Yanli Meng, Li Wang, Francisco Chiclana, Haijun Yang, Sha Wang
{"title":"A dynamic cost compensation mechanism driven by moderator preferences for group consensus in lending platforms","authors":"Yanli Meng, Li Wang, Francisco Chiclana, Haijun Yang, Sha Wang","doi":"10.1007/s10479-024-06424-4","DOIUrl":null,"url":null,"abstract":"<div><p>The matching service the lending platform (moderator) provides acts as a facilitative conduit for reaching a loan consensus, facilitating agreements among multiple lenders and borrowers (decision makers). In light of the reality that decision-makers exhibit varying sensitivities to compensation expectations in response to opinion adjustment, the moderator’s demonstration of a preferred compensation mechanism determines the efficiency of the matching service. This article proposes a dynamic cost compensation mechanism driven by moderator preferences for group consensus in lending platforms. Firstly, the utility function describes adjusters’ preferences, defining three unit cost compensation preferences: Power-type I, II and right-partial S-shaped preferences. Subsequently, we construct a generalized dynamic minimum-cost consensus decision model to determine the optimal unit compensation strategies within the opinion interval delineated by the moderator. For the likelihood of equitable concerns arising from fluctuations in unit compensation costs, we enforce the fairness of the compensation strategy by incorporating the Gini coefficient as a constraint within the consensus model. To validate the effectiveness and applicability of the proposed models, we apply the proposed models to online lending utilizing data obtained from an online peer-to-peer lending platform.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"347 3","pages":"1425 - 1454"},"PeriodicalIF":4.4000,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Operations Research","FirstCategoryId":"91","ListUrlMain":"https://link.springer.com/article/10.1007/s10479-024-06424-4","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
The matching service the lending platform (moderator) provides acts as a facilitative conduit for reaching a loan consensus, facilitating agreements among multiple lenders and borrowers (decision makers). In light of the reality that decision-makers exhibit varying sensitivities to compensation expectations in response to opinion adjustment, the moderator’s demonstration of a preferred compensation mechanism determines the efficiency of the matching service. This article proposes a dynamic cost compensation mechanism driven by moderator preferences for group consensus in lending platforms. Firstly, the utility function describes adjusters’ preferences, defining three unit cost compensation preferences: Power-type I, II and right-partial S-shaped preferences. Subsequently, we construct a generalized dynamic minimum-cost consensus decision model to determine the optimal unit compensation strategies within the opinion interval delineated by the moderator. For the likelihood of equitable concerns arising from fluctuations in unit compensation costs, we enforce the fairness of the compensation strategy by incorporating the Gini coefficient as a constraint within the consensus model. To validate the effectiveness and applicability of the proposed models, we apply the proposed models to online lending utilizing data obtained from an online peer-to-peer lending platform.
期刊介绍:
The Annals of Operations Research publishes peer-reviewed original articles dealing with key aspects of operations research, including theory, practice, and computation. The journal publishes full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies that present new and innovative practical applications.
In addition to regular issues, the journal publishes periodic special volumes that focus on defined fields of operations research, ranging from the highly theoretical to the algorithmic and the applied. These volumes have one or more Guest Editors who are responsible for collecting the papers and overseeing the refereeing process.