Journal of Cleaner Production

Volume 112, Part 1, 20 January 2016, Pages 521-531
Journal of Cleaner Production

Analysis of the construction waste management performance in Hong Kong: the public and private sectors compared using big data


There is an ongoing debate concerning the disparity between the public and private sectors in relation to construction waste management (CWM) performance: some argue that CWM performance between the two sectors should have no difference since they are under the governance of the same set of CWM related regulations, while others argue that public sector clients should perform better as they are subject to greater social scrutiny. Previous studies comparing CWM performance have suffered from insufficient quality data, leaving the debate on the CWM performance disparity largely inconclusive. Informed by the Coase Invariant Theorem, this research empirically compares CWM performance between public and private projects. It does so by using big data in the form of 2 million waste disposal records generated from around 5700 projects undertaken in Hong Kong during 2011 and 2012. It is found that there is a notable CWM performance disparity between the public and private sectors, with contractors performing better in managing both inert and non-inert waste in public projects than they do in private projects. Furthermore, the interviews and case studies conducted as part of the research suggest that CWM transaction costs are not high enough to incentivize contractors to manage waste conscientiously and therefore other institutional arrangements, such as promoting the value of environment protection leadership, are critical for achieving superior CWM performance. The research therefore supports the corollary of Coase Invariant Theorem, which asserts that certain forms of institutions would improve CWM performance by reducing transaction cost even though both sectors are subject to the same set of CWM-related formal public policies.


Construction and demolition waste
Construction waste management
Waste generation rate
Coase invariant theorem
Big data