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Analyzing the Spillover Roles of User Generated Online...
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AnalyzingtheSpilloverRolesofUser-GeneratedOnlineProductReviewsonPurchases:
EvidencefromClickstreamData
YoungKwark*,GeneMooLee**,PaulA.Pavlou***,andLiangfeiQiu*
*UniversityofFlorida,**UniversityofTexasatArlington,***TempleUniversity
Abstract:Onlineproductreviewsareincreasinglyimportantforshapingconsumerpurchasingdecisions.
In this study,using clickstream data, we examine the spillover roles of online product reviews on
consumer purchasing acrosssubstitute versus complementary products byleveragingtext to quantify
the similarity of pairwise products. We also investigate how product characteristics (e.g., niche
product)andthechannel(whethertheproductreviewisviewedonamobiledeviceoraPC)moderate
the proposed spillover roles.Our study hasmanagerialimplications on how to leverage the spillover
rolesofonlineproductreviewsonsubstitute/complementaryproducts.
Keywords:Spilloverroles,Onlineproductreviews,Substituteproducts,Complementaryproducts
Introduction
Onlineproductreviewshavereceivedmuchinterestfromacademicsandpractitionersalike.Thisis
becauseconsumersdorelyonthereviewsdeliveredbyotherconsumerstoreduceproductuncertainty
(e.g.,Dimoka,Hong,Pavlou2012;HongandPavlou2014).Previousstudieslargelyfocusedontheeffect
ofonlineproductreviewsonaggregateproductdemand(e.g.,Archaketal.,2011;Formanetal.,2008;
Goesetal.,2014),and,ingeneral,theyshowedtheinfluentialeffectofonlineproductreviewson
consumerpurchasingdecisions(e.g.,ChevalierandMayzlin2006;Hu,Pavlou,andZhang2009;Zhuand
Zhang2010).However,theliteratureexclusivelyfocusedontheeffectofonlineproductreviewsona
singleproduct,ignoringtheir“spillover”roleonotherproducts.Extendingtheliterature,weuse
clickstreamdatatoexaminethespilloverroleofonlineproductreviewsinconsumerpurchasing
decisionsforsubstitute/complementaryproducts.Wealsoexaminehowproductcharacteristicsand
channelmediamoderatethespilloverroleofonlineproductreviewsonotherrelatedproducts.
Clickstreamdatafromconsumerswhoshoponaretailer’swebsiteallowustoobservecompleterecords
ofonlineproductreviewsconsumersviewed,enablingustoclearlydefineaconsumer’sconsideration
setandexaminewhethertheonlinereviewsforafocalproducttheconsumerviewedaffecther
likelihoodofpurchasingotherproductsofthesamebrand,and/orpurchasingcompetingproductsofa
differentbrand.Weaimtoanswertworesearchquestions:(1)Howdotheonlinereviewsofafocal
productaffecttheprobabilityofaconsumerpurchasingcompetingproducts?(2)Howdoproduct
characteristics(e.g.,nicheproducts),competitionintensity(e.g.,complementaryversuscompeting
products),andchannelmedia(e.g.,mobileorPC)moderatetheroleoftheonlinereviewsofafocal
productoncompetingproducts?
At the core of our study is the notion of “competing products.” And defining competing products in
practice is not trivial.We leverage consumer co-visitswith a textmining algorithm. If consumers co-
visitedapairofproductsinasession,wecaninferthoseproductstobe“related.”Weuseatextmining
algorithmoftopicmodelingonproductdescriptionstoquantifythesimilarityofpairwiseproducts.Once
webuildvarioussimilaritymeasuresamongproducts,wecanestimate thecompetitionorhaloeffect
with respect to different similarity levels. For example, if two products are almost identical in text
similarity,wemayobserve stronger spillovereffects. Inotherwords,wecanquantify the intensityof
productcompetition.
