Skip to main content
Log in

The energy efficiency of China’s regional construction industry based on the three-stage DEA model and the DEA-DA model

  • Construction Management
  • Published:
KSCE Journal of Civil Engineering Aims and scope

Abstract

China’s construction industry has constantly been confronted with the problems, such as high resource consumption, serious pollution and low energy efficiency. Thus, improving the energy efficiency of the construction industry and reducing its energy consumption can not only promote the sustainable development of the socio-economy and eco-economy, but also enhance the overall development level of the construction industry. In the context, the objectives are to put forward a set of systematic methodologies for measuring the energy efficiency of the regional construction industry and analyzing its change trends. First, the energy efficiency index system of the construction industry and its influencing factors are constructed through the literature review. Second, two research methods (the three-stage Data Envelopment Analysis (DEA) model and the Data Envelopment Analysis-Discriminant Analysis (DEA-DA) model) are applied to analyze the energy efficiency in 30 provinces of China and the change trends from 2003 to 2011. The results indicate that after eliminating the influence of the environment factors and random errors, the energy efficiency values of the construction industry in most of the provinces were improved. The mean of China’s energy efficiency of the construction industry in each year was approximately 0.92. Except Shandong with the lowest values, the mean of the other provinces was over 0.8, which reflected that the energy management and utilization levels in the construction industry were relative mature. However, the energy efficiency in most of provinces fluctuated constantly during these nine years, with the peak in 2004 and a downward trend in the overall efficiency after 2004. From the regional aspect, the energy efficiency of the construction industry in the eastern, central and western regions decreased successively; as the development level of the local economy had less significant effects on the energy efficiency, the gaps among the three regions were not obvious.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Banker, R. D., Charnes, A., and Cooper, W. W. (1984). “Some models for estimating technical and scale inefficiencies in data envelopment analysis.” Management Science, Vol. 30, No. 9, pp. 1078–1092.

    Article  Google Scholar 

  • Battese, G. E., Coelli, T. J., and Colby, T. C. (1989). “Estimation of frontier production functions and the efficiencies of Indian farms using panel data from ICRISAT’s village level studies.” Journal of Quantitative Economics, Vol. 5, No. 1, pp. 327–348.

    Google Scholar 

  • Bert, H. and Kelly, L. (2007). Structural change and energy use: Evidence from China’s provinces, 2006 China Working Paper Series.

    Google Scholar 

  • Boyd, G. A. and Pang, J. X. (2000). “Estimating the linkage between energy efficiency and productivity.” Energy Policy, Vol. 28, No. 5, pp. 289–296.

    Article  Google Scholar 

  • Charnes, A., Cooper, W. W., and Rhodes, E. (1978). “Measuring the efficiency of decision making units.” European Journal of Operational Research, Vol. 2, No. 6, pp. 429–444.

    Article  MathSciNet  Google Scholar 

  • Coelli, T. (1996a). A guide to DEAP version 2.1: A data envelopment analysis (computer) program, Centre for Efficiency and Productivity Analysis.

    Google Scholar 

  • Coelli, T. (1996b). A guide to Frontier version 4.1: A computer) program for stochastic frontier production and cost function estimation, Centre for Efficiency and Productivity Analysis.

    Google Scholar 

  • Cohen, W. and Lebinthal, D. (1989). “Innovation and learning: The two faces of R&D.” The Economic Journal, Vol. 99, No. 397, pp. 569–596.

    Article  Google Scholar 

  • Cornwell, C., Schmidt, P., and Sickles, R. C. (1990). “Production frontiers with cross-sectional and time-series variation in efficiency levels.” Journal of Econometrics, Vol. 46, Nos. 1–2, pp. 185–200.

    Article  Google Scholar 

  • Cui, Q. and Li, Y. (2014). “The evaluation of transportation energy efficiency: An application of three-stage virtual frontier DEA.” Transportation Research Part D: Transport and Environment, Vol. 29, pp. 1–11.

    Article  Google Scholar 

  • Dai, Y. A. and Chen, C. (2010). “Technical efficiency in China’s construction industry and its influencing factors.” China Soft Science, Vol. 1, No. 1, pp. 87–95.

    Google Scholar 

  • Ebrahimnejad, A., Tavana, M., Lotfi, F. H., Shahverdi, R., and Yousefpour, M. (2014). “A three-stage data envelopment analysis model with application to banking industry.” Measurement, Vol. 49, No. 1, pp. 308–319.

    Article  Google Scholar 

  • Edenhofer, O. and Jaeger, C. C. (1998). “Power shifts: The dynamics of energy efficiency.” Energy Economics, Vol. 20, Nos. 5–6, pp. 513–537.

    Article  Google Scholar 

  • Fan J. T. (2010). China construction industry market structure, performance and competition policy, Shanghai University of Finance and Economics Press, Shanghai.

    Google Scholar 

  • Farla, J., Cuelenaere, R., and Blok, K. (1998). “Energy efficiency and structure change in the Netherlands, 1998–1990.” Energy Economics, Vol. 20, No. 1, pp. 1–28.

