References
- Andersen, P., and N. C. Petersen. 1993. “A Procedure for Ranking Efficient Units in Data Envelopment Analysis.” Management Science 39 (10): 1261–1294. doi:https://doi.org/10.1287/mnsc.39.10.1261.
- Avkiran, N. K. 1999. Productivity Analysis in the Services Sector with Data Envelopment Analysis. 1st ed. Camira, Queensland: NK Avkiran.
- Azadeh, A., M. S. Amalnick, S. F. Ghaderi, and S. M. Asadzadeh. 2007. “An Integrated DEA PCA Numerical Taxonomy Approach for Energy Efficiency Assessment and Consumption Optimization in Energy Intensive Manufacturing Sectors.” Energy Policy 35: 3792–3806. doi:https://doi.org/10.1016/j.enpol.2007.01.018.
- Bian, Y. W., and H. Xu. 2013. “DEA Ranking Method Based upon Virtual Envelopment Frontier and TOPSIS.” Systems Engineering - Theory & Practice 33 (2): 482–488.
- Brockett, P. L., A. Charnes, W. W. Cooper, Z. M. Huang, and D. B. Sun. 1997. “Data Transformations in DEA Cone Ratio Envelopment Approaches for Monitoring Bank Performances.” European journal of operational research 98: 250–268. doi:https://doi.org/10.1016/S0377-2217(97)83069-X.
- Charnes, A., W. W. Cooper, and E. Rhodes. 1978. “Measuring the Efficiency of Decision Making Units.” European journal of operational research 2 (6): 429–444. doi:https://doi.org/10.1016/0377-2217(78)90138-8.
- Chen, Y. 2005. “Measuring Super-efficiency in DEA in the Presence of Infeasibility.” European journal of operational research 161: 545–551. doi:https://doi.org/10.1016/j.ejor.2003.08.060.
- Chen, Y., and A. I. Ali. 2004. “DEA Malmquist Productivity Measure: New Insights with an Application to Computer Industry.” European journal of operational research 159: 239–249. doi:https://doi.org/10.1016/S0377-2217(03)00406-5.
- Chiu, Y. H., Y. C. Chen, and X. J. Bai. 2011. “Efficiency and Risk in Taiwan Banking: SBM super-DEA Estimation.” Applied economics 43 (5): 587–602. doi:https://doi.org/10.1080/00036840802599750.
- Coelli, T. J., and D. Rao. 2005. “Total Factor Productivity Growth in Agriculture: A Malmquist Index Analysis of 93 Countries, 1980-2000.” Agricultural Economics 32: 115–134. doi:https://doi.org/10.1111/j.0169-5150.2004.00018.x.
- Cui, Q., and Y. Li. 2014. “The Evaluation of Transportation Energy Efficiency: An Application of Three-stage Virtual Frontier DEA.” Transportation Research 29: 1–11.
- Cui, Q., and Y. Li. 2015. “An Empirical Study on the Influencing Factors of Transportation Carbon Efficiency: Evidences from Fifteen Countries.” Applied Energy 141: 209–217. doi:https://doi.org/10.1016/j.apenergy.2014.12.040.
- Cui, Q., Y. Li, C. L. Yu, and Y. M. Wei. 2016. “Evaluating Energy Efficiency for Airlines: An Application of Virtual Frontier Dynamic Slacks Based Measure.” Energy 113: 1231–1240. doi:https://doi.org/10.1016/j.energy.2016.07.141.
- Cui, Q., Y. Z. Wang, and Y. Li. 2015. “Evaluating Airline Efficiency: An application of Virtual Frontier Network SBM.” Transportation Research, Part E. Logistics and Transportation Review 81: 1–17. doi:https://doi.org/10.1016/j.tre.2015.06.006.
- Cullinane, K., T. F. Wang, D. W. Song, and P. Ji. 2006. “The Technical Efficiency of Container Ports: Comparing Data Envelopment Analysis and Stochastic Frontier Analysis.” Transportation Research Part A 40 (4): 354–374.
