What effect the demand for homestays: evidence from Airbnb in China

ABSTRACT

Using multi-ordered logit models dealing with influence factors on the homestay demands under collaborative consumption, and crawling the dataset of Airbnb listings from provincial cities or municipal cities in China, this paper concludes that the economic factor, the characteristics and locations of homestays are the fundamental factors. To be specific, the rental prices have significant negative effects on homestays demand in developed regions in China, while positive effects in underdeveloped areas. Meanwhile, the characteristics such as the count of bedrooms and types of homestays have significant impacts on the demand for homestays in most regions, and family-travelling is very popular in China.

KEYWORDS:

• Homestay
• multi-ordered logit model
• demand
• effect factor
• airbnb

JEL CLASSIFICATION:

• D12
• C51

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by Scientific Research Fund of Hunan Provincial Education Department [19C0798].