Abstract
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.
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