경영정보학연구 (Information Systems Review)

  • 제24권1호
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  • Pages.157-181
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  • 2022
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  • 2982-6551(pISSN)
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  • 2982-6837(eISSN)
한국경영정보학회 (The Korea Society of Management Information Systems)
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소셜미디어 어낼리틱스 기반 서비스품질 평가: 항공산업을 중심으로

Service Quality Evaluation based on Social Media Analytics: Focused on Airline Industry

  • 한명기 (국민대학교 데이터사이언스학과 대학원) ;
  • 최병구 (국민대학교 경영대학)
  • Myoung-Ki Han (Department of Data Science, Kookmin University) ;
  • Byounggu Choi (College of Business Administration, Kookmin University)
  • 투고 : 2021.12.28
  • 심사 : 2022.02.21
  • 발행 : 2022.02.28
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초록

항공산업의 경쟁이 치열해짐에 따라 효과적인 항공사 서비스 품질 측정은 주요 과제 중 하나가 되었다. 특히 빅데이터 어낼리틱스가 새로운 연구 패러다임으로 각광받게 됨에 따라 소비자가 직접 작성한 온라인 리뷰 분석을 통한 항공사 서비스 품질 측정 연구들이 새롭게 시도되고 있다. 그러나 이러한 연구들은 리뷰 제목을 분석에 활용하지 않았다는 점, 학습 데이터 셋 구축을 위한 레이블링(labeling)에 있어 사람의 개입이 많이 요구되는 지도 학습(supervised learning)에 의존한다는 점, 서비스 품질 차원 분류에 있어 항공사 특성을 고려하지 못한다는 점 등이 문제로 지적되고 있다. 기존 연구의 한계를 극복하기 위해 본 연구에서는 제목과 본문을 포함한 온라인 리뷰 전체를 자가학습(self-training)과 감성 분석을 활용해 AIRQUAL 서비스 품질 차원으로 분류함으로써 객관적이고 정교한 서비스 품질측정을 시도하였으며 이를 기반으로 서비스 품질 차원이 서비스 만족도에 미치는 영향을 파악하였다. 분석 결과 온라인 리뷰로부터 AIRQUAL의 다섯 가지 서비스 품질 차원을 효과적으로 추출할 수 있었으며 각 서비스 품질 차원은 모두 서비스 만족도에 유의한 영향을 미치는 것으로 나타났다. 나아가 리뷰 제목이 서비스 만족도에 미치는 영향 또한 유의한 것으로 파악되었다. 본 연구는 항공산업의 특성을 반영한 서비스 품질 차원 측정 및 이의 효과에 대한 분석이라는 측면에서 학문 및 실무적 의의가 있다.

As competition in the airline industry intensifies, effective airline service quality evaluation has become one of the main challenges. In particular, as big data analytics has been touted as a new research paradigm, new research on service quality measurement using online review analysis has been attempted. However, these studies do not use review titles for analysis, relyon supervised learning that requires a lot of human intervention in learning, and do not consider airline characteristics in classifying service quality dimensions.To overcome the limitations of existing studies, this study attempts to measure airlines service quality and to classify it into the AIRQUAL service quality dimension using online review text as well as title based on self-trainingand sentiment analysis. The results show the way of effective extracting service quality dimensions of AIRQUAL from online reviews, and find that each service quality dimension have a significant effect on service satisfaction. Furthermore, the effect of review title on service satisfaction is also found to be significant. This study sheds new light on service quality measurement in airline industry by using an advanced analytical approach to analyze effects of service quality on customer satisfaction. This study also helps managers who want to improve customer satisfaction by providing high quality service in airline industry.

키워드

과제정보

이 논문은 2020년 대한민국 교육부와 한국연구재단의 지원을 받아 수행된 연구임(NRF-2020S1A5A2A01047070).

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