    Article  Google Scholar 

  • Farrell, M. J. (1957). “The measurement of productive efficiency.” Journal of the Royal Statistical Society: Series A General, Vol. 120, No. 3, pp. 253–290.

    Article  Google Scholar 

  • Fisher-Vanden, K., Jefferson, G. H., Liu, H. M., and Tao, Q. (2004). “What is driving China’s decline in energy intensity?.” Resource and Energy Economics, Vol. 26, No. 1, pp. 77–97.

    Article  Google Scholar 

  • Fisher-Vanden, K., Jefferson, G. H., Ma, J. K., and Xu, J. Y. (2006). “Technology development and energy productivity in China.” Energy Economics, Vol. 28, Nos. 5–6, pp. 690–705.

    Article  Google Scholar 

  • Fleiter, T., Fehrenbach, D., Worrell, E., and Eichhammer, W. (2012). “Energy efficiency in the German pulp and paper industry-A modelbased assessment of saving potentials.” Energy, Vol. 40, No. 1, pp. 84- 99.

    Article  Google Scholar 

  • Fried, H. O., Lovell, C. A. K., Schmidt, S. S., and Yaisawarng, S. (2002). “Accounting for environmental effects and statistical noise in data envelopment analysis.” Journal of Productivity Analysis, Vol. 17, Nos. 1–2, pp. 157–174.

    Article  Google Scholar 

  • Giacone, E. and Mancò, S. (2012). “Energy efficiency measurement in industrial processes.” Energy, Vol. 38, No. 1, pp. 331–345.

    Article  Google Scholar 

  • Gielen, D. and Taylor, P. (2009). “Indicators for industrial energy efficiency in India.” Energy, Vol. 34, No. 8, pp. 962–969.

    Article  Google Scholar 

  • Hang, L. M. and Tu, M. Z. (2007). “The impacts of energy prices on energy intensity: Evidence from China.” Energy Policy, Vol. 35, No. 5, pp. 2978–2988.

    Article  Google Scholar 

  • Hasanbeigi, A. and Price, L. (2012). “A review of energy use and energy efficiency technologies for the textile industry.” Renewable and Sustainable Energy Reviews, Vol. 16, No. 6, pp. 3648–3665.

    Article  Google Scholar 

  • Henryson, J., Håkansson, T., and Pyrko, J. (2000). “Energy efficiency in buildings through information Swedish perspective.” Energy Policy, Vol. 28, No. 3, pp. 169–180.

    Article  Google Scholar 

  • Honma, S. and Hu, J. L. (2008). “Total-factor energy efficiency of regions in Japan.” Energy Policy, Vol. 36, No. 2, pp. 821–833.

    Article  Google Scholar 

  • Hsu, F. M. and Hsueh, C. C. (2009). “Measuring relative efficiency of government-sponsored projects: A three-stage approach.” Evaluation and Project Planning, Vol. 32, No. 2, pp. 178–186.

    Article  Google Scholar 

  • Hu, J. L. and Kao, C. H. (2007). “Efficient energy saving targets for APEC economies.” Energy Policy, Vol. 35, No. 1, pp. 373–382.

    Article  Google Scholar 

  • Hu, J. L. and Wang, S. C. (2006). “Total factor energy efficiency of regions in China.” Energy Policy, Vol. 34, No. 17, pp. 3206–3217.

    Article  Google Scholar 

  • Jenne, C. A. and Cattell, R. K. (1983). “Structural change and energy efficiency in industry.” Energy Economics, Vol. 5, No. 2, pp. 114–123.

    Article  Google Scholar 

  • Johansson, M. T. and Soderstrom, M. (2011). “Options for the Swedish steel industry-Energy efficiency measures and fuel conversion.” Energy, Vol. 36, No. 1, pp. 191–198.

    Article  Google Scholar 

  • Keller, T. W. (2002). “Geographic localization of international diffusion.” American Economic Review, Vol. 92, No. 1, pp. 120–142.

    Article  Google Scholar 

  • Laurijssen, J., De Gram, F. J., Worrell, E., and Faaij, A. (2010). “Optimizing the energy efficiency of conventional multi-cylinder dryers in the paper industry.” Energy, Vol. 35, No. 9, pp. 3738–3750.

    Article  Google Scholar 

  • Liu, B. S., Chen, X. H., Wang, X. Q., and Chen, Y. (2014). “Development potential of Chinese construction industry in the new century based on regional difference and spatial convergence analysis.” KSCE Journal of Civil Engineering, KSCE, Vol. 18, No. 1, pp. 11–18.

    Article  Google Scholar 

  • Liu, B. S., Wang, X. Q., Chen, C. L., and Ma, Z. J. (2014). “Research into the dynamic development t rend of the competitiveness of China’s regional construction industry.” KSCE Journal of Civil Engineering, KSCE, Vol. 18, No. 1, pp. 1–10.

    Article  Google Scholar 

  • Lovell, C. A. K. (1993). Production frontiers and productive efficiency, in Fried, H.O., Lovell, C.A.K., Schmidt, S.S. (Eds.), The Measurement of Productive Efficiency: Techniques and Applications, Oxford University Press, Oxford, pp. 3–67.

