On the use of hidden information as a measure of complexity in supply chains

• Main Author: Dickinson, P. R.
• Published: University of Salford 2015
• Subjects: 658
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.674946

With the increase in globalisation, mass customisation becoming ever more ubiquitous, product life cycles becoming shorter, midlife upgrades becoming more popular; with some product based solutions transitioning to service based solution, the supporting industry supply chains are becoming ever more complex. There is a likelihood that this complexity will increase with increasing access to emerging market cost effective capabilities and an international customer base. Working with this complexity is one of the challenges facing the supply chain executive, and there is no reason to think this increasing complexity will go away over the coming few years. Creating and managing an effective supply chain structure will be a key performance target and potentially a key differentiator. One element of the management task will be the understanding of structure and how it impacts on the overall key performance indicators. Structures can be represented as activities and connections. These structures can be set out to reflect the complexity of the structure necessary to cover all potential business scenarios. A key determinant of a structure will be how ‘mixed up’ it needs to be to cope with the demands of complexity, flexibility and agility necessary for all the business scenarios. It is possible these structures can be represented as a matrix and, using information theory, analysed to measure complexity. This thesis looks to use a matrix approach and address these challenges by offering a revised model for structural complexity in the supply chain. Like most research in this field, this thesis will be experimental and laboratory based; however, the scenarios used in the analysis will be validated externally. The aim of this research is to make a contribution to the research in this field by distinguishing between complexity, variability and structural complexity; providing a framework and quantifiable measure of complexity for a supply chain governance structure using information theory and graph theory; analysing the impact of language aggregation on the hierarchical business process. Additionally the research assumptions have the aim of making this research practical for the management practitioner.