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Being at the cutting edge of online shopping: Role of recommendations and discounts on privacy perceptions

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dc.contributor.authorVenkatesh, Viswanathen
dc.contributor.authorHoehle, Hartmuten
dc.contributor.authorAloysius, John A.en
dc.contributor.authorNikkhah, Hamid Rezaen
dc.date.accessioned2022-05-26T19:29:06Zen
dc.date.available2022-05-26T19:29:06Zen
dc.date.issued2021-08-01en
dc.date.updated2022-05-09T00:08:19Zen
dc.description.abstractDespite the explosion of selling online, customers continue to have privacy concerns about online purchases. To alleviate such concerns, shopping sites seek to employ interventions to encourage users to buy more online. Two common interventions used to promote online sales are: (1) recommendations that help customers choose the right product either based on historic purchase correlations or recommendations suggested by the retailer; and (2) discounts that increase the value of products. Building on privacy calculus, we theorize about how and why key, representative combinations of recommendations and discounts influence the effects of inhibitors and enablers on online purchase intention. Our research design incorporated recommendations coming from different sources for the recommendation (retailer and other customers’ preferences) product relatedness (related products with historic purchases correlated to the focal product and unrelated products with no historic purchase correlation to the focal product) and two types of discounts (regular and bundle). Participants completed a browsing task in a controlled online shopping environment and completed a survey (n = 496). We found mixed results of moderating effects of recommendations and product relatedness on the effect of inhibitors and enablers on purchase intention. Although recommendations did not enhance the effects of inhibitors, they did enhance the effects of enablers on online purchase intention. We also found that product relatedness did not enhance the effect of privacy enablers on online purchase intentions. The results also showed that discounts enhance the effects of enablers, and that discounts can counteract the moderating effect of recommendations on the relationship between inhibitors and purchase intention under certain circumstances. We discuss theoretical and practical implications.en
dc.description.notesSource info: Venkatesh, V., Aloysius, J.A., Hoehle, H., and Nikkhah, H. 'Being at the Cutting Edge of Online Shopping: Role of Recommendations and Discounts on Privacy Perceptions,' Computers in Human Behavior (121), 2021, 106785. https://doi.org/10.1016/j.chb.2021.106785en
dc.description.versionAccepted versionen
dc.format.extent17 page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifierARTN 106785 (Article number)en
dc.identifier.doihttps://doi.org/10.1016/j.chb.2021.106785en
dc.identifier.eissn1873-7692en
dc.identifier.issn0747-5632en
dc.identifier.orcidVenkatesh, Viswanath [0000-0001-8473-376X]en
dc.identifier.urihttp://hdl.handle.net/10919/110344en
dc.identifier.volume121en
dc.language.isoenen
dc.publisherPergamon-Elsevieren
dc.relation.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000651382100005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=930d57c9ac61a043676db62af60056c1en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectCALCULUS MODELen
dc.subjectCONSUMERS DECISIONen
dc.subjectDiscountsen
dc.subjectE-COMMERCEen
dc.subjectINFORMATION PRIVACYen
dc.subjectMODERATING ROLEen
dc.subjectNEURAL-NETWORKSen
dc.subjectPRICE DISCOUNTSen
dc.subjectPrivacy calculusen
dc.subjectPrivacy paradoxen
dc.subjectPsychologyen
dc.subjectPsychology, Experimentalen
dc.subjectPsychology, Multidisciplinaryen
dc.subjectRecommendation agentsen
dc.subjectRecommendation systemsen
dc.subjectSALES PROMOTIONen
dc.subjectSELF-DISCLOSUREen
dc.subjectSOCIAL NETWORKING SITESen
dc.subjectSocial Sciencesen
dc.titleBeing at the cutting edge of online shopping: Role of recommendations and discounts on privacy perceptionsen
dc.title.serialComputers in Human Behavioren
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherArticleen
dcterms.dateAccepted2021-03-11en
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Pamplin College of Businessen
pubs.organisational-group/Virginia Tech/Pamplin College of Business/Business Information Technologyen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Pamplin College of Business/PCOB T&R Facultyen

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