Directional distance based efficiency decomposition for series system in network data envelopment analysis

Abstract

The multiplier network directional distance function (DDF) model capable of handling negative data received little attention in the field of data envelopment analysis (DEA). The series system is a basic network one. Under the assumption of variable returns to scale (VRS), this paper extends the multiplier series DEA model for use with the DDF. The proposed series DDF model is non-oriented and can deal with negative data. The resulting system efficiency score can be decomposed as a weighted average of process efficiency scores. In the context of DDF, the issue of possible alternate process efficiencies is addressed. The proposed model can also be applied to the assumption of constant returns to scale (CRS). Moreover, we derive the mathematical relationship between the CRS form of our series DDF model and the series CCR model. Two empirical examples in the literature illustrate the applicability and advantages of the new model.

Keywords:

• Data envelopment analysis
• efficiency
• performance measurement

Acknowledgement

The authors are grateful to anonymous reviewers for their constructive comments, which have helped us to improve the paper significantly in both content and style.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work was supported by the National Natural Science Foundation of China under Grant (71971163); the Natural Science Foundation of Zhejiang Province, China, under Grant (LY17G010004).