Future Skills Needs Analysis by Patent Analysis - Focus on Rechargeable Batteries
for the Automobile Industry as Industrial Convergence
Gyu-Hee Hwang, Beyong-Yeol Coh, In-Joong Ju
This study seeks to develope a methodology for future skills needs analysis through the patent analysis of the basis for the knowledge and knowledge network theories. A patent data analysis of rechargeable batteries for automobiles will be conducted and knowledge units will be extracted as future skills demand. Thereafter, this will be applied to curriculum analysis.
The present study raises the possibility in the theoretical debate over convergence knowledge production modes of a knowledge network analysis through patent analysis. It also analyzes detailed technological trends and knowledge and functions required in conjunction with the migration of the major rechargeable battery market to mobile, and examines the purposes of automobile and energy storage through a network analysis of rechargeable battery related patents.
In this study, skills, which is regarded as a concept compatible with knowledge, includes technology and techniques. Viewed from this standpoint, knowledge becomes an object that represents (knowledge) networks, which in turn means that the analysis of such knowledge networks can be planned. While the data structure hidden inside of patents can work as a critical “proxy meter” for identifying scientific and technological activities and the related knowledge structure, this study identifies the development and structure of knowledge by quantifying and structuring patent data.
The primary contribution of this study is to advance a methodology by displaying the manner in which patent data analysis can be used in future skills needs analysis. The future skills needs analysis conducted via the patent data analysis in this study can be utilized as follows:
- To provide a systematic approach to the qualitative discordance matters that continuously recur in the cultivation and utilization of science and engineering professionals.
- To support a more reasonable policy making process in conjunction with the establishment of policies for future key growth engines and prospective industries.
- To improve employability by providing information on future skills needs and promote the development of related curriculum in universities and training centers.
