Dr Wendy Jiao is a Senior Lecturer in Operations Management at the University of Exeter Business School since September 2021. Prior to joining Exeter, Wendy was a Lecturer in Operations Management at Loughborough University and a post-doctoral fellow at The Hong Kong Polytechnic University.
Wendy is the Principle Investigator of British AcademyLeverhulme Small Research Grant, “Dynamic Bargaining Games in the Container Leasing Industry”. In addition, she is a core member of a large research grant of the NSFC/RGC Joint Research Scheme about container leasing, in which she played a leading role in coordinating research groups in universities of Hong Kong and Beijing, container users and leasing companies.
Qualifications
Research interests
- Revenue Management
- Capacity Management
- Inventory Management
Dr Wendy Jiao’s research covers operations research and stochastic optimization, mainly concentrating on dynamic revenue management, capacity management, and inventory management. She specifically investigates different theoretical and analytical methods and adopts them to examine dynamic linear/nonlinear pricing problems of stochastic rental systems given various features of rental suppliers and different characteristics of customers.
Wendy started on the container rental pricing research since her PhD study. With a comprehensive understanding of the problem, she applied her research methodologies and results to the container leasing industry and the media advertising industry in the past three years. Besides, she extended the research into general pricing problems in sharing economies in industry and built up industrial collaborations and investigated application issues in some related companies in the United Kingdom, Hong Kong and Mainland China.
Research projects
Wendy’s ongoing research focuses on B2B revenue management and fleet management in the container leasing industry.
Research projects
2020-2022: British Academy/Leverhulme Small Research Grant. Dynamic Bargaining Dynamic Bargaining Games in the Container Leasing Industry. Principle Investigator
2020-2021: Company-funded Research Project. Demand Analysis and Forecast in Radio Advertising. Principle Investigator
2019-2021: Young Scientists Fund of the National Natural Science Foundation of China. The Price of Anarchy in Reverse Supply Chains with Disaster Relief Inventory Refreshment. Co-Investigator
2018-2020: Young Scientists Fund of the National Natural Science Foundation of China. Resource Sharing and Optimization for Shipping Companies. Co-Investigator
2017-2021: National Natural Science Foundation of China/Research Grants Council Joint Research Scheme. Dynamic Revenue Management and Fleet Management for Stochastic Container Leasing. Co-Investigator
Key publications | Publications by category | Publications by year
Publications by category
Journal articles
Yang X, Jiao W, Zhang J, Yan H (2022). Capacity management for a leasing system with different equipment and batch demands.
Production and Operations Management,
31(7), 3004-3020.
Abstract:
Capacity management for a leasing system with different equipment and batch demands
AbstractThis work explores the admission and capacity allocation for a leasing system with two types of equipment and three kinds of batch demands: elementary specified, premium specified, and unspecified demands. The demands arrive following mutually independent Poisson processes, and the rental duration of equipment follows a negative exponential distribution. The lessor can satisfy partially the specified demands with the required type of equipment and satisfy partially the unspecified demands with any type of equipment. The objective is to maximize the expected discounted revenue. We formulate this problem as a Markov decision process, prove the anti‐multimodularity of the value function, and characterize the structure of the optimal policy. We show that the optimal policy has a simple structure and is characterized by state‐dependent rationing and priority thresholds. Moreover, a solution algorithm is proposed to calculate the optimal policy. We study the impacts of the system state on the optimal action and find that the optimal action has limited sensitivity to the system state. Numerical studies are conducted to compare the performance of the optimal policy with that of two heuristic methods and to derive some managerial insights by analysis. We further discuss batch acceptance.
Abstract.
DOI.
Jiao W (2022). Dynamic allocation and pricing for capacitated stochastic container leasing systems with dynamic arrivals.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY,
73(10), 2186-2203.
Author URL.
DOI.
Yang X, Zhang J, Jiao W, Yan H (2022). Optimal Capacity Rationing Policy for a Container Leasing System with Multiple Kinds of Customers and Substitutable Containers.
Management Science DOI.
Chen Y, Tao K, Jiao W, Yang D (2020). Investigating the underlying social psychology of the innovation adoption in container trucking industry.
Transportation Research Part a Policy and Practice,
137, 259-270.
DOI.
Li Q, Guan X, Shi T, Jiao W (2019). Green product design with competition and fairness concerns in the circular economy era.
