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This study measured the levels of Digital-Intelligence Integration (DII) and ecological resilience in cities within the Yellow River Basin from 2011 to 2022 using the entropy weight TOPSIS method and a coupling coordination model. The spatio-temporal evolution of DII was further analyzed. Building on these measurements, seemingly unrelated regression (SUR) and moderated mediation models were employed to investigate the effects, underlying mechanisms, and moderating factors influencing the relationship between DII and urban ecological resilience in the region. The results showed that the overall level of DII in the Yellow River Basin increased from 0.144 to 0.353 during the study period. By 2022, most cities had transitioned out of states of extreme and severe imbalance. A distinct spatial clustering pattern was observed for DII, with cluster centers predominantly located in the Shandong Peninsula and provincial capitals. The gap between these cluster centers and non-central cities was found to be widening. DII exerted a significantly positive overall effect on urban ecological resilience (regression coefficient = 0.197, p<0.01). However, its effect on the resistance dimension of ecological resilience was significantly negative (coefficient = -0.011, p<0.01), suggesting a potential weakening effect. Green innovation and public environmental concern acted as significant mediators. The regression coefficients of DII on green innovation and public environmental concern were 0.744 (p<0.01) and 0.345 (p<0.05), respectively. Financial development positively moderated these mediating roles, as the interaction terms between financial development and DII yielded significant coefficients of 0.122 and 0.146 (both p<0.01) for green innovation and public environmental concern, respectively. Heterogeneity analysis indicated that DII significantly enhanced urban ecological resilience only in downstream regions (coefficient=0.302, p<0.01), with no significant effects observed in upstream or midstream regions. Moreover, non-resource-based cities and those designated as big data comprehensive pilot zones exhibited stronger effects (coefficients = 0.235 and 0.285, respectively, both p<0.01) compared to other cities. These findings provide scientific support and policy references for optimizing urban ecological resilience in the Yellow River Basin in the era of digital intelligence.

, authors=Mei-fang HA^*, Ming-qiang SUI, authorsList=Mei-fang HA, Ming-qiang SUI, authorCompany=null, correspAuthors=Mei-fang HA, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1314917817577734256, articleId=1314917817070223470, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=数智融合对黄河流域城市生态韧性的影响研究, columnId=1234106419604157142, journalTitle=中国环境科学, columnName=环境影响评价与管理, runingTitle=null, highlight=null, articleAbstract=

通过熵权Topsis、耦合协调模型测算了2011~2022年黄河流域城市的数智融合和生态韧性水平，并分析了数智融合的时空演进．在此基础上利用似不相关回归以及有调节的中介模型等，探究了数智融合影响黄河流域城市生态韧性的效应、机制及机制调节因素．结果表明：研究期内黄河流域数智融合的整体水平由0.144逐渐上升到0.353，截至2022年各城市已基本摆脱极度和严重失调．数智融合存在明显的空间聚集现象，聚集中心主要分布在山东半岛及各省省会，且聚集中心和非中心的差距逐渐增大．数智融合对黄河流域城市生态韧性的总体影响在1%的统计水平显著为正，回归系数为0.197，但对生态韧性抵抗力层面的影响在1%的统计水平显著为负，系数为-0.011，存在一定削弱作用．绿色创新和公众环境关注发挥了机制作用，数智融合对绿色创新和公众环境关注的回归系数分别为0.744、0.345，分别在1%、5%统计水平下显著．金融发展水平能正向调节绿色创新和公众环境关注的机制作用，金融发展水平和数智融合的交互项对绿色创新和公众环境关注的回归系数分别为0.122、0.146，均在1%统计水平下显著．异质性分析表明，仅下游地区的数智融合显著提升了城市生态韧性，系数为0.302，在1%统计水平下显著，上、中游并不明显，非资源型、大数据综合试点城市较其他城市效果更优，系数分别为0.235、0.285，均在1%统计水平下显著．研究结果为黄河流域城市生态韧性在数智时代下的优化提供了科学依据和政策参考．

, authors=哈梅芳^*, 隋明强, authorsList=哈梅芳, 隋明强, authorCompany=null, correspAuthors=哈梅芳, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=vA3X6PKl01IJAqRU/8Q6eQ==, magXml=3vT5/j8M/OU6vkoRsvgrQA==, pdfUrl=null, pdf=Bd/6j1UIccubgDENizgN9Q==, pdfFileSize=1232103, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=QgDbgmmVecGuiuk43vJ3Ag==, mapNumber=null, fund=null)}, authors=[Author(id=1314917819402256501, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314917817070223470, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=17811276657@163.com, emailSecond=null, emailThird=null, correspondingAuthor=1, authorType=1, ext={EN=AuthorExt(id=1314917819515502711, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314917817070223470, authorId=1314917819402256501, language=EN, stringName=Mei-fang HA, firstName=Mei-fang, middleName=null, lastName=HA, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^*, address=School of Economics and Management, Ningxia University 750021, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1314917819591000184, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314917817070223470, authorId=1314917819402256501, language=CN, stringName=哈梅芳, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^*, address=宁夏大学经济管理学院，宁夏 银川 750021, bio={"content":"

哈梅芳（1973-），女，宁夏青铜峡人，教授，博士，从事财政税收理论与政策、资源环境经济学研究．发表论文30余篇．17811276657@163.com.

"}, bioImg=null, bioContent=

哈梅芳（1973-），女，宁夏青铜峡人，教授，博士，从事财政税收理论与政策、资源环境经济学研究．发表论文30余篇．17811276657@163.com.

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