{"title":"区域绿色创新生态系统的共生演化:基于Lotka-Volterra模型的中国省际分析","authors":"Qinwen Deng , Yue Long","doi":"10.1016/j.ecolmodel.2025.111244","DOIUrl":null,"url":null,"abstract":"<div><div>The development of the regional green innovation ecosystem (RGIE) can boost the global economy and mitigate environmental risks. However, RGIE exhibits significant heterogeneity in actor interactions, resource allocation, and evolutionary pathways. This study integrates symbiosis theory to construct a tripartite RGIE framework involving the government (GOV), enterprises (ENT), and academic institutions (ACD), and applies the Lotka-Volterra model to qualitatively and quantitatively analyze the symbiotic relationships of RGIE in 30 provinces in China. The findings reveal that: (1) The symbiotic relationships primarily present three patterns: mutualism, parasitism, and competition. GOV-ENT primarily exhibits mutualistic symbiosis, GOV-ACD primarily shows parasitism, and ENT-ACD predominantly demonstrates competitive symbiosis. (2) Mutualistic symbiosis can maximize the development of t RGIE, while parasitic and competitive symbioses may lead to system instability or insufficient innovation drive. (3) Regional resource endowments and institutional environments shape the symbiotic paths. Coastal areas are more likely to achieve mutualistic equilibrium due to market-based coordination, whereas central and western regions are trapped in parasitic lock-ins due to resource misallocation. Based on these findings, differentiated policy tools are proposed: implementing green patent revenue feedback mechanisms in mutually beneficial regions, promoting green performance-based agreements in parasitic regions, and designing resource quota trading markets in competitive regions. This study provides empirical support for the government in formulating precise green innovation policies through the interdisciplinary integration of ecological models and policy design, and offers insights for the global optimization of green innovation ecosystems.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"508 ","pages":"Article 111244"},"PeriodicalIF":3.2000,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Symbiotic evolution in regional green innovation ecosystems: A Lotka-Volterra model analysis of China's provincial\",\"authors\":\"Qinwen Deng , Yue Long\",\"doi\":\"10.1016/j.ecolmodel.2025.111244\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The development of the regional green innovation ecosystem (RGIE) can boost the global economy and mitigate environmental risks. However, RGIE exhibits significant heterogeneity in actor interactions, resource allocation, and evolutionary pathways. This study integrates symbiosis theory to construct a tripartite RGIE framework involving the government (GOV), enterprises (ENT), and academic institutions (ACD), and applies the Lotka-Volterra model to qualitatively and quantitatively analyze the symbiotic relationships of RGIE in 30 provinces in China. The findings reveal that: (1) The symbiotic relationships primarily present three patterns: mutualism, parasitism, and competition. GOV-ENT primarily exhibits mutualistic symbiosis, GOV-ACD primarily shows parasitism, and ENT-ACD predominantly demonstrates competitive symbiosis. (2) Mutualistic symbiosis can maximize the development of t RGIE, while parasitic and competitive symbioses may lead to system instability or insufficient innovation drive. (3) Regional resource endowments and institutional environments shape the symbiotic paths. Coastal areas are more likely to achieve mutualistic equilibrium due to market-based coordination, whereas central and western regions are trapped in parasitic lock-ins due to resource misallocation. Based on these findings, differentiated policy tools are proposed: implementing green patent revenue feedback mechanisms in mutually beneficial regions, promoting green performance-based agreements in parasitic regions, and designing resource quota trading markets in competitive regions. This study provides empirical support for the government in formulating precise green innovation policies through the interdisciplinary integration of ecological models and policy design, and offers insights for the global optimization of green innovation ecosystems.</div></div>\",\"PeriodicalId\":51043,\"journal\":{\"name\":\"Ecological Modelling\",\"volume\":\"508 \",\"pages\":\"Article 111244\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Modelling\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0304380025002303\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Modelling","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304380025002303","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
Symbiotic evolution in regional green innovation ecosystems: A Lotka-Volterra model analysis of China's provincial
The development of the regional green innovation ecosystem (RGIE) can boost the global economy and mitigate environmental risks. However, RGIE exhibits significant heterogeneity in actor interactions, resource allocation, and evolutionary pathways. This study integrates symbiosis theory to construct a tripartite RGIE framework involving the government (GOV), enterprises (ENT), and academic institutions (ACD), and applies the Lotka-Volterra model to qualitatively and quantitatively analyze the symbiotic relationships of RGIE in 30 provinces in China. The findings reveal that: (1) The symbiotic relationships primarily present three patterns: mutualism, parasitism, and competition. GOV-ENT primarily exhibits mutualistic symbiosis, GOV-ACD primarily shows parasitism, and ENT-ACD predominantly demonstrates competitive symbiosis. (2) Mutualistic symbiosis can maximize the development of t RGIE, while parasitic and competitive symbioses may lead to system instability or insufficient innovation drive. (3) Regional resource endowments and institutional environments shape the symbiotic paths. Coastal areas are more likely to achieve mutualistic equilibrium due to market-based coordination, whereas central and western regions are trapped in parasitic lock-ins due to resource misallocation. Based on these findings, differentiated policy tools are proposed: implementing green patent revenue feedback mechanisms in mutually beneficial regions, promoting green performance-based agreements in parasitic regions, and designing resource quota trading markets in competitive regions. This study provides empirical support for the government in formulating precise green innovation policies through the interdisciplinary integration of ecological models and policy design, and offers insights for the global optimization of green innovation ecosystems.
期刊介绍:
The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).