Forecasting Construction Manpower Demand by Gray Model

Abstract

Construction is a labor-intensive industry that is heavily reliant on the availability of local manpower. The construction workload also fluctuates in either a cyclical or random manner. As a result, there is always either a shortage or surplus of manpower. Although a number of good forecasting models have been developed, they require input of sufficient and good-quality data to produce accurate results. The aim of this paper is to explore the use of the gray model in forecasting construction manpower based on a limited amount of data. A wide range of forecasting models in the literature is first reviewed. A single-variable first-order gray model is then proposed to forecast construction manpower one quarter ahead. The model is tested using manpower data based on the Quarterly Report on General Household Survey published by the Census and Statistics Department of the HKSAR Government. Data from 64 quarters, covering the first quarter of 1992 to the fourth quarter of 2007, are included. A computer program is formulated to manipulate all of the calculations involved. Based on the minimum mean absolute percentage error (MAPE) criterion, it is found that the optimal sample size is 5. Based on the input of data from five quarters, the MAPE of the overall forecast is only 3.21%, and the maximum absolute percentage error is 8.92%. It is thus concluded that the gray model produces very accurate results. The results of this study also suggest that this model is applicable to forecasts of other time series particularly when limited data are available.

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