International Journal of Production Research,
58(1), 165-179.
DOI.
Ye Y, Jiao W, Yan H (2019). Managing Relief Inventories Responding to Natural Disasters: Gaps Between Practice and Literature.
Production and Operations Management,
29(4), 807-832.
DOI.
Jiao W, Zhang J-L, Yan H (2017). The stochastic lot-sizing problem with quantity discounts.
Computers & Operations Research,
80, 1-10.
DOI.
Jiao W, Yan H, Pang K-W (2016). Nonlinear pricing for stochastic container leasing system.
Transportation Research Part B Methodological,
89, 1-18.
DOI.
Conferences
Gao D, Jiao W, Zhang J (2010). Capacitated Facility Location Problem with Freight Cost Discount. 2010 7th International Conference on Service Systems and Service Management.
DOI.
Publications by year
2022
Yang X, Jiao W, Zhang J, Yan H (2022). Capacity management for a leasing system with different equipment and batch demands.
Production and Operations Management,
31(7), 3004-3020.
Abstract:
Capacity management for a leasing system with different equipment and batch demands
AbstractThis work explores the admission and capacity allocation for a leasing system with two types of equipment and three kinds of batch demands: elementary specified, premium specified, and unspecified demands. The demands arrive following mutually independent Poisson processes, and the rental duration of equipment follows a negative exponential distribution. The lessor can satisfy partially the specified demands with the required type of equipment and satisfy partially the unspecified demands with any type of equipment. The objective is to maximize the expected discounted revenue. We formulate this problem as a Markov decision process, prove the anti‐multimodularity of the value function, and characterize the structure of the optimal policy. We show that the optimal policy has a simple structure and is characterized by state‐dependent rationing and priority thresholds. Moreover, a solution algorithm is proposed to calculate the optimal policy. We study the impacts of the system state on the optimal action and find that the optimal action has limited sensitivity to the system state. Numerical studies are conducted to compare the performance of the optimal policy with that of two heuristic methods and to derive some managerial insights by analysis. We further discuss batch acceptance.
Abstract.
DOI.
Jiao W (2022). Dynamic allocation and pricing for capacitated stochastic container leasing systems with dynamic arrivals.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY,
73(10), 2186-2203.
Author URL.
DOI.
Yang X, Zhang J, Jiao W, Yan H (2022). Optimal Capacity Rationing Policy for a Container Leasing System with Multiple Kinds of Customers and Substitutable Containers.
Management Science DOI.
2020
Chen Y, Tao K, Jiao W, Yang D (2020). Investigating the underlying social psychology of the innovation adoption in container trucking industry.
Transportation Research Part a Policy and Practice,
137, 259-270.
DOI.
2019
Li Q, Guan X, Shi T, Jiao W (2019). Green product design with competition and fairness concerns in the circular economy era.
International Journal of Production Research,
58(1), 165-179.
DOI.
Ye Y, Jiao W, Yan H (2019). Managing Relief Inventories Responding to Natural Disasters: Gaps Between Practice and Literature.
Production and Operations Management,
29(4), 807-832.
DOI.
2017
Jiao W, Zhang J-L, Yan H (2017). The stochastic lot-sizing problem with quantity discounts.
Computers & Operations Research,
80, 1-10.
DOI.
2016
Jiao W, Yan H, Pang K-W (2016). Nonlinear pricing for stochastic container leasing system.
Transportation Research Part B Methodological,
89, 1-18.
DOI.
2010
Gao D, Jiao W, Zhang J (2010). Capacitated Facility Location Problem with Freight Cost Discount. 2010 7th International Conference on Service Systems and Service Management.
DOI.
- Early Career Researchers Committee member, The Operational Research Society, UK
- Reviewer for Production and Operations Management, Computers & Operations Research, Omega, Transportation Research Part B, Transportation Research Part E.
I am currently teaching the following modules:
- BEMM460 Statistics and Mathematics for Business Analytics
- BEMM173 International Operations Management
I taught several modules at Loughborough University.
- Logistics System Operations (Postgraduate)
- Logistics Modelling and Operations Analytics (Postgraduate)
- Logistics and Supply Chain Management Project (Postgraduate)
- Operations Management (Undergraduate, Postgraduate, EMBA)
- Data Analysis for Management (Undergraduate)
- Business Optimisation (Undergraduate)
- Project Management (Undergraduate)
Modules
2023/24
