Efficiency decomposition in network data envelopment analysis with slacks-based measures

Kao, Chiang

doi:10.1016/j.omega.2013.12.002

Cited by 118 publications

(38 citation statements)

References 23 publications

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“…Tone and Tsutsui (2010) present a non-radial distance function to address long-term performance within a dynamic DEA framework accounting for slacks and find considerable gains in overall efficiency ranking over the nondynamic case, while Tone and Tsutsui (2014) extend a dynamic DEA slacks-based framework to the network setting. Kao (2014) further extends Tsutsui (2010, 2014) models by proposing a general slacks-based model for network systems and decomposing the system efficiency into a weighted average of the process efficiencies. More applications of dynamic network DEA are found in Avkiran (2014) and Hung et al (2014).…”

Section: Introductionmentioning

confidence: 97%

Analyzing the impact of investment spikes on dynamic productivity growth

Kapelko

Stefanou

2015

Omega

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Section: Introductionmentioning

confidence: 97%

Analyzing the impact of investment spikes on dynamic productivity growth

Kapelko

Stefanou

2015

Omega

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“…The discretionary link is the same as the free link in network DEA. Kao [13] considered general multistage systems in which exogenous inputs are consumed in addition to intermediate products. Cheng and Gao [14] proposed a matrix-type network model which uses data in input-output tables; it is tested and can be feasible in evaluating the relative performance.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Procedure to Solve Network DEA Based on a Virtual Gap Measurement Model

Liu

2017

Mathematical Problems in Engineering

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Network DEA models assess production systems that contain a set of network-structured subsystems. Each subsystem has input and output measures from and to the external network and has intermediate measures that link to other subsystems. Most published studies demonstrate how to employ DEA models to establish network DEA models. Neither static nor dynamic network DEA models adjust the links. This paper applies the virtual gap measurement (VGM) model to construct a mixed integer program to solve dynamic network DEA problems. The mixed integer program sets the total numbers of "as-input" and "as-output" equal to the total number of links in the objective function. To obtain the best-practice efficiency, each DMU determines a set of weights for inputs, outputs, and links. The links are played either "as-input" or "as-output." Input and as-input measures reduce slack, whereas output and as-output measures increase slacks to attain their target on the production frontier.

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“…These applications address evacuation performance without distinguishing among perspectives, systems, processes, and/or evacuation strategies. Classical DEA assumes a production technology as a "black box" where a set of inputs feed a process, which in turn generates outputs [21,22]. It does not consider the set of production sub-technologies, if they exist, that are embedded within the production technology.…”

Section: Evacuation: Perspectives Systems and Underlying Processesmentioning

confidence: 99%