- Dennis, J. A., K. L. Ca, and S. Peter. 1977. “Formulation and Estimation of Stochastic Frontier Production Function Models.” Journal of Econometrics 6: 21–37. doi:https://doi.org/10.1016/0304-4076(77)90052-5.
- Evan, K., Doğan, and Tırtıroğlu. 1998. “Bank Efficiency in Croatia: A Stochastic-frontier Analysis.” Journal of comparative economics 26 (2): 282–300. doi:https://doi.org/10.1006/jcec.1998.1517.
- Feng, B., and X. Q. Wang. 2015. “Research on Carbon Decoupling Effect and Influence Factors of Provincial Construction Industry in China.” China Population,Resources and Environment 25 (4): 28–34.
- Fried, H. O., C. A. K. Lovell, S. S. Schmidt, and S. Yaisawarng. 2002. “Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis.” Journal of Productivity Analysis 17 (1–2): 157–174. doi:https://doi.org/10.1023/A:1013548723393.
- Hjalmarsson, L., and A. Veiderpass. 1992. “Productivity in Swedish Electricity Retail Distribution.” The Scandinavian Journal of Economics 94: 193–205. doi:https://doi.org/10.2307/3440259.
- Hu, X., and C. Liu. 2015. “Managing Undesirable Outputs in the Australian Construction Industry Using Data Envelopment Analysis Models.” Cleaner Production 101: 148–157. doi:https://doi.org/10.1016/j.jclepro.2015.03.077.
- Hu, X., and C. Liu. 2016. “Profitability Performance Assessment in the Australian Construction Industry: A Global Relational Two-stage DEA Method.” Construction Management and Economics 34 (3): 147–159. doi:https://doi.org/10.1080/01446193.2016.1180415.
- Kapelko, M., M. HortaI, A. S. Camanho, and A. O. Lansink. 2015. “Measurement of Input-specific Productivity Growth with an Application to the Construction Industry in Spain and Portugal.” International Journal of Production Economics 166: 64–71. doi:https://doi.org/10.1016/j.ijpe.2015.03.030.
- Kapelko, M., A. O. Lansink, and S. E. Stefanou. 2014. “Assessing Dynamic Inefficiency of the Spanish Construction Sector Pre- and Post-financial Crisis.” European journal of operational research 237 (1): 349–357. doi:https://doi.org/10.1016/j.ejor.2014.01.047.
- Kulshreshtha, M., and J. K. Parikh. 2002. “Study of Efficiency and Productivity Growth in Opencast and Underground Coal Mining in India: A DEA Analysis.” Energy Economics 24: 439–453. doi:https://doi.org/10.1016/S0140-9883(02)00025-7.
- Meeusen, W., and C. V. D. Broeck. 1977. “Efficiency Estimation from Cobb–Douglas Production Functions with Composed Error.” International Economic Review 18: 435–444. doi:https://doi.org/10.2307/2525757.
- Mohamed, M., and Mostafa. 2009. “Modeling the Efficiency of Top Arab Banks: A DEA-Neural Network Approach.” Expert Systems with Application 36 (1): 309–320. doi:https://doi.org/10.1016/j.eswa.2007.09.001.
- Mukherjee, K., S. C. Ray, and S. M. Miller. 2001. “Productivity Growth in Large US Commercial Banks: The Initial Post-deregulation Experience.” Journal of Banking& Finance 25: 913–939. doi:https://doi.org/10.1016/S0378-4266(00)00103-5.
- Önüt, S., and S. Soner. 2007. “Analysis of Energy Use and Efficiency in Turkish Manufacturing Sector SMEs.” Energy Conversion and Management 48: 384–394. doi:https://doi.org/10.1016/j.enconman.2006.07.009.
- Resende, M. 2008. “Efficiency Measurement and Regulation in US Telecommunications: Arobustness Analysis.” International Journal of Production Economics 114 (1): 205–218. doi:https://doi.org/10.1016/j.ijpe.2008.01.007.
