About

Professor Raveesh Mayya is an Assistant Professor of Technology, Operations, and Statistics at NYU Stern, having joined the school in 2020. His research primarily focuses on digital platform policies and platform governance, examining technology-enabled platforms such as online sharing markets and smartphone app stores. His work explores how these platforms facilitate efficient transactions and address issues related to asymmetric information, with a particular interest in understanding the repercussions of private policy changes initiated by platforms. Through his research, he aims to contribute to the regulatory space and improve the governance aspects of private digital platforms. Additionally, Professor Mayya investigates questions related to Generative AI technologies, with the goal of enabling equitable utilization of GenAI in collaborative settings. His research has been recognized at multiple conferences and he has received several prestigious awards, including the ISR Reviewer of the Year Award 2024, the Management Science Distinguished Service Award 2023, and the highest doctoral awards at the Smith School of Business. He holds a Ph.D. in Information Systems from the University of Maryland's Smith School of Business, an MBA from the University of Delhi, and a Bachelor of Engineering from Visveswaraya Technological University. Prior to his academic career, he had brief stints in the Mahindra Group and Cisco Systems in India.

Research topics

• Computer Science
• Business
• Internet privacy
• Public economics
• Telecommunications
• Finance
• Economics
• Multimedia
• Marketing
• Human–computer interaction

Selected publications

• Growing Platforms by Adding Complementors Without a Contract

  Information Systems Research · 2025-02-20 · 3 citations

  article1st authorCorresponding

  Practitioner-Oriented Abstract Online platforms often face challenges in sustaining growth, especially in competitive markets such as food delivery. This paper examines a novel strategy in which platforms list nonpartnered restaurants, allowing consumers to order from them via third-party deliverers. Whereas these restaurants gain visibility without paying commissions, concerns arise about potential harm because of lack of control over menus and pricing. We analyze the impact of this strategy using data from Grubhub and a California policy change that banned nonpartnered listings. We find that being listed as nonpartnered boosts takeout revenue for these restaurants, particularly independent ones. Additionally, there’s a positive spillover effect on partnered restaurants. However, regulatory delisting reverses these gains, highlighting the delicate balance between platform growth strategies and regulatory actions. For platform owners, this study underscores the potential of noncontracted partnerships as a growth strategy, especially if there are third-party enablers on the platform such as deliverers. However, it also cautions against potential disruptions from regulatory changes, urging businesses to adapt their strategies accordingly. For restaurant owners, our finding emphasizes the importance of adapting to changes by enhancing operational readiness to capitalize on increased visibility. They should advocate for regulations that enhance their choices and overall transparency, not inadvertently decrease them. Policy-Oriented Abstract In the competitive landscape of online platforms, the pursuit of growth often necessitates innovative strategies. Whereas such strategies are deemed controversial and get pushbacks from some participants, how should policymakers respond? This research provides insights into such a scenario by investigating a novel growth strategy in which food delivery platforms onboarded nonpartnered restaurants, enabling consumer interactions without formal contracts, promising an increased visibility without commission fees. Leveraging data from Grubhub and a policy change in California, we find that being listed boosts takeout revenue significantly, especially for independent restaurants, with positive spillovers on partnered restaurants. However, delisting reverses these gains. For policymakers, these findings challenge the narrative that nonpartnered listings are inherently harmful. They highlight the potential of such arrangements to increase market access and revenue, particularly for independent businesses. However, the study also underscores the need for balanced regulation. Whereas protecting restaurants is crucial, overly restrictive policies can limit their choices and growth opportunities. We recommend a policy approach that empowers restaurants by requiring platforms to obtain explicit consent before listing them. Additionally, enhancing transparency around nonpartnered listings and associated fees can enable customers to make informed choices. This approach fosters a fair market, preserving the benefits of platform-enabled growth for all stakeholders.

