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Big Data-Based Analysis of Consumer Behavior in Global Chicken Franchises -Deriving Success Factors and Proposing Strategies for Overseas Expansion Through a Comparative Analysis of BBQ and KFC's Localization Strategies-

첫 페이지 보기
  • 발행기관
    국제인공지능학회(구 한국인터넷방송통신학회) 바로가기
  • 간행물
    The International Journal of Advanced Smart Convergence 바로가기
  • 통권
    Volume 14 Number 3 (2025.09)바로가기
  • 페이지
    pp.266-273
  • 저자
    Seung-hoon Cho, Gi-Hwan Ryu, Yoon-pyo Hong, Sung-jun Kim
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A474333

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원문정보

초록

영어
This study addresses the need to understand brand success by analyzing a crucial source of customer feedback: online reviews. We designed a comparative analysis to investigate the different factors that drive the success of two major fast-food brands, BBQ and KFC, in the competitive market. To achieve this, we combined several advanced analytical techniques, including text mining, sentiment analysis, TF-IDF, and CONCOR network analysis, to systematically process and evaluate their respective customer review data. Our results from the sentiment analysis showed that both brands garnered strong positive feedback, progressing from 'satisfaction' to 'recommendation' and 'best.' The TF-IDF analysis successfully identified key keywords for each brand, while the CONCOR network analysis revealed distinct competitive clusters: 'quality, localization, and service' for BBQ and 'price, convenience, and global' for KFC. These findings provide valuable insights into brand strategy. The effects of this study are the proposal of four major success factors— advanced localization, quality control, data capability strengthening, and local partnerships—which offer a strategic framework for businesses operating in this industry.

목차

Abstract
1. Introduction
2. Related Work
2.1 Big Data and Sentiment Analysis
2.2 TF-IDF And Network Analysis
3. Research Methods
3.1 Data Collection
3.2 Analysis Procedure
4. Analysis Results
4.1 TF-IDF Keyword Comparative Analysis
4.2 Comparison of Detailed Sentiment Category Frequencies
4.3 Comparison of Localization Networks as Core Keywords
5. Conclusion
References

키워드

Big Data Analysis Sentiment Analysis TF-IDF Network Analysis Consumer Behavior Localization Strategy

저자

  • Seung-hoon Cho [ Master D. Student, Department of Tourism and Food Industry, Graduate School of Smart Convergence, Kwangwoon University, Seoul, Korea ]
  • Gi-Hwan Ryu [ Professor, Department of Tourism and Food Industry, Graduate School of Smart Convergence, Kwangwoon University, Seoul, Korea ] Corresponding Author
  • Yoon-pyo Hong [ Master D. Student, Department of Tourism and Food Industry, Graduate School of Smart Convergence, Kwangwoon University, Seoul, Korea ]
  • Sung-jun Kim [ Master D. Student, Department of Tourism and Food Industry, Graduate School of Smart Convergence, Kwangwoon University, Seoul, Korea ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    국제인공지능학회(구 한국인터넷방송통신학회) [The International Association for Artificial Intelligence]
  • 설립연도
    2000
  • 분야
    공학>전자/정보통신공학
  • 소개
    인터넷방송, 인터넷 TV , 방송 통신 네트워크 및 관련 분야에 대한 국내는 물론 국제적인 학술, 기술의 진흥발전에 공헌하고 지식 정보화 사회에 기여하고자 한다.

간행물

  • 간행물명
    The International Journal of Advanced Smart Convergence
  • 간기
    계간
  • pISSN
    2288-2847
  • eISSN
    2288-2855
  • 수록기간
    2012~2025
  • 십진분류
    KDC 326 DDC 380

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