Authors:
Yinglak Dangjaroen
1
;
Mongkolchai Wiriyapinit
2
and
Sukree Sinthupinyo
3
Affiliations:
1
Technopreneurship and Innovation Management Program, Graduate School, Chulalongkorn University, Bangkok, Thailand
;
2
Department of Commerce, Chulalongkorn Business School, Chulalongkorn University, Bangkok, Thailand
;
3
Department of Computer Engineering, Faculty of Engineer, Chulalongkorn University, Bangkok, Thailand
Keyword(s):
Knowledge Transfer, Knowledge Transfer Factors, EV Transition, Artificial Intelligent, Machine Learning.
Abstract:
This study aims to identify the factors influencing knowledge transfer within companies transitioning from the internal combustion engine (ICE) industry to the electric vehicle (EV) industry through an extensive literature review. In addition to summarizing findings and proposing strategies for utilizing artificial intelligence in knowledge transfer, our framework reveals the relevance of three key knowledge transfer factors and three distinct forms of artificial intelligence, including machine learning, in facilitating knowledge transfer. These insights can prove invaluable to entrepreneurs operating within the internal combustion engine automotive sector, offering essential guidance for enhancing the knowledge transfer process and navigating the transition to the electric vehicle industry. By implementing these strategies, businesses can maintain and support their competitiveness in this evolving business.