By Chiang Kao
This booklet offers the underlying conception, version improvement, and functions of community information Envelopment research (DEA) in a scientific means. the sphere of community DEA extends and enhances traditional DEA via contemplating not just inputs and outputs while measuring procedure potency, but additionally the interior constitution of the approach being analyzed. through examining the potency of person inner elements, and extra rather through learning the results of relationships between elements that are modeled and carried out by way of a number of community constructions, the “network DEA” procedure is ready to aid determine and deal with the explicit elements that give a contribution inefficiencies into the general structures. This fairly new strategy contains a major analytical software in line with mathematical programming concepts, with priceless implications to construction and operations administration. the prevailing versions for measuring the potency of platforms of particular community buildings also are mentioned, and the relationships among the procedure and part efficiencies are explored. This ebook may be in a position to encourage new learn and new functions according to the present country of the art.
Performance overview is a crucial job in administration, and is required to (i) larger comprehend the previous accomplishments of a company and (ii) plan for its destiny improvement. besides the fact that, this job turns into really difficult while a number of functionality metrics are concerned. DEA is a robust device to deal with such concerns. For structures or operations composed of interrelated techniques, managers want to know how the performances of many of the strategies evaluated and the way they're aggregated to shape the final functionality of the process. This e-book offers a sophisticated exposition on functionality review of structures with community constructions. It explores the community nature of so much construction and operation platforms, and explains why community analyses are beneficial.
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Extra info for Network Data Envelopment Analysis: Foundations and Extensions
Since the DMUs being eliminated are efficient ones, they will fall outside of the region encompassed by the new frontier, and their efficiency scores calculated based on this frontier will be greater than one. This is why this efficiency index is said to measure super efficiency. The following is an output model for calculating the super efficiency of the focal DMU under variable returns to scale: 38 2 Output–Input Ratio Efficiency Measures Y Fig. 7 Calculation of super efficiency 10 E 8 D 6 B 4 F G S 1 ¼ min: E0 Xm 2 4 6 8 10 X vi Xi0 þ v0 uY r¼1 r r0 i¼1 X s Xm s:t: C A 2 O S’ vi Xij þ v0 !
2), the one under constant returns to scale, is the inclusion of the intercept u0. 8) can be linearized by assigning the denominator to one, and leaving the numerator as the objective function. 8) has multiple solutions, in that if (u*, v*) is an optimal solution, then so is (cu*, cv*), for c > 0. Assigning the denominator to one to reduce one degree of freedom will thus not alter the optimal objective value, E0, although the optimal solution (u*, v*) may be different. The linear fractional constraints are easily linearized by multiplying both sides by the denominator to obtain the following linear programming model: E0 ¼ max: s X ur Y r0 À u0 r¼1 s:t: m X vi Xi0 ¼ 1 i¼1 s X r¼1 ur Y rj À u0 À m X vi Xij 0, j ¼ 1, .
In contrast, Andersen and Petersen (1993) proposed eliminating the focal DMU to construct the frontier from the remaining n À 1 DMUs in order to calculate an efficiency index for ranking. However, this method is only for ranking efficient DMUs. Since the DMUs being eliminated are efficient ones, they will fall outside of the region encompassed by the new frontier, and their efficiency scores calculated based on this frontier will be greater than one. This is why this efficiency index is said to measure super efficiency.