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Analyzing the ecological relations of technology innovation of the Chinese high-tech industry based on the Lotka-Volterra model.
Xia, Ming; He, Xiangwu; Lin, Hui; Xie, Zhimin; Zhou, Yubin.
  • Xia M; School of Economics and Management, Tongji University, Shanghai, China.
  • He X; Business School, Jiaxing University, Jiaxing, China.
  • Lin H; School of Economics and Management, Tongji University, Shanghai, China.
  • Xie Z; School of Economics and Management, Tongji University, Shanghai, China.
  • Zhou Y; School of Economics and Management, Tongji University, Shanghai, China.
PLoS One ; 17(5): e0267033, 2022.
Article in English | MEDLINE | ID: covidwho-1933223
ABSTRACT
Technology innovation has become an important driving force of economic and social development and has received wide attention from academics. Most scholars mainly take technology innovation as an overall variable to explore its impact on the economy and society. The main contribution of this study is to open the black box of technology innovation and introduce the lotka-Volterra model to explore the internal structure of technology innovation in the Chinese high-tech industry and to analyze the ecological relationships, evolutionary trends, equilibrium states of six technology innovation species including independent innovation (II), technology import (TI), research & development (RD), technology renovation (TR), foreign technology acquisition (FTA), and domestic technology purchase (DTP). The results of the study show that, First, the ecological relationship between prey and predator is observed between RD and TR, DTP and FTA, and II and TI. Second, no equilibrium state is observed between TD and TF and II and TI. Third, an unstable equilibrium state is observed between RD and TR.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Inventions / Industry Country/Region as subject: Asia Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article Affiliation country: Journal.pone.0267033

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Inventions / Industry Country/Region as subject: Asia Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article Affiliation country: Journal.pone.0267033