Multilevel regresion between supply chain 4.0 and environmental performance in large Brazilian companies

Multilevel regresion between supply chain 4.0 and environmental performance in large Brazilian companies | 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 Multilevel regresion between supply chain 4.0 and environmental performance in large Brazilian companies Mike Militello, Patrícia Belfiore Fávero, Luiz Paulo Fávero This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8585345/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 13 You are reading this latest preprint version Abstract Supply chain 4.0 refers to the application of industry 4.0 in the context of the supply chain, and few studies have explored its impacts. The objective of this study is to evaluate the association between the use of digital technologies in the supply chain and its respective environmental performance. A sample of companies from different sectors, and indicators of use of digital technologies in supply chain, and of environmental performance (in case, solid waste disposal) were defined. With the data collected, factor analysis was applied to decrease the number of variables related to the use of digital technologies. To test the formulated hypotheses, linear multilevel regressions, with three levels, were subsequently performed. The results revealed four groups of digital technologies, and only one group was associated with a decrease in environmental performance. In addition, all the contingencies considered (sector, sector’s technological intensity, and tier) represented a small positive moderate effect on the investigated relationships. From a theoretical point of view, the results respond to the association between the use of digital technologies and solid waste disposal. From a practical point of view, the results can help professionals prioritize groups of digital technologies for implementation and internal training according to the desired performance. digital technologies supply chain multilevel regression environmental performance Full Text Additional Declarations No competing interests reported. Supplementary Files DatasetTableA.docx DatasetTableB.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 07 May, 2026 Reviews received at journal 01 May, 2026 Reviews received at journal 29 Apr, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviewers agreed at journal 27 Apr, 2026 Reviews received at journal 02 Mar, 2026 Reviewers agreed at journal 18 Feb, 2026 Reviews received at journal 02 Feb, 2026 Reviewers agreed at journal 02 Feb, 2026 Reviewers invited by journal 29 Jan, 2026 Editor assigned by journal 16 Jan, 2026 Submission checks completed at journal 16 Jan, 2026 First submitted to journal 12 Jan, 2026 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. 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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-8585345","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":581875774,"identity":"2d29db6d-0a98-4e43-8626-73e277d6de63","order_by":0,"name":"Mike 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