Innovative replenishment management for perishable items using logistic regression and grey analysis
by Jia-Yen Huang
International Journal of Business Performance Management (IJBPM), Vol. 15, No. 2, 2014

Abstract: In this paper, an innovative decision support system is proposed, by consolidating the newsboy model, logistic regression, and grey relation analysis, to develop an efficient replenishment policy, which maximises the total profit of perishable items in a convenience store. First, the basic order quantity of the overall meal-box is determined by the newsboy model. Next, we develop a wastage-free system by employing logistic regression to adjust the overall basic order quantity, which may deviate from the real demand due to the effect of uncertain factors such as the weather and the number of customers. Finally, grey relation analysis is conducted to allocate the order quantity of each kind of meal-box efficiently. Based on actual data from a convenience store of the President Chain Store Corporation in Taiwan, the superiority of the decision support system was evaluated. The experimental findings reveal that the proposed policy can outperform the traditional replenishment policy. Since customers' tastes can be precisely monitored through this system, daily needs can be estimated and controlled more accurately and the quantities of shortage and wastage can be reduced. This system is believed to raise customer satisfaction and increase the profit of the store.

Online publication date: Mon, 16-Jun-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Performance Management (IJBPM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email