DEA for non-homogenous parallel networks

• Published in: Omega (Oxford) 2015-10, Vol.56, p.122-132
• Main Authors: Du, Juan, Chen, Yao, Huo, Jiazhen
• Format: Article
• Language: English
• Subjects: Assembly lines; Business metrics; Data envelopment analysis; Data envelopment analysis (DEA); Efficiency; Input output; Network; Non-homogeneous sub-units; Studies
• ISSN: 0305-0483; 1873-5274
• DOI: 10.1016/j.omega.2014.10.001

In practice, systems are often composed of a group of sub-units. Each sub-unit 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. •This paper deals with non-homogenous sub-units within parallel network structures.•Different sets of inputs/outputs are allowed for parallel sub-units within a DMU.•Input/output measures across sub-units can be either disjoint or commonly shared.•Both overall performance and component efficiency for sub-units can be evaluated.•The models are applied to a dataset of steel fabrication industry.