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Efficient Volunteer Matching: Combining Data Science and Economics

Our latest tool “The Efficient Volunteer Matching Applet” is now available on our website:

It was also featured in a blog post I wrote for TechSoup, available here: How Data Science Can Be Used to Power Civil Society Across the World.

The tool employs a variant of the Top-Trading Cycle algorithm developed by Shapley, Scarf and Gale. This algorithm has many very nice properties which should improve volunteer engagement:

First, the algorithm will always terminate. This means regardless of how many people we have, or how many jobs, or who wants what job, the algorithm (and the applet) will always generate a match for everyone.

Second, there is no other matching which each volunteer prefers just as much and at least one volunteer prefers more. In technical terms, this is called pareto efficiency.

Third, all of the volunteers who had a task last year are assigned a task they prefer at least as much as their previous task. So there is a reason for seasoned volunteers to buy into this new system. This is called individual rationality.

Fourth, no group of volunteers who had a task last year can swap tasks among themselves and improve their assignments. This is called core stability.

As it turns out, the Top Trading Cycle algorithm is the only algorithm which achieves all four properties together. It also has the added bonus of “truthfulness,” meaning there is no incentive for volunteers to misreport preferences. A volunteer will not get a better job if they list their second choice first, or their third choice second, etc.

Because of these attributes, the TTC algorithm has been used to: match doctors with hospitals for residencies, students with public schools, and patients with organ donors. Volunteer matching, like the examples listed, attempts to balance the preferences of the individual and the preferences of the organization at large.

For this very reason, I believe the TTC algorithm is perfect for solving the problem of matching volunteers to jobs. Our applet implementation is automated and systematic, so it saves staff time. It shows respect for individual preferences, and as a result it will cultivate committed and experienced volunteers who can take an organization to new heights.

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