빅데이터 분석을 활용한 외식기업의 ESG경영에 관한 연구

This study conducted an analysis of big data by using text mining, to examine consumers’ perceptions of ESG management of food service corporations and social issues about it. Keywords regarding food service companies’ ESG management were collected, from portal sites such as Naver, Daum, Google, etc. A total of 15,651 keywords were extracted and a total of 80 keywords were selected at higher ranks, except for unnecessary ones. Analyses of consumers’ perceptions of food service companies’ ESG management by using UCINET 6 and NetDraw showed the following: First, the degree centrality was highest for ‘food service industry’, followed by ‘global’, ‘business’, ‘activity’, ‘support’, ‘society’, ‘environment’, ‘Korea’, etc. Second, the eigenvector was highest for ‘global’, followed by ‘activity’, ‘food service industry’, ‘USA’, ‘chairman’, ‘business’, ‘Korea’, ‘group’, etc. Finally, the CONCOR analysis was conducted to show that keywords were divided into six groups: ‘ESG management trend’, ‘non-financial attention’, ‘interest in restaurants’, ‘MSCI assessment’, ‘extension of franchises’ and ‘global activity’. Based on the findings, consumers’ perceptions of food service corporations’ ESG management and issues about it were understood. This study is expected to contribute to establishing marketing strategies for the sustainable growth of food service corporations, by providing basic data about food service corporations’ ESG management.