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Slacks-based data envelopment analysis for eco-efficiency assessment in the Australian construction industry

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  • Xiancun Hu
  • Chunlu Liu

Abstract

Eco-efficiency as an important indicator for sustainability assessment can describe an integrated manner of economic growth, resource conservation and environmental protection. However, the current research could not correctly assess eco-efficiency and mostly utilize qualitative methods. This paper presents a new method called slacks-based Data Envelopment Analysis (DEA) to assess eco-efficiency based on directly and systematically dealing with the slacks of reducing resource consumption and minimizing environmental impacts, together with adding production value. Two DEA models are respectively, defined using inter-temporal and window benchmark techniques, so as to compare eco-efficiency results in temporal and spatial dimensions and then identify production benchmarks and gaps. Efficiency change and technological change, which are two driving forces for eco-efficiency change, are also investigated through a production-theoretical decomposition analysis. Data from the Australian construction industry from 1990 to 2013 are employed to specify the two DEA models. The research results illustrate that the construction industries in the Australian regions showed significant increases in eco-efficiency during the research period, but the gaps among them were increased due to the severe underperformance of technological change. This research primarily provides a innovative pathway for accurate eco-efficiency assessment and quantitative identification of reducing resource consumption, minimizing environmental impacts and adding production value. The developed research framework is generic and can assist worldwide construction projects, organizations and industries to measure, compare and assess eco-efficiency systematically.

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  • Xiancun Hu & Chunlu Liu, 2017. "Slacks-based data envelopment analysis for eco-efficiency assessment in the Australian construction industry," Construction Management and Economics, Taylor & Francis Journals, vol. 35(11-12), pages 693-706, December.
    • Handle: RePEc:taf:conmgt:v:35:y:2017:i:11-12:p:693-706
    DOI: 10.1080/01446193.2017.1325963
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    2. Malte L. Peters & Stephan Zelewski, 2021. "Upper and lower satisficing levels in efficiency analysis: a corporate social responsibility perspective," NachhaltigkeitsManagementForum | Sustainability Management Forum, Springer, vol. 29(3), pages 187-195, December.
    3. Yonglin Li & Zhili Zuo & Deyi Xu & Yi Wei, 2021. "Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China," IJERPH, MDPI, vol. 18(10), pages 1-22, May.
    4. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    5. Maria Julia Xavier Belem & Milton Vieira Junior & Giovanni Mummolo & Francesco Facchini, 2021. "An AHP-Based Procedure for Model Selection for Eco-Efficiency Assessment," Sustainability, MDPI, vol. 13(21), pages 1-21, November.

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