A holistic method for radical concept generation based on technological evolution: A case application of DC charging pile. (May 2023) - Zhang, Lulu; Tan, Runhua; Peng, Qingjin; Yang, Wendan; Zhang, Junlei; Wang, Kang
Highlights: A holistic method is proposed for the ex-ante generation of radical concepts. A method is developed for searching the parasitic technology. An artificial neural network is used to improve the objectivity and effectiveness of the technological evolution law selection. Abstract: In the rapidly changeable market, radical innovation (RI) is highly demanded by enterprises to improve their product competitiveness. Enterprises need to efficiently generate ideal radical concepts for the successful implementation of RI. However, the existing research on RI mainly focuses on identifying radical concepts through various evaluation methods from the perspective of business and management. This is a post-hoc analysis, which limits the guidance for enterprises to plan and purposefully generate radical concepts from an ex-ante perspective. For the development of RI products in the engineering field, enterprises lack an effective method for the ex-ante generation of radical concepts. To fill the gap, this paper proposes a holistic method for the ex-ante generation of radical concepts according to the technological evolution. An identification method for radical technology opportunities is proposed based on the evolutionary characteristics of the RI technological trajectory. Technological evolution laws and artificial neural networks are used to determine the evolution direction of subsystems for RI, thereby identify the search direction of new technologies. This paper also establishes a technical knowledge evaluation method and an analogy process for the ex-ante generation of radical concepts. The proposed method is applied in the ex-ante design of a DC charging pile for its feasibility and effectiveness. The proposed method not only provides an efficient ex-ante generation process of the radical concept for enterprise engineers, but also has the potential to enrich research on the RI and knowledge innovation.