Application of DEA-Based Malmquist Productivity Index Measure to the Construction Industry in China


See related content

by Xiaodong Li, Associate Professor; Department of Construction and Real Estate, Harbin Institute of Technology, Harbin, China, lixd@hit.edu.cn,
Qiping Shen, Professor; Department of Building and Real Estate, The Hong Kong Polytechnic University, Kowloon, HK, bsqpshen@polyu.edu.hk,
Xiaolong Xue, Ph.D. Candidate; Department of Construction and Real Estate, Harbin Institute of Technology, Harbin, China, xlxue@hit.edu.cn,



Document Type: Proceeding Paper

Part of: Construction Research Congress 2005: Broadening Perspectives

Abstract: Although productivity is not the only determinant of economic growth, it is a measure of the economic prosperity and degree of competitiveness of an industry. Productivity analysis can provide valuable information about the effectiveness of economic policies. It is also a useful tool for policy makers to improve decisions on economic development and industry performance. Data envelopment analysis (DEA) measures the relative efficiency of decision-making units, which avoids functional specification to express production relationship between inputs and outputs. DEA-based Malmquist productivity index (MPI) approach has been applied to express the productivity change over time. This paper presents the method for calculating input-oriented DEA-based MPI. The MPI, which comprises technical efficiency change and empirical production frontier shift, is used to measure the productivity changes of the construction industry of China's different regions over the period of 1997 to 2002. The calculated results indicate that productivity of the construction industry in China experiences a continuous improvement from 1997 to 2001 and starts a slight decline in the time period of 2001 to 2002. However, there still are different gaps of productivity development level of the construction industry between western, midland, eastern and northeastern regions. It is necessary to adopt effective policies and measures to improve the performance of productivity and competitiveness of the construction industry, and to promote the sustainable development of the construction industry in different regions. The DEA-based MPI approach provides a practical tool to assist policies design and make strategic decisions for improving the total performance of the construction industry in China.

Subject Headings: Construction industry | Productivity | Construction methods | Economic factors | Industries | Information management | Data analysis | China | Asia

Services: Buy this book/Buy this article

 

Return to search