Earticle

초록

영어

This study explores the spatiotemporal expansion patterns of Airbnb hosts by applying the K-shape time-series clustering algorithm to host-level panel data. The analysis covers two periods—pre-pandemic (June 2014–December 2019) and post-pandemic (March 2021–July 2024)—while excluding the COVID-19 disruption phase. Hosts’ property expansion trajectories were examined over 24- and 36-month windows to identify recurring temporal patterns. The results reveal multiple forms of expansion and contraction behaviors, ranging from gradual and sustained growth to temporary decline and recovery. Comparing the two periods shows that post-pandemic host operations became more stable and less volatile. The study contributes to the literature on business expansion and professionalization in short-term rentals and provides practical insights for policymakers and platform managers aiming to foster sustainable and balanced market development.

목차

Abstract
Introduction
Literature review
Business expansion, contraction, and the importance of pattern exploration
Multi-unit hosts and spatial patterns in STRs
Method
Data collection
K-Shape time-series clustering
Data preprocessing and analytical procedure
Results
Cluster test
Main results
Conclusion
Acknowledgments
References

키워드

저자

• 엄태휘 [ 경희대학교 호텔관광대학 ]
• 전재헌 [ 광운대학교 경영대학 ]
• 구철모 [ 경희대학교 호텔관광대학 ]
• 정남호 [ 경희대학교 호텔관광대학 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국경영정보학회 정기 학술대회 [KMIS Conference]

• 간기

  반년간

• 수록기간

  1990~2025

• 십진분류

  KDC 325 DDC 658