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온라인 리뷰의 텍스트 분석을 통한 Kano 모델 품질속성 판별 기법

Identifying Kano Model Quality Attributes based on Text Analysis of Online Reviews

서용원|윤민지
한국생산관리학회 (The Korean Production And Operations Management Society)|2020.02|한국생산관리학회지 (Journal of the Korean Production and Operations Management Society)|제31권 제1호|pp. 95-109|DOI 10.21131/kopoms.31.1.202002.95

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키워드

Kano 모델텍스트분석호텔서비스품질온라인리뷰품질속성
주제분류경영학

초록

Kano 모델은 제품 및 서비스의 종합적 만족도를 관리하기 위한 유용한 도구로서 널리 활용되고 있다. 최근 고객이 인지하는 품질 만족도를 이해함에 있어 온라인 리뷰의 중요성이 강조됨에 따라, 온라인 리뷰와 고객 평점의 관계로부터 제품이나 서비스의 품질속성을 파악하는 방안에 대한 연구가 제시되고 있다. 그러나, 일관된 기준의 고객 평점이 존재하지 않는 많은 온라인 리뷰에서는 평점 기반의 방법이 적용되기 어렵다. 이에 따라 본 연구에서는 고객 평점에 의존하지 않고 온라인 리뷰에서 텍스트 분석을 통해 Kano 모델의 품질속성을 판별하는 것을 목표로 한다. 이를 위해 먼저, 호텔 예약 사이트를 대상으로 온라인 리뷰 데이터를 수집하여 형태소 분석을 통해 호텔의 주요 서비스 속성을 추출한 후, 속성어 사전을 구축하고 속성어의 긍정 및 부정 도출 빈도를 기반으로 극성을 파악하여 최종적으로 Kano 모델 품질속성을 판별하는 방법을 제시하였다. 이러한 결과를 통해 실제 Kano 설문조사 결과와 비교하여 비교적 높은 일치도가 나타남을 확인하였다.

Abstract

Kano model is widely utilized as a customer satisfaction management tool. As online reviews are helpful in understanding customers’ perceptions of quality attributes, many research have discussed several methods to identify quality attributes by analyzing the relationship between review texts and customer ratings. However, such approaches cannot be readily applied to reviews with inconsistent customer rating scores. Thus, in this research, we propose a method to identify Kano’s quality attributes by analyzing online textual reviews without relying on customer ratings. We first crawl online reviews from a hotel reservation site, extract major attribute words by utilizing part-of-speech tagging, and build a dictionary of the attribute words. We then analyze the frequency of occurrence of each attribute word in both positive and negative contexts, based on which the polarity of each attribute word is identified. Finally, we identify Kano’s quality attributes based on the frequency of occurrence and polarity of each attribute word. We validate the result by comparing it with the result achieved from the Kano survey.

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