Wang, X; Chen, Y; Liu, B; Shen, Y and Sun, H (2013) A total factor productivity measure for the construction industry and analysis of its spatial difference: A case study in China. Construction Management and Economics, 31(10), pp. 1059-1071. ISSN 1466433X
Abstract
In the context of unbalanced regional economic development in China, there are large regional differences in the development of the construction industry. These long-standing and increasing differences not only influence the total productivity of China's construction industry but also hinder effective resource distribution. Total factor productivity (TFP) is a measure of long-term economic growth and a comprehensive industry-level productivity measure. The objectives are to put forward a set of systematic methodologies for selecting a productivity index, to develop a TFP measure for the construction industry and to conduct an analysis of spatial differences. First, the input and output index system of the construction industry is established, and China's construction industry TFP is measured with the DEA-Malmquist index. Second, spatial differences in the construction industry TFP are analysed in terms of the coefficient of variation (CV) and using spatial clustering analysis. The results indicate that China's construction industry TFP has improved steadily. This improvement has been due mainly to improvements in pure technology efficiency, technological progress and scale efficiency. In the past five years, the CV of China's construction industry productivity has generally been small and has changed only slightly. China's construction industry TFP for all regions exhibits a ladder-like distribution that is different from the distribution by economic areas among the central, western and eastern regions.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | coefficient of variation; dea-malmquist index; spatial clustering analysis; total factor productivity |
| Index terms: | case study, efficiency, productivity, construction industry, economic growth, clustering, regional economic, total factor productivity, methodology, variation, China |
| Subjects: | data science, economic analysis, production economics, data collection methods, industry analysis, contractual condition, Geography, economic development, management, research methods, performance management |
| Topics: | Sustainability, Business Strategy, Geographical Context, Research Practice, Contract Administration, Digital Applications, Quality Management |
| Descriptive scope: | 5 PCTEA |
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