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DEA for non-homogenous parallel networks
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DOI：10.1016/j.omega.2014.10.001.png)
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In practice, systems are often composed of a group of sub-units. Each subunit has a set of performance metrics that are classified as inputs and outputs in data envelopment analysis (DEA). Conventional DEA views such a system as a black-box, other DEA-based models are developed to investigate the inner structure, either with a serial structure where components are connected by intermediate products, or with a parallel system under the key assumption that all sub-units are associated with the same type of inputs and outputs (in differing amounts) without the links. In many applications, however, this property of identical input/output factors may not hold. For example, factories may have various manufacturing lines whose inputs and outputs differ from one another. The current paper proposes a series of DEA models to accommodate settings where non-homogenous sub-units operate in parallel network structures with intermediate measures or links. Both the overall performance of the entire parallel network system and efficiency decomposition for each sub-unit can be evaluated through our method. (C) 2014 Elsevier Ltd. All rights reserved.
Keyword:
Data envelopment analysis (DEA)
Efficiency
Network
Non-homogeneous sub-units
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