Collaborative decision-making research on customized cultural and creative products considering regret avoidance and fairness degree

preprint OA: closed CC-BY-4.0
📄 Open PDF Full text JSON View at publisher

Abstract

Abstract Cultural and creative products(CCPs) have gained significant popularity, with platforms like Amazon experiencing notable growth in such customized product sales. However, a mismatch existing in between consumers' cultural and spiritual needs and the supply of CCPs causes reduced consumer satisfaction, weak market demand, and resource waste, among other effects. To address this, we propose a bilateral matching approach that incorporates regret-averse psychological behaviors and personalized needs of consumers. We calculate consumers' willingness to purchase CCPs based on personalized demand weights and manufacturer evaluations. To enhance matching accuracy, we introduce a difference coefficient to refine the fuzzy representations of both parties, amplifying their differences. We then establish a stable, goal-oriented matching model aimed at maximizing satisfaction for both parties, incorporating fairness to improve the model. We analyze three matching scenarios: focusing on satisfaction, fairness, and both satisfaction and fairness. Our findings indicate that the regret-avoidance coefficient and fairness weight are crucial factors influencing the matching outcome. Effective bilateral matching between CCPs and consumers involves aligning preferences with product characteristics and dynamically adjusting fairness and satisfaction weights for long-term optimization. Finally, we validate the effectiveness and feasibility of our model using real data from the Shanghai Museum online gift shop. JEL:C44;D11;D16;M11
Full text 10,651 characters · extracted from preprint-html · click to expand
Collaborative decision-making research on customized cultural and creative products considering regret avoidance and fairness degree | 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 Collaborative decision-making research on customized cultural and creative products considering regret avoidance and fairness degree Qinyu Song, Panpan Zhu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7106095/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Cultural and creative products(CCPs) have gained significant popularity, with platforms like Amazon experiencing notable growth in such customized product sales. However, a mismatch existing in between consumers' cultural and spiritual needs and the supply of CCPs causes reduced consumer satisfaction, weak market demand, and resource waste, among other effects. To address this, we propose a bilateral matching approach that incorporates regret-averse psychological behaviors and personalized needs of consumers. We calculate consumers' willingness to purchase CCPs based on personalized demand weights and manufacturer evaluations. To enhance matching accuracy, we introduce a difference coefficient to refine the fuzzy representations of both parties, amplifying their differences. We then establish a stable, goal-oriented matching model aimed at maximizing satisfaction for both parties, incorporating fairness to improve the model. We analyze three matching scenarios: focusing on satisfaction, fairness, and both satisfaction and fairness. Our findings indicate that the regret-avoidance coefficient and fairness weight are crucial factors influencing the matching outcome. Effective bilateral matching between CCPs and consumers involves aligning preferences with product characteristics and dynamically adjusting fairness and satisfaction weights for long-term optimization. Finally, we validate the effectiveness and feasibility of our model using real data from the Shanghai Museum online gift shop. JEL: C44;D11;D16;M11 cultural and creative products personalization bilateral matching regret avoidance Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-7106095","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":486006343,"identity":"49213098-ac68-415f-98ac-8de12e560eec","order_by":0,"name":"Qinyu Song","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYBAC+QYwZcO4AUTxEKPF4ACYSiNFC4Q6TIoW9t7DL962nZfdLpHA+OBtG4O8OSEt8j3n0izntt023jkjgdlwbhuD4c4GQnpu5JgZ87bdTtxwI4FNmreNIQHqO4JazoG0sP8mVovxY962A2BbmInSYnDmjBnjnHPJxhvOPGyWnHNOwnADIS3y7T3GH96U2cluOJ58EMiwkSfsMAYGNgleNhDN2AAkJAirBwLmDzx/iFI4CkbBKBgFIxUAAAtmRW78sFuKAAAAAElFTkSuQmCC","orcid":"","institution":"Donghua University","correspondingAuthor":true,"prefix":"","firstName":"Qinyu","middleName":"","lastName":"Song","suffix":""},{"id":486006344,"identity":"3054798f-84e3-49de-a427-db8a72d9156c","order_by":1,"name":"Panpan Zhu","email":"","orcid":"","institution":"Donghua University","correspondingAuthor":false,"prefix":"","firstName":"Panpan","middleName":"","lastName":"Zhu","suffix":""}],"badges":[],"createdAt":"2025-07-12 06:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7106095/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7106095/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91221378,"identity":"b8b526f6-0409-4113-8eb1-3b01b8dddf2a","added_by":"auto","created_at":"2025-09-12 22:16:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":871391,"visible":true,"origin":"","legend":"","description":"","filename":"Collaborativedecisionmakingresearchoncustomizedculturalandcreativeproductsconsideringregretavoidanceandfairnessdegree.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7106095/v1_covered_219682ae-efc8-4427-80e5-7c135400202b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Collaborative decision-making research on customized cultural and creative products considering regret avoidance and fairness degree","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"cultural and creative products, personalization, bilateral matching, regret avoidance","lastPublishedDoi":"10.21203/rs.3.rs-7106095/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7106095/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCultural and creative products(CCPs) have gained significant popularity, with platforms like Amazon experiencing notable growth in such customized product sales. However, a mismatch existing in between consumers' cultural and spiritual needs and the supply of CCPs causes reduced consumer satisfaction, weak market demand, and resource waste, among other effects. To address this, we propose a bilateral matching approach that incorporates regret-averse psychological behaviors and personalized needs of consumers. We calculate consumers' willingness to purchase CCPs based on personalized demand weights and manufacturer evaluations. To enhance matching accuracy, we introduce a difference coefficient to refine the fuzzy representations of both parties, amplifying their differences. We then establish a stable, goal-oriented matching model aimed at maximizing satisfaction for both parties, incorporating fairness to improve the model. We analyze three matching scenarios: focusing on satisfaction, fairness, and both satisfaction and fairness. Our findings indicate that the regret-avoidance coefficient and fairness weight are crucial factors influencing the matching outcome. Effective bilateral matching between CCPs and consumers involves aligning preferences with product characteristics and dynamically adjusting fairness and satisfaction weights for long-term optimization. Finally, we validate the effectiveness and feasibility of our model using real data from the Shanghai Museum online gift shop.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJEL:\u003c/strong\u003eC44;D11;D16;M11\u003c/p\u003e","manuscriptTitle":"Collaborative decision-making research on customized cultural and creative products considering regret avoidance and fairness degree","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-17 14:47:37","doi":"10.21203/rs.3.rs-7106095/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65ceb7ae-6462-426f-b5b3-984ee41e9bb0","owner":[],"postedDate":"July 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-12T22:08:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-17 14:47:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7106095","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7106095","identity":"rs-7106095","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","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.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: preprint-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
unpaywall
last seen: 2026-05-22T02:00:06.705733+00:00
License: CC-BY-4.0