Data
DataarecollectedfromaUK-basedbigboxretailer,andtheycontainindividuallevelclickstreamdatafor
250,000 consumers, includingwebsite visits, product page views, reviews read, and purchasesmade.
Consumers’viewsandtransactionsontheretailer’swebsiteweretrackedoverthetwomonths intwo
productcategoriesof“Technology”and“Home&Garden.”
Analysis
Toexaminethespilloverroleoftheonlineproductreviewsonthefocalproduct,weconsiderapair-wise
relationshipofthefocalproductandtheotherproductsinaconsumer’schoiceset.Thekeyvariablesof
fourtypesoftheotherproductsandfocalproductsaredescribedasfollows.
Table1.KeyVariablesinResearchModel
Wepresentourpreliminaryresultsbelow:
(1) Baselineestimation:SubstitutesVs.Complements
Inthefirstsetofregressionmodels,wedonotdifferentiatebetweensubstitutesproducedbythe
samebrandordifferentbrands.Thedependentvariableispurchase,andtheindependentvariablesare
rate_focal,vol_focal,rate_subs,andrate_comp.Amongthepairsofproductsconsumersco-visitedina
session,wemeasure thesimilaritymeasuresgeneratedby topicmodeling. If similarity isgreater than
0.8,wecallthemsubstitutes;ifthevalueissmallerthan0.2,wecallthemcomplements.Theresultsare
robusttodifferentthresholdsofsimilarity.
Weuse fixed effectsmodels to control for unobserved individual heterogeneity and all standard
errorsareclusteredinconsumers.Thebaselineresultisthatthecoefficientonrate_subsisnegativeand
significant,whilethecoefficientonrate_compispositiveandsignificant,consistentwithourintuitionon
substitutesandcomplements(Column1inTable2).
Table2.TheSpilloverRolesofOnlineProductReviews(“Home”Category)
(2) Substitutesvs.ComplementsofSamevs.DifferentBrands
In the next estimation, the dependent variable is purchase, and the independent variables are
rate_focal, vol_focal, price_focal, rate_subs_samebrand, rate_comp_samebrand, rate_subs_diffbrand,
andrate_comp_diffbrand.Ourbasicfindingsareasfollows(Column2inTable2):(1)thefocalproduct
ratingandthe focalproduct reviewvolumehaveapositive impactonpurchasesof the focalproduct.
Price has a negative impact. (2) rate_subs_diffbrand has a larger negative impact than
rate_subs_samebrand. The implication is that the negative spillover role of the online reviews of
substitute products from different brands is greater than that of the same brand. (3)
rate_comp_diffbrand has a largerpositive impact than rate_comp_samebrand. The implication is that
thepositivespilloverroleofonlinereviewsofsubstituteproductsfromdifferentbrandsisgreaterthan
thatof thesamebrand.Summarizing (2)and(3),weshowthat themagnitudeof thespilloverroleof
onlineproductreviewscriticallydependson(a)whethertheproductisasubstituteoracomplement;(b)
whethertheproduct isproducedbythesamebrandoradifferentbrand.Theresultsarequalitatively
consistentinbothcategories(home&technology).
(3) ModeratingEffects
Weexaminehowthespilloverrole(differentbrands)orhalorole(samebrands)ismoderatedbyother
factors,suchasproductcharacteristics,specifically theproductbeinga“niche”one(measuredbythe
volumeofreviewsorpurchases)andchannelmedia(measuredbythedeviceusedtoviewproducts---
mobileorPC).Wefindthatthenegativeimpactoftheonlinereviewsforsubstituteproductsisstronger.
ConcludingRemark
Using clickstream data, we investigate the "spillover” role of online product reviews on competing
products at the individual consumer level. This study will provide managerial implications for
practitioners to better leverage online product reviews by shedding light on spillover role of product
reviewsandhelpingthedesignofonlineproductreviewsystems.
REFERENCESAVAILABLEUPONREQUEST