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2005•The Singapore Economic ReviewRequires access

SUBJECT MATCHING: A CASE STUDY ON TWO-SIDED MATCHING

Xiaolin Xing, Yunhua Liu

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Abstract

This paper investigates subject matching in the National University of Singapore (NUS). The matching process is conducted in a primary market and a secondary market. In the primary market, students and departments are matched by a centralized matching procedure, based on their submitted preferences. Students who are not satisfied with their allocations in the primary market can choose to join the secondary market. By comparing matching results in these two markets, we show how a centralized matching procedure and a decentralized matching procedure can work together to produce a desirable outcome, especially in a many-to-many matching market.

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What this paper is about

This paper investigates subject matching in the National University of Singapore (NUS). The matching process is conducted in a primary market and a secondary market. In the primary market, students and departments are matched by a centralized matching procedure, based on their submitted preferences. Students who are not satisfied with their allocations in the primary market can choose to join the secondary market. By comparing matching results in these two markets, we show how a centralized matching procedure and a decentralized matching procedure can work together to produce a desirable outcome, especially in a many-to-many matching market.

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Available abstract

This paper investigates subject matching in the National University of Singapore (NUS). The matching process is conducted in a primary market and a secondary market. In the primary market, students and departments are matched by a centralized matching procedure, based on their submitted preferences. Students who are not satisfied with their allocations in the primary market can choose to join the secondary market. By comparing matching results in these two markets, we show how a centralized matching procedure and a decentralized matching procedure can work together to produce a desirable outcome, especially in a many-to-many matching market.

Key concepts: Matching (statistics), Subject (documents), Optimal matching, Outcome (game theory), Work (physics), Process (computing), Computer science, Economics

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