Asymmetric Location Configurations Shaping Hot/Cold Spots Of Airbnb Guest Engagement: A Mixed-Method Analysis Framework

Document Type

Article

Publication Date

1-1-2026

School

Marketing

Abstract

This study examines spatial hot and cold spots of Airbnb guest engagement and the asymmetric location configurations shaping them. We propose a novel mixed-method framework combining qualitative and quantitative approaches, including hot spot analysis, fuzzy-set qualitative comparative analysis (fsQCA), and spatial statistical techniques to analyze Airbnb listings and point of interest data from London. Results reveal distinct spatial patterns driven by guest engagement and listing supply across property types, revealing a significant spatial mismatch between market demand and property supply. Findings highlight the asymmetric and context-dependent effects of location factors on the hot and cold spots of guest engagement. By advancing the application of fsQCA in spatial analysis, this study provides an effective analytical framework for understanding Airbnb's spatial dynamics. The results offer actionable insights for hosts, platforms, and policymakers seeking to optimize guest engagement and promote sustainable urban tourism through strategic location planning.

Publication Title

International Journal of Hospitality Management

Volume

132

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