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온라인 리뷰 분석을 통한 공항 서비스 속성 평가

Priortizing Airport Service Attributes via Online Review

최영배|전민지
서비스사이언스학회 (The Society of Service Science)|2024.12|서비스 연구 (Journal Of Service Research and Studies)|제14권 제04호|pp. 215-234|DOI http://dx.doi.org/10.18807/jsrs.2024.14.4.215

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키워드

공항감성분석Airport온라인 리뷰카노모델Kano modelService attributes서비스디자인Sentiment analysis구조적 토픽모델링Service designOnline review서비스속성Structural topic modleing
주제분류학제간연구

초록

본 연구는 전 세계 주요 공항에서 제공되는 서비스 속성과 고객 만족도 간의 관계를 분석하고, 이를 통해 공항 서비스의 개선 방안을 도출하고자 하였다. 이를 위해 온라인 리뷰 사이트 Skytrax에 게시된 957개 공항의 41,438개 리뷰를 수집하고, 구조적 토픽모델링(STM)과 감정 분석을 활용하여 공항 서비스 속성을 도출하였다. 분석 결과, 공항 서비스 속성은 시설 및 편의, 직원 서비스, 보안 절차, 대기 시간 등 총 17개의 토픽으로 분류되었으며, 각 토픽에 대한 긍정 및 부정 감정 점수가 고객 만족도에 미치는 영향을 파악하기 위해 회귀분석과 카노 모델을 적용하였다. 특히, 공항별 서비스 개선 사항을 도출하기 위하여 온라인 리뷰 단위의 데이터를 각 공항별 주제별 감정점수로 변환하여 회귀분석을 실시하였다. 회귀분석의 결과를 바탕으로 카노 모델에 적용한 결과, ‘체크인 및 보안 절차’와 ‘특별 지원 서비스’는 긍정·부정 감정이 모두 고객 만족도에 유의한 영향을 미치는 일원적 품질로 나타났으며, ‘시설 및 편의’, ‘프리미엄 서비스’는 고객 만족을 높이는 매력적 품질로 확인되었다. 반면, ‘청결 및 위생’, ‘전반적 공항 경험’ 등은 부정 감정이 만족도에 영향을 미치는 필수적 품질로 분류되었다. 특히, 고객의 부정적 감정이 긍정적 감정보다 만족도에 더 큰 영향을 미치는 비대칭적 효과가 일부 속성에서 확인되었다. 본 연구는 공항 서비스 속성을 감정 반응을 기반으로 세분화하여 고객 경험 관리의 새로운 접근을 제시하며, 온라인 리뷰를 활용한 비정형 데이터 분석을 통해 공항 서비스의 개선 방향에 대한 실질적 시사점을 제공한다. 또한, 공항 서비스 속성을 매력적·필수적·일원적 품질로 분류하여 자원의 효율적 배분과 고객 만족 극대화를 위한 전략 수립에 기여할 수 있을 것으로 기대된다.

Abstract

This study aims to analyze the relationship between service attributes provided at major airports worldwide and customer satisfaction, with the goal of deriving recommendations for airport service improvements. For this purpose, 41,438 reviews from 957 airports were collected from the Skytrax website. Using Structural Topic Modeling (STM) and sentiment analysis, the study identified 17 key service topics, including facilities and amenities, staff interactions, security processes, and waiting times. To evaluate the impact of positive and negative sentiment scores of each topic on customer satisfaction, regression analysis and the Kano model were applied. Specifically, the individual review data was converted into topic-based sentiment scores for each airport to facilitate regression analysis on airport-level service improvements. According to the results, “Check-in and Security Processes” and “Special Assistance Services” were classified as one-dimensional qualities that significantly impact customer satisfaction in both positive and negative aspects, while “Facilities and Amenities” and “Staff Interactions and Premium Services” were identified as attractive qualities that enhance customer satisfaction. In contrast, “Cleanliness and Hygiene” and “Overall Airport Experience” were categorized as must-be qualities, where negative experiences significantly affected satisfaction. Notably, some attributes showed an asymmetrical effect, where negative sentiment had a greater impact on satisfaction than positive sentiment. This study presents a new approach to managing customer experience by segmenting airport service attributes based on emotional responses and offers practical insights for service improvements through unstructured data analysis of online reviews. By classifying airport service attributes into attractive, must-be, and one-dimensional qualities, this study contributes to the efficient allocation of resources and strategic planning for maximizing customer satisfaction.

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