2024
Online Algorithms for Matching Platforms with Multichannel Traffic
Manshadi V, Rodilitz S, Saban D, Suresh A. Online Algorithms for Matching Platforms with Multichannel Traffic. Management Science 2024 DOI: 10.1287/mnsc.2022.00910.Peer-Reviewed Original ResearchExternal trafficTwo-sided platformsRevenue managementMarketing analyticsOnline appendixOmar BesbesWebsite trafficInternational trafficMatching platformTrafficRecommendation algorithmStrong performancePerformance of ACOnline algorithmPlatform problemsNumerical studyTargeting opportunitiesCompetitive ratioOnline matchingExternal linksNonprofitsAdaptive capacityOpportunitiesMarketRevenueCommitment 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 ResearchFood 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-offsAdoptionTaskCommitmentPlatformDynamic Matching with Post-allocation Service and its Application to Refugee Resettlement
Bansak K, Lee S, Manshadi V, Niazadeh R, Paulson E. Dynamic Matching with Post-allocation Service and its Application to Refugee Resettlement. 2024, 673-673. DOI: 10.1145/3670865.3673572.Peer-Reviewed Original ResearchCommitment 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. 2024, 674-674. DOI: 10.1145/3670865.3673488.Peer-Reviewed Original ResearchMarket thicknessOptimal level of commitmentMatching functionLevel of commitmentOptimal myopic policyMyopic policyFood Rescue U.S.Random marketsSpot marketMarket participantsCrowdsourcing platformsMatching efficiencyMarketTwo-sided marketplacesOptimal levelPolicyTrade-offsNegative impactPromote growthConstant-factor approximationVolunteer characteristicsRecurring tasksFood recovery organizationsMatching process
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 ResearchMinimum 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 ResearchSocial 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 ResearchFake 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 ResearchHigh-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 ResearchOnline 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 ResearchOptimal 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 ResearchExternal 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 ResearchMarket 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 ResearchInformation 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 informationInformationFair Dynamic Rationing
Manshadi V, Niazadeh R, Rodilitz S. Fair Dynamic Rationing. 2021, 694-695. DOI: 10.1145/3465456.3467554.Peer-Reviewed Original ResearchMinimum fill rateSequence of demandsValue-to-goAdaptation policiesDemand-to-supply ratioCorrelated demandsEmergency Management AgencyFederal Emergency Management AgencySocial plannerDynamic rationalityAlternative objective functionsWhite HouseSocial goodConditional momentsEquityManagement agenciesLower-bound functionsPolicyFairness guaranteesTheoretical guaranteesEfficient rationingFilling ratePerformance guaranteesTheoretical developmentsDistributed knowledgeLearning Product Rankings Robust to Fake Users
Golrezaei N, Manshadi V, Schneider J, Sekar S. Learning Product Rankings Robust to Fake Users. 2021, 560-561. DOI: 10.1145/3465456.3467580.Peer-Reviewed Original ResearchFake usersLearning algorithmsSub-optimal rankingsEfficient learning algorithmNew learning algorithmsCustomer actionsImplementing multiple levelsFraudulent behaviorFraudulent usersPerformance guaranteesIncurring large costsOptimal rankingOnline platformsUsersPairwise relationshipsClick farmingAlgorithmRanking robustnessProduct rankingInformation environmentCross-learningEfficient convergencePlatformLearningLearning processDesigning Approximately Optimal Search on Matching Platforms
Immorlica N, Lucier B, Manshadi V, Wei A. Designing Approximately Optimal Search on Matching Platforms. 2021, 632-633. DOI: 10.1145/3465456.3467530.Peer-Reviewed Original ResearchSocial welfareTwo-sided matching marketsUnique stationary equilibriumDecentralized two-sided matching marketEquilibrium social welfareOptimal social welfareMeeting rateStationary equilibriumMatching marketsOptimal welfareIncentive issuesWelfareEquilibriumPairwise preferencesEasy-to-implementAgent searchesMatching platformPreferencesPotential partnersBipartite graphsConstant factorIncentivesMarketNP-hardDesign problemOnline Resource Allocation Under Partially Predictable Demand
Hwang D, Jaillet P, Manshadi V. Online Resource Allocation Under Partially Predictable Demand. Operations Research 2021, 69: 895-915. DOI: 10.1287/opre.2020.2017.Peer-Reviewed Original ResearchOnline resource allocationOnline algorithmAnalysis of online algorithmsAdversarial modelAdversarial componentResource allocationArrival modelSequence of arrivalsReal-time resource allocationMultiple stopping rulesCapacity scalingStochastic demand modelDesign online algorithmsModel of demandImprove allocation decisionsDemand modelStochastic componentAlgorithm designOnline decisionsAllocation decisionsPredicted demandCustomersOnline allocationUnpredictable componentsAlgorithm
2020
Diffusion in Random Networks: Impact of Degree Distribution
Manshadi V, Misra S, Rodilitz S. Diffusion in Random Networks: Impact of Degree Distribution. Operations Research 2020, 68: 1722-1741. DOI: 10.1287/opre.2019.1945.Peer-Reviewed Original ResearchDegree distributionRandom networksOptimal seeding strategyMean-field approximation methodMean-fieldAdoption proportionFixed costsViral marketingDiffusion processCost efficiencyApproximation methodFirmsNon-adoptersEndogenous effectsEffect of diffusionSeeding budgetSocial networksApproximationMarketAdoptionDiffusion trajectoriesRegimeSeeding strategyAverage degreeProduct Ranking on Online Platforms
Derakhshan M, Golrezaei N, Manshadi V, Mirrokni V. Product Ranking on Online Platforms. 2020, 459-459. DOI: 10.1145/3391403.3399483.Peer-Reviewed Original ResearchConsumer welfareMarket sharePreference weightsSequential search modelPlatform’s market shareExternal effectsSearch modelModeling primitivesMaximum likelihood estimationWelfareConsumer considerationLikelihood estimationSharingConsumersPreferencesSearch policyInsufficient screeningMarketExternalitiesDecreasing orderPolicyInformation 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. 2020, 349-350. DOI: 10.1145/3391403.3399504.Peer-Reviewed Original ResearchHigh-need usersService providersKnowledge of users’ typesHigher waiting costsBayesian persuasion frameworkLevel of congestionFull informationUser typesInformation advantageServer queueing systemReduce congestionTraffic managementPareto improvementWaiting costStylized modelFirst-best welfareLong queuesCongestionSocial servicesInformation designInformational leversWelfare improvementCoordination devicePublic housing authoritiesQueue
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