Affiliation:
1. Old Dominion University, Norfolk, VA, USA
Abstract
Airbnb is an Internet-based firm that connects potential short-term renters with hosts who own or control rental properties. Its rapidly expanding activities are tracked by Airdna, an independent firm that generates seemingly conventional performance metrics describing Airbnb. These metrics include occupancy rates, average daily rates, and revenue per available room. However, Airdna does not adhere to long-established STR definitions for these variables. Using data from Virginia Beach, Virginia, we demonstrate that Airdna’s performance metrics exhibit notable upward biases vis-á-vis STR’s metrics. Potential rental hosts, hoteliers, tax collectors, and investors are at risk if they act on the assumption that Airdna’s metrics are comparable with widely understood measures used by STR and tourism experts.
Subject
Tourism, Leisure and Hospitality Management
Cited by
22 articles.
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