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Estimating stockout costs and optimal stockout rates: a case on the management of ugly produce inventory
Stanley Lim1, Elliot Rabinovich2, Sanghak Lee2, Sungho Park3
1Eli Broad College of Business, Michigan State University, USA; 2W.P. Carey School of Business, Arizona State University, USA; 3SNU Business School, Seoul University, South Korea
Efficiently managing inventories requires an accurate estimation of stockout costs. This estimation is complicated by challenges in determining how to compensate consumers monetarily to ensure they will maintain the same level of utility they would have obtained had stockouts not occurred. This paper presents an analysis of these compensation costs, as applied to the design of optimal stockout rates by an online retailer marketing to consumers aesthetically substandard fruits and vegetables.
Artificial intelligence based systems for reducing food waste
Yu Nu, Elena Belavina, Karan Girotra
SC Johnson College of Business, Cornell University/Cornell Tech, New York, NY 10044
In this study, we evaluate the effectiveness of AI-based systems in reducing the food waste generated in commercial kitchens. Using a multi-year field experiment in 500+ commercial kitchens, we estimate the waste reductions due to the use of (1) an automated transaction-level scaling system, and (2) an automated weighing and computer vision based waste-classification system. We also explore methods that use the waste data to identify the root causes behind the sub-optimal levels of food waste.
Relay logistics optimize long-haul shipments through a pit-stop network and separate drivers. This model benefits drivers and the environment, while reducing costs and lead times. An efficient algorithm solves the Relay Pickup-and-Delivery Problem, generating multiple arcs for optimal routing. Real-world experiments confirm its superiority over benchmarks, resulting in fewer miles traveled and win-win outcomes for sustainability.
