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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Support vector frontiers: A new approach for estimating production functions through support vector machines
Daniel Valero-Carreras, Juan Aparicio, Nadia M. Guerrero
Omega (2021) Vol. 104, pp. 102490-102490
Open Access | Times Cited: 43

Showing 26-50 of 43 citing articles:

Measuring dynamic inefficiency through machine learning techniques
Juan Aparicio, Miriam Esteve, Magdalena Kapelko
Expert Systems with Applications (2023) Vol. 228, pp. 120417-120417
Open Access | Times Cited: 4
Adjustable robust optimization approach for SVM under uncertainty
F. Hooshmand, F. Seilsepour, S.​A. MirHassani
Omega (2024) Vol. 131, pp. 103206-103206
Closed Access | Times Cited: 1
Analysis of Heart Diseases Using Soft Computing Technique
Subhalaxmi Das, Sateesh Kumar Pradhan, Sujogya Mishra, et al.
(2021) Vol. 542, pp. 178-184
Closed Access | Times Cited: 10
A Radial Basis Function Neural Network for Stochastic Frontier Analyses of General Multivariate Production and Cost Functions
Parag C. Pendharkar
Neural Processing Letters (2023) Vol. 55, Iss. 5, pp. 6247-6268
Open Access | Times Cited: 3
How to peel a data envelopment analysis frontier: A cross-validation-based approach
Juan Aparicio, Miriam Esteve
Journal of the Operational Research Society (2022) Vol. 74, Iss. 12, pp. 2558-2572
Closed Access | Times Cited: 5
A maximum-margin multisphere approach for binary Multiple Instance Learning
Annabella Astorino, Matteo Avolio, Antonio Fuduli
European Journal of Operational Research (2021) Vol. 299, Iss. 2, pp. 642-652
Closed Access | Times Cited: 6
The defence economy: an assessment of productivity change in NATO countries
Mónica Domínguez Sánchez, Juan Aparicio, Antonio Fonfría
Applied Economics (2023) Vol. 56, Iss. 18, pp. 2158-2175
Closed Access | Times Cited: 2
Complex interplay of R&D, advertising and exports in USA manufacturing firms: differential effects of capabilities
He‐Boong Kwon, Jooh Lee, Ian Brennan
Benchmarking An International Journal (2024)
Open Access
Semi-Parametric Estimation of the Team Wage Frontier of European Football Technology
Gabriel Villa, Sebastián Lozano
(2024)
Closed Access
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, et al.
Computers & Operations Research (2024) Vol. 171, pp. 106793-106793
Open Access
Measuring environmental inefficiency through machine learning: An approach based on Efficiency Analysis Trees and by-production technology
María D. Guillen, Juan Aparicio, Magdalena Kapelko, et al.
European Journal of Operational Research (2024)
Open Access
Prediction of confined compressive strength of concrete column strengthened with FRCM composites
Prashant Kumar, Harish Chandra Arora, R. Siva Chidambaram, et al.
Structural Concrete (2024)
Closed Access
Machine Learning Techniques and Efficiency Evaluation: A Survey of Methodological Contributions
Juan Aparicio, Miriam Esteve, Qianying Jin
Infosys science foundation series (2024), pp. 201-234
Closed Access
Merging Data Envelopment Analysis and Structural Risk Minimization: Some Examples of Use of Multi-output Machine Learning Techniques on Real-World Data
Nadia M. Guerrero, Juan Aparicio, Raúl Moragues, et al.
Infosys science foundation series (2024), pp. 1-32
Closed Access
Environmental sustainability performance of US airlines: implications of financial performance and technical efficiency
Sepideh Kaffash, Fahimeh Rahmanniyay, Emel Aktaş
Journal of the Operational Research Society (2024), pp. 1-21
Closed Access
Estimating non-overfitted convex production technologies: a stochastic machine learning approach
María D. Guillen, Vincent Charles, Juan Aparicio
European Journal of Operational Research (2024)
Open Access
Ranking the Importance of Variables in a Nonparametric Frontier Analysis Using Unsupervised Machine Learning Techniques
Raúl Moragues, Juan Aparicio, Miriam Esteve
Mathematics (2023) Vol. 11, Iss. 11, pp. 2590-2590
Open Access | Times Cited: 1
Evaluating different methods for ranking inputs in the context of the performance assessment of decision making units: A machine learning approach
Daniel Valero-Carreras, Raúl Moragues, Juan Aparicio, et al.
Computers & Operations Research (2023) Vol. 163, pp. 106485-106485
Open Access | Times Cited: 1
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