  PublisherDOI

• Startup Accelerators, Information Asymmetry, and Corporate Venture Capital Investments

  Management Science · 2025-03-03 · 10 citations

  article1st authorCorresponding

  Beyond financial incentives, investments by Corporate Venture Capitalists (CVCs) are often motivated by strategic objectives, such as gaining early exposure to emerging technologies. However, in the presence of information asymmetry, CVCs tend to invest in startups with a high degree of business relatedness—startups that are less risky but lacking in knowledge novelty—which are not ideal for achieving their strategic objectives. With startup accelerators showing promise in mitigating the information asymmetry problem, we examine how a CVC’s investment pattern in a region shifts following a startup accelerator’s entry, with a particular interest in the degree of business relatedness between the CVC’s parent corporation and its portfolio companies. Analyses reveal that CVCs increase investments in startups that are dissimilar to their parent’s business following the entry of startup accelerators. We show that the two pathways through which accelerators reduce information asymmetry—quality signals, and mentorship and training—likely contribute to this change. In addition, the change is most pronounced for CVCs whose parent firm operates in an IT-using—rather than an IT-producing—industry, suggesting that accelerators help IT-using firms gain a foothold in the technology space through CVC investments. These findings deepen the understanding of the role that startup accelerators play in the entrepreneurial ecosystem against the backdrop of digital transformation occurring in nearly every industry. This paper was accepted by Kartik Hosanagar, information systems. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2020.03494 .

  PublisherDOI

• Information Technology Firms and Revenue Stall, 1950-2015: Theory and Empirical Evidence

  MIS Quarterly · 2025-07-03

  articleSenior author

  A slowdown in revenue growth, referred to as revenue stall in this study, is a key concern for any firm. We examine how information technology-producing firms (i.e., IT firms) differ from non-IT firms in experiencing revenue stall and in benefiting from R&D investments in terms of reduced revenue stall. We hypothesize that whereas IT firms experience more revenue stall than non-IT firms, R&D investments reduce revenue stall to a greater extent in IT firms than in non-IT firms. Our empirical analyses of a longitudinal dataset of more than 1,400 large public firms in the United States from 1950 to 2015 broadly support our hypotheses. Consistent with the theoretical arguments underlying our hypotheses, we also find that IT firms experience higher competition, dynamism, and turbulence, and have higher intangible assets than non-IT firms.

  PublisherDOI

• Token Tradability as a Form of Platform Deregulation: Intended and Unintended Consequences of a Policy Change

  SSRN Electronic Journal · 2024-01-01

  articleOpen access
  PublisherDOI

• The Impact of Large Language Models on Open-source Innovation: Evidence from GitHub Copilot

  arXiv (Cornell University) · 2024-09-12 · 7 citations

  preprintOpen access

  Large Language Models (LLMs) have been shown to enhance individual productivity in guided settings. Whereas LLMs are likely to also transform innovation processes in a collaborative work setting, it is unclear what trajectory this transformation will follow. Innovation in these contexts encompasses both capability innovation that explores new possibilities by acquiring new competencies in a project and iterative innovation that exploits existing foundations by enhancing established competencies and improving project quality. Whether LLMs affect these two aspects of collaborative work and to what extent is an open empirical question. Open-source development provides an ideal setting to examine LLM impacts on these innovation types, as its voluntary and open/collaborative nature of contributions provides the greatest opportunity for technological augmentation. We focus on open-source projects on GitHub by leveraging a natural experiment around the selective rollout of GitHub Copilot (a programming-focused LLM) in October 2021, where GitHub Copilot selectively supported programming languages like Python or Rust, but not R or Haskell. We observe a significant jump in overall contributions, suggesting that LLMs effectively augment collaborative innovation in an unguided setting. Interestingly, Copilot's launch increased iterative innovation focused on maintenance-related or feature-refining contributions significantly more than it did capability innovation through code-development or feature-introducing commits. This disparity was more pronounced after the model upgrade in June 2022 and was evident in active projects with extensive coding activity, suggesting that as both LLM capabilities and/or available contextual information improve, the gap between capability and iterative innovation may widen. We discuss practical and policy implications to incentivize high-value innovative solutions.

