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Title: Nonlinear pricing for stochastic container leasing system
Authors: Jiao, Wen
Yan, Hong
Pang, King-Wah
Keywords: Container leasing
Nonlinear pricing problem
Price discrimination
Dynamic mechanism design
Issue Date: 2016
Publisher: © Elsevier
Citation: JIAO, W., YAN, H. and PANG, K-W., 2016. Nonlinear pricing for stochastic container leasing system. Transportation Research Part B: Methodological, 89, pp. 1-18.
Abstract: With the substantial upsurge of container traffic, the container leasing company thrives on the financial benefits and operational flexibility of leasing containers requested by shippers. In practice, container lease pricing problem is different from the consumer product pricing in consideration of the fair value of container, limited customer types and monopolistic supply market. In view of the durability of container and the diversified lease time and quantity, the pricing is a challenging task for the leasing company. This paper examines the monopolist’s nonlinear pricing problems in static and dynamic envi- ronments. In particular, the leasing company designs and commits a menu of price and hire quantity/time pairs to maximize the expected profit and in turn customers choose hire quantities/time to maximize their surpluses according to their hire preferences. In a static environment, closed-form solutions are obtained for different groups of customers with multiple types subject to capacity constraint. In a dynamic environment, we address two customer types and derive closed-form solutions for the problem of customers with hire time preference. Further, we show that the effect of the capacity constraint increases with time of the planning horizon when customers have the same hire time preference; while in the case with different hire time preferences, the capacity constraint has opposite effects on the low and high type customers. Last, the case of customers with hire quantity preference is discussed. We focus on the lease with alternative given sets of hire time and use dynamic programming to derive the numerical optimal hire time sequence.
Description: This paper was accepted for publication in the journal Transportation Research Part B: Methodological and the definitive published version is available at https://doi.org/10.1016/j.trb.2016.03.012
Version: Accepted for publication
DOI: 10.1016/j.trb.2016.03.012
URI: https://dspace.lboro.ac.uk/2134/26457
Publisher Link: https://doi.org/10.1016/j.trb.2016.03.012
ISSN: 0191-2615
Appears in Collections:Published Articles (Business School)

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