Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric framework

By K. Hervé Dakpo, P. Jeanneaux, Laure Latruffe *. European Journal of Operational Research, 2016

305 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Environmental Engineering, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/20e822b3fee07baac2f0a08742546dd93554ae54

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Joe Zhu
2. Yao Chen
3. Ali Emrouznejad
4. Yi Yang
5. Haibo Zhou
6. Guo-liang Yang
7. Chiang Kao
8. Wade D. Cook

In Environmental Engineering

1. Yao Chen
2. Ali Emrouznejad
3. Yi Yang
4. Joe Zhu
5. Haibo Zhou
6. Guo-liang Yang

In Management Science and Operations Research

1. Ali Emrouznejad
2. Joe Zhu
3. Yao Chen
4. Guo-liang Yang
5. Yi Yang
6. Haibo Zhou
7. Chiang Kao
8. Wade D. Cook

Citations in the corpus

• A framework for measuring global Malmquist–Luenberger productivity index with CO2 emissions on Chinese manufacturing industries (2016, background): “[13] proposed a general review the most relevant methods in this field of modelling pollution-generating technologies in performance benchmarking with limits and strengthens.”
• Data envelopment analysis application in sustainability: The origins, development and future directions (2018, background): “Although Dakpo et al. (2016) make a critical review on methods integrating environmental aspects into productive efficiency, their study focuses on only environmental factors, especially the undesirable outputs in production technology modeling, and does not include social factors, another…”