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Introducing cross-productivity: A new approach for ranking productive units over time in Data Envelopment Analysis


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Título :
Introducing cross-productivity: A new approach for ranking productive units over time in Data Envelopment Analysis
Autor :
Aparicio Baeza, Juan
Ortiz Henarejos, Lidia
Pastor Ciurana, Jesús Tadeo
Zabala Iturriagagoitia, Jon Mikel
Editor :
Elsevier
Departamento:
Departamentos de la UMH::Estadística, Matemáticas e Informática
Fecha de publicación:
2020
URI :
https://hdl.handle.net/11000/38280
Resumen :
Cross-efficiency has been developed for the evaluation of cross-sectional data in Data Envelopment Analysis. This paper extends cross-efficiency evaluation introducing the concept of cross-productivity. The extension proposed here is aimed at providing a dynamic peer-evaluation of decision making units, based on the standard Luenberger indicator, when the same set of units is observed over time. In particular, we show how to decompose the change in the ranking score of the different units into a component linked to catch-up and a term associated with technical change and innovation. As a result, we determine why the ranking provided by this novel cross-efficiency approach can vary period by period for the assessed set of units. Finally, the introduced cross-productivity approach is illustrated in the context of 28 national innovation systems in Europe, through the panel data included in the European Innovation Scoreboard for the years 2014 and 2015.
Palabras clave/Materias:
data envelopment analysis
performance evaluation
cross-efficiency
productivity
Luenberger indicator
European Innovation Scoreboard
Área de conocimiento :
CDU: Ciencias puras y naturales: Matemáticas
CDU: Ciencias puras y naturales: Matemáticas: Análisis
Tipo de documento :
info:eu-repo/semantics/article
Derechos de acceso:
info:eu-repo/semantics/closedAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
DOI :
https://doi.org/10.1016/j.cie.2020.106456
Publicado en:
Computers & Industrial Engineering
Aparece en las colecciones:
Artículos - Estadística, Matemáticas e Informática



Creative Commons La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.