Hostname: page-component-76fb5796d-5g6vh Total loading time: 0 Render date: 2024-04-26T18:11:15.383Z Has data issue: false hasContentIssue false

TWO-ECHELON PRODUCTION INVENTORY SYSTEMS WITH STRATEGIC CUSTOMERS

Published online by Cambridge University Press:  27 September 2019

Ata G. Zare
Affiliation:
Department of Management Sciences, University of Waterloo, Waterloo, ON, N2L 3G1, Canada E-mail: aghareha@uwaterloo.ca, haboueemehrizi@uwaterloo.ca
Hossein Abouee-Mehrizi
Affiliation:
Department of Management Sciences, University of Waterloo, Waterloo, ON, N2L 3G1, Canada E-mail: aghareha@uwaterloo.ca, haboueemehrizi@uwaterloo.ca
Oded Berman
Affiliation:
Rotman School of Management, University of Toronto, Toronto, ON, M5S 3E6, Canada E-mail: Berman@rotman.utoronto.ca

Abstract

We consider a two-echelon production inventory system with a manufacturer having limited production capacity and a distribution center (DC). There is a positive transportation time between the manufacturer and the DC. Customers gain a value by receiving the product and incur a waiting cost when facing a delay. We assume that customers' waiting cost depends on their degree of impatience with respect to delay, which is captured by a convex waiting cost function. Customers are strategic with respect to joining the system and either place an order or balk from the system upon their arrival depending on their expected waiting time. We study the Stackelberg equilibrium assuming that the DC acts as a Stackelberg leader and customers are the followers. We first obtain the total expected revenue and then provide a heuristic to derive the optimal base-stock levels in the warehouse and the DC as well as the optimal price of the product.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Abouee-Mehrizi, H., Berman, O., Shavandi, H., & Zare, A.G. (2011). An exact analysis of a joint production-inventory problem in two-echelon inventory systems. Naval Research Logistics 58(8): 713730.10.1002/nav.20477CrossRefGoogle Scholar
2.Afèche, P., Sanajian, N. (2013). Competition among risk-averse newsvendors. Working Paper.Google Scholar
3.Agrawal, V. & Seshadri, S. (2000). Impact of uncertainty and risk aversion on price and order quantity in the newsvendor problem. Manufacturing & Service Operations Management 2(4): 410423.10.1287/msom.2.4.410.12339CrossRefGoogle Scholar
4.Berman, O. & Schnabel, J.A. (1986). Mean-variance analysis and the single-period inventory problem. International Journal of Systems Science 17(8): 11451151.CrossRefGoogle Scholar
5.Chen, X., Sim, M., Simchi-Levi, D., & Sun, P. (2007). Risk aversion in inventory management. Operations Research 55(5): 828842.CrossRefGoogle Scholar
6.Du, J., Zhang, J., & Hua, G. (2015). Pricing and inventory management in the presence of strategic customers with risk preference and decreasing value. International Journal of Production Economics 164: 160166.10.1016/j.ijpe.2015.02.013CrossRefGoogle Scholar
7.Edelson, N.M. & Hilderbrand, D.K. (1975). Congestion tolls for poisson queuing processes. Econometrica: Journal of the Econometric Society 43(1): 8192.10.2307/1913415CrossRefGoogle Scholar
8.Hassin, R. (2016). Rational queueing. New York: Chapman and Hall/CRC.10.1201/b20014CrossRefGoogle Scholar
9.Hassin, R. & Haviv, M. (2003). To queue or not to queue: Equilibrium behavior in queueing systems, Vol 59. Springer, Boston, MA: Springer Science & Business Media.CrossRefGoogle Scholar
10.He, Q.-M., Jewkes, E.M., & Buzacott, J. (2002). Optimal and near-optimal inventory control policies for a make-to-order inventory–production system. European Journal of Operational Research 141(1): 113132.10.1016/S0377-2217(01)00257-0CrossRefGoogle Scholar
11.Liu, Q. & Van Ryzin, G.J. (2008). Strategic capacity rationing to induce early purchases. Management Science 54(6): 11151131.CrossRefGoogle Scholar
12.Naor, P. (1969). The regulation of queue size by levying tolls. Econometrica: Journal of the Econometric Society 37(1): 1524.10.2307/1909200CrossRefGoogle Scholar
13Osuna, E.E. (1985). The psychological cost of waiting. Journal of Mathematical Psychology 29(1): 82105.10.1016/0022-2496(85)90020-3CrossRefGoogle Scholar
14.Simchi-Levi, D. & Zhao, Y. (2007) Three generic methods for evaluating stochastic multi-echelon inventory systems. Technical report,Working paper, Massachusetts Institute of Technology, Cambridge.Google Scholar
15.Wang, Q. (2011). Control policies for multi-echelon inventory systems with stochastic demand. In Supply chain coordination under uncertainty. Berlin, Heidelberg: Springer, pp. 83108.10.1007/978-3-642-19257-9_4CrossRefGoogle Scholar
16.Yechiali, U. (1971). On optimal balking rules and toll charges in the gi/m/1 queuing process. Operations Research 19(2): 349370.CrossRefGoogle Scholar
17.Yechiali, U. (1972). Customers' optimal joining rules for the gi/m/s queue. Management Science 18(7): 434443.10.1287/mnsc.18.7.434CrossRefGoogle Scholar
18.Zare, A.G., Abouee-Mehrizi, H., & Berman, O. (2017). Exact analysis of the (R, Q) inventory policy in a two-echelon production–inventory system. Operations Research Letters 45(4): 308314.10.1016/j.orl.2017.04.011CrossRefGoogle Scholar
19.Zipkin, P.H. (2000). Foundations of inventory management, Vol 2. New York: McGraw-Hill.Google Scholar