    Chapter  Google Scholar 

  • Lutzenhiser, L. (1994). “Innovation and organization networks barriers to energy efficiency in the US housing industry.” Energy Policy, Vol. 22, No. 10, pp. 867–876.

    Article  Google Scholar 

  • Miketa, A. (2001). “Analysis of energy intensity developments in manufacturing sectors in industrialized and developing countries.” Energy Economics, Vol. 29, No. 10, pp. 769–775.

    Google Scholar 

  • Nakano, M. and Managi, S. (2008). “Regulatory reforms and productivity: An empirical analysis of the Japanese electricity industry.” Energy Policy, Vol. 36, No. 1, pp. 201–209.

    Article  Google Scholar 

  • National Bureau of statistics of China (2012). China statistical yearbook 2004–2012, China Statistics Press, Beijing.

    Google Scholar 

  • Pardo Martínez, C. I. (2009). “Energy efficiency developments in the manufacturing industries of Germany and Colombia, 1998-2005.” Energy for Sustainable Development, Vol. 13, No. 3, pp. 189–201.

    Article  Google Scholar 

  • Pardo Martínez, C. I. (2010). “Energy use and energy efficiency development in the German and Colombian textile industries.” Energy for Sustainable Development, Vol. 14, No. 2, pp. 94–103.

    Article  Google Scholar 

  • Patterson, M. C. (1996). “What is energy efficiency? Concepts, indicators and methodological issues.” Energy Policy, Vol. 24, No. 5, pp. 377–390.

    Article  Google Scholar 

  • Rashe, R. and Tatom, J. (1977). “Energy resources and potential GNP.” Federal Reserve Bank of St. Louis Review, Vol. 59, No. 6, pp. 10–23.

    Google Scholar 

  • Ryghaug, M. and Soreensen, K. H. (2009). “How energy efficiency fails in the building industry.” Energy Policy, Vol. 37, No. 3, pp. 984–991.

    Article  Google Scholar 

  • Rohdin, P. and Thollander, P. (2006). “Barriers to and driving forces for energy efficiency in the non-energy intensive manufacturing industry in Sweden.” Energy, Vol. 31, No. 12, pp. 1836–1844.

    Article  Google Scholar 

  • Shephard, R. W. (1970). Theory of cost and production functions, Princeton University Press.

    Google Scholar 

  • Shi, D. (2006). “Regional differences in China's energy efficiency and conservation potentials.” China Industrial Economy, Vol. 10, No. 10, pp. 49–58.

    Google Scholar 

  • Shi, G. M., Bi, J., and Wang, J. N. (2010). “Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing nonenergy inputs.” Energy Policy, Vol. 38, No. 10, pp. 6172–6179.

    Article  Google Scholar 

  • Shyu, J. and Chiang, T. (2012). “Measuring the true managerial efficiency of bank branches in Taiwan: A three-stage DEA analysis.” Expert Systems with Applications, Vol. 39, No. 13, pp. 11494–11502.

    Article  Google Scholar 

  • Sueyoushi, T. (1999). “DEA-Discriminant analysis in the view of goal programming.” European Journal of Operational Research, Vol. 115, No. 3, pp. 564–582.

    Article  Google Scholar 

  • Suryoshi, T. and Goto, M. (2012). “Efficiency-based rank assessment for electric power industry: A combined use of data envelopment analysis (DEA) and DEA-discriminant analysis (DA).” Energy Economics, Vol. 34, No. 3, pp. 634–644.

    Article  Google Scholar 

  • Timmer, C. P. (1971). “Using a probabilistic frontier production function to measure technical efficiency.” Journal of Political Economy, Vol. 79, No. 4, pp. 776–794.

    Article  Google Scholar 

  • Wang, Z. P. and Tao, C. Q. (2010). “Regional production efficiency and its influence factors analysis in China-based on 2001-2008 interprovincial panel-data and SFA method.” Systems Engineering-Theory & Practice, Vol. 30, No. 10, pp. 1762–1773.

    Google Scholar 

  • Wang, Z. H., Zeng, H. L., Wei, Y. M., and Zhang, Y. X. (2012). “Regional total factor energy efficiency: An empirical analysis of industrial sector in China.” Applied Energy, Vol. 97, pp. 115–123.

    Article  Google Scholar 

  • Wei, Y. M., Liao, H., and Fan, Y. (2007). “An empirical analysis of energy efficiency in China’s iron and steel sector.” Energy, Vol. 32, No. 12, pp. 2262–2270.

    Article  Google Scholar 

  • Wilson, B. I., Trieu, L. H., and Bowen, B. (1994). “Energy efficiency trends in Australia.” Energy Policy, Vol. 22, No. 4, pp. 287–289.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bingsheng Liu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Y., Liu, B., Shen, Y. et al. The energy efficiency of China’s regional construction industry based on the three-stage DEA model and the DEA-DA model. KSCE J Civ Eng 20, 34–47 (2016). https://doi.org/10.1007/s12205-015-0553-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12205-015-0553-3

Keywords

Navigation