Geographical Urban Planning Research (GUPR)

Geographical Urban Planning Research (GUPR)

Structural Equation Modeling to Measure Factors Affecting the Implementation of Intelligent Transportation Systems in the City of Ahvaz

Document Type : Article extracted From phd dissertation

Authors
1 Associate Professor of Geography and Urban Planning, Shahid Chamran University of Ahvaz, Ahvaz, Iran
2 Associate Professor of Geography and Rural Planning, Department of Geography and Urban Planning, Shahid Chamran University of Ahvaz, Ahvaz, Iran
3 Ph.D student in Geography and Urban Planning, Department of Geography and Urban Planning, Shahid Chamran University of Ahvaz, Ahvaz, Iran
10.22059/jurbangeo.2026.403146.2111
Abstract
Intelligent Transportation Systems (ITS) represent one of the most significant innovations in urban mobility, leveraging advanced technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT) to enhance traffic management, alleviate congestion, improve road safety, and promote urban sustainability. Nevertheless, conventional transportation systems continue to dominate in many Iranian cities, including Ahvaz, resulting in persistent challenges such as traffic congestion, environmental pollution, and operational inefficiency. This study employed a descriptive–analytical methodology, utilizing a structured questionnaire as the primary data collection instrument. The statistical population comprised Ahvaz residents and urban transport stakeholders. Based on Sample Power software, a sample of 300 respondents was selected using random sampling. The validity of the questionnaire was confirmed through expert evaluation, while its reliability was verified utilizing Cronbach's alpha coefficient. Data were analyzed using SPSS and AMOS software through Structural Equation Modeling (SEM). The findings revealed that socio-behavioral, managerial-institutional, policy-regulatory, and technological dimensions exerted significant effects on ITS implementation, with the proposed model explaining 68% of the variance in the dependent variable. Among these dimensions, socio-behavioral (β = 0.86) and managerial-institutional (β = 0.85) factors demonstrated the strongest effects, whereas the technological factor (β = 0.38) exhibited the weakest influence. The results indicate that the successful implementation of ITS in Ahvaz depends not only on the development of technical infrastructure but also on strengthening public trust, enhancing institutional coordination, ensuring sustainable financial resources, and establishing supportive policy and regulatory frameworks.
Keywords


Articles in Press, Accepted Manuscript
Available Online from 19 July 2026