Publication:
Managing consumer returns with technology-enabled countermeasures

dc.contributor.coauthorAktürk, M. Serkan
dc.contributor.coauthorKetzenberg, Michael
dc.contributor.departmentDepartment of Industrial Engineering
dc.contributor.kuauthorYıldız, Barış
dc.contributor.kuprofileFaculty Member
dc.contributor.otherDepartment of Industrial Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.yokid258791
dc.date.accessioned2024-11-09T23:13:37Z
dc.date.issued2021
dc.description.abstractThis paper examines retail return abuse with respect to both opportunistic and fraudulent consumer behavior. The decisions of interest are the retailer's price for purchases and refund amount for returns. Our analysis provides managerial insight into how a retailer makes these decisions to mitigate return abuse. Including both forms of return abuse in a base model, we find that there is an interaction effect that meaningfully changes a retailer's optimal decisions and profit, from what would be observed if only opportunism was present. We also evaluate two innovative technology-enabled countermeasures designed to mitigate return abuse: customer profiling and product tracking. A customer profiling system identifies opportunistic customers by using their personal identification and transaction history. In contrast, a product tracking system identifies fraudulent returns by recording each transaction of a product through the use of unique identifiers. We develop prescriptive models for these technologies and investigate the value of making such investments. Our analyses demonstrate the conditions in which it is advantageous to adopt these technologies and when such investments should be avoided. We find that when a retailer is able to charge restocking fees, it is well equipped to mitigate opportunism and fraud with only its price and refund decisions. Hence, the value of consumer profiling and product tracking technologies is limited. However, when a retailer is constrained to offer a full refund due to market dynamics, employing these technologies may hold significant value. Our analysis details the determinants of value, model sensitivity, and comparisons between models. We also address how these countermeasures impact a retailer's profitability, demand structure, and decisions with respect to price and refund amount.
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.openaccessNO
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume102
dc.identifier.doi10.1016/j.omega.2020.102337
dc.identifier.eissn1873-5274
dc.identifier.issn0305-0483
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-85091225591
dc.identifier.urihttp://dx.doi.org/10.1016/j.omega.2020.102337
dc.identifier.urihttps://hdl.handle.net/20.500.14288/10017
dc.identifier.wos640926400001
dc.keywordsReturn Abuse
dc.keywordsOpportunism
dc.keywordsRetail Fraud
dc.keywordsReturn Policy Product Returns
dc.keywordsPolicies
dc.keywordsRetailer
dc.keywordsImpact
dc.languageEnglish
dc.publisherPergamon-Elsevier Science Ltd
dc.sourceOmega-International Journal of Management Science
dc.subjectManagement
dc.subjectOperations Research Management Science
dc.titleManaging consumer returns with technology-enabled countermeasures
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.authorid0000-0002-3839-8371
local.contributor.kuauthorYıldız, Barış
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relation.isOrgUnitOfPublication.latestForDiscoveryd6d00f52-d22d-4653-99e7-863efcd47b4a

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