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Title : Course allocation with minimum quotas, by Bichler, Hammerl, Waldherr, and Morrill
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Course allocation with minimum quotas, by Bichler, Hammerl, Waldherr, and Morrill

How to Assign Scarce Resources Without Money:  Designing Information Systems that are Efficient, Truthful, and (Pretty) Fair
Martin Bichler, Alexander Hammerl, Stefan Waldherr,  Thayer Morrill
INFORMATION SYSTEMS RESEARCH, forthcoming.

Matching with preferences has great potential to coordinate the efficient allocation of scarce resources in organizations when monetary transfers are not available, and thus can provide a powerful design principle for information systems. Unfortunately, it is well-known that it is impossible to combine all three properties of truthfulness, efficiency, and fairness (i.e. envy-freeness) in matching with preferences. Established mechanisms are either efficient or envy-free, and the efficiency loss in envy-free mechanisms is substantial. We focus on a widespread representative of a matching problem: course assignment where students have preferences for courses and organizers have priorities over students. An important feature in course assignment is that a course has both a maximum capacity and a minimum required quota. This is also a requirement in many other matching applications such as school choice, hospital-residents matching, or the assignment of workers to jobs. We introduce RESPCT, a mechanism that respects minimum quotas and is truthful, efficient, and has
low levels of envy. The reduction in envy is significant and is due to two remarkably effective heuristics. We follow a design science approach and provide analytical and experimental results based on field data from a large-scale course assignment application. These results have led to a policy change and the proposed assignment system is now being used to match hundreds of students every semester.

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