Urban Economics and Planning

Urban Economics and Planning

Modeling the Smart City of Tabriz in the 2030 Horizon: A Comprehensive Study of Infrastructure, Economic, and Governance Indicators

Document Type : Original Article

Authors
Leila Baghali Aghdam 1
Seyed Kamal Sadeghi 2
Elham Nobahar 3
1 Master of Economics, Faculty of Economics and Management, University of Tabriz, Iran
2 Professor, Faculty of Economics and Management, University of Tabriz, Iran
3 Assistant Professor, Faculty of Economics and Management, University of Tabriz, Iran
10.22034/uep.2025.501394.1588
Abstract
Introduction 
Given the growing trend of urbanization and the complexities of urban management, the use of modern technologies in the form of smart cities has been proposed as a sustainable solution to optimize urban performance and improve the quality of life of citizens. A smart city is a city that uses digital technologies to increase productivity, reduce resource consumption, improve urban services, and strengthen participatory governance. The development of smart cities in the world has become one of the strategic goals of metropolises, and countries such as South Korea, Singapore, and Germany have succeeded in creating advanced models in this field.
Tabriz, as one of the important metropolises of Iran, faces challenges such as rapid population growth, transportation problems, environmental pollution, and inefficiency of traditional infrastructure. Given these challenges, making Tabriz smart can be an important step towards sustainable development, improving management performance, and increasing citizen satisfaction. However, the successful implementation of a smart city model requires a careful examination of its various dimensions, including environmental, economic, and governance indicators. This study, with the aim of providing a comprehensive model for the smartization of Tabriz city by 2030, has examined and analyzed key indicators. Since no specific and codified model has been presented for the implementation of the smart city of Tabriz, this study can be used as a basis for metropolitan decision-making and future planning.
Materials and Methods
This research is of a developmental‌ـ applied type and was conducted with a descriptive‌ـ analytical approach. The statistical population includes 300 managers, researchers, experts, and employees related to the fields of urban management and economics who are directly or indirectly active in these fields. The expert Delphi method was used to identify the factors affecting the smart city, and the data was collected through a specialized questionnaire.
Data analysis was performed using SPSS and Smart PLS software, and structural equation modeling was used to test the conceptual model of the research. Hypotheses were tested at a significance level of 0.05, and key indicators in three dimensions of environment, economy, and governance were examined.
Findings
The study results show that environmental, economic, and governance indicators significantly impact the smartization of Tabriz city in the 2030 horizon.
Environmental indicators: Internet access: The expansion of speed internet networks and universal access to digital services is one of the requirements of smart cities.
Smart transportation infrastructure: The development of smart public transportation systems, smart traffic management, and the integration of urban transportation systems have an important impact on improving the city’s performance. Digital systems: Using big data, the Internet of Things (IoT), and artificial intelligence in urban management leads to optimizing energy consumption and cost reduction. Economic indicators: Smart innovation: Supporting technological startups, developing digital businesses, and strengthening the knowledge‌ـ based economy are essential in a smart city. Digital energy: Developing sustainable energy sources such as solar and wind energy and using smart energy management systems can significantly impact economic productivity. Smart culture: Increasing citizens’ digital literacy, promoting a culture of using new technologies, and employing smart learning systems are requirements for developing a smart city. Governance indicators: Smart citizen services: Digitizing urban services, creating electronic service portals, and developing smart urban management systems increase transparency and reduce administrative costs.Smart business services: Integrating e-commerce systems, facilitating financial processes, and improving access to digital markets are requirements for a smart economy. Smart management and communications: Using urban data to optimize decision-making processes, increase citizen interactions, and improve crisis management are other key components of smart governance. The results of structural equation modeling show that all the aforementioned indicators have a significant positive effect on the smart city of Tabriz at a significant level (t>1.96; p<0.05). Also, the model presented for the smart city of Tabriz in the 2030 horizon has a good fit and can be the basis for future policymaking.
