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The impact of demand information sha...
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Tan, Gek Woo.
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The impact of demand information sharing on supply chain network.
Record Type:
Electronic resources : Monograph/item
Title/Author:
The impact of demand information sharing on supply chain network./
Author:
Tan, Gek Woo.
Description:
87 p.
Notes:
Source: Dissertation Abstracts International, Volume: 60-12, Section: A, page: 4512.
Contained By:
Dissertation Abstracts International60-12A.
Subject:
Business Administration, Management. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9953155
ISBN:
0599561165
The impact of demand information sharing on supply chain network.
Tan, Gek Woo.
The impact of demand information sharing on supply chain network.
- 87 p.
Source: Dissertation Abstracts International, Volume: 60-12, Section: A, page: 4512.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.
This thesis evaluates the impact of demand information sharing policies on supply chain network structures, product structures and demand mix. Research suggests that information sharing reduces the bullwhip effect in a supply chain network. Furthermore, different types of information sharing are beneficial for different supply chain network structures. The overall question of the thesis is: Does demand information sharing improve supply chain network performance?
ISBN: 0599561165Subjects--Topical Terms:
626628
Business Administration, Management.
The impact of demand information sharing on supply chain network.
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Tan, Gek Woo.
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The impact of demand information sharing on supply chain network.
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87 p.
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Source: Dissertation Abstracts International, Volume: 60-12, Section: A, page: 4512.
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Adviser: Michael J. Shaw.
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Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.
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This thesis evaluates the impact of demand information sharing policies on supply chain network structures, product structures and demand mix. Research suggests that information sharing reduces the bullwhip effect in a supply chain network. Furthermore, different types of information sharing are beneficial for different supply chain network structures. The overall question of the thesis is: Does demand information sharing improve supply chain network performance?
520
$a
The study is carried out via simulation. A multi-agent simulation system is developed based on the complex adaptive system paradigm to model the supply chain network. The system simulates the actions of the enterprises as they interact with each other and with the environment. The state variables of the agents are periodically probed and recorded. The emergent behavior of the supply chain network arises from interactions of the enterprise agents over time.
520
$a
The findings of the study are summarized as follows: enterprises incorporate a safety stock to buffer against unpredictable demand. The inclusion of the safety stock in their orders distorts the demand signal which partially causes the bullwhip effect. Information sharing cuts through the distortion by directly monitoring the state variables of the customers. When demand is uniform and equal, information sharing policies perform well because they reduce the bullwhip effect. However, in scenarios with multiple end products and volatile demand mixes, no information sharing performs better because the buffer cushions the enterprise from erratic fluctuations in demand. For products with multiple input components, the performance is influenced by the inventory holding cost policy used.
520
$a
Each information sharing policy monitors different state variables and unique characteristic behavior. The behaviors remain constant throughout different supply chain network structures. Convergent supply networks have no effect on the performance while divergent distribution networks marginally diminish the bullwhip effect. Increasing the number of tiers increases the bullwhip effect.
520
$a
The conclusion of the study is that there is no overall information sharing policy that has superior performance in all scenarios. A hybrid information sharing policy is a solution that combines the best of both worlds by matching one policy's strength to another's weakness.
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School code: 0090.
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University of Illinois at Urbana-Champaign.
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Dissertation Abstracts International
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60-12A.
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Shaw, Michael J.,
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advisor
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Ph.D.
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1999
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9953155
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