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Maximizing Benefits for Women: A Charitable Donation Allocation Problem

Listed author(s):
  • Jenna Toussaint


    (Department of Economics, University of Delaware)

  • Shang Wu


    (Department of Applied Economics & Statistics, University of Delaware)

  • Kent D. Messer


    (Department of Applied Economics & Statistics, University of Delaware)

Charitable foundations should endeavor to allocate their limited resources to best serve their constituents. However, few foundations use mathematical programming techniques despite overwhelming evidence of their superiority at selecting projects that yield higher levels of total benefits. The Fund for Women, a Delaware foundation that makes grants to programs serving women, is a notable exception to this pattern as they have begun using a novel “Hybrid Selection Model” that combines both binary linear programming and the heuristic rank-based model. Using data from the foundation, this study shows how the rank-based selection model that was previously used by this group, and currently in use by most foundations, yields lower levels of aggregate benefits compared to binary linear programming or goal programming. Using historical data from 2010, this research shows that a Hybrid model would have selected the top three ‘signature’ projects can maintain an above average project benefits while also securing a 180% improvement in the number of projects funded, 66% improvement in the number of women served, and a 139% improvement in total benefits achieved. The Fund for Women incorporated the Hybrid model in their selection process in 2012 and this paper describes the benefits achieved and the challenges with adopting this approach in a foundation context, including educating and achieving consensus amongst the selection committee and individual member’s project selection preferences that were outside of the initial model’s objective function.

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Paper provided by University of Delaware, Department of Economics in its series Working Papers with number 12-12.

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Length: 28 pages
Date of creation: 2012
Handle: RePEc:dlw:wpaper:12-12.
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  1. Messer, Kent D. & Allen, William L., 2010. "Applying Optimization and the Analytic Hierarchy Process to Enhance Agricultural Preservation Strategies in the State of Delaware," Agricultural and Resource Economics Review, Cambridge University Press, vol. 39(03), pages 442-456, October.
  2. Liu, Zhuo & Messer, Kent D. & Korch, Mary A. & Bounds, Thomas, 2011. "Applying Optimization to the Conservation Project Selection Process: A Case Study of Readiness and Environmental Protection Initiative," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103997, Agricultural and Applied Economics Association.
  3. Roy E. Marsten & Michael R. Muller & Christine L. Killion, 1979. "Crew Planning at Flying Tiger: A Successful Application of Integer Programming," Management Science, INFORMS, vol. 25(12), pages 1175-1183, December.
  4. Hotvedt, James E., 1983. "Application of Linear Goal Programming to Forest Harvest Scheduling," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 15(01), pages 103-108, July.
  5. Zevi Azzaino & Jon M. Conrad & Paul J. Ferraro, 2002. "Optimizing the Riparian Buffer: Harold Brook in the Skaneateles Lake Watershed, New York," Land Economics, University of Wisconsin Press, vol. 78(4), pages 501-514.
  6. Messer, Kent D. & Allen, William L., III, 2010. "Applying Optimization and the Analytic Hierarchy Process to Enhance Agricultural Preservation Strategies in the State of Delaware," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 39(3), October.
  7. Hotvedt, James E., 1983. "Application Of Linear Goal Programming To Forest Harvest Scheduling," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 15(01), July.
  8. Stephen Polasky & Jeffrey D. Camm & Brian Garber-Yonts, 2001. "Selecting Biological Reserves Cost-Effectively: An Application to Terrestrial Vertebrate Conservation in Oregon," Land Economics, University of Wisconsin Press, vol. 77(1), pages 68-78.
  9. Victor Blanco & Luisa Carpente & Yolanda Hinojosa & Justo Puerto, 2010. "Planning for Agricultural Forage Harvesters and Trucks: Model, Heuristics, and Case Study," Networks and Spatial Economics, Springer, vol. 10(3), pages 321-343, September.
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