{"title":"基于乘客和出行特征的感知服务质量:结构方程建模方法","authors":"Mahmoud Mesbah , Mina Sahraei , Amirali Soltanpour , Meeghat Habibian","doi":"10.1016/j.jrtpm.2022.100340","DOIUrl":null,"url":null,"abstract":"<div><p><span>In order to improve public transit as a customer-oriented service, it is essential to evaluate service quality from the customers' perspective. Various groups of passengers perceive service quality differently based on their demographic and trip characteristics. In addition to a naïve market segmentation which is based on pre-defined groups, this study proposes a cluster analysis to identify groups with combined characteristics. This paper utilizes a customer satisfaction survey (CSS) to better understand the impact of several attributes on satisfaction perceived by different groups of passengers. 1028 valid survey responses are utilized from a case study that is a mass transit rail in Tehran, a less focused context in the literature. </span>Structural Equation Modeling (SEM) is used to identify the most effective attributes in each group. The results indicate that different groups do perceive certain aspects of the service quality differently which underscores the necessity of undertaking a market segmentation analysis by clustering. Despite differences among groups/clusters, passengers will be more satisfied with a secure and convenient transit system. The findings from this study can be used to develop strategies for specific customer groups and evaluate factors that influence customer satisfaction of such groups.</p></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"23 ","pages":"Article 100340"},"PeriodicalIF":2.6000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Perceived service quality based on passenger and trip characteristics: A structural equation modeling approach\",\"authors\":\"Mahmoud Mesbah , Mina Sahraei , Amirali Soltanpour , Meeghat Habibian\",\"doi\":\"10.1016/j.jrtpm.2022.100340\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span>In order to improve public transit as a customer-oriented service, it is essential to evaluate service quality from the customers' perspective. Various groups of passengers perceive service quality differently based on their demographic and trip characteristics. In addition to a naïve market segmentation which is based on pre-defined groups, this study proposes a cluster analysis to identify groups with combined characteristics. This paper utilizes a customer satisfaction survey (CSS) to better understand the impact of several attributes on satisfaction perceived by different groups of passengers. 1028 valid survey responses are utilized from a case study that is a mass transit rail in Tehran, a less focused context in the literature. </span>Structural Equation Modeling (SEM) is used to identify the most effective attributes in each group. The results indicate that different groups do perceive certain aspects of the service quality differently which underscores the necessity of undertaking a market segmentation analysis by clustering. Despite differences among groups/clusters, passengers will be more satisfied with a secure and convenient transit system. The findings from this study can be used to develop strategies for specific customer groups and evaluate factors that influence customer satisfaction of such groups.</p></div>\",\"PeriodicalId\":51821,\"journal\":{\"name\":\"Journal of Rail Transport Planning & Management\",\"volume\":\"23 \",\"pages\":\"Article 100340\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2022-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Rail Transport Planning & Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2210970622000403\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Rail Transport Planning & Management","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210970622000403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
Perceived service quality based on passenger and trip characteristics: A structural equation modeling approach
In order to improve public transit as a customer-oriented service, it is essential to evaluate service quality from the customers' perspective. Various groups of passengers perceive service quality differently based on their demographic and trip characteristics. In addition to a naïve market segmentation which is based on pre-defined groups, this study proposes a cluster analysis to identify groups with combined characteristics. This paper utilizes a customer satisfaction survey (CSS) to better understand the impact of several attributes on satisfaction perceived by different groups of passengers. 1028 valid survey responses are utilized from a case study that is a mass transit rail in Tehran, a less focused context in the literature. Structural Equation Modeling (SEM) is used to identify the most effective attributes in each group. The results indicate that different groups do perceive certain aspects of the service quality differently which underscores the necessity of undertaking a market segmentation analysis by clustering. Despite differences among groups/clusters, passengers will be more satisfied with a secure and convenient transit system. The findings from this study can be used to develop strategies for specific customer groups and evaluate factors that influence customer satisfaction of such groups.