Conclusion
The analysis of the research findings shows that realizing the smart city of Tabriz in the 2030 vision requires a comprehensive and coordinated approach among different urban sectors. Developing digital infrastructure, improving smart transportation, strengthening the knowledge‌ـ based economy, and promoting smart governance are among the key requirements in this direction. Given the existing challenges, it is suggested that urban managers and policymakers consider the following solutions, which specifically address the challenges examined. A strategy for optimizing transportation and reducing economic costs: One of the biggest challenges of Tabriz is transportation and traffic problems, which greatly impact the urban economy. The proposed strategy includes developing intelligent transportation systems (ITS) and optimizing urban traffic through data analysis. Implementation strategies: Development and expansion of the smart public transport network (smart buses, metro, smart taxis) that uses traffic data analysis to suggest optimal routes for passenger movement. Creation of smart traffic monitoring systems that continuously monitor traffic conditions and adjust traffic light timing using real‌ـ time data. Travel demand management through online public transport booking systems helps reduce congestion and optimize travel time. Strategy for natural resource management and sustainable development: In Tabriz, environmental problems such as air pollution, lack of green space, and water crisis have become economic problems. The proposed strategy uses smart technologies to manage natural resources and improve environmental sustainability. Implementation strategies: Development of smart air quality monitoring systems that continuously measure air pollution and send preventive warnings. These systems help officials design effective policies to reduce pollution and reduce health costs caused by pollution. Using smart water resources management technologies to optimize water consumption in different urban areas. These technologies can help reduce the costs of water crises and also prevent the waste of natural resources. Expanding smart green spaces that use automatic irrigation systems and smart management of soil and water resources. This strategy is especially effective in reducing urban costs and improving the quality of urban life. Strategy to strengthen industry and economic productivity: as one of the country’s industrial hubs, Tabriz needs strategies to improve productivity and reduce costs. The proposed strategy is to use smart technologies in industries, especially in the field of energy and production processes. Implementation strategies: Developing green industries using renewable energy and smart energy management systems to reduce energy costs and increase productivity in Tabriz industries. Use of industrial automation systems and production data analysis to optimize production processes and reduce waste. These measures can greatly help increase the competitiveness of Tabriz Industries in domestic and foreign markets. Encourage and attract investors in industrial innovations and digital technologies to increase production and improve industrial product quality in Tabriz. Strategy for developing smart tourism and increasing revenue generation: Tourism can become a sustainable source of income for Tabriz, but there is a need for smart strategies for optimal management of this sector. Implementation strategies: Create digital platforms for tourism management that provide tourists with accurate information about historical attractions, traffic conditions, visit capacity, and prices. Develop smart management of tourist flows using big data to simulate tourist behavior and predict their needs. This can help Tabriz expand its services to meet market needs and exploit tourism capacities more effectively. Improving the tourist experience through mobile applications that allow tourists to choose appropriate routes to visit Tabriz’s historical monuments and avoid congestion. By implementing these measures, Tabriz can take steps towards realizing a leading smart city at the national and international levels. The findings of this research can be used as a scientific basis for metropolitan policies and future decision-making in the direction of sustainable urban development.
Keywords
PLS
Smart City Indicators
Smart City Modeling
Smart City

