코로나19 발생 후 외식산업 연구주제에 대한 연구

Abstract

The purpose of this study is to find ways to develop the food service industry through analysis of research trends related to the food service industry after COVID-19. In this study, through detailed search on RISS, 133 papers related to 'food service' with English abstracts were analyzed using R package to analyze keyword frequency, word clouding, keyword network analysis, LDA topic modeling, and TF, TF.-IDF verification was performed. The analysis results are as follows. First, as a result of keyword frequency analysis and word clouding, it was found that keywords related to service, food, restaurant, intention, customer, consumer, satisfaction, quality etc. were frequently used. In addition, the appearance of delivery and covid related to Corona 19 was confirmed. Second, As a result of word network analysis, each word was related to food, customer, franchaise, company, brand, consumption, consumer, etc. centering on service, and it was found that business, job, hmr, relationship, convenience, performance, foodservice, etc. were studied separately. Third, as a result of TF and TF-IDF analysis, words related to COVID-19 such as stress, honbab, stability, coffee, complain, solo, hmr, conflict, retro, and eatingout did not appear in Hi-TF, but appeared in Hi-TF-IDF. From this, it can be seen that COVID-19 is having a great impact on the food service industry. Finally, as a result of LDA topic modeling, the appropriate number of topics was found to be 10, which is being studied as the subject of delivery, franchise, HMR, corporate strategy, employee, customer satisfaction, COVID-19, globalization, customer attributes, and store environment according to each characteristic. confirmed.