A Bilevel Analytical Model for Dynamic Storage Pricing in a Supply Hub in Industrial Park (SHIP)

A Supply Hub in Industrial Park (SHIP) is a thirdparty business entity that leases storage space and logistics services among manufacturers located in the same industrial park. Manufacturers may hire warehouses outside the park if SHIP´s storage price is exorbitant. This paper discusses how SHIP and manufacturers interact to optimize their decisions on storage pricing, replenishment, and delivery. A dynamic storage pricing strategy depending on storage length is adopted. This problem is modeled as a bilevel program where the SHIP is the leader and manufacturers are followers. Based on further assumptions, the proposed bilevel model is solved in closed-form. A series of sensitivity analyses are conducted to examine the influences of major cost parameters. The results show that SHIP´s delivery charge has little impact on the total cost of large manufacturers, and its increase will not always bring profit improvement to SHIP. Contrary to intuition, the SHIP could attract more space demands from large manufacturers when charging higher in delivery or when the public warehouse´s delivery charge is lower, and more space demands from small manufacturers when the market storage price is lower. Note to Practitioners-It becomes increasingly common for an industrial park to provide a supply hub for its member enterprises to share warehousing and transportation services. The SHIP gains its main revenue from leasing storage space. Hence, it is natural that SHIP must establish a suitable storage pricing strategy to attain the maximum profit. Being motivated by this challenge, this paper investigates a dynamic storage pricing of SHIP in a typical supply chain with one SHIP and multiple manufacturers. We develop a bilevel model to study this problem and derive the optimal solutions in closed-form for special cases. We provide valuable managerial guidance for the SHIP operator to charge dynamic storage price, and for member enterprises to schedule their replenishment and deliver- under different scenarios. Several counterintuitive findings are obtained regarding the influence of delivery costs inside and outside the industrial park, which will attract attention from managers of SHIP and member firms. This paper is limited to certain assumptions in deriving the optimal decisions. In future research, we will relax the assumption and design other methods to solve the proposed bilevel model. We will also investigate other forms of storage pricing strategies, which will shed further light on SHIP´s decision automation.