Article ID: | iaor20171117 |
Volume: | 27 |
Issue: | 1 |
Start Page Number: | 78 |
End Page Number: | 114 |
Publication Date: | Mar 2017 |
Journal: | International Journal of Logistics Systems and Management |
Authors: | Zailani Suhaiza, Aghapour Ali Haj, Marthandan Govindan, Fie David Yong Gun |
Keywords: | management, risk, manufacturing industries, statistics: empirical, decision, simulation, optimization |
Risk management has become an important area in supply chain management since the late 1990s. However, less empirical studies have been reported in the literature that links risk management practices to performance, especially among SMEs. This paper aims to empirically investigate the sequential impact of this managerial process on non‐financial performance of three execution decision areas of the SCOR model. Therefore, a cross‐sectional study was conducted among manufacturing SMEs in Iran. Data was collected from 160 high managers with knowledge of past and present organisational practices. Using partial least squares modelling (PLS‐SEM), analysis of manufacturing plants from six industries indicates that superior risk identification supports the subsequent risk assessment and this in turn leads to better risk mitigation. The model also explains 38% of the variance observed in supply chain operation performance. Accordingly, to ensure better supply chain operations in terms of reliability, flexibility and responsiveness, cost and assets, the findings of this study recommend SMEs to pay more attention towards risk analysing practices on one hand and distribution KPIs on the other hand. However, the study was based on decision makers' perceptions and the participation of divergent industries creates common limitations and future research orientations.