By Juan Aparicio, C. A. Knox Lovell, Jesus T. Pastor

ISBN-10: 3319484591

ISBN-13: 9783319484594

ISBN-10: 3319484613

ISBN-13: 9783319484617

This e-book grows from a convention at the state-of-the-art and up to date advances in potency and productiveness. Papers have been commissioned from prime researchers within the box, and comprise 8 explorations into the analytical foundations of potency and productiveness research. Chapters on modeling advances comprise opposite directional distance functionality, a brand new strategy for estimating technological creation percentages, a brand new distance functionality known as a loss distance functionality, an research of productiveness and value restoration indices, the relation of technical potency measures to productiveness measures, the results for benchmarking and aim atmosphere of enforcing weight regulations on DEA versions, weight regulations in a regulatory atmosphere, and the main of Least Action.

Chapters on empirical purposes comprise a research of leading edge agencies that use innovation inputs to provide innovation outputs, a learn of the impression of strength “coopetition” or cooperation between opponents at the monetary functionality of ecu motor vehicle vegetation, utilizing SFA to estimate the eco-efficiency of dairy farms in Spain, a DEA financial disaster prediction version, a mixed stochastic price frontier research model/mixture probability version, the evolution of power depth in 9 Spanish production industries, and the productiveness folks farmers as they age.

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**Extra info for Advances in Efficiency and Productivity**

**Sample text**

S ð2:43Þ kj ¼ 1; À wÀ i si0 þ s X þ wrþ sr0 ¼ vÃ r¼1 kj ! 0; j ¼ 1; . ; n; þ sÀ i ¼ 1; . ; m; sr0 ! 0; r ¼ 1; . ; s; i0 ! 0; which means that we propose to solve 2m + 2s linear programs. Any of these programs searches for a possibly alternative optimal projection due to the addition Ps P À À þ þ Ã of the last linear restriction m i¼1 wi si0 þ r¼1 wr sr0 ¼ v . 2 Searching for Alternative Optimal Solutions Let us consider in the two input—one output space the next sample of units: U1 (1,6;3), U2(2,6;4), U3(6,2;4), U4(6,1;3) and U5(8,7;2).

Manage Sci 30:1078–1092 Battesse GE, Corra GS (1977) Estimation of a production frontier model: with an application to the pastoral zone of Eastern Australia. Austr J Agric Econ 21(3):169–179 Bogetoft P, Hougaard JL (1999) Efﬁciency evaluations based on potential (non-proportional) improvements. J Prod Anal 12(3):233–247 Briec W, Lesourd JB (1999) Metric distance function and proﬁt: some duality results. J Optim Theory Appl 101(1):15–33 Briec W, Garderes P (2004) Generalized beneﬁt functions and measurement of utility.

N; þ sÀ i ¼ 1; . ; m; sr0 ! 0; r ¼ 1; . ; s; i0 ! 0; which means that we propose to solve 2m + 2s linear programs. Any of these programs searches for a possibly alternative optimal projection due to the addition Ps P À À þ þ Ã of the last linear restriction m i¼1 wi si0 þ r¼1 wr sr0 ¼ v . 2 Searching for Alternative Optimal Solutions Let us consider in the two input—one output space the next sample of units: U1 (1,6;3), U2(2,6;4), U3(6,2;4), U4(6,1;3) and U5(8,7;2). Let us work with the additive model, which is a weighted additive model where all weights equal 1.

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