Estimating contractors’ efficiency with panel data: Comparison of the data envelopment analysis, Cobb-Douglas and translog production function methods

Abstract

Purpose

This paper aims to explore the use of the data envelopment analysis (DEA), Cobb-Douglas and translog production function methods in estimating contractors’ efficiency.

Design/methodology/approach

In this paper, the DEA, translog and Cobb-Douglas methods were used to estimate the technical efficiency of 23 contractors in Hong Kong from 2003 to 2009. For this research, four input and three output variables were identified.

Findings

The results suggest that the efficiency scores obtained from the DEA method were significantly different from those obtained from the translog and Cobb-Douglas methods, while the efficiency scores from the translog method were similar to those from the Cobb-Douglas method. The DEA method further reveals that the company had poor utilisation of its resources over the past few years. On the output side, the current ratio was too small, implying that the company suffered from excess current liabilities relative to its current assets.

Research limitations/implications

Application of efficiency measurement in the built environment is still in its infancy. The current research, therefore, calls for more research to be undertaken to establish the applied literature base for the construction industry.

Practical implications

The DEA method helps the inefficient company explore ways to improve the utilisation of the inputs as well as the process and to maximise the outputs.

Originality/value

Knowing the relative performance of contractors helps understand their competitiveness in the construction industry. By estimating their technical efficiency, contractors can improve the conditions for enhancing performance.

Citation

Hung Chiang, Y. and W.L. Cheng, E. (2014), "Estimating contractors’ efficiency with panel data: Comparison of the data envelopment analysis, Cobb-Douglas and translog production function methods", Construction Innovation, Vol. 14 No. 3, pp. 274-291. https://doi.org/10.1108/CI-07-2013-0033