Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.755781
Title: Research on risk management for healthcare supply chain in hospital
Author: Wang, L.
Awarding Body: Liverpool John Moores University
Current Institution: Liverpool John Moores University
Date of Award: 2018
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Abstract:
Purpose: Unlike the commercial industries, the risks arising from the healthcare industry’s internal system and the surrounding environment may cause serious consequences, even the patients’ health. Concerning the increasing emphasis on risk management in the healthcare supply chain environment, there is an urgent demand for a novel decision support method that supports supply chain risk management in the hospital setting. As the topic is still in the early stage and only a few systematic academic studies on this topic can be found over the last decades. This research aims to propose a novel comprehensive framework and integrated risk management model that takes explicit account of multiple types of risk factors in aiding decision-making as well as compares and ranks the current implemented alternative risk mitigation strategies using fuzzy set theory and multiple criteria decision analysis (MCDA) methods. Methodology: In pursuit of meeting the requirements of the research objectives, this research conducts empirical studies from both China and UK healthcare industries and follows three steps of risk management procedure based on the proposed framework to conduct risk factors identification, assessment and risk mitigation strategies identification. In order to ensure that the analysis is systematic and inclusive, various types of risk factors are identified through a related systematic literature review and are validated through a set of empirical studies. Risk assessment is conducted through two stages of questionnaire surveys and evaluated through Fuzzy Analytic Hierarchy Process (AHP) and Interpretive Structural Modelling (ISM). Thereafter, risk mitigation strategies are identified through conducted empirical studies and evaluated through Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Research Implications: This is the first study which has developed a comprehensive risk management framework in the healthcare supply chain that effectively integrates supply chain risk factors identification, risk assessment as well as mitigation strategy identification and evaluation. The novelty of the developed framework lies in the fact that a systematic and practical decision making tools are proposed supporting hospital managers making strategic decisions on healthcare supply chain risk management. Furthermore, compared with several studies using secondary data, this thesis uses empirical data to conduct the identification and evaluation of risk mitigation strategies, enabling the results closes to the reality of the situation in the healthcare setting. Practical Implications: The profile of risk sources, the priority weighting and inter-relationship among these risks and, the ranking of mitigation strategies provide a guideline for hospital managers to anticipate and proactively deal with potential risks. The proposed framework applies to both the UK and China healthcare industries, the finding can also be applied in other countries and regions.
Supervisor: Ren, J. ; Wang, J. ; Morecroft, C. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.755781  DOI:
Keywords: HD61 Risk Management
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