Exploring the evolutionary driving factors of collaborative innovation networks based on complex network evolutionary game: a case study of China's smart grid industry

IF 10 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Cleaner Production Pub Date : 2025-09-27 DOI:10.1016/j.jclepro.2025.146713

Yuan Tao

{"title":"Exploring the evolutionary driving factors of collaborative innovation networks based on complex network evolutionary game: a case study of China's smart grid industry","authors":"Yuan Tao","doi":"10.1016/j.jclepro.2025.146713","DOIUrl":null,"url":null,"abstract":"<div><div>The collaborative innovation network of China's smart grid industry plays a pivotal role in low-carbon economic transformation, energy security and smart city development. Clarifying its evolutionary driving factors is significant for optimizing the network. Based on collaborative patents of China's smart grid industry from 1987 to 2021, this study combines social network analysis and complex network evolutionary game model to construct collaborative innovation networks at different stages, exploring the impact of macro and micro driving factors on the network evolution. The results show that (1) the evolution depth and speed of the network are greater when the network heterogeneity is large. (2) The increase of allocated benefits, cooperation benefits, penalty for breach of contract, losses from competition and implicit benefits will improve the depth and speed of the network evolution. (3) The initial network state also affects the network evolution. The evolution depth and speed of the network are greater when the network scale is larger, the average number of connections is higher, and the average degree is higher. This study provides a theoretical support for improving the collaborative innovation network of China's smart grid industry and an analytical framework for studying the evolutionary driving factors of collaborative innovation networks through the complex network evolutionary game.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"527 ","pages":"Article 146713"},"PeriodicalIF":10.0000,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cleaner Production","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0959652625020633","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}

引用次数: 0

Abstract

The collaborative innovation network of China's smart grid industry plays a pivotal role in low-carbon economic transformation, energy security and smart city development. Clarifying its evolutionary driving factors is significant for optimizing the network. Based on collaborative patents of China's smart grid industry from 1987 to 2021, this study combines social network analysis and complex network evolutionary game model to construct collaborative innovation networks at different stages, exploring the impact of macro and micro driving factors on the network evolution. The results show that (1) the evolution depth and speed of the network are greater when the network heterogeneity is large. (2) The increase of allocated benefits, cooperation benefits, penalty for breach of contract, losses from competition and implicit benefits will improve the depth and speed of the network evolution. (3) The initial network state also affects the network evolution. The evolution depth and speed of the network are greater when the network scale is larger, the average number of connections is higher, and the average degree is higher. This study provides a theoretical support for improving the collaborative innovation network of China's smart grid industry and an analytical framework for studying the evolutionary driving factors of collaborative innovation networks through the complex network evolutionary game.

查看原文本刊更多论文

基于复杂网络演化博弈的协同创新网络演化驱动因素研究——以中国智能电网产业为例

中国智能电网产业协同创新网络在低碳经济转型、能源安全和智慧城市发展中发挥着举足轻重的作用。阐明其演化驱动因素对优化网络具有重要意义。本研究以1987 - 2021年中国智能电网行业协同专利为基础，结合社会网络分析和复杂网络演化博弈模型，构建了不同阶段的协同创新网络，探讨了宏观和微观驱动因素对网络演化的影响。结果表明：(1)网络异质性越大，网络的演化深度和速度越大。(2)分配利益、合作利益、违约惩罚、竞争损失和隐性利益的增加将提高网络演进的深度和速度。(3)网络的初始状态也会影响网络的演化。网络规模越大、平均连接数越高、平均程度越高，网络的演化深度和速度越快。本研究为完善中国智能电网产业协同创新网络提供了理论支持，也为通过复杂网络演化博弈研究协同创新网络演化驱动因素提供了分析框架。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Journal of Cleaner Production 环境科学-工程：环境

CiteScore

20.40

自引率

9.00%

发文量

4720

审稿时长

111 days

期刊介绍： The Journal of Cleaner Production is an international, transdisciplinary journal that addresses and discusses theoretical and practical Cleaner Production, Environmental, and Sustainability issues. It aims to help societies become more sustainable by focusing on the concept of 'Cleaner Production', which aims at preventing waste production and increasing efficiencies in energy, water, resources, and human capital use. The journal serves as a platform for corporations, governments, education institutions, regions, and societies to engage in discussions and research related to Cleaner Production, environmental, and sustainability practices.