期刊論文
| 學年 | 111 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2023-06-01 |
| 作品名稱 | Forecasting Technological Change via Driving Force Approach based on Innovation Diffusion and Complexity Theory |
| 作品名稱（其他語言） | |
| 著者 | Wu, Chien-Hsin; Wu, Feng-Shang |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | International Journal of Information and Management Sciences 34(2), p.161-178 |
| 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 |
| 語言 | en_US |
| ISSN | 1017-1819 |
| 期刊性質 | 國外 |
| 收錄於 | EI Scopus Airiti Library Taiwan |
| 產學合作 | |
| 通訊作者 | Wu, Chien-hsin |
| 審稿制度 | 是 |
| 國別 | TWN |
| 公開徵稿 | |
| 出版型式 | ,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/125011 ) |