지능정보연구 (Journal of Intelligence and Information Systems)

  • 제27권3호
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  • Pages.1-27
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  • 2021
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  • 2288-4866(pISSN)
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  • 2288-4882(eISSN)
한국지능정보시스템학회 (Korea Intelligent Information System Society)
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COVID-19 팬데믹에서 Airbnb 호스트의 마케팅 전략의 변화가 공유성과에 미치는 영향

The Effect of Changes in Airbnb Host's Marketing Strategy on Listing Performance in the COVID-19 Pandemic

  • 김소영 (국민대학교 데이터사이언스학과) ;
  • 심지환 (국민대학교 데이터사이언스학과) ;
  • 정여진 (국민대학교)
  • 투고 : 2021.05.13
  • 심사 : 2021.09.14
  • 발행 : 2021.09.30
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초록

전 세계적인 COVID-19의 유행으로 인해 관광산업 전반이 큰 타격을 받고 있다. 최근 공유경제의 확산으로 팽창되고 있는 Airbnb와 같은 숙박 공유서비스는 공급자와 수요자 간의 신뢰와 소통을 기반으로 거래가 이루어지기 때문에 팬데믹으로 인한 영향을 특히 크게 받고 있다. 팬데믹 상황이 개인의 여행에 대한 인식과 행동을 변화시킴에 따라 이를 개선하기 위한 전략에 대한 논의가 이루어지고 있지만 대부분의 연구는 전통적인 외식업, 숙박업 공급자와 정부 측면의 거시적 전략을 제시하고 있다. 본 연구는 Peer-to-Peer 거래 중심의 공유경제의 특수성을 고려하여 COVID-19 팬데믹 발생 전후로 Airbnb 개별 호스트의 마케팅 전략의 변화가 공유성과에 미치는 영향을 실증적으로 분석함으로써 개별 호스트 측면의 팬데믹 전략에 대해 논한다. Airbnb의 호스트가 본인의 시설을 홍보하는 통로인 시설소개 텍스트를 수집하여 딥러닝 기반 특성추출방법인 Attention-based aspect extraction 모델로부터 9개의 주요 특성을 추출하였다. 추출된 특성이 해당 텍스트에서 등장하는 빈도가 COVID-19 발생 전후 변화량을 측정하여 이것이 공유성과에 미치는 영향을 분석하였다. 또한 이러한 영향을 숙박시설의 유형 간에 비교함으로써 시설 유형별 효과적으로 작용하는 특성을 관찰하였다. 회귀분석 결과 주방시설, 정원, 호스트와의 교류 순으로 공유성과에 긍정적인 영향을 보이지만 시설 유형에 따라 공유성과에 미치는 영향은 다소 차이가 있었다. 특히 집 전체를 대여하는 경우 개인실 대여에 비해 주방시설에 대한 설명이 상당한 효과를 보여주었다. 이를 통해 본 연구는 공유숙박 서비스의 개별 서비스 제공자가 시설의 종류에 따라 취할 수 있는 팬데믹 위기 대처전략에 대한 아이디어를 제시한다.

The entire tourism industry is being hit hard by the COVID-19 as a global pandemic. Accommodation sharing services such as Airbnb, which have recently expanded due to the spread of the sharing economy, are particularly affected by the pandemic because transactions are made based on trust and communication between consumer and supplier. As the pandemic situation changes individuals' perceptions and behavior of travel, strategies for the recovery of the tourism industry have been discussed. However, since most studies present macro strategies in terms of traditional lodging providers and the government, there is a significant lack of discussion on differentiated pandemic response strategies considering the peculiarity of the sharing economy centered on peer-to-peer transactions. This study discusses the marketing strategy for individual hosts of Airbnb during COVID-19. We empirically analyze the effect of changes in listing descriptions posted by the Airbnb hosts on listing performance after COVID-19 was outbroken. We extract nine aspects described in the listing descriptions using the Attention-Based Aspect Extraction model, which is a deep learning-based aspect extraction method. We model the effect of aspect changes on listing performance after the COVID-19 by observing the frequency of each aspect appeared in the text. In addition, we compare those effects across the types of Airbnb listing. Through this, this study presents an idea for a pandemic crisis response strategy that individual service providers of accommodation sharing services can take depending on the listing type.

키워드

과제정보

본 연구는 산림청(한국임업진흥원) '산림과학기술 연구개발사업(2019150B10-2123-0301)'의 지원에 의하여 이루어진 것입니다.

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