基于结构方程模型的城市轨道交通服务质量影响变量因子分析模型
唐炜1,2陈坚3
Analysis Model of Urban Rail Transit Service Quality Influencing Variable Factors Based on SEM
TANG Wei1,2CHEN Jian3
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作者信息:1.长沙市规划勘测设计研究院，410007，长沙
2.城市交通大数据与模型仿真技术应用湖南省工程研究中心，410007，长沙
3.重庆交通大学交通运输学院，400074，重庆
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Affiliation:1.Changsha Planning & Design Survey Research Institute, 410007, Changsha, China
2.Hunan Engineering Research Center of Urban Transport Data-driven Modeling and Simulation, 410007, Changsha, China
3.School of Traffic and Transportation, Chongqing Jiaotong University, 400074, Chongqing, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2024.08.016
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中图分类号/CLCN:U442.55
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栏目/Col:研究报告
摘要:
［目的］为进一步精准提升城市轨道交通服务，需定量提取城市轨道交通服务质量各影响变量，并分析变量间的内在关系。［方法］运用探索性因子分析提取了6个影响变量公因子，并引入结构方程理论，构建了3个影响变量验证性因子分析模型，采用调查数据对模型进行了验证。［结果及结论］一阶六因子无相关模型无法契合实际数据，一阶六因子有相关模型和二阶因子模型均可以较好地反映因子间的关系，而二阶因子模型的拟合优度明显高于一阶六因子有相关模型，其中绝对适配指数拟合优度平均提高了4.50%，增值适配指数拟合优度平均提高了0.53%，简约适配指数拟合优度平均提高了12.73%。二阶因子模型得到了六个因子对服务质量的贡献度。
Abstracts:
［Objective］ Aiming to further enhance urban rail transit service with precision, it is essential to quantitatively extract the influencing variable factors of urban rail transit service quality and analyze the intrinsic relationship between these variables. ［Method］ Exploratory factor analysis is employed to extract six common influencing factors. SEM (structural equation modeling) is then introduced to construct three confirmatory factor analysis models for the influencing variables. These models are validated using survey data. ［Result & Conclusion］ The results indicate that the first-order six-factor uncorrelated model does not fit the actual data. Both the first-order six-factor correlated model and the second-order factor model adequately reflect the relationship between factors, while the later shows a significantly higher goodness of fit，with an average goodness of fit increase by 4.50% in absolute fit index, 0.53% in incremental fit index, and 12.73% in parsimonious fit index. The second-order factor model effectively quantifies the contributions of the six factors to service quality.
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