Technology trend analysis offers a flexible instrument to understand both opportunity and competition for emerging technologies. Semantic information is used in Science, Technology & Innovation (ST&I) records which makes the technology trend analysis more challenging. This paper proposes a semantic-based approach for technology trend analysis through emphasizing Subject-Action-Object (SAO) structure, It also applies the trend analysis approach to extract technology information and identify and predict the trend of technology development more effectively. An empirical study on Graphene is completed to demonstrate the proposed trend analysis approach.
Author(s): Yang, Chao ; Zhu, Donghua ; Zhang, Guangquan
Organization(s): Beijing Institute of Technology, University of Technology Sydney
Source: 2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)
Identification of technology development trends is essential for supporting decision makers in forecasting and identifying related innovation activities and industrial growth. Different from the traditional technology development trends based on keyword-based quantitative methods, which usually predict trends by finding key technologies without showing how to develop them, our method allows the identification of future direction and industry goal for the technology domain and shows detailed paths for achieving them. Thus, our method has constructed technology roadmapping (TRM) with seven layers (material, technology, influencing factor, component, product, goal, and future direction) on the basis of subject–action–object analysis. The detailed paths for developing this as a trend can be shown by the interaction among these TRM elements. In addition, the method also sets three indicators as a discriminating standard to find key players that can support the trend by engaging technological innovation scenarios. The case of a dye-sensitized solar cell (DSSC) is exemplified to illustrate the detailed procedure of our method. The results reveal the development trends in the field of DSSCs, the detailed paths to achieve them, and key countries that support them.
Author(s): Xuefeng Wang, Pengjun Qiu, Donghua Zhu, Liliana Mitkova, Ming Lei, Alan L. Porter
Organization(s): Beijing Institute of Technology, Georgia Tech
Source: Technological Forecasting and Social Change