Quantitative Software Project Management with Mixed Data: A Comparison of Radial, Non-Radial and Ensemble DEA Models

Data envelopment analysis (DEA) models are often used for benchmarking software projects, and traditional DEA models only allow for the use of continuous variables. This study considers the use of DEA for datasets with mixed continuous and discrete variables to ranking software projects. It uses the existing radial DEA model and extends the nonradial DEA model to allow for the use of mixed variables. Further efficiency scores from the two DEA models are averaged in an ensemble DEA score. Using three real-world software engineering datasets, this study finds that the nonradial DEA and the ensemble DEA models have better discriminating power (lower tied efficiency scores) to rank software projects, and the radial DEA model generates more general ranking distribution (higher entropy) of normalized efficiency scores. The choice between selecting radial and nonradial DEA models for ranking software projects appears to depend on the extent to which managers want to introduce bias into the efficiency score ranking distribution. Radial models appear to have a lower bias than nonradial models. The ensemble DEA model appears to be the best performing DEA model for datasets containing two or more discrete and continuous variables.

This is the peer reviewed version of the following article: [Pendharkar, P.C., and Rodger, J.A. (2021). Quantitative software project management with mixed data: A comparison of radial, nonradial, and ensemble data envelopment analysis models. Journal of Software: Evolution and Process 33.], which has been published in final form at https://doi.org/10.1002/smr.2348. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions: https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html#3.


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Work Title Quantitative Software Project Management with Mixed Data: A Comparison of Radial, Non-Radial and Ensemble DEA Models
Open Access
  1. Parag C. Pendharkar
  2. James A. Rodger
License In Copyright (Rights Reserved)
Work Type Article
  1. Wiley
Publication Date May 7, 2021
Publisher Identifier (DOI)
  1. 10.1002/smr.2348
  1. Journal of Software: Evolution and Process
Deposited February 23, 2022




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