Tourism forecasting research: a bibliometric visualization review (1999–2022)

Abstract

Purpose This paper aims to analyze the research highlights, evolutionary process and future research directions in the field of tourism forecasting. Design/methodology/approach This study used CiteSpace to conduct a bibliometric analysis of 1,213 tourism forecasting articles. Findings The results show that tourism forecasting research has experienced three stages. The institutional collaboration includes transnational collaboration and domestic institutional collaboration. Collaboration between countries still needs to be strengthened. The authors’ collaboration is mainly based on on-campus collaboration. Articles with high co-citation are primarily published in core tourism journals and other relevant publications. The research content mainly pertains to tourism demand, revenue management, hotel demand and tourist volumes. Ex ante forecasting during the COVID-19 pandemic has broadened existing tourism forecasting research. The future forecasting research focuses on the rational use of big data, improving the accuracy of models and enhancing the credibility of forecasting results. Originality/value This paper uses CiteSpace to analyze tourism forecasting articles to obtain future research trends, which supplements existing research and provides directions for future research.