인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 저자정보
피인용 0
초록·키워드
This study aims to analyze the consumer perception structure for personalization of food service using big data. Online text data were collected from Naver, Daum, and Google from June 1, 2023 to May 31, 2026 using the keywords “foodservice + personalization.” A total of 2,945 documents were collected and refined through preprocessing. Keyword frequency analysis and semantic network-based CONCOR analysis were then conducted using the top 50 keywords. The frequency analysis showed that Personalization, Foodservice, and Foodservice Industry were the most frequently appearing keywords, followed by Trend, Service, Consumption, Customer, Menu, Food, and Data. The CONCOR analysis classified the keywords into four groups: Consumer Lifestyle and Food Choice, Personalization Technology and Business Strategy, Delivery Platform Consumption Trends, and Payment and Consumer Benefits. These results indicate that foodservice personalization is perceived not only as a recommendation function based on individual preferences but also as a multidimensional concept associated with lifestyle, health, food choice, digital technology, data utilization, platform services, business strategy, delivery consumption, and consumer benefits. This study contributes to understanding foodservice personalization from the perspective of consumer perceptions expressed in naturally generated online text data. The findings also provide practical implications for foodservice companies and digital platform operators in developing personalized services, recommendation functions, customer management strategies, and differentiated consumer benefits.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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