Abstract
In the fierce competition among hosts on livestreaming platforms, gamified chance-based rewards (i.e., gamified lotteries) stand out as a distinct mechanism to enhance audience engagement and revenue generation. The first study presents an investigation into the instant effects versus slope effects of gamified lotteries on pay-as-you-wish (PAYW) gifting and audience engagement in the entertaining livestreaming industry. Employing a quasi-experimental design, the research utilizes an interrupted time series analysis with a reversed treatment design (ITS-RTD) to capitalize on an unexpected suspension and subsequent reintroduction of the lottery function on a leading livestreaming platform in China. Our findings reveal that the implementation of gamified lottery correlates with a short-term increase of 14% in host income and a 10% rise in audience engagement. However, based on the hedonic adaptation theory, our findings also highlight the double-edged nature of lotteries, indicating the risks of over-reliance on gamified elements that can lead to a hedonic adaptation trap. The impacting mechanisms incorporate perspectives from traffic transference and hedonic adaptation, offering insights into the nuanced impact of gamified lotteries while suggesting a balanced approach for hosts to leverage gamification alongside other engagement strategies to mitigate the risks of over-dependence.Geopolitical crises, such as the Russian-Ukrainian conflict, have profound implications for the cross-border global gig economy. Workers’ public expressions of political stances can significantly impact their employment opportunities and income stability, and understanding how the online culture of political ideology under such conflicts influences work outcomes is critical. The second study investigates the interplay between political ideology and gig work dynamics using a large-scale dataset from a European online labor platform. We examine how workers’ declarations of anti-war stances affect their work performance, employer engagement, and earnings. The findings reveal that workers expressing anti-war stances attract more engagement from ideologically aligned employers, such as those from Ukraine and Belarus, but face reduced opportunities with employers from Russia. Despite fewer engagements overall, these workers often earn higher average incomes per engagement, reflecting a potential premium for aligning with certain client values. Additionally, attributes such as ratings, competitiveness, and experience moderate these effects, with high-quality and experienced workers showing greater resilience to political polarization. This research advances the understanding of the gig economy’s vulnerabilities and resilience during geopolitical crises. It offers theoretical contributions to political polarization and labor market segmentation literature while providing actionable insights for workers, platform designers, and policymakers navigating the challenges of online labor markets in conflict-affected regions.
As digital labor platforms play an increasingly central role in the global workforce, their governance decisions—especially in response to geopolitical crises—have profound implications for market outcomes and worker livelihoods. Despite their growing importance, little is known about how platforms strategically respond to external shocks and how these decisions reshape opportunity structures for different types of freelancers. The third study exploits a natural experiment arising from a platform governance decision to remove all Russian freelancers in May 2022, following the onset of the Russia–Ukraine war. Drawing on a granular panel dataset of 428,401 daily work records linked to 80,141 freelancer profiles, we apply a regression discontinuity in time (RDiT) design to estimate the causal effects of this exogenous labor supply shock. We find that the intervention significantly increased average earnings for the remaining workforce, primarily through higher income per task rather than an increase in task volume. However, these gains were not uniformly distributed: workers with higher reputational capital and those in technical categories such as IT experienced disproportionately greater benefits. Political alignment of a worker’s home country also moderated the effects, though less systematically. By situating the analysis within a platform governance perspective, this study contributes to research on labor market shocks, platform strategy, and algorithmic reallocation. Our findings show that platform responses to geopolitical risk can reinforce structural inequalities through selective opportunity redistribution, highlighting the strategic role of platform governance in shaping post-shock labor market dynamics.
| Date of Award | 27 Aug 2025 |
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| Original language | English |
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| Supervisor | Angela LU (Supervisor) & Jingjun David XU (Co-supervisor) |