Characteristics and influencing factors of Airbnb spatial distribution in China’s rapid urbanization process: A case study of Nanjing

Abstract

As in other countries, short-term rentals for tourism services are growing rapidly in China’s tourist cities, which are mainly operated through Airbnb. This paper explores whether the spatial distribution of Airbnb in China’s rapid urbanization process exhibits characteristics, paths, and drivers that are different from those of cities in other countries. Airbnb is a model for the global sharing economy, but it is increasingly influenced by other functions and facilities in cities as it grows. In this paper, the zero-expansion negative binomial regression was used to study the factors affecting the spatial distribution of Airbnb in Nanjing, China. The results showed that the spatial distribution of Airbnb listings was correlated with the distribution of cultural attractions, universities, public transport accessibility, shopping centers, and business apartments. By analyzing the driving forces of Airbnb’s development in Nanjing, this paper found that a large number of business apartments developed in cities were essential providers of Airbnb listings, and affected its spatial distribution. The gap between short-term and long-term rentals was also correlated with the distribution of Airbnb. In addition, similar to the previous literature findings, the increase in the proportion of professional hosts changes the original intention of Airbnb for sharing and communication. Our empirical results applies to the current situation of Airbnb in Chinese cities, which is conducive to the government’s more intelligent management and effective promotion of the Airbnb market. Our findings also provide positive references for urban renewal policies and public participation methods in China.

¿Nueva disputa o vieja convivencia? Airbnb y el mercado de viviendas de alquiler en pequeñas ciudades turísticas brasileñas

“…Em cidades praianas espanholas, o litoral se mostrou um atrator de unidades enquanto centralidade turística (Cerezo-Medina et al, 2021). A distribuição de universidades, transporte público, shopping centers e apartamentos de negócios também está correlacionada com a distribuição e territorialização de unidades do Airbnb (Sun et al, 2021).…”

Spatiotemporal Patterns and Socioeconomic Influences on Host Participation in Short-Term Rental Markets: Airbnb in San Francisco

“…Another key strand of research, particularly relevant to our study, is the spatial patterns of the sharing economy. In this area, several studies have analyzed geographic distributions of Airbnb properties in a number of major world cities such as New York City [21][22][23], Los Angeles [24,25], and San Francisco [26] in the United States; Syndey, Australia [27]; Madrid, Spain [28]; and Nanjing, China [29]. In some of these studies, the authors have examined spatial patterns of Airbnb properties to understand the motivations of hosts or the supply side actors.…”

Research on Design Strategy of B&B: Based on Text Mining and Machine Learning Method

“…Sun et al studied the factors affecting the spatial distribution of Airbnb in Nanjing of China by using the zeroexpansion negative binomial regression [7].…”