The influence of market structure, collaboration and price competition on supply network disruptions in open and closed markets
| dc.contributor.advisor | Godsell, Janet | |
| dc.contributor.author | Greening, Philip | |
| dc.date.accessioned | 2014-05-22T10:14:55Z | |
| dc.date.available | 2014-05-22T10:14:55Z | |
| dc.date.issued | 2013 | |
| dc.description.abstract | The relaxation of international boundaries has enabled the globalisation of markets making available an ever increasing number of specialised suppliers and markets. Inevitably this results in supply chains sharing suppliers and customers reflected in a network of relationships. Within this context firms buyers configure their supply relationships based on their perception of supply risk. Risk is managed by either increasing trust or commitment or by increasing the number of suppliers. Increasing trust and commitment facilitates collaboration and reduces the propensity for a supplier to exit the relationship. Conversely, increasing the number of suppliers reduces dependency and increases the ease of making alternative supply arrangements. The emergent network of relationships is dynamic and complex, and due in no small part to the influence of inventory management practices, tightly coupled. This critical organization of the network describes a system that contrary to existing supply chain conceptualisation exists far from equilibrium, requiring a different more appropriate theoretical lens through which to view them. This thesis adopts a Complex Adaptive Systems (CAS) perspective to position supply networks as tightly coupled complex systems which according to Normal Accident Theory (NAT) are vulnerable to disruptions as a consequence of normal operations. The consequential boundless and emergent nature of supply networks makes them difficult to research using traditional empirical methods, instead this research builds a generalised supply network agent based computer model, allowing network constituents (agents) to take autonomous parallel action reflecting the true emergent nature of supply networks. This thesis uses the results from a series of carefully designed computer experiments to elucidate how supply networks respond to a variety of market structures and permitted agent behaviours. Market structures define the vertical (between tier) and horizontal (within tier) levels of price differentiation. Within each structure agents are permitted to autonomously modify their prices (constrained by market structure) and collaborate by sharing demand information. By examining how supply networks respond to different permitted agent behaviours in a range of market structures this thesis makes 4 contributions. Firstly, it extends NAT by incorporating the adaptive nature of supply network constituents. Secondly it extends supply chain management by specifying supply networks as dynamic not static phenomena. Thirdly it extends supply chain risk management through developing an understanding of the impact different permitted behaviour combinations on the networks vulnerability to disruptions in the context of normal operations. Finally by developing the understanding how normal operations impact a supply networks vulnerability to disruptions it informs the practice of supply chain risk management. | en_UK |
| dc.identifier.uri | http://dspace.lib.cranfield.ac.uk/handle/1826/8473 | |
| dc.language.iso | en | en_UK |
| dc.publisher | Cranfield University | en_UK |
| dc.rights | © Cranfield University 2013. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright owner. | en_UK |
| dc.subject | Complex adaptive systems | en_UK |
| dc.subject | normal accident theory | en_UK |
| dc.subject | agent based modelling | en_UK |
| dc.subject | Supply chain management | en_UK |
| dc.subject | supply chain risk | en_UK |
| dc.title | The influence of market structure, collaboration and price competition on supply network disruptions in open and closed markets | en_UK |
| dc.type | Thesis or dissertation | en_UK |
| dc.type.qualificationlevel | Doctoral | en_UK |
| dc.type.qualificationname | PhD | en_UK |