Research

3. Saharsh Agarwal, Uttara Ananthakrishnan. Impact of Short-Form Videos on Screentime and Sleep: Evidence from TikTok

Major revision, Management Science

Short-form video platforms have become central to debates about digital overuse and sleep disruption, yet causal evidence on their behavioral impacts remains limited. We study the effects of adopting short-form video in the context of TikTok, which pioneered the format and accounts for a large share of global short-form video consumption. Using granular smartphone touchstream data from a large opt-in panel of U.S. Android users, we track app usage, screen time, and inferred sleep behavior before and after TikTok adoption. We employ a Difference-in-Differences (DiD) framework leveraging a high-frequency app usage dataset from nearly 7,000 TikTok adopters. Our findings reveal a significant increase in overall screen time---averaging 221 minutes per week for heavy TikTok users---following TikTok adoption, alongside notable declines in usage of other social media and gaming apps, suggesting a strong substitution effect. The screen time effects are highest during late night hours. We also observe shifts in sleep patterns, including delayed bedtimes and a moderate reduction in sleep duration, among high-intensity users. We observe no effects for low-intensity users, who engage minimally with TikTok post-adoption. Our findings show that short-form video adoption expands total digital attention rather than merely reallocating it, with important implications for platform design, regulation, and digital well-being. As a side result, our analysis provides clear evidence of substitutability between TikTok and traditional social media platforms, which has immediate implications for ongoing antitrust proceedings. 

2. Li Ding, Saharsh Agarwal, Vivek Choudhary. The Impact of Payment on Delivery on Gig Drivers' Behavior in Developing Economies

Problem definition: In developing economies, gig platforms are widely viewed as engines of income generation, yet a prevalent and central operational feature of these markets, Payment-on-Delivery (POD), has received little attention. Under POD, drivers collect payments from customers and temporarily retain the full order value before settling with the platform. This provides workers with immediate liquidity but also creates frictions, including cash-handling risks and reconciliation responsibilities. Despite its scale and operational importance, we lack empirical evidence on POD’s impact on gig drivers, the primary operational asset of these platforms. We investigate how POD shapes drivers’ decisions about when to stop working, whether to return the next day, and whether to remain active in the longer run. Methodology/Results: We analyze transaction-level data from a leading food delivery platform in India, including 4,776 drivers and ~2.8 million orders over six months. We exploit quasi-random POD order allocation to causally identify how POD affects drivers’ labor supply decisions. We find that receiving a POD order increases the likelihood that a driver ends the shift by four percent, consistent with cash-targeting behavior in which workers treat collected cash as salient and immediately usable. The effect becomes stronger when the opportunity cost of stopping is low (e.g., off-peak hours) and when liquidity needs are elevated (e.g., month-end). Although POD induces shift-ending, it increases next-day participation and lowers attrition, resulting in a more stable labor supply over time. Managerial implications: POD is not only as a mechanism for expanding consumer access but also as a lever for improving driver retention. By providing immediate liquidity, POD helps stabilize participation, reduce turnover, and smoothen labor supply in settings where workers face significant financial constraints. Platforms that recognize and manage this liquidity channel can strengthen operational reliability in highly liquidity-dependent developing country markets.

1. Saharsh Agarwal, Uttara Ananthakrishnan, Catherine Tucker. Infrastructural Gatekeeping and its Spillovers

Major revision, Information Systems Research

 Prior research on online governance has largely focused on fine-grained, within-platform content moderation, where platform operators and community members remove individual posts or users. Infrastructural Gatekeeping is a distinct and emerging class of intervention in which third-party infrastructure providers (e.g., cloud hosts and app stores) remove entire platforms from the digital ecosystem due to content related reasons. Unlike within-platform content moderation, infrastructural gatekeeping eliminates entire communicative spaces, raising new questions about how affected communities reorganize across the broader digital ecosystem. We examine the Parler takedown in January 2021, when multiple infrastructure providers terminated the platform’s web and app hosting. Using large-scale mobile touchstream data from over 46,000 Parler users, we analyze how individuals redistributed their activity across alternative platforms. We introduce a governance framework to classify platforms based on permissiveness (lenient/strict) and observability (open/closed) and show that Infrastructural Gatekeeping produces substantial spillovers across all quadrants of this space. Users increase activity not only on ideologically or functionally similar lenient-open platforms but also on lenient-closed and strict-open alternatives. Migration responses differ sharply by prior engagement: heavy users rapidly consolidate into closed, less observable environments, while light users exhibit broader and more transient experimentation. Infrastructural Gatekeeping interventions also heighten exposure to low-quality and misleading content for the most engaged users. These findings show that infrastructural gatekeeping is a qualitatively distinct governance mechanism with ecosystem-level consequences, potentially shifting harmful activity into less observable environments rather than eliminating it.