Title: Applying grey prediction model for forecasting emerging technology

Authors: Benjamin J.C. Yuan, Li-Min Tsai, Jia-Horng Shieh, Tsai-Hua Kang

Addresses: Graduated Institute of Management of Technology, National Chiao Tung University, 7F, Assembly Building 1, No. 1001, Ta-Hsueh Road, Hsinchu (300), Taiwan. ' Graduated Institute of Management of Technology, National Chiao Tung University, 7F, Assembly Building 1, No. 1001, Ta-Hsueh Road, Hsinchu (300), Taiwan. ' Graduated Institute of Leisure & Recreation Management and Department of Hospitality & Management, Hsing-Wu Institute of Technology, No. 101, Sec.1, Fenliao Rd., LinKou District, New Taipei City (244), Taiwan. ' Department of Electronic Engineering, De Lin Institute of Technology, No. 1, Lane 380, Qingyun Rd., Tucheng District, New Taipei City (236), Taiwan

Abstract: Doing the research of technology forecasting, numerous quantitative and qualitative methods can be employed. When utilising a quantitative method to estimate the future performance of a technology, many assumptions need to be conformed. But for an emerging technology, historical data is rare and the upper limit is usually unknown. In this paper, we try to use grey prediction model for technology forecasting and examine the performance of the model by comparing with the Gompertz model and Bass model, which are also used for upper limit unknown and few data forecasting. Three criteria, the MSE, the MAE and the MAPE, will be used for comparison. The result shows that grey predicting model performs better than the other two models for forecasting the emerging technology.

Keywords: technology forecasting; grey theory; emerging technologies; prediction modelling.

DOI: 10.1504/IJFIP.2011.043020

International Journal of Foresight and Innovation Policy, 2011 Vol.7 No.4, pp.271 - 285

Published online: 25 Apr 2015 *

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