Assessing the effects of perceived service quality and customer satisfaction on behavioral intention in airline industry : using online review and text-mining = 인지된 항공 서비스 품질과 고객만족이 행동의도에 미치는 영향 연구 : 온라인 이용후기와 텍스트 마이닝을 중심으로using online review and text-mining
Customer-generated online reviews have become informative resources for marketers to observe customer perceptions in the service industry. Various studies have mainly focused on customers’ experiences and feedback on services or firms’ performance. However, these studies have remained mostly exploratory and there is difficulty in how to interpret reviews to represent different dimensions of service quality. The aim of this paper is to explore online customer reviews to establish causal relationships among service quality, customer satisfaction, and behavioral intention, and identify different customer segments. This paper demonstrates that latent dirichlet allocation (LDA) extracts service attributes from online reviews and that ratings and recommendations measure customer satisfaction and behavioral intention, respectively. The data set includes 33,193 online reviews for 84 airlines operating in 46 countries and including 23 low-cost carriers. After validation procedures, LDA identifies service attributes that affect dimensions of customer satisfaction, and in turn, these dimensions influence behavioral intention. Managerially, marketers are provided with insights to focus on specific service attributes to improve each dimensions of customer satisfaction and behavioral intention, based on identified customer segments.