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.
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.
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.
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.
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.
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.
This research is partially supported through the research grants of NIDA Business School.
It is interesting to observe that an area of research that can significantly improve the retailer’s replenishment operations efficiency is to develop an optimal order quantity model that can include the shelf space as a decision variable along with the associated cost of shelf space investment. One possible approach is to extend the mathematical programming model developed by Hariga et al. (2007). Another avenue of related research is to develop a model that can jointly determine optimal replenishment decisions from both vendors’ and retailers’ perspectives when the backroom and the in-store handling costs are included.
Chiralaksanakul, A. and Sukhotu, V. (2016), "An optimal order quantity with shelf-refill trips from backroom for efficient store operations", Journal of Modelling in Management, Vol. 11 No. 4, pp. 967-984. https://doi.org/10.1108/JM2-04-2014-0025Download as .RIS
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