This research examines the impacts of locational variables on the price of Airbnb listings. With a web-scraped sample of more than 10000 Airbnb units in Beijing, this research adopts the hedonic pricing theory as the theoretical approach and presents spatial econometric models of Airbnb apartments to test the effects. The results show that proximity to city center and airport have significant positive impacts on price whereas proximity to high-speed railway stations has significant negative impact on price. Though OLS model shows that the effects of proximity to subway stations and tourist spots are positive, these effects are not significant when spatial autocorrelation are considered in the regression models. These findings are useful for Airbnb hosts to form reasonable pricing strategies for their listings and also for P2P lodging platforms to conduct more in-depth analysis.