A data-driven approach to competitor identification and categorization in the hotel industry

The intensifying competition in the hotel industry necessitates a comprehensive competitor analysis for strategic positioning. Traditional research, relying on surveys or managers’ subjective experience, often overlooks emerging competitors, resulting in flawed strategies. While recent studies introduced data-driven approaches, they often rely on limited features, primarily from online reviews or booking records, neglecting critical factors such as service offerings, spatial proximity, and other operational characteristics. To address these limitations, this paper introduces Hotel Competitor Profiling , a novel data-driven approach that leverages multidimensional data from online travel agencies to identify and categorize competitors. Adopting a customer-centric view, this study uses K-prototype clustering for competitor identification and applies Kamensky’s theory of competitor categorization to map competitive terrain and categorize competitors into four types. A case study involving hotels in Shanghai demonstrated the method’s efficiency, with questionnaire results suggesting practical value. Findings help hotel managers better understand their competitive terrain, enhance strategic planning, and improve performance. • A data-driven method that identifies and categorizes hotel competitors is proposed. • The criteria and features for categorizing hotel competitors are provided. • A case study is conducted to illustrate the application of the proposed method. • The proposed method's effectiveness is demonstrated by employing a questionnaire. • Knowledge that can help managers understand competitive terrain is provided.