A target-oriented data envelopment analysis for regional construction efficiency improvement in mainland China

Abstract

Construction industry is a significant contributor to China’s national economy during the past decades. But as one of the pillar sectors, the development of construction industry is still labor intensive with low productive efficiency. Stagnant performance of construction productivity has been recognized as a main barrier to rapid and sustainable development of construction industry. Productivity remains to be a critical issue perplexing academia and industry for a long period of time, due to the heterogeneous metrics for measurement and improvement. Therefore, it is crucial for policy-makers to estimate the productivity change and have insightful information on regional input and output for further strategic planning and policy fine-tuning. Data envelopment analysis (DEA) is an objective benchmarking methodology for multiple inputs and outputs, which has been employed repeatedly for productivity measurement in construction industry. However, owing to the model restriction, traditional DEA model cannot provide detailed insights into efficient use of different inputs to produce desirable output in the state of full efficiency. With this respect, effective strategies might not be formulated and implemented for further productivity improvement. In context of unbalanced regional development in China, this paper aims to apply an updated DEA model, with integration of Distance friction minimization (DFM) method and target-oriented (TO) approach, to explore regional differences of China’s construction industry. The results indicate that the unbalanced performance of regional construction productive efficiency is caused by unreasonable allocation and utilization of critical resources. To improve regional construction efficiency, recommendations are made for policy makings and strategic decisions based on the stepwise projection results of TO-DFM model with target efficiency scores (TES).