Improving the public transportation system to compete with the private modes requires an understanding of passenger perceptions of the service quality (SQ). In the literature, various models have been developed to identify effective SQ attributes and to assess their relationship with passenger satisfaction. However, most of them either ignore the socioeconomic and trip characteristics or consider them by a market segmentation approach. Since these variables can affect passenger perceptions, it is important to include them in the model. This paper aims to capture the effect of socioeconomic and trip variables by combining them with SQ attributes in a satisfaction analysis. An ordered logit model considering SQ latent variables is calibrated to model passenger satisfaction. The measurement part of a Structural Equation Model (SEM) is applied to construct latent variable structures. The case study was on the Tehran metro. The SQ attributes were used to form five SQ latent variables: “comfort,”“information,”“cleanliness,”“service,” and “safety/security.” The results indicate that socioeconomic and trip characteristics, as well as the SQ latent variables, had a significant effect on passenger satisfaction. From the results of this study, “service” and “comfort” were found to be the most effective contributors to satisfaction levels among the SQ latent variables. Among socioeconomic and trip characteristics, gender, education, driving license, egress mode, access time, and trip origin type (i.e., work, education, etc.) were also important in passenger satisfaction.

改善公共交通系统以与私人交通工具竞争，需要了解乘客对服务质量（SQ）的看法。在文献中，已经开发出各种模型来识别有效的SQ属性并评估它们与乘客满意度的关系。但是，它们中的大多数要么忽略了社会经济和旅行特征，要么通过市场细分方法考虑了它们。由于这些变量会影响乘客的感知，因此将它们包括在模型中非常重要。本文旨在通过在满意度分析中将SQ属性与SQ属性相结合来捕获社会经济和旅行变量的影响。对考虑SQ潜变量的有序logit模型进行校准，以模拟乘客满意度。结构方程模型（SEM）的测量部分用于构造潜在变量结构。案例研究在德黑兰地铁上进行。SQ属性用于形成五个SQ潜在变量：“舒适”，“信息”，“清洁度”，“服务”和“安全/安保”。结果表明，社会经济和出行特征以及SQ潜在变量对乘客满意度有显着影响。从这项研究的结果中，发现“服务”和“舒适”是SQ潜在变量中满意度水平最有效的因素。在社会经济和出行特征中，性别，教育程度，驾驶执照，出站方式，出行时间和出行来源类型（即工作，教育等）对于旅客满意度也很重要。案例研究在德黑兰地铁上进行。SQ属性用于形成五个SQ潜在变量：“舒适”，“信息”，“清洁度”，“服务”和“安全/安保”。结果表明，社会经济和出行特征以及SQ潜在变量对乘客满意度有显着影响。从这项研究的结果中，发现“服务”和“舒适”是SQ潜在变量中满意度水平最有效的因素。在社会经济和出行特征中，性别，教育程度，驾驶执照，出站方式，出行时间和出行来源类型（即工作，教育等）对于旅客满意度也很重要。案例研究在德黑兰地铁上进行。SQ属性用于形成五个SQ潜在变量：“舒适”，“信息”，“清洁度”，“服务”和“安全/安保”。结果表明，社会经济和出行特征以及SQ潜在变量对乘客满意度有显着影响。从这项研究的结果中，发现“服务”和“舒适”是SQ潜在变量中满意度水平最有效的因素。在社会经济和出行特征中，性别，教育程度，驾驶执照，出站方式，出行时间和出行来源类型（即工作，教育等）对于旅客满意度也很重要。结果表明，社会经济和出行特征以及SQ潜在变量对乘客满意度有显着影响。从这项研究的结果中，发现“服务”和“舒适”是SQ潜在变量中满意度水平最有效的因素。在社会经济和出行特征中，性别，教育程度，驾驶执照，出站方式，出行时间和出行来源类型（即工作，教育等）对于旅客满意度也很重要。结果表明，社会经济和出行特征以及SQ潜在变量对乘客满意度有显着影响。从这项研究的结果中，发现“服务”和“舒适”是SQ潜在变量中满意度水平最有效的因素。在社会经济和出行特征中，性别，教育程度，驾驶执照，出站方式，出行时间和出行来源类型（即工作，教育等）对于旅客满意度也很重要。