Dr. Jackson Li, has made several research accomplishments in high quality academic journals. For example, he has recently been publishing in Production and Operations Management (ABDC [Australian Business Deans] Ranking: A*), Decision Sciences (ABDC Ranking: A*), and International Journal of Production Economics (ABDC Ranking: A) among others.
Dr. Jackson Li’s overall research lies on stochastic modeling and its application to inventory management.
The first important paper “Optimizing Inventory’s Contribution to a Regulated Utility”, which was published in International Journal of Production Economics, reveals the inefficiency of inventory management in American power companies. The research was conducted using dynamic DEA model and they noticed that among the different inputs, inventory was the most inefficient one. This finding explains the Averch-Johnson effect in inventory management in such utility industry.
In another paper “A Stochastic Joint Replenishment Problem with Dissimilar Items”, Dr. Jackson Li and his coauthor Dr. Charles P. Schmidt studied the basic two-echelon supply chain in the stochastic manner, i.e., stochastic joint replenishment problem (SJRP). They explored the properties of this problem and suggest several heuristics to solve the problem efficiently. This research was published in Decision Sciences.
The most recent research “Managing Equipment Rentals: Unreliable Fleet, Impatient Customers, and Finite Commitment Capacity” in year 2022, discussed the equipment rental problem with a queueing model of quasi-birth-death process. The availability of the rental equipment depends on the fleet size of the firm and has a direct impact on its profitability. They developed an efficient recursive algorithm to solve the underlying two-dimensional stochastic single-player model. Their extensive managerial insights quantify the behavior of various performance measures in the single-player model regarding repair performance of the firm, customer impatience level, traffic intensity, and equipment rental revenue. They demonstrate that by applying the model to a real case, there is a potential of more than a 4% (400,000 USD) increase in total daily profits. Extending their model to a two-player game, they proposed an approximation heuristic to derive closed-form solutions to estimate equilibrium fleet sizes under complete information. Using their heuristic as the initial solution, they developed a simulation model to determine the exact equilibrium fleet sizes and draw a detailed comparison between the two-player and single-player models. This work was published in Productions and Operations Management.
Congratulations on your research findings, Dr. Jackson Li!