Operations Management Problems in the Application of P2P Platforms: Impacts and Regulation

Peer-to-peer (P2P) platforms have experienced remarkable growth, driven by advancements in internet technology and mobile applications. This rapid expansion has reshaped markets and introduced complex dynamics that warrant deeper exploration. This dissertation focuses on three critical dimensions of this field: the impact of platform introduction, platform regulation, and environmentally sustainable platform operations.

First, we study how the emergence of ride-hailing platforms has impacted the automotive industry by influencing both the sales and rental markets. Dealers and rental agencies, which once operated in separate markets, have become indirect competitors because car owners in the sales market offer rides to consumers in both the sales and rental markets through the platform. Therefore, to fully understand the platform’s impact, it is essential to consider these markets simultaneously. To this end, we develop a comprehensive model incorporating the manufacturer, dealer, and rental agency to analyze how a platform’s presence influences firm decisions and total car ownership. We show that the dealer increases its orders for products with high marginal costs due to the value enhancement effect, wherein car ownership becomes more valuable with the presence of a platform. Importantly, we find that neglecting the rental market - as most of the existing literature does - underestimates this effect. While the value enhancement effect does not extend to the rental market, a platform's presence may motivate the rental agency to increase its orders for products with low marginal costs and new-car valuation. However, the increase in rental cars is generally relatively modest compared to the decrease in personally owned cars, resulting in an overall increase in total ownership only for products with sufficiently high marginal costs and rental-car valuation. Moreover, we show that failing to consider both markets and their interactions may lead to inaccurately assessing the total change in ownership compared to the platform's absence. Finally, we discuss the implications of car owners' partial or heterogeneous participation rate in the platform and demonstrate that our results generally hold.

Second, we focus on the 90-day cap regulation in San Francisco and Berkeley to investigate the effectiveness of this supply restriction in improving the affordability of housing in the city. We specifically investigate 1) whether the regulation accurately targets landlords in the sharing market and increases the supply in the local long-term rental market and 2) whether the regulation achieves its goal of making housing more affordable for the targeted lower-income population in the city. We exploit a detailed dataset on Airbnb and Zillow in this empirical analysis. Using standard DID regression analysis, the paper finds that the regulation significantly decreased the listing number by about 29.6% and increased the overall average daily rate of short-term rentals by about 14.6% on the platform while decreasing the average price of long-term rentals by about 4.1% in the local residential market, in the year following the enforcement of the regulation. Meanwhile, we find that the benefit of the regulation effectively targeted affordable homes in the long-term rental market but did not affect the high-end and single-family markets significantly. In particular, using quantile DID methods, we show that the regulation only reduces the average rental price (of all types of homes) in only about 30% of the lower end of the local long-term rental market. The regulation also made a heterogeneous impact on different types of listings on the platform, making hosted listings increase their supply and benefit from the spillover effects, especially since it works efficiently to figure out landlords and sharers for multi-home host listings.

Third, we examine a ride-hailing platform's optimal subsidy design to increase electric vehicle (EV) adoption among drivers, which has been a key operational goal for P2P platforms as they increasingly prioritize sustainability. To this end, we model the choices made by drivers when selecting between gasoline gasoline vehicles (GVs) and EVs, considering the heterogeneity of drivers in their time costs. We examine how market segments are shaped by differences in the marginal costs of usage and prices between the two types of vehicles. These analyses reveal the distinct trade-offs faced by drivers with high supply compared to those with low supply. Motivated by practice, we consider three types of subsidies a platform may adopt to achieve full adoption of EVs, i.e., set-up bonuses, earning boosts, and charging discounts. We find that the earning boost subsidy consistently drives greater EV usage than the other subsidy types. However, we also find that a profit-driven platform is more likely to favor earning boosts when its per-unit profit is relatively high, even if this may not align with the most environmentally beneficial outcomes. This highlights the need for careful consideration of the platform’s subsidy design, as profit-maximizing strategies might conflict with environmental objectives.