Vahideh Hosseinikhah Manshadi
Michael H. Jordan Professor of OperationsDownloadHi-Res Photo
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Michael H. Jordan Professor of Operations
Biography
Professor Manshadi’s research interests include real-time decision-making and dynamic optimization under uncertainty with various applications, such as online markets, health-care operations, and maritime port logistics, as well as matching markets and social networks.
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School of Management
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Assistant ProfessorSecondary
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Research at a Glance
Publications Timeline
A big-picture view of Vahideh Hosseinikhah Manshadi's research output by year.
35Publications
539Citations
Publications
2024
Commitment on Volunteer Crowdsourcing Platforms: Implications for Growth and Engagement
Lo I, Manshadi V, Rodilitz S, Shameli A. Commitment on Volunteer Crowdsourcing Platforms: Implications for Growth and Engagement. Manufacturing & Service Operations Management 2024, 26: 1787-1805. DOI: 10.1287/msom.2020.0426.Peer-Reviewed Original ResearchConceptsFood Rescue U.S.Optimal myopic policyAdoption levelTwo-sided marketsOptimal design cruciallyMyopic policyTwo-sided platformsVolunteer management literatureMarket thicknessMarket participantsLevel of adoptionManagement literatureOnline appendixOptimal policyCrowdsourcing platformsConstant-factor approximationMarketVolunteer characteristicsPolicyFood recovery organizationsTrade-offsAdoptionTaskCommitmentPlatform
2023
Fair Dynamic Rationing
Manshadi V, Niazadeh R, Rodilitz S. Fair Dynamic Rationing. Management Science 2023, 69: 6818-6836. DOI: 10.1287/mnsc.2023.4700.Peer-Reviewed Original ResearchCitationsConceptsMinimum fill rateFederal Emergency Management AgencySequence of demandsEmergency Management AgencyDemand-to-supply ratioRevenue managementMarketing analyticsSocial goodCorrelated demandsPolicyOnline appendixOmar BesbesAdaptation policiesSocial plannerManagement agenciesTheoretical guaranteesConditional momentsUpper boundFilling rateCOVID-19 pandemicEfficient rationingAllocation challengesMedical suppliesTheoretical developmentsDesigning Approximately Optimal Search on Matching Platforms
Immorlica N, Lucier B, Manshadi V, Wei A. Designing Approximately Optimal Search on Matching Platforms. Management Science 2023, 69: 4609-4626. DOI: 10.1287/mnsc.2022.4601.Peer-Reviewed Original ResearchCitationsConceptsSocial welfareTwo-sided matching marketsUnique stationary equilibriumDecentralized two-sided matching marketFirst-best social welfareEquilibrium social welfareImproved approximation factorMeeting rateStationary equilibriumMatching marketsAgents' incentivesOptimal welfareOmar BesbesBipartite graphsIncentive issuesSearch designAgent typesApproximation factorOnline appendixConstant factorWelfareMarketMarketing analyticsSearch problemDesign problemLearning Product Rankings Robust to Fake Users
Golrezaei N, Manshadi V, Schneider J, Sekar S. Learning Product Rankings Robust to Fake Users. Operations Research 2023, 71: 1171-1196. DOI: 10.1287/opre.2022.2380.Peer-Reviewed Original ResearchCitationsConceptsFake usersOnline learning algorithmLearning algorithmsProduct rankingDetect fake usersEfficient learning algorithmClick farmingImplementing multiple levelsMachine learning algorithmsE-commerce platformsFraudulent behaviorFraudulent usersSuboptimal rankingsUser feedbackCorrupted dataData analyticsFraudulent actorsE-commerceOptimal rankingOnline platformsUsersTD managementDisplay orderLearning methodologyAlgorithmInformation Design for Congested Social Services: Optimal Need-Based Persuasion
