경영정보학연구 (Information Systems Review)

  • 제25권4호
  • /
  • Pages.89-112
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  • 2023
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  • 2982-6551(pISSN)
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  • 2982-6837(eISSN)
한국경영정보학회 (The Korea Society of Management Information Systems)
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감염병 확산에 따른 레스토랑 선택속성 변화 분석: 텍스트마이닝 기법 적용

Analysis of Changes in Restaurant Attributes According to the Spread of Infectious Diseases: Application of Text Mining Techniques

  • 유준일 (경희대학교 스마트관광원) ;
  • 이은지 (경희대학교 스마트관광원) ;
  • 구철모 (경희대학교 스마트관광원)
  • Joonil Yoo (Smart Tourism Education Platform, Kyung Hee University) ;
  • Eunji Lee (Smart Tourism Education Platform, Kyung Hee University) ;
  • Chulmo Koo (Smart Tourism Education Platform, Kyung Hee University)
  • 투고 : 2023.06.21
  • 심사 : 2023.08.27
  • 발행 : 2023.11.30
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초록

2020년 3월, 코로나바이러스 팬데믹으로 선포되면서, 다양한 방역 조치가 취해져 왔다. 이에 따라, 관광 및 환대 산업 내의 많은 변화들이 야기되었다. 특히 레스토랑 산업에서는 비대면 서비스 및 좌석 간 거리두기 등 방역 지침이 시행되었다. 전통적으로 레스토랑 선택속성에 대한 연구는 분위기, 서비스 품질, 음식의 품질을 포함한 3가지 속성의 중요성이 강조해 온 데 반해, 코로나19 이후 레스토랑 이용자를 대상으로 레스토랑 선택속성을 탐색한 연구는 미비한 실정이다. 이에 따라, 본 연구에서는 코로나19라는 환대 산업 내의 환경적 변화에 대한 이해에 기반하여, 국내 온라인 리뷰 데이터 상에서 새로운 레스토랑 경험적 속성을 확인하기 위한 탐색적인 접근을 시도하였다. 본 연구는 서울 을지로 지역에 위치한 일반음식점 및 휴게음식점 475개로 네이버 플레이스에 등록된 총 31,115개의 온라인 리뷰를 분석 단위로 고려하였다. 분석 방법은 단어 빈도와 역문서 빈도의 곱으로 산출된 TF-IDF와 잠재적 토픽들을 추출하는 확률적 모델 알고리즘인 LDA 토픽모델링 기법을 통해 온라인 리뷰 내에서 단어들의 군집화를 통해 레스토랑 선택속성을 재분류하고자 하였다. 분석 결과, 분위기, 서비스 품질, 음식 품질과 함께 코로나19 이후 레스토랑의 새로운 속성으로 "감염병 예방"요인이 도출되었다. 본 연구는 기존 레스토랑 선택속성에서 제시하는 세 가지 속성들을 범주화하고, 나아가 새로운 속성을 제시하였다는 점에서 기존 레스토랑 선택속성 문헌을 확장하여 학술적 의의가 있다. 나아가, 분석 결과에 기반하여 레스토랑 운영의 측면 및 정책적 관점에서의 실무적 제언을 시도하였다.

In March 2020, as it was declared a COVID-19 pandemic, various quarantine measures were taken. Accordingly, many changes have occurred in the tourism and hospitality industries. In particular, quarantine guidelines, such as the introduction of non-face-to-face services and social distancing, were implemented in the restaurant industry. For decades, research on restaurant attributes has emphasized the importance of three attributes: atmosphere, service quality, and food quality. Nevertheless, to the best of our knowledge, research on restaurant attributes considering the COVID-19 situation is insufficient. To respond to this call, this study attempted an exploratory approach to classify new restaurant attributes based on understanding environmental changes. This study considered 31,115 online reviews registered in Naverplace as an analysis unit, with 475 general restaurants located in Euljiro, Seoul. Further, we attempted to classify restaurant attributes by clustering words within online reviews through TF-IDF and LDA topic modeling techniques. As a result of the analysis, the factors of "prevention of infectious diseases" were derived as new attributes of restaurants in the context of COVID-19 situations, along with the atmosphere, service quality, and food quality. This study is of academic significance by expanding the literature of existing restaurant attributes in that it categorized the three attributes presented by existing restaurant attributes and further presented new attributes. Moreover, the analysis results have led to the formulation of practical recommendations, considering both the operational aspects of restaurants and policy implications.

키워드

과제정보

이 논문은 2023년 대한민국 교육부와 한국연구재단의 지원을 받아 수행된 연구임(NRF-2023S1A5C2A03095253).

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