- Sarica, K., and I. Or. 2007. “Efficiency Assessment of Turkish Power Plants Using Data Envelopment Analysis.” Energy 32 (8): 1484–1499. doi:https://doi.org/10.1016/j.energy.2006.10.016.
- Shang, W. P. 2000. “Definition and Evaluation Index System of Sustainable Development.” China Economic Studies 01: 56–60.
- Shen, L. Y., X. N. Song, Y. Wu, S. J. Liao, and X. L. Zhang. 2016. “Interpretive Structural Modeling Based Factor Analysis on the Implementation of Emission Trading System in the Chinese Building Sector.” Journal of cleaner production 127: 214–227. doi:https://doi.org/10.1016/j.jclepro.2016.03.151.
- Sun, Q. X. 2016. “Energy Conservation and Emission Reduction Make Buildings More Environmentally Friendly.” China Awards for Science and Technology 8: 29–30.
- Tone, K. 2001. “A Slacks-Based Measure of Efficiency in Data Envelopment Analysis.” European journal of operational research 130: 498–509. doi:https://doi.org/10.1016/S0377-2217(99)00407-5.
- Tone, K. 2003. “Dealing with Undesirable Outputs in DEA: A Slacks-Based Measure(SBM) Approach.” Grips Research Report Series. Tokyo, 1-2003-0005.
- Tsolas, I. E. 2011. “Modelling Profitability and Effectiveness of Greek-listed Construction Firms: An Integrated DEA and Ratio Analysis.” Construction Management and Economics 29 (8): 795–807. doi:https://doi.org/10.1080/01446193.2011.610330.
- Wang, F. 2019. “Measurement and Analysis of Interprovincial Environmental Regulation Intensity China—Based on 2003~2016 Data.” Sustainable Development 9 (2): 260–269. doi:https://doi.org/10.12677/SD.2019.92033.
- Wang, X., Y. Chen, B. Liu, Y. Shen, and H. Sun. 2013. “A Total Factor Productivity Measure for the Construction Industry and Analysis of Its Spatial Difference: A Case Study in China.” Construction Management and Economics 31 (10): 1059–1071. doi:https://doi.org/10.1080/01446193.2013.826371.
- Wanke, P., and C. P. Barros. 2016. “Efficiency in Latin American Airlines: A Two-stage Approach Combining Virtual Frontier Dynamic DEA and Simplex Regression.” Journal of Air Transport Management 54: 93–103. doi:https://doi.org/10.1016/j.jairtraman.2016.04.001.
- Xue, M., and P. T. Harker. 2002. “Ranking DMUs with Infeasible Super-efficiency DEA Methods.” Management science 48 (5): 705–710. doi:https://doi.org/10.1287/mnsc.48.5.705.7805.
- Xue, X., Q. P. Shen, Y. Wang, and J. Lu. 2008. “Measuring the Productivity of the Construction Industry in China by Using DEA-based Malmquist Productivity Indices.” Journal of Construction Engineering and Management 134:1 (64): 64–71. doi:https://doi.org/10.1061/(ASCE)0733-9364(2008)134:1(64).
- Xue, X., H. Wu, X. Zhang, J. Dai, and C. Su. 2015. “Measuring Energy Consumption Efficiency of the Construction Industry: The case of China.” Journal of Cleaner Production 107: 509–515. doi:https://doi.org/10.1016/j.jclepro.2014.04.082.
- Yan, J., T. Zhao, T. Lin, and Y. Li. 2017. “Investigating Multi-regional Cross-industrial Linkage Based on Sustainability Assessment and Sensitivity Analysis: A Case of Construction Industry in China.” Journal of cleaner production 142: 2911–2924. doi:https://doi.org/10.1016/j.jclepro.2016.10.179.
- Zhu, J. 2001. “Super-efficiency and DEA Sensitivity Analysis.” European journal of operational research 129: 443–455. doi:https://doi.org/10.1016/S0377-2217(99)00433-6.