Data for: Integrated Data Envelopment Analysis Methods for Measuring Technical, Environmental, and Eco-efficiencies

Published: 14 August 2019| Version 1 | DOI: 10.17632/ppwj2p6bky.1
Contributors:
Shengchao Zhou, Jianhui Xie, Ya Chen

Description

We consider the provincial road transport subsystems as DMUs and measure their relative technical, environmental, and eco-efficiencies on the basis of the following seven input–output indices. Inputs: length of highways (million kilometers), civil vehicles (million), employees (million), and energy consumption (〖10〗^15 kJ); Desirable outputs: passenger turnover (billion passenger-km) and freight turnover (billion ton-km); Undesirable output: CO2 (million tons). We collect and extract data from China’s Statistical Yearbook 2017 and China’s Energy Statistical Yearbook 2017, which provide economic, transport, and energy data of Regional Road Transport Systems in 2016. Considering that the energy data for Tibet are missing, we only consider the 30 other provincial road transport systems in the following study. The data concerning length of highways, civil vehicles, employees, passenger turnover, and freight turnover are collected directly from the Yearbooks. By contrast, the energy consumptions and CO2 emissions are computed based on the consumption of gasoline and diesel oil. In particular, the energy consumption is computed on the basis of the average low calorific value of gasoline (43070 kJ/kg) and diesel oil (42652 kJ/kg), which are provided in China’s Energy Statistical Yearbook 2017. we compute the CO2 emissions depending on the methodology provided by the Intergovernmental Panel on Climate Change Guidelines for the National Greenhouse Gas Inventories (IPCC, 2006).

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Data Envelopment Analysis, Eco-Efficiency

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