Does Business Environment Optimization Improve Carbon Emission Efficiency? Evidence from Provincial Panel Data in China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Does Business Environment Optimization Improve Carbon Emission Efficiency? Evidence from Provincial Panel Data in China Peiyu Li, Xinzhi Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3688268/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Mar, 2024 Read the published version in Environmental Science and Pollution Research → Version 1 posted 5 You are reading this latest preprint version Abstract Previous research has yielded varied conclusions regarding the effect of business environment (BE) optimization to improve carbon emission efficiency (CEE). In this study, CEE and BE are assessed using energy consumption and economic growth data from 30 provinces in China. The research employs fixed effects, quantile, and mediation effect models to analyze the direct impact, nonlinear characteristics, mechanism, and heterogeneity of BE on CEE. The research found that. Firstly, the BE optimization enhances CEE, with a 1% increase leading to a 0.095% improvement in CEE. Secondly, the influence of the BE on CEE exhibits marginal diminishing traits that decline as CEE improves. Thirdly, the analysis of mechanisms reveals that the BE primarily impacts CEE through positive mechanisms such as industrial structure optimization and green technology progress, as well as a negative mechanism known as the energy rebound effect. Lastly, the analysis of heterogeneity indicates that the BE exerts a more substantial influence on CEE in regions characterized by robust government governance, younger officials, and highly educated officials. These findings offer valuable insights for local governments seeking to leverage the BE to enhance energy efficiency and foster sustainable development. Business environment Carbon emission efficiency Industrial structure optimization Green technology progress Energy rebound effect Full Text Supplementary Files GraphicalAbstract.pdf Cite Share Download PDF Status: Published Journal Publication published 04 Mar, 2024 Read the published version in Environmental Science and Pollution Research → Version 1 posted Editorial decision: Major Revision 27 Jan, 2024 Reviewers agreed at journal 29 Dec, 2023 Reviewers invited by journal 29 Dec, 2023 Editor assigned by journal 06 Dec, 2023 First submitted to journal 29 Nov, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3688268","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":264346513,"identity":"cf50da61-312b-49bd-ba4a-c02a0b40cc84","order_by":0,"name":"Peiyu Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYBADOfvjjY0PP5CixZjhzOFmYwlStCQ23EhvE+AhRqk5+9mDjyvbDic2znzYxiDBYCen20BAi2VPXrLh2bbDxs3SiW0PChiSjc0OENBicCDHTLKx7bBsm3Riu4EEw4HEbQS1nH9j/hOohbFH8mCbBA9RWm7kmDECtSjOkGAkUovljHfJkg3n0o0NeBKBgWxAhF/M+XMPfmwos5YzYD/+8OGHCjs5wt5nAMYFIxuCSxiAtTD8IULlKBgFo2AUjFwAAIWmRWHWSyx6AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0002-3279-4661","institution":"Shandong University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Peiyu","middleName":"","lastName":"Li","suffix":""},{"id":264346514,"identity":"6d6dbd33-b919-4253-8888-49421df10109","order_by":1,"name":"Xinzhi Liu","email":"","orcid":"","institution":"Southwest University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xinzhi","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2023-11-30 17:43:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3688268/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3688268/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11356-024-32694-3","type":"published","date":"2024-03-04T15:01:29+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52432227,"identity":"62b873ab-ce69-4504-95f3-6f98784a1e1f","added_by":"auto","created_at":"2024-03-11 15:11:36","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":560467,"visible":true,"origin":"","legend":"","description":"","filename":"Researchpapers.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3688268/v1_covered_c3f02efb-e268-45b6-bcb5-b662dcece1d9.pdf"},{"id":49037016,"identity":"8ac8eff1-500d-418b-94a8-57f8f2686cea","added_by":"auto","created_at":"2024-01-02 02:58:46","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":177889,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3688268/v1/3e5d91c8ac80804934d9c2c3.pdf"}],"financialInterests":"","formattedTitle":"Does Business Environment Optimization Improve Carbon Emission Efficiency? Evidence from Provincial Panel Data in China","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"
[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Business environment, Carbon emission efficiency, Industrial structure optimization, Green technology progress, Energy rebound effect","lastPublishedDoi":"10.21203/rs.3.rs-3688268/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3688268/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePrevious research has yielded varied conclusions regarding the effect of business environment (BE) optimization to improve carbon emission efficiency (CEE). In this study, CEE and BE are assessed using energy consumption and economic growth data from 30 provinces in China. The research employs fixed effects, quantile, and mediation effect models to analyze the direct impact, nonlinear characteristics, mechanism, and heterogeneity of BE on CEE. The research found that. Firstly, the BE optimization enhances CEE, with a 1% increase leading to a 0.095% improvement in CEE. Secondly, the influence of the BE on CEE exhibits marginal diminishing traits that decline as CEE improves. Thirdly, the analysis of mechanisms reveals that the BE primarily impacts CEE through positive mechanisms such as industrial structure optimization and green technology progress, as well as a negative mechanism known as the energy rebound effect. Lastly, the analysis of heterogeneity indicates that the BE exerts a more substantial influence on CEE in regions characterized by robust government governance, younger officials, and highly educated officials. These findings offer valuable insights for local governments seeking to leverage the BE to enhance energy efficiency and foster sustainable development.\u003c/p\u003e","manuscriptTitle":"Does Business Environment Optimization Improve Carbon Emission Efficiency? Evidence from Provincial Panel Data in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-02 02:58:41","doi":"10.21203/rs.3.rs-3688268/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revision","date":"2024-01-27T14:10:58+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2023-12-29T13:21:28+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-12-29T09:50:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-12-06T05:18:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Science and Pollution Research","date":"2023-11-29T07:23:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"
[email protected]","identity":"environmental-science-and-pollution-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"espr","sideBox":"Learn more about [Environmental Science and Pollution Research](https://www.springer.com/journal/11356)","snPcode":"11356","submissionUrl":"https://submission.nature.com/new-submission/11356/3","title":"Environmental Science and Pollution Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"300acab7-83b7-44e6-a432-0d010fdac0bb","owner":[],"postedDate":"January 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-03-11T15:09:16+00:00","versionOfRecord":{"articleIdentity":"rs-3688268","link":"https://doi.org/10.1007/s11356-024-32694-3","journal":{"identity":"environmental-science-and-pollution-research","isVorOnly":false,"title":"Environmental Science and Pollution Research"},"publishedOn":"2024-03-04 15:01:29","publishedOnDateReadable":"March 4th, 2024"},"versionCreatedAt":"2024-01-02 02:58:41","video":"","vorDoi":"10.1007/s11356-024-32694-3","vorDoiUrl":"https://doi.org/10.1007/s11356-024-32694-3","workflowStages":[]},"version":"v1","identity":"rs-3688268","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3688268","identity":"rs-3688268","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.