Understanding supply chain disruption risk with the aid of social networks and information flows analysis


Autoria(s): Singh, Amrik
Data(s)

03/10/2013

Resumo

Supply Chain Risk Management (SCRM) has become a popular area of research and study in recent years. This can be highlighted by the number of peer reviewed articles that have appeared in academic literature. This coupled with the realisation by companies that SCRM strategies are required to mitigate the risks that they face, makes for challenging research questions in the field of risk management. The challenge that companies face today is not only to identify the types of risks that they face, but also to assess the indicators of risk that face them. This will allow them to mitigate that risk before any disruption to the supply chain occurs. The use of social network theory can aid in the identification of disruption risk. This thesis proposes the combination of social networks, behavioural risk indicators and information management, to uniquely identify disruption risk. The propositions that were developed from the literature review and exploratory case study in the aerospace OEM, in this thesis are:- By improving information flows, through the use of social networks, we can identify supply chain disruption risk. - The management of information to identify supply chain disruption risk can be explored using push and pull concepts. The propositions were further explored through four focus group sessions, two within the OEM and two within an academic setting. The literature review conducted by the researcher did not find any studies that have evaluated supply chain disruption risk management in terms of social network analysis or information management studies. The evaluation of SCRM using these methods is thought to be a unique way of understanding the issues in SCRM that practitioners face today in the aerospace industry.

Formato

application/pdf

Identificador

http://eprints.aston.ac.uk/20859/1/Studentthesis-2013.pdf

Singh, Amrik (2013). Understanding supply chain disruption risk with the aid of social networks and information flows analysis. PhD thesis, Aston University.

Relação

http://eprints.aston.ac.uk/20859/

Tipo

Thesis

NonPeerReviewed