2020, Emerald Publishing Limited. Purpose: The objective of this research is to model supply chain network resilience for low frequency high impact disruptions. The outputs are aimed at providing policy and practitioner guidance on ways to enhance supply chain resilience. Design/methodology/approach: The research models the resilience of New Zealand's log export logistical network. A two-tier approach is developed; linear programming is used to model the aggregate-level resilience of the nation's ports, then discrete event simulation is used to evaluate operational constraints and validate the capacity of operational flows from forests to ports. Findings: The synthesis of linear programming and discrete event simulation provide a holistic approach to evaluate supply chain resilience and enhance operational efficiency. Strategically increasing redundancy can be complimented with operational flexibility to enhance network resilience in the long term. Research limitations/implications: The two-tier modelling approach has only been applied to New Zealand's log export supply chains, so further applications are needed to insure reliability. The requirement for large quantities of empirical data relating to operational flows limited the simulation component to a single region Practical implications: New Zealand's log export supply chain has low resilience; in most cases the closure of a port significantly constrains export capacity. Strategic selection of location and transportation mode by foresters and log exporters can significantly enhance the resilience of their supply chains. Originality/value: The use of a two-tiered analytical approach enhances validity as each level's limitations and assumptions are addressed when combined with one another. Prior predominantly theoretical research in the field is validated by the empirical investigation of supply chain resilience.
Childerhouse, P., Al Aqqad, M., Zhou, Q. and Bezuidenhout, C. (2020), "Network resilience modelling: a New Zealand forestry supply chain case", The International Journal of Logistics Management, Vol. 31 No. 2, pp. 291-311.