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Raul Moragues, Juan Aparicio, & Miriam Esteve (2023). An unsupervised learning-based generalization of Data Envelopment Analysis. Operations Research Perspectives, 11, 100284.

Raul Moragues (Operations Research Center, University Miguel Hernández of Elche), Juan Aparicio (Operations Research Center, University Miguel Hernández of Elche) and Miriam Steve (Operations Research Center, University Miguel Hernández of Elche)
Abstract:
In this paper, different upgrading strategies are investigated in the context of the
p-center problem. The possibility of upgrading a set of connections to different centers […]

Juan Aparicio, Miriam Esteve, & Magdalena Kapelko (2023). Measuring dynamic inefficiency through machine learning techniques. Expert Systems with Applications, 228, 120417.

Juan Aparicio (Center of Operations Research, Miguel Hernandez University of Elche; valgrAI – Valencian Graduate School and Research Network of Artificial Intelligence), Miriam Esteve (Center of Operations Research, Miguel Hernandez University of Elche) and Magdalena Kapelko (Department of Logistics. Wrocław University of Economics and Business, Komandorska)
Abstract:
This paper contributes by developing new models for assessing dynamic […]

Maria D. Guillen, Juan Aparicio, & Victor J. España (2023). boostingDEA: A boosting approach to Data Envelopment Analysis in R. SoftwareX, 24, 101549.

María D. Guillén (Center of Operations Research, Miguel Hernandez University of Elche), Juan Aparicio (Center of Operations Research, Miguel Hernandez University of Elche) and Víctor J. España (Center of Operations Research, Miguel Hernandez University of Elche)
Abstract:
boostingDEA is a new package for R that includes functions to estimate production frontiers and make ideal output predictions in […]

Jesus T. Pastor, José Luis Zofío, Juan Aparicio, & D. Pastor (2023). A general direct approach for decomposing profit inefficiency. Omega, 119, 102889.

Jesús T. Pastor (Center of Operations Research, Universidad Miguel Hernandez of Elche), José Luis Zofío (Department of Economics. Universidad Autónoma de Madrid; Erasmus Research Institute of Management, Erasmus University), Juan Aparicio (Valencian Graduate School and Research Network of Artificial Intelligence (valgrAI) and D. Pastor (Department of Sport Sciences, Universidad Miguel Hernández of Elche)
Abstract:
Considering any graph […]

Jose Luis Zofio, Juan Aparicio, Javier Barbero, & Jon Mikel Zabala-Iturriagagoitia (2023). The influence of bottlenecks on innovation systems performance: Put the slowest climber first. Technological Forecasting and Social Change, 193, 122607.

Jose Luis Zofio (Department of Economics, Universidad Autónoma de Madrid; Erasmus Research Institute of Management (ERIM), Erasmus University, Rotterdam), Juan Aparicio (Centro de Investigación Operativa, Universidad Miguel Hernández de Elche), Javier Barbero (Department of Economics, Universidad Autónoma de Madrid) and Jon Mikel Zabala-Iturriagagoitia (Deusto Business School, University of Deusto, San Sebastián
;South Eastern University Norway, Kongsberg; […]

Raul Moragues, Juan Aparicio, & Miriam Esteve (2023). Measuring technical efficiency for multi-input multi-output production processes through OneClass Support Vector Machines: a finite-sample study. Operational Research, 23, 47.

Raúl Moragues (Center of Operations Research, Miguel Hernandez University of Elche; PhD Program in Economics (DEcIDE), Elche, Spain), Juan Aparicio (Center of Operations Research, Miguel Hernandez University of Elche; Valencian Graduate School and Research Network of Artificial Intelligence (valgrAI) and Miriam Esteve (Center of Operations Research, Miguel Hernandez University of Elche)
Abstract:
We introduce a new method […]

Raul Moragues, Juan Aparicio, & Miriam Esteve (2023). Ranking the Importance of Variables in a Nonparametric Frontier Analysis Using Unsupervised Machine Learning Techniques. Mathematics, 11, 2590.

Raúl Moragues (Center of Operations Research, Miguel Hernandez University of Elche; Ph.D. Program in Economics (DEcIDE), Miguel Hernandez University of Elche), Juan Aparicio (Center of Operations Research, Miguel Hernandez University of Elche; Joint Research Unit, Valencian Graduate School and Research Network of Artificial Intelligence (valgrAI) and Miriam Steve (Center of Operations Research, Miguel Hernandez University […]

Juan Aparicio, & José L. Zofío (2023). Decomposing profit change: Konüs, Bennet and Luenberger indicators. Socio-Economic Planning Sciences, 87, 101573.

Juan Aparicio (Center of Operations Research, Miguel Hernandez University of Elche; valgrAI – Valencian Graduate School and Research Network of Artificial Intelligence) and José L. Zofío (Department of Economics, Universidad Autónoma de Madrid; Erasmus Research Institute of Management, Erasmus University)
Abstract:
We introduce complementary decompositions of profit change that, relying on the duality between the profit function […]

Juan Aparicio, Magdalena Kapelko, & Lidia Ortiz (2023). Enhancing the measurement of firm inefficiency accounting for corporate social responsibility: A dynamic data envelopment analysis fuzzy approach. European Journal of Operational Research, 306, 986-997.

Juan Aparicio (Center of Operations Research, Miguel Hernandez University of Elche), Magdalena Kapelko (Department of Logistics, Wrocław University of Economics and Business, ul. Komandorska) and Lidia Ortiz (Center of Operations Research, Miguel Hernandez University of Elche)
Abstract:
This paper contributes to research on the corporate social responsibility (CSR) field and the inefficiency measurement of firms by proposing […]

Maria D. Guillen, Juan Aparicio, & Miriam Esteve (2023). Gradient tree boosting and the estimation of production frontiers. Expert Systems with Applications, 214, 119134.

María D. Guillén (Center of Operations Research. Miguel Hernandez University of Elche), Juan Aparicio (Center of Operations Research. Miguel Hernandez University of Elche) and Miriam Esteve (Center of Operations Research. Miguel Hernandez University of Elche)
Abstract:
In production theory and engineering, a topic of interest is the determination of technical efficiency of firms from the estimation of […]