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FACULTY RESEARCH PROFILE ​

Dr. Xinxin Hu is a recipient of the Marilyn Davies Outstanding Research Award, which recognizes faculty who have published in A or A* publications, as ranked by the Australian Business Deans Council (ABDC) list. Learn more about her paper below: 

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​​ Xinxin Hu

Xinxin Hu, Ph.D. 

Associate Professor, Supply Chain Management. General Business, Marketing, and Supply Chain Management Department​​

Special Certifications/Licenses:​


Research and Creative Interests:Disruption and risk control in operations and supply chain. Contracting, channel design, and coordination in supply chain

Courses Taught
  • ​Supply Chain Management 
  • Decision Analytics with Excel Modeling 
  • Operations Management 
  • Operations Processes 
  • Materials Management​

 

​Lateral Transshipment with Partial Request and Random Switching

ABSTRACT:  : A large body of inventory management research has been devoted to lateral transshipment. Most of the existent models assume that the unmet local demand will automatically request transshipment, and that the unmet local demand does not seek inventory at other locations within the same echelon. In contrast, we investigate a two-store retailer’s inventory replenishment and transshipment decisions when those two assumptions do not hold. Specifically, we use a fixed request rate to model partial demand for transshipment at the shortage store and a random switch rate to model the arrival of the unmet demand at the surplus store. We characterize the optimal transshipment and inventory replenishment policies. We find that it is not always in the best interest of the retailer to satisfy as much as possible the transshipment demand. In light of the switched demand flowing to the surplus store, the retailer may benefit from saving the leftover inventory at the surplus store for the switched demand. The optimal transshipment policy follows a double-threshold structure when the prospect of the switched demand is not large enough; and a transshipment quantity of zero becomes optimal otherwise. Through an extensive numerical analysis, we examine the impact of the request rate and the switch rate, together with other parameters. We also evaluate a few simple-to-use transshipment heuristics, including one that we devise based on the structure of the optimal transshipment policy. The consistent, near-optimal performance of the devised heuristic is a confirmation of the importance of our theoretical work on the optimal policy.​
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What inspired you to write about this?

I am interested in how the supply chain can coordinate to achieve the better service to the consumers. The consumers now are also smart, and they have the tools to search and compare the goods they want to buy. Hence, I would like to see how the retailers can take that features of the consumers into their operations and work together to improve both the customers satisfaction and their own profitability.

What is the impact you hope this research will have?

Lateral transshipment is a very commonly applied practice between retailers to pooling the inventory. At the same time, the strategic customers behaviors play more and more important roles in the market. Hence, there are quite a few interesting topics we can study in the retailing business when we combine these two together. 

What else are you working on? 

Besides the supply chain coordination and contracts, I am also working on various issue that a production business may face, such as customer management , energy consumption, and startup financing.





Last updated 2/2/2021 5:46 AM