|Title:||An inventory model for overseas supplier in the quick response retailing industry|
Hong Kong Polytechnic University -- Dissertations
Department of Management
|Pages:||vi, 50,  leaves : ill. ; 30 cm|
|Abstract:||In the Quick Response retailing industry, retailers and suppliers are working together to form a partnership in the product supply chain. The idea is to increase the efficiency of their respective operations by exchanging information and data on a routine basis. In such a way, by eliminating unnecessary stock, double and triple handling, they both want to maximize availability for sales in store at minimized inventory cost and administrative cost. The decision making on the inventory level is now not simple at all, particularly when the supplier who also owns its manufacturing plant in overseas. In such a case, the replenishment lot size will affecting the cost of transportation, and at the same time, choice of transportation method will also affecting the replenishment lead-time. Thus to achieve optimal, factors affecting the lost sales at the stores, inventory holding cost at the warehouse, as well as the transportation and ordering cost incurred are all need to be considered. However, traditional EOQ system approach is not appropriated. Instead, a stochastic approach is adopted in designing the inventory model. In this study, customer demands at stores are described by the Poisson distribution and the losts associated in replenishment are expected values. Assuming stockouts at the warehouse is backordered and the stockouts at the stores are lost-sales, a multi-echelon inventory model is employed to compute the expected lost sales cost and the inventory holding cost. Finally, by considering the discounted transportation cost on different shipping lot size, a solution on the re-ordering point, re-ordering lot sizes are found and the choice of transportation method is also suggested. The result is then compared with the basic EOQ system and is found that EOQ approach is not as optimal as the one find by the stochastic method employed in this study.|
|Rights:||All rights reserved|
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