Framework for Embedding Optimisation and Simulation Tools in Supply Chain Management

MESTIYAGE DON, Ranjika (2021). Framework for Embedding Optimisation and Simulation Tools in Supply Chain Management. Doctoral, Sheffield Hallam University.

MestiyageDon_2021_PhD_FrameworkForEmbedding.pdf - Accepted Version
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Supply chain management (SCM) is a pivotal area for academic research due to its influence on businesses competing in today's complex global economy. To support the managers, the concept of SCM has been imperatively adopted by many business leaders to assist in designing, planning, controlling, and enhancing the network of facilities and tasks that comprise many stages of the supply chain. In turn, Optimisation and Simulation Tools (OST) provide virtual environments to fine-tune this supply chain operational logic and processes to develop the best operational configurations and strategies before the execution of any real business planning or investment decisions. However, the review of existing literature, survey, and interviews conducted using industry professionals and subject experts revealed that in most instances, these tools are typically deployed to address specific problems in isolation. Therefore, users are failing to reap their full potential. Thus, the main aim of this research is to design and develop a novel framework that should enable businesses to embed these tools in their decision-making processes. Both quantitative and qualitative approaches are exploited in the research design and methodology to provide sound visibility and a clear path to achieve this research aim and objectives. Therefore, the proposed framework serves as a complete guide in Supply Chain Network Design (SCND) and Management, which helps the businesses, entrepreneurs, or any in the OST community to start their journey from scratch or over a re-design of any existing network. Such a proposal will stimulate and build the full confidence in the OST community to reap the maximum benefits in returns out of their investments over these tools. The proposed Framework is validated by a set of subject and industry professionals through a survey questionnaire, and necessary refinements recognised are executed. Then at the end, the novel contribution to the knowledge, limitations that exist and direction for future research are also well presented.

Item Type: Thesis (Doctoral)
Thesis advisor - Zhang, Hongwei [0000-0002-7718-021X]
Thesis advisor - Perera, Terrence
Additional Information: Director of Studies: Dr Hongwei Zhang Supervisor: Prof. Terrence Perera
Research Institute, Centre or Group - Does NOT include content added after October 2018: Sheffield Hallam Doctoral Theses
Identification Number:
Depositing User: Justine Gavin
Date Deposited: 15 Sep 2022 15:43
Last Modified: 11 Oct 2023 15:20

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