Consumers' affective needs matter: Open innovation through mining luxury hotels' online reviews

Abstract

Extant research on hotel open innovation rarely explores innovative ideas from customer-generated online reviews and pays little attention to consumers' affective needs. To bridge these gaps, this study aims to identify service innovation opportunities by mining online reviews from the perspective of customers' affective needs. Specifically, we adopt Kansei Engineering, an effective tool for extracting users' affective needs, to develop the research framework. The opportunity algorithm is also introduced to quantify the innovation opportunity levels of different service attributes. By analyzing 317,518 online reviews of luxury hotels crawled from Ctrip.com, we find that the service attributes with high innovation opportunity levels include Cleanliness, Facility, and Room attributes; the findings further reveal which innovative initiatives may trigger consumers' positive emotions, e.g., providing automated robot services, offering fragrant scents and ergonomic pillows/beds in hotel rooms, etc. This work advances hospitality open innovation research, and practical implications and methodological contributions are also discussed.