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• W2573050065 abstract "In data envelopment analysis (DEA) and with a variable returns-to-scale (VRS) technology, we implement Baumol et al.’s [1] concept of “cost minimizing industry structure”, which features reallocation of outputs and a variable number of firms. The characterization of this type of optimal allocation adds to the literature on structural efficiency, which so far has not dealt with it in such a general framework. At the theoretical level, we both determine a decomposition of the industry measure, which establishes the relationship between group and individual measures, and provide its rigorous economic interpretation based on the ray average cost. Moreover, our framework allows to highlight the relationship between the industry measure and different returns-to-scale characterizations of the technology. At the applicative level we devise an algorithm to solve the related non-linear programming problem, thus providing the decision maker with a method to compute the optimal industry structure and the corresponding efficiency components. Empirical illustration is given with reference to the Italian local-public-transit sector employing a multiple input and output technology." @default.
• W2573050065 created "2017-01-26" @default.
• W2573050065 creator A5031784348 @default.
• W2573050065 date "2018-03-01" @default.
• W2573050065 modified "2023-10-02" @default.
• W2573050065 title "Industry cost efficiency in data envelopment analysis" @default.
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• W2573050065 doi "https://doi.org/10.1016/j.seps.2017.01.001" @default.
• W2573050065 hasPublicationYear "2018" @default.
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