Urban Economics and Planning

Urban Economics and Planning

Prioritization of Urban Smart Tourism Axes (Case Study: Selected Area from Districts 11 and 12 of Tehran)

Document Type : Original Article

Authors
Mehrshad Jahanabadi 1
Atiyeh Asgari 2
1 M.Sc in Urban Planning, Department of Urbanism. ST.C., Islamic Azad University, Tehran, Iran
2 Assistant Professor, Department of Urbanism. ST.C., Islamic Azad University, Tehran, Iran
10.22034/uep.2025.532299.1664
Abstract
Introduction 
The tourism industry is recognized as a fundamental pillar of urban sustainability and prosperity. The advent of new information and communication technologies (ICT) has introduced a novel concept: “smart tourism.” This paradigm, leveraging technological advancements such as the Internet of Things (IoT), big data, and artificial intelligence, seeks to enhance the quality of the tourist experience and optimize the efficiency of urban resources. This approach places sustainable development at its core. Nevertheless, developing megacities, including Tehran, grapple with significant structural and managerial obstacles. Inconsistencies in infrastructure and the absence of comprehensive information systems are among the fundamental challenges confronting these cities. Tehran’s Districts 11 and 12, given their rich historical background and unique cultural attractions, possess considerable potential for smart tourism development. The complexities of urban management in these areas underscore the increasing necessity for strategic and intelligent planning. The present study aims to address existing gaps in the academic literature by identifying and prioritizing smart tourism axes within the selected study areas of Tehran’s Districts 11 and 12. This will be achieved by applying multi-criteria decision-making models, thereby charting a clear path for sustainable and intelligent development in these regions.
Materials and Methods
This research adopts an applied approach in terms of its objective and a descriptive-analytical framework in its methodology, employing a mixed-methods design (quantitative and qualitative). Data collection was multifaceted, drawing from field observations, questionnaire distribution, and library research. The statistical population for this study comprises 19,953 residents from Ferdowsi and Enghelab neighborhoods in Districts 11 and 12 of Tehran. 377 questionnaires were distributed within this population using a simple random sampling method to gather the necessary information. For data analysis and prioritizing research axes, the Shannon Entropy method was utilized for scoring, and the ARAS (Additive Ratio Assessment) technique, a multi-criteria decision-making (MCDM) model, was employed. It is worth noting that the Cronbach’s Alpha coefficient for the 15-item questionnaire was calculated at 0.830, indicating a high level of reliability for the measurement instrument in this study.
Findings
This research offers diverse and insightful findings. Demographically, 53% of respondents were male and 47% were female. The largest age group, accounting for 30%, was 25 to 35 years old, indicating significant youth participation in this study.
Regarding the current state of smart tourism, certain aspects, such as smart transportation systems, smart healthcare services, and online tourism portals, were satisfactory. However, significant challenges persist. These include limited citizen participation in decision-making processes (58% low participation), deficiencies in tourism technology training, and poor coordination among government entities (39.9% dissatisfaction).
The prioritization of smart tourism axes using the multi-criteria decision-making model yielded interesting results:
• Nofel Loshato Avenue ranked first with a score of 0.826, highlighting its high potential for smart development.
• Valiasr Street secured the second position with a score of 0.707.
• Ferdowsi Street came in third with a score of 0.470.
• Lalehzar, Jomhouri, and Enghelab avenues followed in subsequent ranks.
Furthermore, the study identified the most crucial indicators for urban tourism smartification:
• “Coordination among government agencies” (C10) was recognized as the most vital factor with a weight of 0.086.
• Following closely were “air and water quality monitoring and energy management” (C4) with a weight of 0.084, and “cultivating public awareness and citizen participation in urban decision-making” (C3) with a weight of 0.082.
These findings underscore the critical need for systemic integration, a focus on environmental sustainability, and the active involvement of citizens in smart tourism planning and development processes.
Conclusion
This research successfully addresses its central question regarding prioritizing smart tourism axes in Tehran’s Districts 11 and 12. The findings affirm that achieving sustainable smart tourism development in these areas necessitates a balanced approach. This approach must not only focus on technological advancements but also simultaneously overcome root challenges in human, managerial, and environmental dimensions.
Despite the relatively satisfactory state of technological aspects, insufficient citizen participation, inadequate training, and a lack of coordination among government entities have been identified as key obstacles to achieving comprehensive and sustainable smartification. Analyses using multi-criteria decision-making models clearly indicate that Nofel Loshato Avenue holds the highest priority for investment, followed by Valiasr and Ferdowsi avenues. This quantitative prioritization offers a valuable roadmap for the optimal allocation of resources and adopting strategic decisions in smart tourism development.
By providing a novel and localized methodological model, this study has taken a significant step toward filling the existing gap in academic literature. Consequently, the findings and the proposed framework of this research can serve as a practical blueprint for other Iranian cities and developing countries, substantially accelerating the process of tourism smartification in these regions.
Keywords
Smart Tourism
Multi-Criteria Decision-Making
Selected Study Area
Districts 11 and 12 of Tehran

Subjects

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Urban Economics and Planning
Volume 6, Issue 3
Summer 2025
Pages 144-163

  • Receive Date 15 July 2025
  • Revise Date 25 July 2025
  • Accept Date 30 July 2025