About

Yanru Cui is a Postdoctoral Associate at the Meinig School of Biomedical Engineering at Cornell University. She is affiliated with the Jiang Lab within the Duffield Engineering community, which is recognized for its collaborative and dynamic environment dedicated to excellence in education, groundbreaking research, and technological innovation. Her research focus is not explicitly detailed on the page, but her association with biomedical engineering suggests involvement in advancing biomedical technologies and research.

Research topics

• Business
• Industrial organization
• Computer science
• Economics
• Microeconomics

Selected publications

• Bonus Competition in the Gig Economy

  Production and Operations Management · 2025-10-09 · 2 citations

  article

  The success of a gig platform is crucially driven by its ability to compete for labor supply. However, gig workers are independent contractors whose working schedules are not fully controlled by the platform. To overcome this challenge, gig platforms have commonly relied on bonus strategies to drive the participation of gig workers. We study the impact of bonus strategies on gig platforms and their welfare implications. We consider two types of bonus strategies used by gig platforms: (1) fixed bonus that is paid in addition to commissions as long as a service provider participates and (2) contingent bonus that is paid only if a service provider participates consistently over time. We develop a game theory model to study platform competition with bonus strategies. Our analysis shows that the two types of bonuses will arise in equilibrium under different market conditions. First, when labor supply is thick, fixed bonus will be offered. In this case, fixed bonus improves platform profit by eliminating a prisoner’s dilemma that arises when the platforms compete only on commissions. However, social welfare will be reduced because the utilization of the labor supply is reduced due to the softened platform competition. Second, when labor supply is thin, contingent bonus will be offered. In this case, contingent bonus reduces platform profit because it intensifies platform competition and traps the platforms in a prisoner’s dilemma where they are forced to offer too much bonus. It further causes inefficiency in matching labor supply with demand and hence reduces social welfare.

  PublisherDOI

• Unlocking the Benefit of Exchangeable Tickets: A Study of Customer Behavior in Sports Events

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• <p>NFT Market Design: Resale Royalty, Decentralization, and Interoperability</p>

  SSRN Electronic Journal · 2025-01-01 · 1 citations

  preprintOpen accessSenior author
  PublisherDOI

• Supply Chain Transparency and Blockchain Design

  Management Science · 2023-11-09 · 162 citations

  article1st authorCorresponding

  Companies that are investing in blockchain technology to enhance supply chain transparency face challenges in fostering collaborations with others and deciding what information to share. Transparency over the actions of supply chain partners can improve operational decisions, but sharing own data on the blockchain can put firms at a competitive disadvantage. In this paper, we investigate the resulting questions of when blockchain should be adopted in a supply chain and how it should be designed by analyzing two ways that it can enhance supply chain transparency: making the manufacturer’s sourcing cost transparent to the buyers (i.e., vertical cost transparency) and making the ordering status of buyers transparent to each other (i.e., horizontal order transparency). Given such transparency, firms can design a smart contract that automates transactions contingent on the revealed information and enables them to realize better equilibrium outcomes. We find that blockchain increases supply chain profit only when the manufacturer’s capacity is large and decreases supply chain profit otherwise. If the capacity is sufficiently large to eliminate the buyers’ competition, blockchain leads to a win–win–win and the incentives of all participants are naturally aligned. If the capacity is only moderately large, the manufacturer needs to compensate the buyers to facilitate a blockchain implementation. However, if the capacity is small, horizontal order transparency enabled by the blockchain mitigates the buyers’ overorder incentive to compete for the manufacturer’s capacity and increases double marginalization. For such cases, we show that a blockchain that only enables vertical cost transparency should (and can) still be adopted in a range of small capacity cases, and we propose an access control layer for the logistics data to implement such a blockchain. This paper was accepted by David Simchi-Levi, operations management. Funding: J. Liu was supported by the National Natural Science Foundation of China [Grant 72101110] and The MOE (Ministry of Education in China) Project of Humanities and Social Sciences [Grant 20YJC630084]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4851 .

