عنوان انگلیسی مقاله:
Costs of resilience and disruptions in supply chain network design models: A review and future research directions
ترجمه فارسی عنوان مقاله:
هزینه های انعطاف پذیری و اختلالات در مدل های طراحی شبکه زنجیره تامین: یک مرور و دستورالعمل های آینده تحقیق
Sciencedirect - Elsevier - International Journal of Production Economics, 235 (2021) 108103: doi:10:1016/j:ijpe:2021:108103
Supply chain network design (SCND) is a key strategic decision in supply chain management (SCM). One particular area of SCND is concerned with disruption risk modelling. This paper presents a systematic literature review of quantitative models of SCND under disruption risks in industrial SCM and logistics. More specifically, our analysis is focused on different costs induced by the planning of proactive investments in robustness and through parametrical/structural adaptation at the recovery stage. This review can be of value for researchers and decision-makers alike for several reasons. First, we categorise the existing knowledge based on decision-making problems, which can be instructive for a convenient association of a particular SCND problem to a modelling domain according to network-wise, supply-side and demand-side perspectives. Second, our analysis focuses on the costs specifically induced by disruption risks and resilience investments. Third, we offer a dedicated section related to disruption probability formulation methods and their impact on resilience costs. Fourth, the integration of different SCM dimensions (i.e., social impact, environmental impact, responsiveness, and risk- aversion) and the associated multi-objective modelling settings are discussed along with disruption risks in SCND models. Finally, we summarize our findings as insights from a managerial perspective. Drawbacks and missing aspects in the related literature are highlighted, and we lay out several research directions and open questions for future research.
Keywords: Supply chain network design | Facility location | Disruption risk | Resilience cost | Ripple effect | Covid-19