大数据
营销
顾客满意度
业务
分析
酒店业
计算机科学
知识管理
数据科学
数据挖掘
旅游
政治学
法学
作者
Hyekyung Park,Minwoo Lee,Ki-Joon Back,Agnes DeFranco
标识
DOI:10.1177/10963480221132758
摘要
This study aims to identify the critical hotel guest technology that enhances the hotel customer experience. By applying the two-factor theory, the study discovers the asymmetry impact of hotel guest technology on customer satisfaction and dissatisfaction. This study uses an integrated approach of big data analytics and impact asymmetry analysis on a dataset of 520,757 online reviews of 435 hotels in New York City derived from TripAdvisor.com. Big data analytics is implemented to identify significant attributes of hotel guest technology. Then, the five unique roles of hotel guest technology in customer satisfaction and/or dissatisfaction are identified through impact asymmetry analysis. The integrated approach reconciles inconsistent findings from prior research and guides hotel operators to prioritize hotel guest technology to increase customer experience.
科研通智能强力驱动
Strongly Powered by AbleSci AI