Discovery of smart hotels’ competitiveness based on online reviews
提出一个基于在线评论的人工智能框架，通过情感分析和异常挖掘识别智慧酒店的竞争优劣势，帮助管理者制定提升竞争力的策略。
The rapid expansion of smart hotels in recent years has aroused researchers' interest in their competitiveness. While previous research has identified factors influencing the competitiveness of smart hotels, little effort has been devoted to understanding the specific competitive strengths and weaknesses of individual smart hotels. This study addresses the research gap by proposing a novel artificial intelligence framework that analyzes the competitive strengths and weaknesses of smart hotels based on online review data. The framework employs aspect-level sentiment analysis, outlying aspect mining, and theory of lodging to identify detailed competitive strengths and weaknesses of smart hotels from different perspectives. The effectiveness of the proposed framework is demonstrated through a case study of major smart hotels worldwide. The results extend the theory of lodging by incorporating new factors related to smart hotels and provide valuable insights that can help smart hotel practitioners develop strategies to enhance competitiveness at the firm, brand, and market levels. • A framework that understands the competitiveness of smart hotels is proposed. • The influencing factors of smart hotel competitiveness are identified. • The theory of lodging is expanded to analyze lodging experience in smart hotels. • The effectiveness of the framework is demonstrated using online review data from Google Maps. • Knowledge that may help managers enhance smart hotel competitiveness is provided.