  PublisherDOI

• Value and Design of Traceability-Driven Blockchains

  Manufacturing & Service Operations Management · 2023-01-23 · 141 citations

  article1st authorCorresponding

  Problem definition: This paper provides a theoretical investigation into the value and design of a traceability-driven blockchain under different supply chain structures. Methodology/results: We use game theory to study the quality contracting equilibrium between one buyer and two suppliers and identify two fundamental functionalities of a traceability-driven blockchain. In serial supply chains, the ability to trace the sequential production process creates value by mitigating double moral hazard. In this case, traceability always improves product quality and all firms’ profits and naturally creates a win-win. In parallel supply chains, the ability to trace the product origin enables flexible product recall, which can reduce product quality. In this case, traceability can benefit the buyer while hurting the suppliers, creating an incentive conflict. Managerial implications: Firms operating in different kinds of supply chains could face unique challenges when they adopt and design a traceability-driven blockchain. First, in serial supply chains, any firm can be the initiator of the blockchain, whereas in parallel supply chains, it may be critical for the buyer to take the lead in initiating the blockchain and properly compensate the suppliers. Second, in serial supply chains, a restricted data permission policy where each supplier shares their own traceability data with the buyer but not with each other can improve the supply chain profit, whereas in parallel supply chains, it is never optimal to restrict a firm’s access to the traceability data. Third, the suppliers’ incentive to enhance the governance of data quality is more aligned with the supply chain optimum in serial supply chains compared with parallel supply chains. Funding: M. Hu was supported by the Natural Sciences and Engineering Research Council of Canada [Grants RGPIN-2015-06757 and RGPIN-2021-04295]. J. Liu was supported by the National Natural Science Foundation of China [Grant 72101110] and The MOE (Ministry of Education in China) Project of Humanities and Social Sciences [Grant 20YJC630084]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2022.1161 .

  PublisherDOI

• E-Companions to "Should Gig Platforms Decentralize Dispute Resolution?"

  SSRN Electronic Journal · 2023-01-01 · 1 citations

  articleOpen accessSenior author
  PublisherDOI

• Unlocking the Value of Real-Time AI Assistance: Who Benefits, and Why?

  SSRN Electronic Journal · 2023-01-01 · 3 citations

  articleOpen access1st authorCorresponding
  PublisherDOI

• Should Gig Platforms Decentralize Dispute Resolution?

  Manufacturing & Service Operations Management · 2023-11-16 · 13 citations

  articleSenior author

  Problem definition: Disputes on online labor platforms have traditionally been mediated by the platform itself, which is often viewed as unhelpful or biased. However, there are emerging platforms that promise to resolve disputes with a novel tribunal system and relegate dispute resolution to individual platform users through a voting mechanism. We aim to examine the dispute resolution systems used by traditional platforms (i.e., the centralized dispute system) and emerging platforms (i.e., the decentralized dispute system) in order to assess whether the latter has an advantage over the former. Methodology/results: We use game theory to analyze both the centralized and decentralized dispute systems, and we model the tribunal’s voting game using the global games framework. Our findings indicate that in order to achieve a fair voting outcome, it is crucial to have sufficient heterogeneity in the assessments of tribunal members. Moreover, the decentralized dispute system outperforms the centralized dispute system only when the freelancer’s skill level is sufficiently high. Lastly, the decentralized dispute system has the potential to induce a more socially optimal quality level from the freelancer. Managerial implications: Our findings provide insights on the optimal adoption and implementation of the decentralized dispute system. The decentralized dispute system is more effective for tasks that involve subjective evaluations, and platforms should avoid strategies that homogenize the assessments of tribunal members. Moreover, platforms should consider switching to the decentralized dispute system only if they are able to verify the skill level of freelancers through certification or other means. Lastly, the decentralized dispute system may be more appealing to policy makers because of its potential to induce a more socially optimal outcome. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0398 .

  PublisherDOI

• Supply Chain Transparency Using Blockchain: Benefits, Challenges, and Examples

  2022-12-08 · 5 citations

  book-chapter1st authorCorresponding
  PublisherDOI

• Tax-Induced Inequalities in the Sharing Economy

  Management Science · 2022-01-12 · 38 citations

  article1st authorCorresponding

  The growth of sharing economy marketplaces like Airbnb has generated discussions on their socioeconomic impact and lack of regulation. As a result, most major cities in the United States have started to collect an “occupancy tax” for Airbnb bookings. In this study, we investigate the heterogeneous treatment effects of the occupancy tax policy on Airbnb listings, using a combination of a generalized causal forest methodology and a difference-in-differences framework. While we find that the introduction of the tax significantly reduces both listing revenues and sales, more importantly, these effects are disproportionately more pronounced for residential hosts with single shared-space (nontarget) listings versus commercial hosts with multiple properties or entire-space (target) listings. We further show that this unintended consequence is caused by customers’ discriminatory tax aversion against nontarget listings. We then leverage these empirical results by prescribing how hosts should optimally set prices in response to the occupancy tax and identify the discriminatory tax rates that would equalize the tax’s effect across nontarget and target listings. This paper was accepted by Victor Martínez-de-Albéniz, operations management.

  PublisherDOI

Frequent coauthors

• Izak Duenyas

  Ross School

  21 shared

• Özge Şahin

  11 shared

• Vishal Gaur

  Cornell University

  10 shared

• Jingchen Liu

  Renmin University of China

  8 shared

• Yeşim Orhun

  Ross School

  6 shared

• Ming Hu

  5 shared

• Andrew M. Davis

  5 shared

• Hau L. Lee

  Stanford University

  4 shared

Labs

• Jiang LabPI

Awards & honors

• SPROUT Awards
• EPICC Awards
• Research, Teaching, and Advising Awards
• Distinguished Alumni Award
• Cheng Distinguished Lecture Series