Online platforms depend heavily on sustained user engagement and high-quality content to generate revenue through advertising impressions and by receiving a portion of tips, where users financially reward content creators directly, providing platforms with an additional revenue stream. To achieve these goals, platform owners implement strategic mechanisms that incentivize continuous participation and content production. Two crucial mechanisms in this regard are peer-driven financial support (tipping) and platform-driven incentive systems, both significantly impacting user behavior, content quality, and platform profitability. Understanding these mechanisms is essential for platform owners to optimize engagement strategies, maximize advertising revenue, and effectively leverage direct financial interactions. In the first essay, I examine tipping behavior and develop a model wherein users determine tip amounts based on their beliefs about an evolving tipping norm, as well as content quality, personal characteristics, and contextual factors. These beliefs are derived from two primary signals: the tips that I receive directly and those I observe others giving to similar content. A novel aspect of my model allows for the correlation of these signals within a type, across different types, and over time. Through Bayesian updating, users assimilate these signals into their perception of the prevailing tipping norm. My findings reveal that both signals significantly influence user behavior, with tips received playing a more decisive role. I further show that tip amounts are primarily driven by the inferred tipping norm, followed by the quality of the content and individual user characteristics. Prediction exercises suggest that strategic information disclosure on the platform can significantly influence tipping behavior even in later stages. In the second essay, I quantify the effects of peer and platform rewards on the quantity and quality of user-generated content. My analysis indicates that monetary rewards from peers, such as tips, robustly increase the frequency and length of user posts, while monetary rewards from the platform promote longer submissions at the cost of posting frequency. Moreover, although individual non-monetary rewards (likes) exert a modest influence, their cumulative volume markedly enhances content production. I also find that non-monetary platform rewards (badges) exhibit a nonlinear effect, with content generation declining upon reaching a milestone and subsequently rising as users approach the next target. These findings offer valuable guidance for designing effective reward systems that encmy age desired sustainable user engagement.