Author:
Chen Kebing,Zhou Haijie,Lei Dong
Abstract
<p style='text-indent:20px;'>In this paper, we develop a two-period inventory model of perishable products with considering the random demand disruption. Faced with the random demand disruption, the firm has two order opportunities: the initial order at the beginning of selling season (i.e., Period 1) is intended to learn the real information of the disrupted demand. When the information of disruption is realized, the firm places the second order, and also decides how many unsold units should be carried into the rest of selling season (i.e., Period 2). The firm may offer two products of different perceived quality in Period 2, and therefore it must trade-off between the quantity of carry-over units and the quantity of young units when the carry-over units cannibalize the sales of young units. Meanwhile, there is both price competition and substitutability between young and old units. We find that the quantity of young units ordered in Period 2 decreases with the quality of units ordered in Period 1, while the pricing of young units is independent of the quality level of old units. However, both the surplus inventory level and the pricing of old units monotonically increase with their quality. We also investigate the influence of two demand disruption scenarios on the optimal order quantity and the optimal pricing when considering different quality situations. We find that in the continuous random disruption scenario, the information value of disruption to the firm is only related to the disruption mean, while in the discrete random disruption scenario, it is related to both unit purchase cost of young units and the disruption levels.</p>
Publisher
American Institute of Mathematical Sciences (AIMS)
Subject
Applied Mathematics,Control and Optimization,Strategy and Management,Business and International Management,Applied Mathematics,Control and Optimization,Strategy and Management,Business and International Management
Reference56 articles.
1. Z. Azadi, S. D. Eksioglu, B. Eksioglu, G. Palak.Stochastic optimization models for joint pricing and inventory replenishment of perishable products, Computers & Industrial Engineering, 127 (2019), 625-642.
2. Y. Aviv.The effect of collaborative forecasting on supply chain performance, Management science, 47 (2001), 1331-1440.
3. İ. S. Bakal, Z. P. Bayındır, D. E. Emer.Value of disruption information in an EOQ environment, European J. Oper. Res., 263 (2017), 446-460.
4. M. A. Begen, H. Pun, X. Yan.Supply and demand uncertainty reduction efforts and cost comparison, International Journal of Production Economics, 180 (2016), 125-134.
5. A. Bensoussan, Q. Feng, S. Luo and S.P. Sethi, Evaluating long-term service performance under short-term forecast updates, International Journal of Production Research, (2003), 1–14.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献