  PublisherOA PDFDOI

• Delaying Informed Consent: An Empirical Investigation of Mobile Apps’ Upgrade Decisions

  Management Science · 2024-12-02 · 9 citations

  article1st authorCorresponding

  In response to users’ evolving desire for choice and control over their personal data, numerous platforms across sectors have been updating privacy policies. Unlike public regulations that mandate uniform compliance, many platforms grant a more flexible time window for complementors to adopt privacy policies. Although several studies have examined the impact of privacy policies, the consequences of delayed policy adoption under time flexibility remain largely unexplored. This study is among the first to investigate the impact of apps delaying policy adoption in the context of a privacy policy change. The context of our research is the upgrade to Android version 6.0, which gave consumers more control over their personal data. Apps were given a three-year grace period to adopt the new privacy policy, during which apps that did not adopt the policy could still run on the latest Android version. We leverage this variation in policy adoption by apps to examine its impact on apps’ marketplace outcomes. By installing over 13,691 popular apps on emulators, we detect exactly when each app upgrades to version 6.0. We combine this unique data set with multiple data sets to quantify the impact of delaying the upgrade. We find that delaying the upgrade results in a significant loss of downloads and user ratings for apps. Frequently maintaining the apps without upgrading can only partially mitigate these declines. In further examining who delays upgrades and why, we find that apps that display in-app advertising and overreach for permissions are more likely to delay upgrading, suggesting a strategic trade-off between marketplace outcomes and the ability to collect data continuously. The findings of our study highlight the need to carefully consider participants’ potential strategic behaviors in designing policy implementation. We discuss the theoretical and practical implications of our findings. This paper was accepted by Chris Forman, information systems. Funding: Financial support from the Ed Snider Center for Enterprise and Markets at the University of Maryland is gratefully acknowledged. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.00334 .

  PublisherDOI

• The Impact of Large Language Models on Open-Source Innovation: Evidence from GitHub Copilot

  SSRN Electronic Journal · 2024-01-01 · 10 citations

  articleOpen access
  PublisherDOI

• Do Non-monetary Virtual Gifts Enhance or Diminish Voluntary Paid Gifts? Evidence From a Video Game Live Streaming Platform

  SSRN Electronic Journal · 2022 · 4 citations

  • Computer Science
  • Computer Science
  • Multimedia
  PublisherDOI

• Do Non-monetary Virtual Gifts Enhance or Diminish Voluntary Paid Gifts on a Live Streaming Platform?

  Academy of Management Proceedings · 2022-07-06 · 1 citations

  article

  This project empirically investigates the impact of a live streaming platform’s viewer-engagement improvement efforts on viewers’ voluntary paid gift giving outcomes. Live streaming platforms employed various strategies such as gamifying viewing and community engagement to increase viewer side engagement. A common gamification strategy is to grant platform ‘coins’ that viewers can exchange for VIP passes or non-monetary gifts that can be given to streamers during live-streams. Given that live streaming platforms utilize Pay-What-You-Want (PWYW) pricing mechanism, it is unclear if increased access to non-monetary gifts substitutes or augments viewers’ voluntary monetary gift sending behavior. To answer this question, we work with a major live streaming platform in Asia and analyze individual-level virtual gift sending records between May and December of 2019. The analyses reveal that encouraging non-monetary gift sending behavior increases viewers’ monetary gift sending behavior by 105.24%. Mechanism analyses suggest that free gifts facilitate habit-forming, resulting in an enhancement rather than a substitution of monetary gift sending. Furthermore, we also provide evidence of attention-seeking gifting behaviors. Consistent with the proposed mechanisms, our heterogeneity analyses suggest that streamers with a previously lesser popularity benefit more from the policy. Our research contributes to the live streaming and platform policy literature and offers guidance to live streaming practitioners in engagement feature designs.

  PublisherDOI

• Seed Accelerators, Information Asymmetry, and Corporate Venture Capital Investments

  SSRN Electronic Journal · 2022-01-01 · 1 citations

  articleOpen access1st authorCorresponding
  PublisherDOI

Frequent coauthors

• Siva Viswanathan

  University of Maryland, College Park

  4 shared

• Shun Ye

  Zhejiang University

  2 shared

• Pearl L. Yu

  New York University

  2 shared

• Doron Yeverechyahu

  2 shared

• Anindya Ghose

  New York University

  2 shared

• Gal Oestreicher-Singer

  Tel Aviv University

  2 shared

• Rajshree Agarwal

  2 shared

• Peng Huang

  1 shared

Awards & honors

• ISR Reviewer of the Year Award 2024
• Management Science Distinguished Service Award 2023
• Best Doctoral Dissertation Award
• Frank T. Paine Award for Academic Excellence
• Allan N. Nash Outstanding Doctoral Student Award