Digital platforms are growing rapidly, leading to increased competition. While conventional wisdom posits that in competitive arenas some platforms will flourish and others might decline, the nuanced dynamics of digital platform competition can sometimes yield mutual benefits. This dissertation examines these dynamics and the resultant spillovers across diverse digital platforms.

The first chapter studies the spillovers between entrant and incumbent platforms. We study the impacts of cost-effective token incentives in the competition between two decentralized exchange platforms. The entrant platform, Sushiswap, launched token incentives to lure liquidity providers away from the incumbent, Uniswap, who then retaliated with its own token incentives. Our analysis shows that the incumbent's own token incentives attract more liquidity to the platform. Yet, surprisingly, the token incentives from its competitor also bring more liquidity and trade volume to the incumbent. We further examine the potential mechanisms by analyzing the role of network effects and information diffusion.

The second chapter analyzes the spillovers between a dominant digital market and its competitors. We investigate the potential impact of consumer experiences on Amazon.com in fostering a broader market comfort in the online retail landscape. Specifically, we focus on the adoption of Amazon Prime, a paid membership that lowers transaction costs on Amazon. Using a bank transaction panel, our findings indicate that after adopting Prime, adopters increase their spending on non-Amazon retailers. However, this increase occurs only among novice users of the digital market. Adopters demonstrate additional evidence of increased market comfort: stronger increases in apparel merchants than in electronics, and increased rates of online returns and variety of stores purchased from.

The third chapter evaluates spillovers induced by different market structures. The cryptocurrency exchange landscape has experienced heightened market fragmentation due to the emergence of numerous trading platforms. Beyond the surge of traditional centralized exchanges (CEXs) like Binance, the accelerated growth of decentralized exchanges (DEXs), exemplified by Uniswap, further intensifies this trend. We focus on the effects of new market entrants, both CEXs and DEXs, on the aggressiveness of token pair orders and price impact. Our findings reveal distinct influences exerted by CEXs and DEXs. While both augment trade volume (in USD) and elevate order submission aggressiveness, the underlying mechanisms diverge. CEXs see an uptick in the number of trades without a corresponding rise in trade size. DEXs, conversely, often report larger individual trades without a surge in their frequency, possibly attributed to substantial blockchain transaction fees and the inherent price predictability due to automated pricing on DEXs. Notably, CEX fragmentation broadens the overall spread, whereas DEXs don't exhibit a significant sway.

The characterization of the pressure-related turbulence terms including pressure–rate-of-strain, pressure diffusion and velocity–pressure-gradient tensor in the Reynolds stress transport equation in canonical turbulent flows is of critical importance for calibrating and improving turbulence models for RANS (Reynolds-Averaged Navier Stokes) based flow simulation. It demands very accurate measurements of the instantaneous velocity fields and the instantaneous pressure fields, which require precise measurement systems and techniques. A water tunnel facility was built at the San Diego State University with the necessary flow quality to perform the measurement of the instantaneous velocity fields using Time-Resolved Tomographic PIV. To ensure the accuracy of the pressure measurement a PIV-based pressure technique called rotating parallel ray omnidirectional integration was developed and it was shown to be very robust and accurate. The rotating parallel ray omnidirectional integration was applied to several cases from the instantaneous pressure measurement around a rising bubble, water surface elevation mapping, density reconstruction and analytical model validation showing a wide scope of applications. Those developments enabled the measurement of all the terms of the Reynolds stress equation for a turbulent shear layer flow impinging on a cavity trailing corner at a 4.0×10^4 including the velocity–pressure-gradient tensor. This new data on the cavity flow provides the opportunity to test and develop Reynolds stress models to improve flow simulation.