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    Collaborative Procurement and Due Date Management in Supply Chains

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    savasaneril_secil_200412_phd.pdf (1.443Mb)
    Date
    2004-11-19
    Author
    Savasaneril, Secil
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    Abstract
    In this thesis we analyze the procurement process of buyers and supply decisions of manufacturers. Companies are looking for ways to decrease their procurement costs, which account for a large percentage of the supply chain costs. We study the effects of demand aggregation and collaborative procurement on buyers' profitability. First, we make a high-level analysis and consider a market with multiple buyers and suppliers where multi-unit transactions for multiple items take place. The procurement costs are effected by economies of scale in the suppliers' production costs and by economies of scope in transportation. We design buyer strategies that model different collaboration levels and assess the role of collaboration under varying market conditions. Next, we analyze the procurement process at a lower level and identify benefits of inter-firm collaboration among buyers who are potential competitors in the end market. We adopt a game-theoretic approach to explore the economics of the basic mechanism underlying collaborative procurement, and determine the conditions that makes it beneficial for the participants. Besides low procurement costs, important considerations in supplier selection are responsiveness and the reliability of the suppliers in meeting demand. Hence, manufacturers face the pressure for quoting short and reliable lead times. We cover several aspects of the manufacturer's problem, such as quoting reliable due-dates based on current workload in the system, maximizing profit considering the lateness cost incurred due to late deliveries, and deciding on the level of inventory to increase responsiveness. We employ a model where demand arrival and manufacturing processes are stochastic, and obtain insights on the optimal due-date quotation policy and on the optimal inventory level.
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    http://hdl.handle.net/1853/4884
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    • Georgia Tech Theses and Dissertations [23877]
    • School of Industrial and Systems Engineering Theses and Dissertations [1457]

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