• 아태비즈니스연구
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• 제14권3호
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• pp.241-250
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• 2023

Purpose - The purpose of this study was to investigate the perception of 'unmanned cafes' on the network through big data analysis, and to identify the latest trends in rapidly changing consumer perception. Based on this, I would like to suggest that it can be used as basic data for the revitalization of unmanned cafes and differentiated marketing strategies. Design/methodology/approach - This study collected documents containing unmanned cafe keywords for about three years, and the data collected using text mining techniques were analyzed using methods such as keyword frequency analysis, centrality analysis, and keyword network analysis. Findings - First, the top 10 words with a high frequency of appearance were identified in the order of unmanned cafes, unmanned cafes, start-up, operation, coffee, time, coffee machine, franchise, and robot cafes. Second, visualization of the semantic network confirmed that the key keyword "unmanned cafe" was at the center of the keyword cluster. Research implications or Originality - Using big data to collect and analyze keywords with high web visibility, we tried to identify new issues or trends in unmanned cafe recognition, which consists of keywords related to start-ups, mainly deals with topics related to start-ups when unmanned cafes are mentioned on the network.

• 한국인터넷방송통신학회논문지
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• 제19권3호
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• pp.1-7
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• 2019

공부하는 트렌드에 변화가 일어나며 단순히 공부하는 공간이 아닌, 복합 문화 환경으로 거듭나야 새로운 수요층의 욕구를 충족할 수가 있다. 답답한 도서관이나 독서실에 비해 비교적 자유롭고 쾌적함에 주목을 받고 있는 스터디카페는 인건비 절감을 통해 보다 큰 이익을 창출할 수 있는 무인 시스템에 적합하다. 하지만 이를 체계적으로 관리해 줄 수 있는 시스템이 아직 미흡하여 보완이 필요하다. 따라서 본 논문에서는 무인 스터디카페를 통합적으로 관리해주고 부가적인 기능을 통해 사용자에게 편의성을 제공하는 안드로이드 애플리케이션을 개발하였다. 사용자와 관리자를 구분하여 사용자는 좌석 예약 및 조회 등을 통하여 해당 지역의 원하는 스터디카페를 이용할 수 있도록 구성하였다. 관리자는 좌석 및 회원을 관리하고 스터티카페의 현재 상황을 외부에서도 확인할 수 있도록 하였다. 부가적으로 커뮤니티 및 소음 측정과 회원의 이용 시간 시각화 기능 등도 추가하여 애플리케이션의 활용도를 높였다.

• 디지털산업정보학회논문지
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• 제20권2호
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• pp.37-47
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• 2024

The food tech market, which uses artificial intelligence robots for the restaurant industry, is gradually expanding. Among them, the robot barista, a representative food tech case for the restaurant industry, is characterized by increasing the efficiency of operators and providing things for visitors to see and enjoy through a 24-hour unmanned operation. This research was conducted through text mining analysis to examine trends related to robot baristas in the restaurant industry. The research results are as follows. First, keywords such as coffee, cafe, certification, ordering, taste, interest, people, robot cafe, coffee barista expert, free, course, unmanned, and wine sommelier were highly frequent. Second, time, variety, possibility, people, process, operation, service, and thought showed high closeness centrality. Third, as a result of CONCOR analysis, a total of 5 keyword clusters with high relevance to the restaurant industry were formed. In order to activate robot barista in the future, it is necessary to pay more attention to functional development that can strengthen its functions and features, as well as online promotion through various events and SNS in the robot barista cafe.