Customer Classification and Decision Making in the Digital Economy based on Scoring Models

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dc.contributor.authorHENNADII MAZUR
dc.contributor.authorNATALIA BURKINA
dc.contributor.authorYURII POPOVSKYI
dc.contributor.authorNADIIA VASYLENKO
dc.contributor.authorVOLODYMYR ZAIACHKOVSKYI
dc.contributor.authorRUSLAN LAVROV
dc.contributor.authorSERHII KOZLOVSKYI
dc.date.accessioned2024-11-18T07:50:51Z
dc.date.available2024-11-18T07:50:51Z
dc.date.issued2023-04-06
dc.description.abstractThe article presents the way of applying cluster models to customer classification and managerial decision on retaining the available clients and acquiring new ones. The objective of the research is to find out the relevant techniques for building scoring models in different fields. The main research was testing the hypothesis: if the number of point models is approximated in different spheres of activity, then the proposed methods will be universal. To check this hypothesis the vector method of k-nearest neighbors support was applied for decision making in the digital economy based on scoring models. In order to realize the principle of customer classification and revealing the client categories with risk of quitting, the client’s classification model was created. Moreover, a risk issue was shown in the example of fraud dynamic. Different fraud categories were studied to define their features. On the basis of the model building results, the authors proposed some recommendations on decision making in risk situations. The model shows how to retain existing clients and how to share client base through the client groups and how to deal with risks of losing clients.
dc.identifier.urihttps://r2.donnu.edu.ua/handle/123456789/3402
dc.language.isoen
dc.publisherКонстанца: Technium Social Sciences Journal
dc.relation.ispartofseries2023. Volume 20, P. 800-814
dc.subjectModellingeng
dc.subjectdecision makingeng
dc.subjectalgorithmseng
dc.subjectscoring modelseng
dc.subjectcustomer classificationeng
dc.subjectdigital economyeng
dc.subjectcluster analysiseng
dc.titleCustomer Classification and Decision Making in the Digital Economy based on Scoring Models
dc.typeArticle
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