On the Efficiency of Grey Modeling in Early-Stage Technological Diffusion Forecasting

The issue of how to obtain an accurate short-term forecast in the beginning stage of the technological diffusion is of great importance for policy makers, researchers and managers. Time-series forecasting has been noticeably neglected in the specific research area due to the prerequisite of having enough data in order to create a time-series. In this paper, Grey modeling is examined as an alternative tool for technology diffusion forecasting in the early diffusion process, where the commonly used aggregate diffusion models usually fail to deliver accurate forecasts. Grey modeling is a unique time-series methodology that requires only a few data points in order to make a forecast. The GM(1,1) model is tested against a classic aggregate diffusion model, the Gompertz model, using only the first four data of mobile broadband diffusion to make an one-step-ahead prediction. The results in the EU15 countries reveal that the Grey model outperforms the Gompertz model in every case, thus stimulating new research guidelines in terms of combinations of the two approaches and further investigation of the value of Grey modeling in the specific area.