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Title: Measuring performance in supply chain networks
Author: Seiler, A. C.
ISNI:       0000 0004 6060 1983
Awarding Body: University of Salford
Current Institution: University of Salford
Date of Award: 2016
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Today, the formation of increasingly complex supply chain networks sets new demands for performance analysis. Performance analysis needs to look beyond the narrow perspective of the focal firm and measure performance not only from a financial perspective. This thesis illustrates how the network position of a focal company in the supply chain network impacts the economic performance of that company. Thereby the supply chain network is in fact scale-free (has no clear boundaries). Based on different statistical models, it is argued that performance measurement tools should take network positioning into account. As such, a network perspective may complement the internal financial perspective of corporate performance measurement. A convenience sample of small and medium-sized companies in the German plastics processing industry is studied. By using real-time enterprise data of 15 focal companies, their network flows of revenues and expenses are merged to create a supply chain network of 448 companies which is then analysed. Social network analysis provides the necessary quantitative data on characteristics of the focal company’s network positioning. By testing corresponding hypotheses, this thesis studies network position characteristics expressing (i) strength of links, (ii) node centrality and (iii) link diversity for their impact on a variety of financial performance measures. The results of applied methods of regression analysis confirm dependencies between characteristics of network positioning and different key financial performance measures. The analysis of different performance measurement models finds that the node centrality measure Bonacich power is a major driver of economic performance. Bonacich power not only considers the sheer number of business partners, but also whether connected business-partners are themselves well-connected. This way a basis for adapting performance measurement tools which generally lack a network orientation is provided. The application of social network analysis to the supply chain network is an important contribution itself. Based on the findings, reasonable suggestions for the rethinking of business strategy and a holistic performance measurement approach are made. Up-to now, companies often try to consider external effects originating from linear supply chains when analysing performance. However, by integrating gained insight from new conceptual work on supply chain network architecture into performance measurement, this thesis goes one step further. This study concentrates on manufacturing supply chains of one particular industry. A transfer to other (non-) manufacturing supply chains might be valuable.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available