In the hustle and bustle of modern urban transportation, multi-party carpooling emerges as an innovative trend taking the streets by storm. Imagine a system where you don’t just share a ride with one friend, but with a whole group of strangers heading in the same direction. It’s like a party on wheels that promises to reduce traffic congestion, save money, and expand social networks. However, like any party, organizing it can be quite a challenge.
Research by our faculty, Dr. Xiaohang Yue, together with Dr. Hao Yu and Dr. Min Huang from Northeastern University in China, dives into the intricacies of multi-party carpooling operations, making it not just a good idea, but a great one.
The issue they tackle is the matching and pricing conundrum in the presence of information asymmetry and decentralized decision-making. Given the voluntary participation nature and the early development stage of multi-party carpooling, the willingness to pay of riders and the opportunity costs of drivers are highly personalized and unpredictable in the absence of a stable market price. Additionally, looser regulation leads to a decentralized decision-making scenario, where the strategic behaviors of self-interested agents can violate the platform’s centralized solutions and incur the price of anarchy.
Dr. Yue’s innovative solution involves auctions. They use double auctions to determine who rides with whom and how much they will pay and receive. It’s like a high-stakes game show where the prizes are shared rides, sponsored by drivers, with allocation and prices based on the bids of all participants and the game rules specified by the platform.
While auctions might seem complicated, Dr. Yue’s work simplifies them. They’ve designed a double auction system that’s strategy-proof and individually rational, meaning participants can just bid what they truly believe is worth without mind games, ensuring they get the best deal. Furthermore, the auction system is budget-balanced and asymptotically efficient, ensuring that the platform doesn’t incur costs and rides are allocated efficiently in a large economy, as if the information were complete.
Dr. Yue’s research also accommodates key features of multi-party carpooling. It incorporates personalized carpooling constraints, crucial due to the closer interactions with strangers. It also integrates frustration-based promotion to prioritize matching proactively and provide differentiated rate subsidies based on riders’ waiting times and operational flexibility, enabling the platform to adjust operational objectives as needed. These features are embedded in the auction mechanisms, allowing for variable operational objectives by adjusting the strength of frustration-based promotion.
Practically, Dr. Yue’s work provides powerful decision support tools for the platform, outperforming counterparts from both practice and literature concerning efficiency and service responsiveness. It also sheds light on choosing alternative mechanisms in response to varying market conditions and the platform’s operational orientations, serving as a practical guide for better market navigation.
So, the next time you’re stuck in traffic, thinking about the environment, your wallet, and the friends you haven’t made yet, remember this work. It figures out how to make carpooling not just a way to get around, but a way to get ahead. The research is a roadmap for a smarter, greener, and more social way to navigate the symbiotic carpooling network.
This research is featured in Production and Operations Management, “Sharing the Shared Rides: Multi-Party Carpooling Supported Strategy-Proof Double Auctions,” Hao Yu, Min Huang, and Xiaohang Yue.
Photo and story courtesy of Dr. Xiaohang Yue.
| Research@Lubar Faculty scholarship in the Lubar College of Business spans the business fields and beyond through both theoretical and applied research that is published in leading journals. Here are some of our faculty’s most recent publications: |
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