Risk Mitigation Policies for Optimal Logistics Provider Selection Decisions in Supply Chains

Abstract

Selecting an optimal logistics provider in supply chains is a challenge for decision-makers. With the risks around the modern world, from wars, economic crises, pandemics and geopolitical conflicts, supply chain decision-makers face significant challenges in satisfying their stakeholders. These complexities create impactful exogenous environments that interrupt optimal decision-making. Hence, the selection process became sophisticated and critical, resulting in short- and long-term impacts. Through an identified research gap of risk awareness in the supply chain’s third-party logistics (3PL) providers’ selection problem. This study develops a hybrid model consisting of two simulation paradigms – Agent-based Modelling (ABM) and System Dynamics (SD) – to optimise the selection of 3PL providers for multi-echelon supply chains and implement mitigations to reduce the impacts of Risk Environment. Diverse exogenous environments in the supply chain’s ecosystems were considered in the current research. This thesis proposes and develops a Risk Environment for a multi-echelon supply chain facing a 3PL providers’ selection problem through mixed research methods. Qualitatively and quantitatively, the development and integration of both paradigms provided a tangible hybrid model to solve this research problem.

Empirically, two real-life case studies were adopted to verify and validate the hybrid model. Based on the collected data from each case study, two different hybrid models were configured to solve their 3PL providers’ selection problem. This resulted in developing Operational and Strategic Risk Environments for two different supply chain networks. In addition, risk scenario planning and policy-design approaches were implemented to propose risk mitigations.

The findings indicate variances in the selection processes between the supply chain components and optimal providers and key risks had been identified. Therefore, mitigation actions and policies from operational and strategic aspects were designed and implemented, resulting in significant cost reductions between 9% and 36% and enhanced customer satisfaction by reducing delivery delays. Finally, practical implications and recommendations were presented.

Date of Award	Jun 2024
Original language	English
Awarding Institution	Aston University
Supervisor	Dr Ammar Al-Bazi (Supervisor) & Ben Clegg (Supervisor)