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