• Asia-Pacific Journal of Business
• /
• v.14 no.3
• /
• pp.241-250
• /
• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.3
• /
• pp.1-7
• /
• 2019

The trend of studying is changing, and it is not a place to study but also a new cultural environment. The study cafe, which is relatively free and comfortable compared to a stuffy library or reading room, is suitable for an unmanned system that can generate greater profits by reducing labor costs. However, the system that can manage this systematically is still insufficient and needs to be supplemented. In this paper, we developed an Android application that integrates the unattended study cafe and provides convenience to users through additional functions. The user and the manager are separated so that the user can use the desired study cafe in the corresponding region through reservation and inquiry of the seat. The manager manages seats and members and allows the outside of the cafeteria to check the current situation. In addition, community and noise measurements and member time visualization capabilities have been added to enhance application utilization.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.20 no.2
• /
• pp.37-47
• /
• 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.