Predicting project approvals: A case of grants from the National Science Council of Taiwan

Predicting project approvals: A case of grants from the National Science Council of Taiwan

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Article ID: iaor20115876
Volume: 40
Issue: 1
Start Page Number: 89
End Page Number: 95
Publication Date: Jan 2012
Journal: Omega
Authors: ,
Keywords: statistics: regression
Abstract:

Project selection is an important task for organizations in achieving their missions using limited budgets and resources. Whether or not a project will be approved is also of primary concern to the applicants. This paper predicts whether a project will be approved for cases where the criteria for evaluating it are known while the scoring system is not. The idea is to construct a frontier function for the approved projects from past performance on the criteria. The relative distance between a proposed project and the frontier serves as an indicator of the possibility that the project will be approved. Data from the Management II Division of the National Science Council of Taiwan in the Topic Research Project are collected to illustrate this approach. From the percentile of the distance measure, an applicant is able to predict the possibility that their project will be approved. Since professors with different levels of experience and different research areas have different research performance, these factors are taken into account in the prediction. A Malmquist productivity index analysis is also conducted to investigate the performance improvement of the applicants in research between two periods.

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