In this study, we proposed a method to support the knowledge creation process, “Knowledge Liquidization & Crystallization”, and a system to support the knowledge creation process, “Knowledge Nebula Crystallizer (KNC)“. (KNC), a system to support the knowledge creation process, were proposed and constructed, and evaluated through user studies. However, in reality, there is no concrete way to apply the theory to practice, and there is a problem that people do not know what they should do for actual knowledge creation. However, in reality, there is no specific method to apply the theory to practice, and the problem arises that it is not clear what should be done for actual knowledge creation. Therefore, in order to show a practical path from “knowledge sharing to collaborative creation,” this study tackled the problem of supporting the knowledge creation process by using the event design process as a subject through a joint research with an actual advertising company. This paper describes the proposed method and system, as well as the results of analysis of user studies.
The aim of this research is to develop a method and a system to apply the theories for knowledge creation to human practices. Though a number of theoretical and practical studies on knowledge creation have been conducted both by researchers and by business-practitioners, practical methods for knowledge creation, i.e., for connecting the theoretical frameworks with the real world knowledge creation are still required. In this paper, the developed method named “Knowledge Liquidization & Crystallization”, and a system named “Knowledge Nebula Crystallizer (KNC)” are described. They were applied to the actual exhibition design processes as an exemplar of knowledge creation, in co-operation with a Japanese advertising company. The effectiveness of the method and system has been examined through user studies and discussions with the professional designers. https://cir.nii.ac.jp/crid/1050564287836121216 Shigenori Amiya, Koichi Hori
This page is auto-translated from /nishio/知識創造過程を支援するための方法とシステムの研究 using DeepL. If you looks something interesting but the auto-translated English is not good enough to understand it, feel free to let me know at @nishio_en. I’m very happy to spread my thought to non-Japanese readers.