Comparing policies for the stochastic multi-period dual sourcing problem from a supply chain perspective

Document Type

Article

Source of Publication

International Journal of Production Economics

Publication Date

1-1-2020

Abstract

© 2020 Elsevier B.V. We study a supply chain that consists of a buyer and two suppliers. The buyer faces stochastic demand and has two different supply sources for the same product: a slower regular supplier and a more expensive expedited supplier. Such dual sourcing inventory systems have been widely studied in the literature, evaluating what is best for the buyer. As the decisions of the buyer may adversely affect the costs of the suppliers, and also, potentially, the supply chain profit, we adopt the perspective of the entire supply chain. We compare the performance of two different policies in a multi-period and two-echelon setting: the Dynamic Order Policy (DOP) and the Standing Order Policy (SOP). In the long run, the DOP policy converges to the Dual-Index Policy (DIP), which is optimal for the buyer in the case of a lead time difference of one period. On the other hand, the SOP policy is appealing from a practical perspective as a fixed (standing) quantity is ordered from the regular supplier in each period. We show that from our supply chain perspective, the DOP policy is not necessarily the better performing policy, and we define the conditions for the preferred policy. We evaluate the policies numerically under various conditions to obtain relevant managerial insights. We find that the preferred policy from a supply chain perspective is mainly the result of a trade-off between responsiveness, flexibility, and cost. Flexibility appears to be valuable if there is a substantial cost difference between the suppliers.

ISSN

0925-5273

Publisher

Elsevier B.V.

Volume

232

First Page

107923

Disciplines

Business

Keywords

Dual sourcing, Inventory management, Policy comparison, Policy evaluation, Supply chain

Scopus ID

85092796420

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Green: A manuscript of this publication is openly available in a repository

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