Chinese airline efficiency under CO2 emissions and flight delays: A stochastic network DEA model

Abstract

This article is focused on the efficiency assessment of 13 major Chinese airlines from 2006 to 2014, applying a stochastic network DEA (SNDEA) to account for randomness in undesirable outputs such as flight delays and CO2 emissions. Two stages are considered: flight and network efficiency. Efficiency estimates are computed using multivariate copulas to control for time (trend) and individual (DMU) effects. A robust regression approach is subsequently developed to address the impact of contextual variables on efficiency levels. Results suggest that more progress has been made over the course of the years in terms of controlling flight delays that in terms of reducing CO2 emissions. These results call for specific policies that can target the latter issue more properly: authorities should pay a closer look on airlines listed in the stock market and that operate international flights to apprehend best practices and design regulatory marks to the sector. This paper also lends a distinctive contribution to the literature by modeling the first time the trade-off between flight delays and CO2 emissions in airline efficiency problems.