{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T23:53:36Z","timestamp":1792108416813,"version":"4.4.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684109","type":"print"},{"value":"9781643684116","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,7,21]],"date-time":"2023-07-21T00:00:00Z","timestamp":1689897600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,7,21]]},"abstract":"<jats:p>Using the quasi-natural event of the promotion of China\u2019s intelligent manufacturing demonstration project, this paper takes China\u2019s A-share listed manufacturing enterprises from 2011 to 2021 as the research sample, takes R&amp;D efficiency as the explained variable, and dummy variable during the experimental period as the explanatory variable. With enterprise age, fixed capital density, cash flow, enterprise growth, asset-liability ratio, return on equity and enterprise size as control variables, propensity score matching and difference-in-differences model (PSM+DID) were used to empirically test the influence of intelligent manufacturing on R&amp;D efficiency of manufacturing enterprises. The research results show that intelligent manufacturing can effectively improve the R&amp;D efficiency of enterprises in pilot demonstration projects, forming a demonstration and promotion effect, and these benchmarking enterprises promote the high-quality development of China\u2019s manufacturing industry. The empirical results enrich the research content of intelligent manufacturing, provide micro-evidence for China\u2019s policy formulation and effect evaluation, and also put forward countermeasures and suggestions for improving the R&amp;D efficiency of manufacturing enterprises, so as to promote the process of \u201cintelligent manufacturing\u201d in China.<\/jats:p>","DOI":"10.3233\/faia230193","type":"book-chapter","created":{"date-parts":[[2023,7,25]],"date-time":"2023-07-25T13:00:18Z","timestamp":1690290018000},"source":"Crossref","is-referenced-by-count":1,"title":["Research on the Influence of Intelligent Manufacturing on R&amp;D Efficiency of Manufacturing Enterprises-Based on the Quasi-Natural Experiment of China\u2019s Intelligent Manufacturing Demonstration Project"],"prefix":"10.3233","author":[{"given":"Zichen","family":"Guo","sequence":"first","affiliation":[{"name":"School of Economics and Management, Xiangnan University, Chenzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Xiangnan University, Chenzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Modern Management Based on Big Data IV"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230193","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,25]],"date-time":"2023-07-25T13:00:20Z","timestamp":1690290020000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230193"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,21]]},"ISBN":["9781643684109","9781643684116"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230193","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,21]]}}}