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Determinants of the optimal network configuration and the implications for coordination


Deflorin, Patricia; Dietl, Helmut; Lang, Markus; Lucas, Eric (2012). Determinants of the optimal network configuration and the implications for coordination. UZH Business Working Paper Series 152, University of Zurich, Institute for Strategy and Business Economics (IOU).

Abstract

This paper develops a simulation model to compare the performance of two stylized manufacturing networks: the lead factory network (LFN) and the archetype network (AN). The model identifies the optimal network configuration and its implications for coordination mechanisms. Using an NK simulation model to differentiate between exogenous factors (configuration) and endogenous factors (coordination), we find low complexity of the production process, low transfer costs and high search costs, as well as a larger number of manufacturing plants benefit LFN compared to AN. Optimally coordinating the chosen network configuration of LFN might require to fully transfer knowledge in the short run but to transfer nothing in the long run. Moreover, a late knowledge transfer from the lead factory to the plants increases the pre-transfer performance of LFN but results in a larger performance drop, yielding a lower short-run but a higher long-run performance of LFN.

Abstract

This paper develops a simulation model to compare the performance of two stylized manufacturing networks: the lead factory network (LFN) and the archetype network (AN). The model identifies the optimal network configuration and its implications for coordination mechanisms. Using an NK simulation model to differentiate between exogenous factors (configuration) and endogenous factors (coordination), we find low complexity of the production process, low transfer costs and high search costs, as well as a larger number of manufacturing plants benefit LFN compared to AN. Optimally coordinating the chosen network configuration of LFN might require to fully transfer knowledge in the short run but to transfer nothing in the long run. Moreover, a late knowledge transfer from the lead factory to the plants increases the pre-transfer performance of LFN but results in a larger performance drop, yielding a lower short-run but a higher long-run performance of LFN.

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Additional indexing

Item Type:Working Paper
Communities & Collections:03 Faculty of Economics > Department of Business Administration
Dewey Decimal Classification:330 Economics
Language:English
Date:2012
Deposited On:28 Aug 2019 14:32
Last Modified:25 Sep 2019 00:43
Series Name:UZH Business Working Paper Series
Number of Pages:39
ISSN:1660-1157
OA Status:Green
Other Identification Number:merlin-id:8051

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