Economic cross-efficiency
Entity
UAM. Departamento de Análisis Económico, Teoría Económica e Historia EconómicaPublisher
ElsevierDate
2021-04-01Citation
10.1016/j.omega.2020.102374
Omega-International Journal of Management Science 100 (2021): 102374
ISSN
0305-0483 (print); 1873-5274 (online)DOI
10.1016/j.omega.2020.102374Funded by
Spanish Ministry for Science and Innovation and the State Research Agency under grants PID2019-105952GB-I00/AEI/10.13039/501100011033 and EIN2020-112260/AEI/10.13039/501100011033Project
Gobierno de España. PID2019-105952GB-I00Editor's Version
https://doi.org/10.1016/j.omega.2020.102374Subjects
Cross-efficiency; Data envelopment analysis; Farrell efficiency; Nerlove (profit) inefficiency; Warehouse efficiency; EconomíaRights
© 2020 The Author(s)Abstract
This paper introduces a series of new concepts under the name of Economic Cross-Efficiency, which is rendered operational through Data Envelopment Analysis (DEA) techniques. To achieve this goal, from a theoretical perspective, we connect two key topics in the efficiency literature that have been unrelated until now: economic efficiency and cross-efficiency. In particular, it is shown that, under input (output) homotheticity, the traditional bilateral notion of input (output) cross-efficiency for unit l, when the weights of an alternative counterpart k are used in the evaluation, coincides with the well-known Farrell notion of cost (revenue) efficiency for evaluated unit l when the weights of k are used as market prices. This motivates the introduction of the concept of Farrell Cross-Efficiency (FCE) based upon Farrell's notion of cost (revenue) efficiency. One advantage of the FCE is that it is well defined under Variable Returns to Scale (VRS), yielding scores between zero and one in a natural way, and thereby improving upon its standard cross-efficiency counterpart. To complete the analysis we extend the FCE to the notion of Nerlovian cross-inefficiency (NCI), based on the dual relationship between profit inefficiency and the directional distance function. Finally, we illustrate the new models with a recently compiled dataset of European warehouses
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Google Scholar:Aparicio, Juan
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Zofío Prieto, José Luis
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