PostdoctoralResearcherTexasAMUniversity2020presentEDUCATION PhDinEconomicsUniversityofSouthernCalifornia2020MAinEconomicsUniversityofSouthernCalifornia2016BAinMathandEconomicsUniversityof ID: 831209
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JisuCao(+1)6083586046jcao@tamu.eduTe
JisuCao(+1)6083586046jcao@tamu.eduTexasA&MUniversity4113TAMU,430BWehner,CollegeStation,TX77843-4113EMPLOYMENTPost-doctoralResearcher,TexasA&MUniversity2020-presentEDUCATIONPh.D.inEconomics,UniversityofSouthernCalifornia2020M.A.inEconomics,UniversityofSouthernCalifornia2016B.A.inMathandEconomics,UniversityofWisconsin{Madison2013RESEARCHFIELDSQuantitativeMarketing,EmpiricalIndustrialOrganizationTopics:DailyDealE-commerce,User-generatedContent,SocialMediaDISSERTATIONConsumerPurchaseTimingandProductReturnsinDailyDealE-commerceCommitteeMembers:ShaYang(Marketing,Co-Chair),GeertRidder(Economics,Co-Chair),Yu-WeiHsieh(Economics),FannyCamara(Economics),andGuofuTan(Economics)WORKINGPAPERSUnderstandingtheImpactofMulti-dimensionalReviewsonSales:DistinguishingbetweenMainstreamandNicheProducts,withXinZheng,XingyaoRen,YiliHong,andShaYang,under3rdroundreviewatMISQuarterlyCanReviewsHelpConsumersGetaBetterDeal?withShaYang,submittedAWARDSANDHONORSBestThemePaper,InternationalConferenceonInformationSystems2018InstituteforNewEconomicThinkingFellowship,USC2017-2018SummerResearchAward,USC2017,2018,2019BestThird-YearPaperAward,USC2017DornsifeCollegeGraduateMeritAward,USC2014-2019CONFERENCE/SEMINARPRESENTATIONSUSC;ICIS2018USC;LACAE;TexasA&M(Mays);UIUC(Gies);UniversityofDelaware(Lerner);Temple(Fox);HKU;Fudan;PKU(GSM);SHUFE;Tongji2019ISMS;WEAI2020EXPERIENCEResearchAssistantTheCenterforEconomicandSocialResearch(CESR)2016TeachingAssistantECON484(Graduate):EconomicConsultingandAppliedEconometrics2016-2017ECON474(Undergraduate):EconomicConsultingandAppliedManagerialEconomics2016-2017ECON317(Undergraduate):IntroductiontoStatistics2015-2016,2019-2020SKILLSLanguagesMandarinChinese,EnglishProgrammingLanguagesR,Stata,Mathematica,Matlab,PythonREFERENCESProf.ShaYang(Co-Chair)Prof.GeertRidder(Co-Chair)D
epartmentofMarketingDepartmentofEconomic
epartmentofMarketingDepartmentofEconomicsUniversityofSouthernCaliforniaUniversityofSouthernCaliforniashayang@marshall.usc.eduridder@usc.eduProf.Yu-WeiHsiehDepartmentofEconomicsUniversityofSouthernCaliforniayuwei.hsieh@usc.eduABSTRACTSConsumerPurchaseTimingandProductReturnsinDailyDealE-commerceJobMarketPaperTheobjectiveofthispaperistostudyconsumerpurchasetimingandproductreturnsfordailydeale-commercewhereproductsareoftensoldinashortwindowoftime(usuallyonetothreedays).LeveragingauniqueproprietarydatasetfromaleadingChinesedailydealwebsite,wendtwointerestingpatterns:(1)consumersgenerallybuyearlierratherthanlaterinsalesevents;and(2)productreturnratesarehigherforconsumerswhopurchaseearlier.Theseempiricalpatternsmaysuggestapotentialproblemfordailydealmerchants:asalespromotiontoencourageconsumerstobuyearliermayactuallyincreasetheirreturnprobabilitiesandpossiblyhurtprots.Tounderstandsuchtradeo s,wedevelopanintegrativemodelofconsumerpurchasetimingandproductreturndecisions.Inapost-purchasestage,consumerknowledgeoftheproducttgetsrealized,andtheconsumercanreturntheproductatsomecost.Inapurchase(order)stage,theconsumerdecidestopurchasebasedonherexpectedutilityconsideringthereturnprobability.Aforward-lookingconsumersolvesanoptimalstoppingproblemforanite-periodgametodecidewhentopurchaseindicatespaperwaspresentedbyco-authors2inasalesevent.Delayingthepurchaseallowsconsumerstoseenewlypostedo ersandtohavemoretimetoconsidertheirpurchases.Weestimateourstructuralmodelbasedonsamplepaneldataofthepurchaseandreturnhistoriesof5,000consumersofwomen'sclothingfromJanuarytoJune2017.Wendthattheproposedmodeltsthedatawellandthatcompetitionsignicantlyincreasestheprobabilitythataconsumerwillbuylater.Inthecounterfactualanalysis,weadjusttheproductpriceoverdaysofasaleseventand
