Predicting Product Information Diffusion for Sustainable Quality Management in Industry 4.0: An Improved Bass Model Approach

Predicting Product Information Diffusion for Sustainable Quality Management in Industry 4.0: An Improved Bass Model Approach | 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 Article Predicting Product Information Diffusion for Sustainable Quality Management in Industry 4.0: An Improved Bass Model Approach Zhongya Han, Xiangtang Chen, Kepao Miao, Xiaoxiang Wang, Qinlin Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6062903/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract In the context of Industry 4.0, the accurate prediction of product information popularity is essential for optimizing marketing strategies and achieving sustainable business growth. While the traditional Bass model has been widely used in diffusion studies, it often fails to account for user decision-making heterogeneity and the interest decay effect, which are critical in the dynamic digital environment. In this study, we propose an improved Bass model that addresses these limitations by incorporating a two-phase process framework. Specifically, we refine the market potential by integrating the decision-making processes of users who share information from diverse sources. Furthermore, we incorporate the interest decay effect into the model, relaxing the assumptions regarding influence coefficients. Experimental results show that our proposed model outperforms the Bass, exponential function improved, and power function improved models in predicting product information popularity. The impact of both internal and external factors on the diffusion of product information exhibits a decay effect, with internal factors also being subject to social pressure. These findings contribute to the development of data-driven approaches for sustainable quality management in Industry 4.0, offering valuable insights for optimizing digital marketing strategies and improving information diffusion efficiency on social media platforms. Physical sciences/Mathematics and computing Physical sciences/Mathematics and computing/Applied mathematics Physical sciences/Mathematics and computing/Statistics Industry 4.0 Product information diffusion The interest decay effect Improved Bass model Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 17 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 17 Apr, 2025 Reviews received at journal 13 Apr, 2025 Reviews received at journal 08 Apr, 2025 Reviewers agreed at journal 08 Apr, 2025 Reviewers agreed at journal 05 Apr, 2025 Reviewers agreed at journal 05 Apr, 2025 Reviewers invited by journal 05 Apr, 2025 Editor assigned by journal 04 Apr, 2025 Submission checks completed at journal 03 Apr, 2025 First submitted to journal 03 Apr, 2025 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. 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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-6062903","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":440363317,"identity":"ac456635-65c8-4b05-89e0-b91c66bfa180","order_by":0,"name":"Zhongya Han","email":"","orcid":"","institution":"Wenzhou University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Zhongya","middleName":"","lastName":"Han","suffix":""},{"id":440363318,"identity":"0110df67-e20b-49ff-aeb7-48c1c78f2aeb","order_by":1,"name":"Xiangtang Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYBAC+4bjBx9+qLBh5mdvIFKLAeOZZGOJM2nskj0HiNXCfMBMgLftML/BjAQitZizHUhjkGw7LG0g+XjjDYYam2iCWix7Dh57UHAu3dhcOq3YguFYWm4DQT03DqQbSJRZJ1vOzjGTYGw4TISW+w/MJHjYmOs33DxDpBaDAweAWtqcmQ1u8BCpRbIBEsjMkj1AvyQQ4xd+BnhUHt5440ONDRF+QXakRAIpyiFaSNUxCkbBKBgFIwMAAJrTQxJihvgnAAAAAElFTkSuQmCC","orcid":"","institution":"Wenzhou University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Xiangtang","middleName":"","lastName":"Chen","suffix":""},{"id":440363319,"identity":"17f41074-6407-40ea-abfe-4bb98c1919c8","order_by":2,"name":"Kepao Miao","email":"","orcid":"","institution":"Wenzhou University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Kepao","middleName":"","lastName":"Miao","suffix":""},{"id":440363320,"identity":"5187ed6d-464f-468e-bd87-72cc32122439","order_by":3,"name":"Xiaoxiang Wang","email":"","orcid":"","institution":"Wenzhou University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Xiaoxiang","middleName":"","lastName":"Wang","suffix":""},{"id":440363321,"identity":"9a43a699-ca66-4f92-9675-d03b938a2dd7","order_by":4,"name":"Qinlin Li","email":"","orcid":"","institution":"Wenzhou University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Qinlin","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-02-19 09:53:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6062903/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6062903/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-09129-1","type":"published","date":"2025-07-17T15:57:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88505965,"identity":"c37ff02c-7990-4433-8f8c-a591209ceebe","added_by":"auto","created_at":"2025-08-07 07:29:43","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":624675,"visible":true,"origin":"","legend":"","description":"","filename":"Revisedmanuscrip.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6062903/v1_covered_fde8d7ff-c0a9-456c-b5df-324daa50854f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predicting Product Information Diffusion for Sustainable Quality Management in Industry 4.0: An Improved Bass Model Approach ","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":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Industry 4.0, Product information diffusion, The interest decay effect, Improved Bass model","lastPublishedDoi":"10.21203/rs.3.rs-6062903/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6062903/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the context of Industry 4.0, the accurate prediction of product information popularity is essential for optimizing marketing strategies and achieving sustainable business growth. 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