An optimal order quantity with shelf-refill trips from backroom for efficient store operations

Author:

Chiralaksanakul Anukal,Sukhotu Vatcharapol

Abstract

Purpose The purpose of this paper is to investigate the impact of backroom storage in supply chain replenishment decision parameters: the order quantity based on the well-established economic order quantity (EOQ) model. Design/methodology/approach The authors develop an EOQ-type model to investigate the operational cost impact of the order quantity with backroom storage. Because of the discrete and discontinuous nature of the problem, a modification of an existing algorithm is applied to obtain an optimal order quantity. Numerical experiments derived from a leading retailer in Thailand are used to study the cost impact of the backroom. Findings The paper shows that the backroom storage will significantly affect the decision regarding the order quantity. If its effect is ignored, the cost increase can be as high as 30 per cent. The costs and operations of additional shelf-refill trips from the backroom must be carefully analyzed and included in the decisions of replenishment operations. Research limitations/implications The model is a simplified version of the actual replenishment process. Validation from a real-world setting should be used to confirm the results. There are many additional opportunities to further integrate other issues in this problem such as shelf space decisions or joint order quantity between vendors and retailers. Practical implications The insights gained from the model will help managers, both retailers and vendors or manufacturers, make better decisions with regard to the order quantity policy in the supply chain. Originality/value Problems with backroom storage have been qualitatively described in the literature in the past decade. This paper is an early attempt to develop a quantitative model to analytically study the cost impact of backroom on order quantity decisions.

Publisher

Emerald

Subject

Management Science and Operations Research,Strategy and Management,General Decision Sciences

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