Use this URL to cite or link to this record in EThOS:
Title: A decision support framework for sustainable supply chain management
Author: Ahmed, Karim H. H.
ISNI:       0000 0004 6494 1643
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2017
Availability of Full Text:
Access from EThOS:
Access from Institution:
Sustainable Supply Chain Management has become a topic of increased importance within the research domain. There is a greater need than ever before for companies to be able to assess and make informed decisions about their sustainability in the Supply Chains. There is a proliferation of research about its understanding and how to implement it in practice. This is mainly since sustainability has been assessed from various disciplines, organizational industries and organizational functional silos . There is a lack of comprehension, unified definition and appropriate implementation of Sustainable Supply Chain Management (SSCM), leading to failure in decision making for sustainability implementation within supply chains. The proposed research identifies the research gaps through the novel application of Systematic Literature Network Analysis (SLNA) to SSCM literature. In doing so, methods including Systematic Literature Review (SLR), Citation Network Analysis (CNA) and Citation Network Mapping of literature have been used to identify definitions, KPIs, barriers and drivers of SSCM from the literature. Furthermore, a combination of methods from Text Mining and Content Analysis has been used to identify KPIs, barriers and drivers from sustainability reports of top global manufacturing companies, to better understand the practices of organizations for SSCM. The consolidation of the findings from literature and practice led to the development of an SSCM Performance Evaluation Framework built on multiple methods. A 4-level hierarchical model has been developed by classifying the identified KPIs into Economic, Environment and Social as well as considering the key decision areas including tactical, strategic and operational. Furthermore, a rigorous data collection process was conducted among supply chain and sustainability managers from top global manufacturing firms and leading academicians in the field, assessing the identified SSCM KPIs. The collected data were analyzed through novel application of hybrid Multi-Criteria Decision Analysis (MCDA) methods, which includes Values Focused Thinking (VFT), Fuzzy Analytical Hierarchical Process (FAHP), Fuzzy Technique of Order Preference by Similarity to Ideal Solution (FTOPSIS) and Total Interpretive Structural Modelling (TISM), for prioritizing and modelling of interdependencies, interactions and weightages among SSCM KPIs. The results obtained were subsequently used to develop a Decision Support System (DSS) that allows managers to evaluate their sustainability by identifying problem areas and yielding guidance on the KPIS and most important areas to focus on for SSCM implementation. The application of DSS has been demonstrated in the context of a case company. From a theoretical development point of view, a Tree perspective framework contributing to the ecological Theory of Sustainability has been proposed through the identification of the most influential organizational theories, and how they interrelate with each other. Overall, the proposed research provides a holistic perspective of SSCM that incorporates the various aspects of organizations, relevant organizational theories and perspectives of academics and practitioners together. The proposed DSS may act as a guiding tool for managers and practitioners for SSCM implementation in companies.
Supervisor: Not available Sponsor: Loughborough University
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: SSCM ; DSS ; MCDA ; Systematic Literature Network Analysis (SLNA)