Anunrojwong J, Iyer K, Manshadi V. Information Design for Congested Social Services: Optimal Need-Based Persuasion. Management Science 2023, 69: 3778-3796. DOI: 10.1287/mnsc.2022.4548.Peer-Reviewed Original ResearchCitationsConceptsHigh-need usersEffectiveness of information designKnowledge of users’ typesPrivate outside optionsAbsence of price discriminationFirst-come-first-served queueRevenue managementMarketing analyticsGabriel WeintraubReduce congestionPrice discriminationStylized modelE-companionImprove social outcomesImprove welfareService providersFull informationWelfare outcomesCongestionCentralized admissionsInformation designUser typesWaiting timeHeterogeneous usersWelfare
2022
Online Policies for Efficient Volunteer Crowdsourcing
Manshadi V, Rodilitz S. Online Policies for Efficient Volunteer Crowdsourcing. Management Science 2022, 68: 6572-6590. DOI: 10.1287/mnsc.2021.4220.Peer-Reviewed Original ResearchCitationsAltmetricConceptsOnline policyTime-sensitive tasksFood Rescue U.S.Constant factor guaranteeMissed tasksCrowdsourcing platformsRandomized policyBipartite matchingTime-varying distributionFood recovery organizationsTask typeTaskDynamic programmingPlatformUpper boundNotificationSuccess cruciallyMarketing analyticsGabriel WeintraubFeasible solutionsMatch probabilityHardness resultsGuaranteesTradeoffPlatform dataImpact of Network Structure on New Service Pricing
Alizamir S, Chen N, Kim S, Manshadi V. Impact of Network Structure on New Service Pricing. Mathematics Of Operations Research 2022, 47: 1999-2033. DOI: 10.1287/moor.2021.1197.Peer-Reviewed Original ResearchCitationsConceptsOptimal pricingConsumption growthFirm's optimal pricingOptimal pricing decisionsNetwork of consumersDynamic pricing problemFaster consumption growthLocal network effectsFirm profitabilityFirm benefitsFirm revenuePricing decisionsConsumer interactionsNetwork externalitiesFirmsPositive externalitiesService pricingPricing problemNetwork effectsRevenuePricingDegree of connectionProfitabilityExternalitiesConsumersOnline Algorithms for Matching Platforms with Multi-Channel Traffic
Manshadi V, Rodilitz S, Saban D, Suresh A. Online Algorithms for Matching Platforms with Multi-Channel Traffic. 2022, 986-987. DOI: 10.1145/3490486.3538326.Peer-Reviewed Original ResearchCitationsConceptsExternal trafficOnline algorithmTwo-sided platformsRecommendation algorithmCompetitive ratioWebsite trafficPerformance of ACInternational trafficMatching platformTrafficStrong performanceRecommendation enginePseudo-rewardsPlatform problemsStochastic rewardsPath-basedCase studyTargeting opportunitiesMulti-channelAlgorithmOnline matchingOpportunitiesExternal linksTheoretical resultsNonprofitsProduct Ranking on Online Platforms
Derakhshan M, Golrezaei N, Manshadi V, Mirrokni V. Product Ranking on Online Platforms. Management Science 2022, 68: 4024-4041. DOI: 10.1287/mnsc.2021.4044.Peer-Reviewed Original ResearchCitationsConceptsMarket shareConsumer welfarePreference weightsSequential search modelPlatform’s market shareGabriel WeintraubExternal effectsSearch modelModeling primitivesMaximum likelihood estimationWelfareConsumer considerationMarketing analyticsLikelihood estimationMarketSharingConsumersPreferencesRevenue managementSearch policyInsufficient screeningExternalitiesWeintraubRevenueDecreasing order
2021
Information Inundation on Platforms and Implications
Allon G, Drakopoulos K, Manshadi V. Information Inundation on Platforms and Implications. Operations Research 2021, 69: 1784-1804. DOI: 10.1287/opre.2021.2119.Peer-Reviewed Original ResearchCitationsAltmetricConceptsInformation inundationPeople access newsInformation sourcesEvolution of beliefsLearning processSpeed of learningConsuming newsInformation consumptionBelief distributionProlonged learning processSocial platformsProcess of learningOpinion formationPsychological biasesPresence of platformsSlow learningGad AllonPolitical mapNewsPresence of uncertaintyLearningMenu sizePlatformConsumer informationInformation