earticle

영어

Understanding the role of service attributes in shaping customer satisfaction is vital for the hospitality industry, where guest experiences can differ widely across brands, locations, and individual properties. This study explores the impact of service attributes on customer satisfaction by analyzing large-scale online hotel review data. Using text mining techniques, we identify six key service attributes from customer-generated reviews: Hotel Facilities, Room Comfort, Customer Service, Breakfast Service, Entertainment & Family, and Dining Experience. For each attribute, both frequency of mention and sentiment are extracted to assess their influence on satisfaction. To provide a nuanced understanding, we employ a two-stage analytical framework. First, a fixed-effects regression model estimates the overall effects of service attributes on customer satisfaction while controlling for structural factors such as hotel class and geographic location. Second, a multi-level approach captures unobserved heterogeneity by allowing attribute effects to vary across hotels, enabling comparisons between within-hotel and between-hotel variations in satisfaction outcomes. Our findings highlight that the impact of service attributes on satisfaction is far from uniform. While certain attributes consistently enhance satisfaction across properties, others exhibit significant variability depending on hotel-specific factors. By integrating text-mined attribute data with hierarchical modeling, this study offers valuable theoretical insights and practical guidance for developing targeted and context-sensitive service improvement strategies in the hospitality industry.