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Total factor productivity measurement with carbon reduction

Total factor productivity measurement with carbon reduction PurposeThe purpose of this paper is to present an approach for productivity measurement that considers both construction growth and carbon reduction.Design/methodology/approachThe approach applied is a sequential Malmquist-Luenberger productivity analysis based on a directional distance function and sequential benchmark technology using the data envelopment analysis (DEA) technique. The sequential Malmquist-Luenberger productivity change index is decomposed into pure technical efficiency, scale efficiency, and technological change indices, in order to investigate the driving forces for productivity change.FindingsThe construction industries of the Australian states and territories were selected implement the new approach. The results indicate that construction growth and carbon reduction can be achieved simultaneously through the learning of techniques from benchmarks.Practical implicationsCurrent research on total factor productivity (TFP) in construction generally neglects carbon emissions. This does not accurately depict the nature of construction and therefore yields biased estimation results. TFP measurement should consider carbon reduction, which is beneficial for policymakers to promote sustainable productivity development in the construction industry.Originality/valueThe approach developed here is generic and enhances productivity and DEA research levels in construction. This research can be used to formulate policies for evaluating performance in worldwide construction projects, organizations and industries by considering undesirable outputs and desirable outputs simultaneously, and for promoting sustainable development in construction by identifying competitiveness factors. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Engineering, Construction and Architectural Management Emerald Publishing

Total factor productivity measurement with carbon reduction

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0969-9988
DOI
10.1108/ECAM-06-2015-0097
Publisher site
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Abstract

PurposeThe purpose of this paper is to present an approach for productivity measurement that considers both construction growth and carbon reduction.Design/methodology/approachThe approach applied is a sequential Malmquist-Luenberger productivity analysis based on a directional distance function and sequential benchmark technology using the data envelopment analysis (DEA) technique. The sequential Malmquist-Luenberger productivity change index is decomposed into pure technical efficiency, scale efficiency, and technological change indices, in order to investigate the driving forces for productivity change.FindingsThe construction industries of the Australian states and territories were selected implement the new approach. The results indicate that construction growth and carbon reduction can be achieved simultaneously through the learning of techniques from benchmarks.Practical implicationsCurrent research on total factor productivity (TFP) in construction generally neglects carbon emissions. This does not accurately depict the nature of construction and therefore yields biased estimation results. TFP measurement should consider carbon reduction, which is beneficial for policymakers to promote sustainable productivity development in the construction industry.Originality/valueThe approach developed here is generic and enhances productivity and DEA research levels in construction. This research can be used to formulate policies for evaluating performance in worldwide construction projects, organizations and industries by considering undesirable outputs and desirable outputs simultaneously, and for promoting sustainable development in construction by identifying competitiveness factors.

Journal

Engineering, Construction and Architectural Management – Emerald Publishing

Published: Jul 17, 2017

References

  • Operational performance of sustainable measures in public buildings
  • Information paper: experimental estimates of industry multifactor productivity
    Australian Bureau of Statistic