Factors Influencing the Blocking of Airbnb Listings: A Detailed Analysis

Home sharing has expanded rapidly within the platform economy. This study evaluates which listing- and host-level attributes are associated with blocking decisions on Airbnb using two New York City datasets (20142016). We summarize price, review, and suspension distributions and then estimate a logistic model that relates the probability of being blocked to log price, Superhost status, review volume, and unit type. Results indicate that higher posted prices and thin reputational histories are linked to a greater likelihood of removal, whereas Superhost oversight substantially lowers risk. A portfolio view reveals a mass of zero suspensions with a persistent right tail, implying that once flagged, some listings remain offline for extended periods. The findings suggest practical steps for hosts and the platformmoderate pricing, accelerate early reviews, and monitor high-intensity operations; the approach can be extended to multi-city panels.