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The use of cascade-correlation neural networks in University fund raising

Author

Listed:
  • B K Wong

    (Lingnan University)

  • T A Bodnovich

    (Youngstown State University)

  • V S-K Lai

    (The Chinese University of Hong Kong)

Abstract

In recent years, many Colleges and Universities in the USA have been facing a serious financial crisis since many state governments have reduced their support for higher education. There is no doubt that one of the solutions to this crisis depends on the successful implementation of University fund raising programs. Identifying the potential donors is an important part of this process. The objective of this research was to develop a cascade-correlation neural network to predict the types of people who would most likely be potential donors. A comparison of the classification accuracy between neural networks and multiple discriminant analyses (MDA) was also conducted. Our results indicated that neural networks could perform as well as MDA in overall accuracy. Furthermore, neural networks could predict with a lot more accuracy the actual donor (Type I hit) than MDA. Our study is the first published case study on the use of artificial neural networks for University fund raising.

Suggested Citation

  • B K Wong & T A Bodnovich & V S-K Lai, 2000. "The use of cascade-correlation neural networks in University fund raising," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(8), pages 913-920, August.
    • Handle: RePEc:pal:jorsoc:v:51:y:2000:i:8:d:10.1057_palgrave.jors.2600996
    DOI: 10.1057/palgrave.jors.2600996
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    Cited by:

    1. R Setiono & S-L Pan & M-H Hsieh & A Azcarraga, 2006. "Knowledge acquisition and revision using neural networks: an application to a cross-national study of brand image perception," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(3), pages 231-240, March.
    2. Badiee, Aghdas & Moshtari, Mohammad & Berenguer, Gemma, 2024. "A systematic review of operations research and management science modeling techniques in the study of higher education institutions," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).

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