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Supply risk management in a supply chain under uncertain supply conditions

Mokhtar, Samira (2020) Supply risk management in a supply chain under uncertain supply conditions. PhD thesis, Murdoch University.

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Abstract

A disruption to the supply of input materials is one of the main threats to manufacturing supply chains. Trade wars, natural disasters, pandemics, cyber-attacks, sudden changes in cost and quality, machine breakdowns and transport accidents are among the causes of disruptions to supply chains. The supply chain is made up of several interconnected parties, where a product or service moves from raw material suppliers through to manufacturing, before its final delivery to customers. The extent and complexity of such interconnections can significantly increase the vulnerability of the supply chain system to disruptions. A disturbance to one party may propagate to other nodes and cause major disruption and financial losses for the whole supply chain.

Many causes of supply disruptions are beyond the control of supply chain managers, therefore the best way to manage them is to be proactive. Supply chain managers undertake a risk management process to prepare the supply chain for mitigating the possible impacts of disruptions. Managers have several options to control their exposure to disruption risks. Two main options available are stocking material in inventory and maintaining a portfolio of suppliers.

This thesis focuses on managing supply disruption risks in supply chains. It aims to assist the supply chain managers to mitigate the risk of supply disruptions and the corresponding effects these will have on profits. This thesis makes its contribution in three broad steps:

(1) Development of a decision-making model to efficiently mitigate the likelihood of a supply disruption. The model determines an optimal supplier portfolio through continuous monitoring of supply risk indicators that detects early warnings of a supply disruption. Risk indicators are based on a supplier’s product price, financial and production stability, and quality. Using an integrated system dynamics and portfolio optimisation solution approach, the model assists decision-makers to rebalance their supplier portfolio in response to early changes in supply risk indicators over a planning horizon.

(2) Development of an optimal inventory strategy model from the perspective of a manufacturer in a supply chain. This model aims to determine the optimal inventory strategy based on the expected supply price and product market demand over a planning horizon. The model seeks to maximise the manufacturer’s profit at the beginning of a planning horizon, rendering the inventory option as managerial flexibility to mitigate the undesirable effects of supply disruptions.

(3) Development of a decision-making model to determine an optimal contracting strategy, sourcing policy and inventory management at each period to maximise the manufacturer’s profit at the beginning of the planning horizon. This third step allows for the concurrent application of managerial flexibilities to manage supply chain risks. This model adopts the view of a manufacturer in a supply chain with two suppliers. It provides the manufacturer with the optimal allocation of supplies, including an optimal long-term contract position with one supplier at the beginning of the planning horizon. The model also enables the decision-makers to find the optimal inventory strategy at each period to mitigate the effects of supply disruptions and maximise profit for the manufacturer.

To develop the decision-making models in steps (2) and (3), this thesis applies a real options analysis method. An American-style option valuation method is used to solve the optimal inventory, sourcing and contracting strategy under uncertain supply price and product demand. This thesis uses a least-square Monte Carlo simulation to solve the underlying dynamic programming model.

The results of the modelling in step (1) demonstrate how a supply portfolio can be developed to provide higher expected profit at a certain level of risk. They also show how the optimal decision depends on the risk propensity of the decision-maker. The results of modelling in step (2) demonstrate the conditions under which inventory flexibility is valuable to a supply chain. Results show how a higher expected supply price during a disruption period and a higher expectation of disruption, increases the value of an inventory flexibility option. Expectations of early disruptions increased the value of the inventory option. Results of modelling in step (3) show how a manufacturer can balance their inventory of supplies and a long-term contract with one supplier at the beginning of the planning horizon to maximise profit.

Item Type: Thesis (PhD)
Murdoch Affiliation(s): Engineering and Energy
Supervisor(s): Bahri, Parisa, James, Adrian and Moayer, Sorousha
URI: http://researchrepository.murdoch.edu.au/id/eprint/59211
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