Analyzing and Modeling Toll Road Service Performance: TRSQ Model and Emerging Influencing Variables

The construction of toll roads supports economic and social mobility while driving regional development. However, toll road services face challenges such as deteriorating road quality, lack of facilities, and traffic disruptions due to accidents or repairs. This study aims to identify variables, examine their relationships, and develop a model for the factors influencing toll road services. The research uses both quantitative and qualitative approaches with explanatory research. The initial model of variables refers to the TRSQ model, which includes information, accessibility, reliability, mobility, safety and security, rest areas, and responsiveness. A questionnaire instrument is used and tested with SPSS for data validity and reliability. The data is then processed with SmartPLS to examine the relationships between variables. The results show a positive and significant impact on toll road service performance. However, ۳۶.۹% of toll road service performance is influenced by factors outside the model. To identify additional variables, bibliometric analysis using VOSviewer and expert opinions was used. The findings revealed that environmental factors, innovation, climate change, and public-private partnerships also affect toll road service performance. This led to the development of a model that serves as a framework for improving toll road service quality.The construction of toll roads supports economic and social mobility while driving regional development. However, toll road services face challenges such as deteriorating road quality, lack of facilities, and traffic disruptions due to accidents or repairs. This study aims to identify variables, examine their relationships, and develop a model for the factors influencing toll road services. The research uses both quantitative and qualitative approaches with explanatory research. The initial model of variables refers to the TRSQ model, which includes information, accessibility, reliability, mobility, safety and security, rest areas, and responsiveness. A questionnaire instrument is used and tested with SPSS for data validity and reliability. The data is then processed with SmartPLS to examine the relationships between variables. The results show a positive and significant impact on toll road service performance. However, ۳۶.۹% of toll road service performance is influenced by factors outside the model. To identify additional variables, bibliometric analysis using VOSviewer and expert opinions was used. The findings revealed that environmental factors, innovation, climate change, and public-private partnerships also affect toll road service performance. This led to the development of a model that serves as a framework for improving toll road service quality.