Resilience or collapse? How sharing economy platforms weather crises

The COVID-19 pandemic exposed vulnerabilities across industries and digital platforms operating in the sharing economy were among the most impacted, with some flourishing unexpectedly while others struggling to survive. In this context, a new study offers a comprehensive conceptual framework for analyzing how such platforms respond to crises and what this reveals about their long-term sustainability.

The study, "Sharing Economy Platforms in the Face of Crises: A Conceptual Framework", published in Sustainability (2025), provides both theoretical grounding and empirical validation. It focuses on three emblematic platforms, Airbnb, Uber Eats, and Prosper, and examines their responses to the COVID-19 pandemic through the lens of short-term impact, medium-term strategy, and long-term resilience. The researchers explore how user dynamics and strategic decisions interplay over time, drawing critical lessons for managing future disruptions.

What explains the contrasting impacts of crises on sharing economy platforms?

The study dissects why digital platforms in the sharing economy experienced dramatically different outcomes during the same global crisis. The authors argue that the immediate effects of an external shock like COVID-19 depend largely on changes in users’ perceived value of the platform compared to alternatives. In a two-sided market, where platforms mediate interactions between two distinct user groups, commonly labeled buyers and sellers, any disruption to perceived utility on either side can influence participation dynamics.

Three crisis scenarios are presented. In the first, platforms such as Airbnb faced a drop in participation on both sides due to travel bans and lockdowns. In the second, platforms like Uber Eats benefited from increased demand from both diners and restaurants as physical distancing forced a shift to digital ordering. The third scenario, illustrated by Prosper, a leading crowdlending platform in the United States, saw asymmetric effects: borrowers surged as traditional credit became harder to access, while lenders hesitated due to growing financial uncertainty.

These distinct patterns set the stage for varying feedback mechanisms. Platforms with symmetric shocks, either positive or negative, tended to spiral in virtuous or vicious cycles. In contrast, platforms with asymmetric shocks faced the challenge of managing imbalance, where one side’s enthusiasm was undermined by the other’s reluctance. These differences underscore the critical role of initial user perception and how network effects amplify early-stage shifts in behavior.

How do platform strategies shape mid-term recovery and stability?

The framework emphasizes that a platform’s strategic response is crucial in the medium term. Once initial user reactions stabilize, platforms can intervene with pricing, policy, or operational changes to either mitigate losses or scale gains. Each case study illustrates a unique strategic path reflective of the underlying crisis dynamics.

Airbnb responded to plummeting demand with enhanced safety protocols, new refund policies for guests, and innovations like virtual experiences. While these moves prioritized guests and helped sustain demand, they also alienated hosts who were burdened with compliance costs. Uber Eats, facing an influx of users on both ends, expanded into grocery delivery, adjusted rider compensation, and maintained high service reliability. Its strategy focused on attracting diners, recognizing that restaurants were already dependent on such platforms to remain operational.

Prosper, dealing with diverging user incentives, opted for structural adjustments. The platform tightened credit policies, enhanced borrower verification, and offered payment relief options to reinforce trust among lenders. These steps helped restore balance between supply and demand of funds and minimized default risks. Notably, Prosper also benefited from federal support, including a loan through the U.S. Paycheck Protection Program, to maintain operations during the crisis.

In all three cases, platform strategies were not equally distributed between user groups. The study highlights that real-world platforms rarely treat both sides symmetrically. Instead, platforms typically support the side that offers stronger network leverage or is harder to attract. These strategic biases are evident in how Airbnb favored guests, Uber Eats favored diners, and Prosper prioritized lenders. This asymmetry, while not built into the authors’ baseline framework, is acknowledged as a crucial factor influencing recovery trajectories.

Are crisis-induced changes reversible in the long term?

The long-term sustainability of sharing economy platforms hinges on whether crisis-driven changes in user behavior and platform strategy are reversible. The study draws on theories of path dependency and behavioral lock-in to explain how crises can permanently alter organizational trajectories and consumer habits.

Airbnb’s post-crisis rebound exemplifies this. While initial user activity dropped sharply, the platform recovered by the second quarter of 2021 and later surpassed pre-crisis metrics. Yet the nature of its business changed. Longer stays, domestic travel, and hybrid work arrangements became more common, reflecting a shift in both demand and supply patterns. Airbnb also adjusted its strategic orientation, initially focusing on guest satisfaction during the crisis, and later turning to host recruitment and retention as travel resumed.

For Uber Eats, the crisis catalyzed enduring growth in user numbers. While restaurant participation dipped slightly post-crisis due to concerns over platform fees and control, it eventually recovered. The platform diversified further by forming partnerships with alcohol, grocery, and flower delivery services. Strategic initiatives were also introduced to better support small restaurants, demonstrating adaptability to stakeholder needs and maintaining long-term revenue growth.

Prosper’s case illustrates the complex dynamics of restoring trust. While borrower participation increased due to tighter bank credit, lender hesitancy persisted initially. Through sustained policy adjustments and data transparency, Prosper gradually rebuilt confidence. Default rates remained lower than peers in the global P2P lending market, validating the platform’s risk management strategy. The firm not only weathered the crisis but secured new capital investments, solidifying its position as the largest U.S. crowdlending platform.

To sum up, the study asserts that the long-term success depends on how platforms respond not only during but also after crises. Behavioral and institutional inertia can either entrench gains or perpetuate losses. Platforms that adapt, re-engage neglected user groups, and rebalance their strategies are more likely to survive and thrive in a post-crisis environment.