Forecasting Technological Change via Driving Force Approach based on Innovation Diffusion and Complexity Theory

Chien-Hsin Wu ； Feng-Shang Wu

《International Journal of Information and Management Sciences》 34卷2期 (2023/06) Pp. 161-178

https://doi.org/10.6186/IJIMS.202306_34(2).0005

摘要

Traditional forecasting methods usually predict industry trends and technologies in only a single direction, either upward or downward. Therefore, the forecasting results would often show surprising deviations, particularly for those industries that are complex and may have abrupt changes. Consequently, this study aims to fill this gap and develop a new approach by making industrial driving forces a concrete tool for forecasting technological changes and industry trends. Both qualitative and quantitative data were collected to examine the future direction of OLED (organic light-emitting diode) technology, which is regarded as complex with highly uncertain opportunities and market potential. The forecasted data were then compared with the actual industrial data. The results indicated that both showed the same cyclical pattern. These preliminary findings imply that the concept of driving forces can be utilized as a forecasting tool when integrated with quantitative data analysis.

關鍵字

Technology forecasting ； Complexity theory ； Complex adaptive systems ； Innovation diffusion ； Driving forces

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