- 期刊
Appling the Grey Prediction Model To Track The Internet's Global Diffusion
並列摘要
The accurate prediction of the adoption of a new technology and its diffusion in a market help managers make better decisions in competitive environments. The emergence of the World-Wide Web (WWW) in 1990s boosts the growth of the Internet and its applications. The Internet has become an important strategic information tool for businesses because of its capability of connecting massive potential customers, enterprises, and their employees in a short time. Tracking the Internet's global diffusion is an arduous but increasingly important task, especially of network capacity planners. Developing models that explain the growth process is essential to policy formulation, capacity planning, and introducing new network hardware and software. A new anticipation model, the Grey model that can be used to predict the global diffusion with few historical data is proposed in this article. The paper aims to apply the Grey prediction model to anticipating the Internet’s global diffusion and to evaluate its effectiveness by comparing its results with those of the methods presented in Rai et al. (1998). The results show that the Grey model can achieve more accurate prediction with less historical data compared with Logistic model, Gompertz model, and Exponential model.