Integrating Relative Efficiency Models with Machine Learning Algorithms for Performance Prediction
Marcos Gonçalves Perroni,
Claudimar Pereira da Veiga,
Elaine Forteski
et al.
Abstract:Predicting operational performance enables organizations to develop operational effectiveness goals considering different combinations of resources. Measuring performance is consolidated with advances in relative efficiency analysis techniques, including data envelopment analysis (DEA) and stochastic frontier analysis (SFA), albeit these methods lack predictive capability. This paper proposes an approach for performance prediction by integrating relative efficiency measurement models with machine learning algo… Show more
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