{"title":"Hybrid Intelligence-driven decision making for green energy technology innovation in manufacturing enterprises","authors":"Huiqi Zhang, Qiansha Zhang","doi":"10.1186/s42162-025-00511-x","DOIUrl":null,"url":null,"abstract":"<div><p>In the context of today’s global environmental challenges, manufacturing enterprises are gradually taking green technology innovation as a strategy to enhance sustainable development ability. This study discusses the application of hybrid intelligent technology in promoting green technology innovation decision-making in manufacturing enterprises. Through data preprocessing and model construction, it is found that energy consumption, emissions, standard compliance, environmental quality and market response are closely related to the green technology innovation score of enterprises. The results show that efficient energy management and active compliance with environmental standards have a significant impact on improving the environmental performance and technological innovation of enterprises. The market’s positive response to green technology has significantly promoted the rapid development and application of the technology. This study not only provides manufacturing enterprises with strategy and decision support for green technology innovation, but also provides policy makers with insights for promoting sustainable development. Through in-depth analysis, this paper emphasizes the importance and effectiveness of comprehensive application of hybrid intelligent technology in the process of green technology promotion.</p></div>","PeriodicalId":538,"journal":{"name":"Energy Informatics","volume":"8 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://energyinformatics.springeropen.com/counter/pdf/10.1186/s42162-025-00511-x","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Informatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/s42162-025-00511-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Energy","Score":null,"Total":0}
引用次数: 0
Abstract
In the context of today’s global environmental challenges, manufacturing enterprises are gradually taking green technology innovation as a strategy to enhance sustainable development ability. This study discusses the application of hybrid intelligent technology in promoting green technology innovation decision-making in manufacturing enterprises. Through data preprocessing and model construction, it is found that energy consumption, emissions, standard compliance, environmental quality and market response are closely related to the green technology innovation score of enterprises. The results show that efficient energy management and active compliance with environmental standards have a significant impact on improving the environmental performance and technological innovation of enterprises. The market’s positive response to green technology has significantly promoted the rapid development and application of the technology. This study not only provides manufacturing enterprises with strategy and decision support for green technology innovation, but also provides policy makers with insights for promoting sustainable development. Through in-depth analysis, this paper emphasizes the importance and effectiveness of comprehensive application of hybrid intelligent technology in the process of green technology promotion.