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|dc.contributor.author||Datta, Partha Priya|
|dc.contributor.author||Christopher, Martin G.|
|dc.description||Datta, Partha Priya, Operations Management Group, Indian Institute of Management, Calcutta, 700104, India; Christopher, Martin G., Centre for Logistics and Supply Chain Management, School of Management, Cranfield University, Bedford, MK43 0AL, United Kingdom|
|dc.description||ISSN/ISBN - 00207543|
|dc.description||DOI - 10.1080/00207540903460216|
|dc.description.abstract||The study aims to investigate the effectiveness of information sharing and coordination mechanisms in reducing uncertainty. Supply chains are constantly subject to unpredictable events that can adversely influence its ability to achieve performance objectives. This paper primarily aims at managing uncertainties originating from unexpectedly large demand spikes. The supply chain literature is full of effective supply chain uncertainty management practices. This paper reviews the different practices for improving management of uncertainty and proposes several combinations of information sharing and coordination mechanism for reducing the uncertainty in supply chains. Next, the proposed combinations are tested on the make-to-stock supply chain of a paper tissue manufacturer using an agent-based simulation approach to show how the use of different levels of information sharing and coordination can be effective in managing uncertainty under daily operations facing a huge mismatch of actual and forecast demand. The findings of this research suggest that, a centralised information structure without widespread distribution of information and coordination is not effective in managing uncertainty of supply chain networks, even with increased frequency of information flow. Similarly, coordinating material flows without widespread information sharing does not improve supply chain uncertainty management. Central coordination of material flows with supply chain wide information sharing across different members is found to be essential in managing supply chains effectively under uncertainty. � 2011 Taylor & Francis.|
|dc.publisher||International Journal of Production Research|
|dc.subject||Agent based model|
|dc.title||Information sharing and coordination mechanisms for managing uncertainty in supply chains: A simulation study|
|Appears in Collections:||Operations Management|
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