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Kun-Jen Chung

Researcher at Chung Yuan Christian University

Publications -  11
Citations -  434

Kun-Jen Chung is an academic researcher from Chung Yuan Christian University. The author has contributed to research in topics: Inventory control & Trade credit. The author has an hindex of 7, co-authored 11 publications receiving 410 citations.

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The optimal retailer's ordering policies for deteriorating items with limited storage capacity under trade credit financing

TL;DR: In this article, the authors proposed a two-warehouse inventory model for deteriorating items under a permissible delay in payments, where the goods are not perishable and the storage capacity is unlimited.
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The optimal ordering policy of the EOQ model under trade credit depending on the ordering quantity from the DCF approach

TL;DR: This paper discusses the optimum order quantity of the EOQ model that is not only dependent on the inventory policy but also on firm' credit policy and develops a new inventory model to generalize Chung.
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An integrated vendor-buyer inventory model with order-processing cost reduction and permissible delay in payments

TL;DR: An integrated inventory model is developed to determine the optimal inventory policy under conditions of order-processing cost reduction and permissible delay in payments, and it is shown that the total annual variable cost function possesses some kinds of convexities.
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The simplified solution algorithm for an integrated supplier–buyer inventory model with two-part trade credit in a supply chain system

TL;DR: This paper can not only derive the optimally closed-form formulations for the optimal numbers of shipments but also develop different algorithms to improve those in Ho et al. (2008).
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Comments on the EOQ model under retailer partial trade credit policy in the supply chain

TL;DR: Huang and Hsu as mentioned in this paper investigated the inventory system as a cost minimization problem to determine the retailer's optimal inventory policy under the supply chain and developed two easy-to-use theorems to locate the optimal policy for the retailer.