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Supply chain management services sharing in headquarters-centered group companies

A headquarters-centered group company considered in this thesis consists of one headquarters and several operationally semi-autonomous production subsidiaries. This research investigates the situation where the headquarters provides supply chain management services shared among subsidiaries to take advantage of risk pooling effect, economies of scale, and information and resource sharing.
This thesis considers three different but related scenarios. The first research scenario formulates two customer order management models. One is Headquarters-centered Common Order Management (HQ-COM) where customer orders are processed by the headquarters and then allocated to the subsidiaries. The other is Subsidiary-Autonomous Order Management (SD-AOM) where subsidiaries process customer orders relatively independent of each other. Two scenarios with demand uncertainty are simulated. One is that the order quantity exceeds the production capacity of each individual subsidiary so that the order has to be split before allocating to the subsidiaries. The other scenario is that the total quantity of selected customer orders is within the production capacity of a single subsidiary so that the orders should be merged into one batch before allocating to one subsidiary. The results show that HQ-COM outperforms SD-AOM in terms of both its performance and its robustness against demand variability. This achievement is largely due to the effects of pooling of different customer orders and sharing of production capacity among the subsidiaries.
The second research scenario develops two sourcing management models: Headquarters-centered Common Sourcing Management (HQ-CSM) and Subsidiary-Autonomous Sourcing Management (SD-ASM). In HQ-CSM, two management policies are examined. One is Order Coordination policy in which common replenishment epochs are proposed by the headquarters and the subsidiaries are encouraged to coordinate the timing of their orders based on the common replenishment epochs. The other is Order Consolidation policy in which the headquarters places a combined order with the supplier. The results show that HQ-CSM outperforms SD-ASM in terms of cost and robustness against demand uncertainties. This achievement is largely due to the synergistic ordering process, the economies of scale and risk pooling effect by the implementation of transshipments. The results also reveal that Order Consolidation policy always performs better than Order Coordination policy especially in face of high demand uncertainties and high service level requirement.
The third scenario considers a headquarters-managed centralized distribution center (HQ-CDC) serving multiple subsidiaries with stochastic demands. There are two kinds of inventory spaces: dedicated space and leased space. Two pricing policie--the constant pricing and the dynamic pricing--are compared. Two decision models are formulated. One is Integrated Model where the group company makes decisions on the replenishment and the space allocation simultaneously. The other is Bilevel Programming Model where the HQ-CDC and the subsidiaries make decisions sequentially. The results show that the HQ-CDC’s profit is noticeably improved in Bilevel Programming Model by the implementation of the constant pricing policy. The results also reveal that the leased space as a supplement of the reserved space leads to a more flexible space utilization and a reduced group company’s total cost especially in face of large demand and high demand fluctuation. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy
Date January 2014
CreatorsZhang, Ting, 张婷
ContributorsHuang, GQ
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Source SetsHong Kong University Theses
Detected LanguageEnglish
RightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works., Creative Commons: Attribution 3.0 Hong Kong License
RelationHKU Theses Online (HKUTO)

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