|Publication type:||Conference paper|
|Type of review:||Not specified|
|Title:||Unlocking the potential of intra-company networks : the effect of complexity|
|Conference details:||Institute for Small Business and Entrepreneurship (ISBE) Conference, Manchester, United Kingdom, 5-6 November 2014|
|Subjects:||Manufacturing; Coordination; Complexity; Network|
|Subject (DDC):||658.5: Production management|
|Abstract:||Objectives: The objective of this paper is to analyse what complexity drivers exist in manufacturing networks, how they affect strategic goal fulfilment and how the complexity drivers can be reduced by manufacturing network configuration and coordination measures. Prior Work: Supply chain complexity has been studied on supply network, a two-stage supply chain or a single manufacturing plant (de Leeuw et al., 2013). Various literatures highlight the items defining manufacturing networks but do not link it to complexity. Approach: Using data from a single case study, we first introduce a framework enabling the analysis of the multi-dimensional characteristic of complexity in manufacturing networks. We then use the introduced framework to analyse the case study data and derive hypotheses, serving as basis for further research. Results: Manufacturing networks are influenced by internal and external complexity drivers. To reduce these complexity drivers, mainly manufacturing network coordination measures, such as a higher degree of standardisation, a lower degree of centralisation, or increased flows of resources, information and knowledge can be implemented. We also found some manufacturing network configuration measures, such as a higher proximity to suppliers, but since a change in the network configuration requires time and big changes in the network, configuration measures are only useful in a long time perspective. Implications: Internal complexity drivers can be reduced by changes in the manufacturing network configuration and coordination, while external complexity drivers cannot be reduced by changes in the network. The analysis which complexity drivers influence which strategic goals and the corresponding values help to decide which measures need to be implemented first do reach the highest possible complexity decrease. Value: A higher level of transparency allows better managing complexity. For academics, the results show how strategic goals, complexity drivers and manufacturing network configuration and coordination are linked and influence each other. For practitioners, the provided transparency shows where complexity can be reduced by manufacturing network configuration and coordination and with which measures additional complexity can be avoided.|
|Fulltext version:||Published version|
|License (according to publishing contract):||Licence according to publishing contract|
|Departement:||School of Management and Law|
|Appears in collections:||Publikationen School of Management and Law|
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