By Wade D. Cook, Joe Zhu (eds.)
This instruction manual serves as a supplement to the Handbook on information Envelopment Analysis (eds, W.W. Cooper, L.M. Seiford and J, Zhu, 2011, Springer) so that it will expand the frontier of DEA study. It offers a accomplished resource for the state-of-the artwork DEA modeling on inner buildings and community DEA. bankruptcy 1 presents a survey on two-stage community functionality decomposition and modeling concepts. bankruptcy 2 discusses the pitfalls in community DEA modeling. bankruptcy three discusses potency decompositions in community DEA less than 3 sorts of constructions, particularly sequence, parallel and dynamic. bankruptcy four experiences the choice of the community DEA frontier. In bankruptcy five additive potency decomposition in community DEA is mentioned. An technique in scale potency size in two-stage networks is gifted in bankruptcy 6. bankruptcy 7 extra discusses the size potency decomposition in level networks. bankruptcy eight deals a bargaining online game method of modeling two-stage networks. bankruptcy nine reports shared assets and potency decomposition in two-stage networks. bankruptcy 10 introduces an method of computing the technical potency rankings for a dynamic creation community and its sub-processes. bankruptcy eleven provides a slacks-based community DEA. bankruptcy 12 discusses a DEA modeling approach for a two-stage community procedure the place the inputs of the second one degree contain either the outputs from the 1st degree and extra inputs to the second one level. bankruptcy thirteen offers an potency size technique for multi-stage creation platforms. bankruptcy 14 discusses community DEA versions, either static and dynamic. The dialogue additionally explores numerous valuable goal features that may be utilized to the types to discover the optimum allocation of assets for tactics in the black field, which are usually invisible to DEA. bankruptcy 15 presents a accomplished overview of assorted style community DEA modeling innovations. bankruptcy sixteen offers shared assets types for deriving mixture measures of bank-branch functionality, with accompanying part measures that make up that combination worth. bankruptcy 17 examines a collection of producing vegetation working below a unmarried umbrella, with the target being to take advantage of the part or functionality measures to determine what could be regarded as each one plant’s middle enterprise. bankruptcy 18 considers challenge settings the place there's clusters or teams of DMUs that shape a hierarchy. the explicit case of a collection off electrical strength vegetation is tested during this context. bankruptcy 19 types undesirable outputs in two-stage community DEA. bankruptcy 20 offers an software of community DEA to functionality dimension of significant League Baseball (MLB) groups. bankruptcy 21 offers an program of a two-stage community DEA version for analyzing the functionality of 30 U.S. airline businesses. bankruptcy 22 then offers precise community potency versions which are utilized to engineering structures.
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Additional info for Data Envelopment Analysis: A Handbook on the Modeling of Internal Structures and Networks
M; μr ! , r ¼ 1, 2, . . 16) can be considered a parametric linear program, and it can be solved via a simple line search method over a certain range of h, as is done in Liang et al. (2006). To secure a search range of h, it is needed to calculate a lower bound and an upper bound on h, which can be done similarly with Liang et al. (2006). See Lim and Zhu (2013) for a detailed discussion and a numerical example. 7 Two Stage Network System with Feedbacks Liang et al. (2011) extend the basic two-stage network system as shown in Fig.
0, d ¼ 1, . . , D λj ! 0, j ¼ 1, . . , n μj ! 0, j ¼ 1, . . 5). 6), can only generate the overall efficiency. In this regard, θ* cannot be treated as the divisional efficiency of stage 1. 5) can be called envelopment DEA network models, as they are similar to the standard envelopment DEA model format. 5), the existing DEA literature claims that the VRS envelopment network DEA model is obtained, since this is how VRS envelopment model is obtained under the standard DEA model. However, we believe that this issue needs to be further examined.
Specifically, let t1 ¼ X p m X X vi xi0 þ wg f g0 hd zd0 i¼1 g¼1 d¼1 β ¼ tt12 , νi ¼ t1vi, ς1d ¼ t1hd, ω1g ¼ t1wg, μr ¼ t2ur, ς2d ¼ t2hd, ω2g ¼ t2wg. D. Cook and J. Zhu s X X 1 βþ Max ω2g f g0 þ μr yr0 2 r¼1 g¼1 p s:t: β ! p D m X X X ς2d zdj À vi xij À β ω2g f gj d¼1 p X i¼1 s X g¼1 m X r¼1 p X ω2g f gj þ i¼1 D X vi xi0 þ β μr yrj À g¼1 D X ς2d zdj d¼1 0 0 ð1:18Þ ω2g f g0 ¼ 1 g¼1 ς2d zd0 ¼ 1 d¼1 νi , ς2d , ω2g , μr ! e. β ∈ (0, 1]. Now, let wg f g0 g¼1 νi ¼ βυi, ςd ¼ ς2d , ωg ¼ ω2g . 18) is then equivalent to the following model: !
Data Envelopment Analysis: A Handbook on the Modeling of Internal Structures and Networks by Wade D. Cook, Joe Zhu (eds.)