Understanding Participation of Competing Firms in Supply Chain Information Sharing Under Disruption
Share when coordination gains outweigh competitive exposure.
Supply chains are exposed to disruptions more frequently, while firms observe them independently, leading to inefficiencies. Although information sharing can improve performance, competing firms may withhold information due to competitive concerns. This study examines a voluntary information-sharing platform for competing firms to exchange disruption-related information while maintaining operational autonomy. We model firms’ decisions as a two-stage game in a two-echelon supply chain subject to stochastic disruptions and private signals. In the first stage, firms decide whether to participate. In the second stage,
they make operational decisions using available information. Our analytical study examines equilibrium platform participation and shows how information power and competition impact firms' incentives. Numerical experiments demonstrate that firms with strong information advantages may hesitate to participate as network density increases, while firms with the same informational capabilities may have different participation incentives depending on the distribution of competitive links.
Batuhan Çelik
PhD Student, Industrial and Systems Engineering, RPI
MATCHING IN THE GIG ECONOMY
Dynamic Matching with Preference Learning in Crowdsourced Delivery Platforms
Use population knowledge early. Personalize every match with feedback.
Crowdsourced delivery platforms must dynamically match couriers and requests while learning user preferences. We study a sequential matching problem where couriers may stochastically accept or reject offers based on preferences. We propose a learning-based matching framework that estimates courier-specific acceptance probabilities via logistic regression and integrates them into the matching procedure. Computational experiments show our approach consistently outperforms distance-based heuristics and average-courier benchmarks across diverse settings, improving efficiency and service quality on the platform.
Ran Hu
PhD Student, Industrial and Systems Engineering, RPI
