Download Data Envelopment Analysis: A Handbook on the Modeling of by Wade D. Cook, Joe Zhu (eds.) PDF

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 presents a accomplished resource for the state-of-the paintings DEA modeling on inner constructions and community DEA. bankruptcy 1 offers 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 below 3 different types of constructions, particularly sequence, parallel and dynamic. bankruptcy four reports the choice of the community DEA frontier. In bankruptcy five additive potency decomposition in community DEA is mentioned. An strategy in scale potency size in two-stage networks is gifted in bankruptcy 6. bankruptcy 7 extra discusses the size potency decomposition in degree networks. bankruptcy eight deals a bargaining video game method of modeling two-stage networks. bankruptcy nine stories shared assets and potency decomposition in two-stage networks. bankruptcy 10 introduces an method of computing the technical potency ratings for a dynamic creation community and its sub-processes. bankruptcy eleven provides a slacks-based community DEA. bankruptcy 12 discusses a DEA modeling process for a two-stage community strategy the place the inputs of the second one degree comprise either the outputs from the 1st level and extra inputs to the second one degree. bankruptcy thirteen offers an potency dimension method for multi-stage construction platforms. bankruptcy 14 discusses community DEA versions, either static and dynamic. The dialogue additionally explores a number of precious goal services that may be utilized to the versions to discover the optimum allocation of assets for approaches in the black field, which are as a rule invisible to DEA. bankruptcy 15 presents a finished assessment of assorted sort community DEA modeling ideas. bankruptcy sixteen provides shared assets types for deriving combination measures of bank-branch functionality, with accompanying part measures that make up that combination price. bankruptcy 17 examines a collection of producing vegetation working lower than a unmarried umbrella, with the target being to take advantage of the part or functionality measures to determine what can be regarded as each one plant’s middle company. bankruptcy 18 considers challenge settings the place there is clusters or teams of DMUs that shape a hierarchy. the categorical case of a collection off electrical strength crops is tested during this context. bankruptcy 19 versions undesirable outputs in two-stage community DEA. bankruptcy 20 provides an program of community DEA to functionality size of significant League Baseball (MLB) groups. bankruptcy 21 provides an software of a two-stage community DEA version for interpreting the functionality of 30 U.S. airline businesses. bankruptcy 22 then provides distinctive community potency types 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

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1, for example, by introducing additional (independent) inputs to the second stage, the resulting models are not necessarily linear. D. Cook and J. Zhu For example, Li et al. (2012) considers a situation depicted in Fig. 2, where stageÀ2 inputs to the second stage are denoted as xhj (h ¼ 1, 2, . , H). 2) now becomes maxθ1o à θ2o ¼ max D X wd zdo s X d¼1 m X r¼1 à vi xio i¼1 d¼1 m X s:t: D H X X stageÀ2 wd zdo þ Qh xho d¼1 D X wd zdj ur yro h¼1 8j 1 ð1:14Þ vi xij i¼1 s X ur yrj r¼1 D X H X 1 8j stageÀ2 Qh xhj wd zdj þ d¼1 h¼1 vi , wd , Qh , ur !

7). 7) in order to calculate the optimal intermediate measures so that we obtain the correct frontier projection as (θà xio , ez Ãdo , yro ) or (θ*xio, ∑ λÃj zij, yro). Since Fig. 7). In a complicated network structure, such task may not be possible. 2 Network DEA Pitfalls: Divisional Efficiency and Frontier Projection 41 Such frontier projections have an interesting aspect. We consider the two-stage network structure involving 24 Taiwanese non-life insurance companies studied in Kao and Hwang (2008).

Based upon the discussion in the previous section, we know that for an inefficient DMU to be projected onto the network DEA frontier, its intermediate measures will have to be adjusted (increased or decreased). In fact, Chen et al. 7). 7) in order to calculate the optimal intermediate measures so that we obtain the correct frontier projection as (θà xio , ez Ãdo , yro ) or (θ*xio, ∑ λÃj zij, yro). Since Fig. 7). In a complicated network structure, such task may not be possible. 2 Network DEA Pitfalls: Divisional Efficiency and Frontier Projection 41 Such frontier projections have an interesting aspect.

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