Improving the predictive accuracy of production frontier models for efficiency measurement using machine learning : the LSB-MAFS method
María D. Guillen, Juan Aparicio, José L. Zofío, Victor J. España
| Year of publication: |
2024
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|---|---|
| Authors: | Guillen, María D. ; Aparicio, Juan ; Zofío, José L. ; España, Victor J. |
| Published in: |
Computers & operations research : an international journal. - Amsterdam [u.a.] : Elsevier, ISSN 0305-0548, ZDB-ID 1499736-8. - Vol. 171.2024, Art.-No. 106793, p. 1-19
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| Subject: | Production frontiers | Least squares boosting (LSB) | Multivariate Adaptive Frontier Splines (MAFS) | Machine Learning | Prediction Accuracy | Data Envelopment Analysis | Künstliche Intelligenz | Artificial intelligence | Data-Envelopment-Analyse | Data envelopment analysis | Technische Effizienz | Technical efficiency | Prognoseverfahren | Forecasting model | Theorie | Theory | Produktionsfunktion | Production function | Schätzung | Estimation |
Online Resource
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.cor.2024.106793 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10015066453