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A Study on the Relationship among Internship Job Satisfaction, Career Decision, and Turnover Intention of Culinary Arts Students Integrating Survey and Big Data Analysis

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.128-133
  • 저자
    Suk-Joon, Jung
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A474320

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원문정보

초록

영어
This study empirically analyzed the effects of internship job satisfaction on career decision-making and turnover intention among culinary arts students at university, while also incorporating big data–based text analysis to explore the potential for convergence between social science and data science research. A survey was conducted with 500 culinary arts students across universitys nationwide, with respondents consisting of 87% male and 13% female students. The collected data were analyzed using IBM SPSS Statistics and AMOS through descriptive statistics, correlation analysis, regression analysis, and structural equation modeling (SEM), with mediation effects also tested. In addition, text mining and sentiment analysis were performed on internship review texts collected from online job portals and blogs to complement the quantitative findings with qualitative insights. The results revealed that internship job satisfaction had a positive effect on career decision-making and a negative effect on turnover intention, while also playing a significant mediating role in the relationship between career decision-making and turnover intention. The text analysis further confirmed that positive keywords such as “learning,” “growth,” and “professionalism” were closely associated with job satisfaction and career decision-making, whereas negative keywords such as “long working hours,” “low pay,” and “hierarchical culture” were strongly related to turnover intention. This study provides practical baseline data for career development and internship program improvement for culinary arts students at university, while also offering academic and practical contributions by presenting a novel methodological framework that integrates social science research with big data analysis.

목차

Abstract
1. Introduction
2. Theoretical Background and Research Model
2.1. Concepts of job satisfaction, career decision, and intention to change jobs
2.2. Concepts of job satisfaction, career decision, and intention to change jobs
2.3. Research model and hypothesis
3. Research Method
3.1. Research subjects and data collection
4. Results
5. Conclusion
REFERENCES

키워드

Internship Job Satisfaction Career Decision Turnover Intention Text Mining Big Data Analysis

저자

  • Suk-Joon, Jung [ Professor, Department of Food Service Industry, Baekseok University, Korea ] Corresponding Author

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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