Wu, J., Chu, J., Zhu, Q., Yin, P., & Liang, L. (2016). DEA cross-efficiency evaluation based on satisfaction degree: an application to technology selection. International Journal of Production Research, 1-18.
Wu, J., Chu, J., Zhu, Q., Li, Y., & Liang, L. (2016). Determining common weights in data envelopment analysis based on the satisfaction degree.Journal of the Operational Research Society.
Wu, J., Chu, J., Sun, J., Zhu, Q., & Liang, L. (2016). Extended secondary goal models for weights selection in DEA cross-efficiency evaluation.Computers & Industrial Engineering, 93, 143-151.
Wu, J., Chu, J., Sun, J., & Zhu, Q. (2016). DEA cross-efficiency evaluation based on Pareto improvement. European Journal of Operational Research,248(2), 571-579. (Wu, J, is the advisor of Junfei Chu in USTC)
Wu, J., Chu, J. F., & Liang, L. (2015). Target setting and allocation of carbon emissions abatement based on DEA and closest target: An application to 20 APEC economies. Natural Hazards, 1-18.
Wu, J., Chu, J., An, Q., Sun, J., & Yin, P. (2016). Resource reallocation and target setting for improving environmental performance of DMUs: An application to regional highway transportation systems in China.Transportation Research Part D: Transport and Environment.
Chu, J. F., Wu, J., & Song, M. L. (2016). An SBM-DEA model with parallel computing design for environmental efficiency evaluation in the big data context: a transportation system application. Annals of Operations Research, 1-20.
Chu, J., Wu, J., Zhu, Q., An, Q., & Xiong, B. (2016). Analysis of China’s Regional Eco-efficiency: A DEA Two-stage Network Approach with Equitable Efficiency Decomposition. Computational Economics, 1-23.
Wu, J., Yin, P., Sun, J., Chu, J., & Liang, L. (2016). Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspective. European Journal of Operational Research, 254(3), 1047-1062.
Wu, J., Zhu, Q., Chu, J., An, Q., & Liang, L. (2016). A DEA-based approach for allocation of emission reduction tasks. International Journal of Production Research, 1-16.
Wu, J., Zhu, Q., Chu, J., Liu, H., & Liang, L. (2015). Measuring energy and environmental efficiency of transportation systems in China based on a parallel DEA approach. Transportation Research Part D: Transport and Environment.
Wu, J., Zhu, Q., Chu, J., & Liang, L. (2015). Two-stage network structures with undesirable intermediate outputs reused: A DEA based approach.Computational Economics, 46(3), 455-477.
Wu, J., Zhu, Q., Ji, X., Chu, J., & Liang, L. (2016). Two-stage network processes with shared resources and resources recovered from undesirable outputs. European Journal of Operational Research, 251(1), 182-197.
Liu, H., Zhang, Y., Zhu, Q., & Chu, J. (2016). Environmental efficiency of land transportation in China: A parallel slack-based measure for regional and temporal analysis. Journal of Cleaner Production.
Liu, X., Chu, J., Yin, P., & Sun, J. (2016). DEA cross-efficiency evaluation considering undesirable output and ranking priority: a case study of eco-efficiency analysis of coal-fired power plants. Journal of Cleaner Production.
Liu, X., Zhu, Q., Chu, J., Ji, X., & Li, X. (2016). Environmental Performance and Benchmarking Information for Coal-Fired Power Plants in China: A DEA Approach. Computational Economics, 1-16.
Guo, X., Zhu, Q., Lv, L., Chu, J., & Wu, J. (2017). Efficiency evaluation of regional energy saving and emission reduction in China: A modified slacks-based measure approach. Journal of Cleaner Production, 140, 1313-1321.
Yu, Y. F., & Chu, J. F. (2016). Operating Efficiency Analysis of 24 Coal-Firms in China: An Application Based on Context-Dependent DEA.International Journal of Intelligent Technologies and Applied Statistics, 9(1), 19-36.
An, Q., Yang, M., Chu, J., Wu, J., & Zhu, Q. (2017). Efficiency evaluation of an interactive system by data envelopment analysis approach. Computers & Industrial Engineering, 103, 17-25.
Wu, J., Zhu, Q., An, Q., Chu, J., & Ji, X. (2016). Resource allocation based on context-dependent data envelopment analysis and a multi-objective linear programming approach. Computers & Industrial Engineering, 101, 81-90.