Developing a new chance constrained NDEA model to measure the performance of humanitarian supply chains

Abstract

Data envelopment analysis (DEA) is a method for measuring performance of decision making units (DMUs). Conventional DEA models view DMUs as black boxes. Network DEA (NDEA) models have been developed to overcome this shortfall. This paper develops a new NDEA model based on modified enhanced Russell measure model. This paper measures performance of humanitarian supply chains (HSCs) by an NDEA model. Capabilities of the proposed model are addressed by theorems. However, in the real world, there might be stochastic data. This paper presents a stochastic version of the proposed NDEA model to measure the performance of HSCs. We analyse main properties of our model. We present a case study to demonstrate the applicability of the proposed model.

Keywords:

• performance measurement
• humanitarian supply chain
• humanitarian disasters
• data envelopment analysis (DEA)
• network data envelopment analysis (NDEA)
• stochastic network DEA

Acknowledgments

Authors would like to appreciate constructive comments of two anonymous reviewers.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. For more details regarding the used indicators, see Santarelli et al. (2015)

2. The General Algebraic Modeling System (GAMS) is a high-level modelling system for mathematical optimization. GAMS is designed for modelling and solving linear, nonlinear, and mixed-integer optimization problems.