What determines the ride-hailing usage behaviors in China? Insights from combined social media and questionnaire analyses

被引:0
作者
Lyu, Zhongwang [1 ]
Huang, Jiahui [2 ]
Sun, Heyuan [3 ]
机构
[1] Hong Kong Shue Yan Univ, Dept Sociol, 10 Wai Tsui Crescent,Braemar Hill, Hong Kong, Peoples R China
[2] Anhui Jianghuai Automobile Grp Corp Ltd, 176 Dongliu Rd, Hefei, Anhui, Peoples R China
[3] Univ Sheffield, Sch Architecture & Landscape, Sheffield, England
关键词
Ride-hailing; Events; Latent dirichlet allocation; Sentiment analysis; Structural equation model; STRUCTURAL EQUATION MODELS; PUBLIC PERCEPTION; SERVICES; TRUST; INTENTION; RISK; TAXI; VARIABLES; SECURITY; ADOPTION;
D O I
10.1007/s11116-025-10629-2
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Frequent events lead the public to question the security and refuse to use ride-hailing, which could hinder future ride-hailing development. Previous studies investigated the factors influencing the usage intention based on a single qualitative or quantitative approach. However, quantitative methods fail to reveal all the significant factors of public concern. Furthermore, qualitative analysis methods lack statistical correlations between factors related to usage intention, failing to comprehensively predict the internal mechanisms affecting the intention. The research constructed a framework for multi-source data fusion to understand the primary factors that the public is really concerned and whether these factors significantly influence the intention. We adopted a qualitative analysis method to extract the topics of public concern under the ride-hailing events and constructed a comprehensive framework based on the topics. Structural equation model and Analysis of variance were adopted to investigate the correlation and heterogeneity of factors influencing usage intention. The results indicated how attitude, media exposure, trust, security risk, government, and perceived security affect the usage intention. Furthermore, excessive media publicity also results in public fear of ride-hailing services. The research provides a new perspective for combining social media data and traditional questionnaires in the field of traveling intention.
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页数:29
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