comparethemerchants'protsunderdi
comparethemerchants'protsunderdi erentpricingschedules.Ourcounterfactualresultsrevealimportantmanagerialinsightsthatcanhelpdailydealmerchantsselectapricingscheduletoimproveprot.UnderstandingtheImpactofMulti-dimensionalReviewsonSales:DistinguishingbetweenMainstreamandNicheProducts,withXinZheng,XingyaoRen,YiliHong,andShaYang,under3rdroundreviewatMISQuarterlyAwarded\BestThemePaper"atthe2018InternationalConferenceonInformationSystemsTohelpconsumersevaluateproductsthatoftendi eralongmultipledimensions,manyonlinereviewplatformshavestartedtoimplementmulti-dimensionalratingsystemsinadditiontotheoverallproductrating.Inanattempttoreconcilethemixedndingsinpreviousstudiesone ectsofratingvariance,weextendtheperspectivefromasingleoverallratingtomulti-dimensionalratingsanddecomposethevarianceofmulti-dimensionalratingsintotwotypes:inter-dimensionalandintra-dimensionalratingvariance.Wendthatdi erentcontextualfactors(producttype:mainstreamandniche;productdimensiontype:verticalandhorizontal)moderatethee ectsofinter-andintra-dimensionalratingvarianceonproductsales.Weconductthreecomplementarystudiesintwoproductcategories(i.e.,automobileandlaptop)withdi erentmethods(paneldataanalysesofauniqueproprietarydatasetcombiningmulti-dimensionalratinginformationon384carmodelswiththeircorrespondingmonthlysales,andtwolabexperiments).Ourpaperrevealsthreekeyinsightsinthissetting:a)thee ectoftheinter-dimensionalratingvarianceonproductsalesismorenegativewhentheproductisforamainstreammarketthanwhenitisforanichemarket;b)thee ectoftheintra-dimensionalratingvarianceonproductsalesismorenegativewhentheproductdimensionisverticalthanwhenitishorizontal;andc)themoderatingin uencesofbothproducttypeandproductdimensiontypeonproductsalesaremediatedbyperceivedriskfromratingvariance.Our
ndingso erimportanttheoreticala
ndingso erimportanttheoreticalandmanagerialimplicationsforabetterunderstandingoftheimpactofvariancesinmulti-dimensionalratingsystemsonthesalesofhigh-involvementproducts.CanReviewsHelpConsumersGetaBetterDeal?withShaYangAwarded\BestThird-yearPaper",USCTheobjectiveofthispaperistounderstandtheimpactofreviewsonconsumerdemandfordurablegoodswhenconsumerscannegotiateapurchaseprice.Althoughpriorstudieshaveanalyzedtheimpactofreviewsonconsumerbaselinepreferences,nonehasexploredsuchanimpactondemandwhenthepurchasepriceisnegotiated.Leveragingauniquedatasetonconsumers'automobilepurchasesandtransactionprices,ourpapershowsadouble-edgedsworde ectofreviewsondemandinsuchasetting.Ontheonehand,goodreviewsincreasedemandbyraisingconsumerbaselinepreferences;ontheotherhand,theyalsoincreasetheseller'sbargainingpower,andthisalongwiththeincreasedconsumerbaselinepreferencesleadstoahigherpurchaseprice,therebyhurtingdemand.Wedevelopastructuralmodeltouncoverthemultiplerolesreviewshaveondemandthroughbaselinepreferences,bargainingpower,andnegotiatedprice.Ignoringtheimpactofreviewsonthenegotiatedpriceleadstoabiasedestimationofthee ectivenessofreviews.Incounterfactuals,wequantifytheeconomicvalueofreviewfeaturesandprovideprotimplicationsofreviewsforsellers.3DOCTORALCOURSEWORKMarketingInstructor(s)StrategicandMarketingMixModelsS.SiddarthandGerardJ.TellisAdvancedQuantitativeModelsinMarketingDinaMayzlinandShaYangEconomicsMicroeconomicTheoryIJuanD.CarrilloMicroeconomicTheoryIIMichaelMagillProbabilityandStatisticsforEconomistsGeertRidderEconometricMethodsHyungsikRogerMoonAppliedEconometricsChengHsiaoEmpiricalIndustrialOrganizationYu-WeiHsiehIndustrialOrganizationGuofuTanEconomicsofRegulatedIndustriesGuofuTanGameTheorySimonWilkieHighDimensionalStatisticsandBigDataProblemsJinchiLvLastupdate:September29,20