Analysis of tourists’ willingness to stay longer: Seasonal data and behavioral changes
心理学
地理
环境科学
作者
Hadi Rafiei Darani,Roya Sadat Alavipour,Lida Gohari Gharaei
出处
期刊:Consumer behavior in tourism and hospitality [Emerald (MCB UP)] 日期:2025-07-23
标识
DOI:10.1108/cbth-07-2024-0240
摘要
Purpose The length of stay is one of the most essential decision-making variables for tourists, and it significantly impacts the host society and the economy of tourist destinations. Although most studies have emphasized and focused on investigating tourists’ behavior during their stay and the factors affecting it, this study aims to investigate tourists’ willingness to stay longer in Mashhad, Iran. Design/methodology/approach This study’s data were obtained by completing a questionnaire from 4,555 domestic tourists across six sampling stages between 2022 and 2023. Considering the hierarchical structure of the data and the dependent variable of willingness and unwillingness, this study used a multilevel logit model for data analysis. Findings The results showed that tourists’ behavior regarding their willingness to stay longer during different sampling periods is different. Also, economic variables (such as income), satisfaction with various tourism facilities and services, and length of stay have significantly influenced tourists’ decision to stay longer. Moreover, the tourists who travel to Mashhad as family, tourists who travel to Mashhad by train and airplane, groups of male tourists and tourists with previous experience traveling there are less willing to stay longer. Practical implications This study used a multilevel logit regression model to assess tourists’ willingness to stay longer in Mashhad, even if this does not occur in practice. The results show that this willingness can be used as a strategic tool for destination management. Identifying the effective factors and analyzing the gap between “willingness” and “actual behavior” provides the basis for improving infrastructure and tourism services and designing longer-stay incentive packages. This analysis can lead to better demand forecasting, identification of economic, cultural or service barriers, and ultimately improve the quality of tourism destination management. Originality/value The research is one of the few studies on “willingness” to stay longer, and it has contributed to the literature on this topic. In addition, since the data of this study was obtained by completing the questionnaire from tourists during different seasons (six different seasons), the results showed that tourists’ behavior varies during their stay. Therefore, this study presents an approach that can help researchers deal with better and more accurate analyses of tourism data by using multilevel methods in data analysis.