industry. Results demonstrated that the cognitive dimension and the sub-dimension of employee contributions must be accounted as the most effective characteristics of the RHRM. In addition, skill was determined as the most significant sub-dimension of the cognitive dimension. This is the first study that investigates and optimizes the impact of resilience engineering on HRM in a coal mine industry. Second, a unique RHRM is presented and solved by multi-objective mathematical model. It is a practical approach, which can be implemented by decision makers in coal industries.

Keywords: Coal mine industry; Human resource management (HRM); Resilience engineering (RE); Data envelopment analysis (DEA); Statistical methods; Organizational resiliency (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s13198-018-0728-7

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