How to Assign Scarce Resources Without Money: Designing Information Systems that are Efficient, Truthful, and (Pretty) Fair

Martin Bichler (), Alexander Hammerl (), Thayer Morrill () and Stefan Waldherr ()
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Martin Bichler: Department of Informatics, Technical University of Munich, 80333 Munich, Germany
Alexander Hammerl: Department of Informatics, Technical University of Munich, 80333 Munich, Germany
Thayer Morrill: Department of Economics, North Carolina State University, Raleigh, North Carolina 27695
Stefan Waldherr: Department of Informatics, Technical University of Munich, 80333 Munich, Germany

Information Systems Research, 2021, vol. 32, issue 2, 335-355

Abstract: 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 E xtended S eat P rioritized C linch and T rade with a widened R ange of guarantees (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.

Keywords: top trading cycles; course assignment; design science (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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