Subjects

Al Sharif, R., & Pokharel, S. (2022). Smart city dimensions and associated risks: Review of literature. Sustainable Cities and Society, 77, 103542. https://doi.org/10.1016/j.scs.2021.103542
Albino, V., Berardi, U., & Dangelico, R. M. (2015). Smart cities: Definitions, dimensions, performance, and initiatives. Journal of urban technology, 22(1), 3‌ـ 21. https://doi.org/10.1080/10630732.2014.942092
Apanavičienė, R., & Shahrabani, M. M. N. (2023). Key factors affecting smart building integration into smart city: Technological aspects. Smart Cities, 6(4), 1832–1857. https://doi.org/10.3390/smartcities6040085
Arnstein, S. (2020). A ladder of citizen participation: Journal of the American Institute of Planners (1969). In The city reader (pp. 290–302). Routledge. https://doi.org/10.1080/01944363.2018.1559388
Barni, A., Capuzzimati, C., Fontana, A., Pirotta, M., Hänninen, S., Räikkönen, M., & Uusitalo, T. (2022). Design of a lifecycle‌ـ oriented environmental and economic indicators framework for the mechanical manufacturing industry. Sustainability, 14(5), 2602. https://doi.org/10.3390/su14052602
Bashirkhodaparasti, R., & Bagheri Garbollagh, H. (2023). Exploring the role of urban entrepreneurship, digital technologies and smart logistics on sustainable business in the smart city: The moderating role of market turbulence. Journal of International Business Administration, 6(2), 155–175. https://doi.org/10.22034/jiba.2023.53879.1966
Buhalis, D., Leung, D., & Lin, M. (2023). Metaverse as a disruptive technology revolutionizing tourism management and marketing. Tourism Management, 97, 104724. https://doi.org/10.1016/j.tourman.2023.104724
Camero, A., & Alba, E. (2019). Smart city and information technology: A review. Cities, 93, 84–94. https://doi.org/10.1016/j.cities.2019.04.014
Chivandire, C., Masunda, T., & Chirisa, I. (2021). Environmental resilience—Food and the city. In Environmental resilience: Food and the city—Zimbabwe (pp. 1–16). Springer Singapore. https://doi.org/10.1007/978‌ـ 981‌ـ 16‌ـ 0305‌ـ 1_1
Conde, J., Munoz‌ـ Arcentales, A., Choque, J., Huecas, G., & Alonso, Á. (2022). Overcoming the barriers of using linked open data in smart city applications. Computer, 55(12), 109–118. https://doi.org/10.1109/MC.2022.3206144
Conley, J. M., Cadigan, R. J., Davis, A. M., Juengst, E. T., Kuczynski, K., Major, R., & Henderson, G. E. (2023). The promise and reality of public engagement in the governance of human genome editing research. The American Journal of Bioethics, 23(7), 9–16. https://doi.org/10.1080/15265161.2023.2207502
De Esteban Escobar, D., De‌ـ Pablos‌ـ Heredero, C., Montes‌ـ Botella, J. L., Blanco Jiménez, F. J., & García, A. (2022). Business incubators and survival of startups in times of COVID‌ـ 19. Sustainability, 14(4), 2139. https://doi.org/10.3390/su14042139
Fares, N. Y., Nedeljkovic, D., & Jammal, M. (2023, December). AI‌ـ enabled IoT applications: Towards a transparent governance framework. In 2023 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT) (pp. 109–114). IEEE. https://doi.org/10.1109/GCAIoT61060.2023.10385106
Farmanbar, M., Parham, K., Arild, Ø., & Rong, C. (2019). A widespread review of smart grids towards smart cities. Energies, 12(23), 4484. https://doi.org/10.3390/en12234484
Ferraro, S. (2013). Smart Cities, Analysis of a Strategic Plan. (Master thesis). https://amslaurea.unibo.it/id/eprint/5420
Fisher, D. R., Jasny, L., Redmond, J., & Heaume, F. (2021). Environmental governance. Handbook of Environmental Sociology, 333–353. https://doi.org/10.1007/978‌ـ 3‌ـ 030‌ـ 77712‌ـ 8_16
Freund, D., Ramírez García, I., Boluk, K. A., Canut‌ـ Cascalló, M., & López‌ـ Planas, M. (2024). Exploring the gendered tourism entrepreneurial ecosystem in Barcelona and responses required: A feminist ethic of care. Journal of Sustainable Tourism, 32(3), 637–655. https://doi.org/10.1080/09669582.2023.2207780
Grimsrud, A., & Wilkinson, L. (2021). Acceleration of differentiated service delivery for HIV treatment in sub‌ـ Saharan Africa during COVID‐19. African Journal of Reproduction and Gynaecological Endoscopy, 24(6), e25704. https://doi.org/10.1002/jia2.25704
Hadari, S., Hakkak, M., Sepahvand, R., & Nazarpoury, A. (2022). A comparative study of smart city with organizational architecture of information‌ـ communication technology of the municipality. Journal of Iranian Social Development Studies, 53(12), 189–204. https://doi.org/10.35050/JIPM010.2016.028
Haji Shah Karam, M., & Mohammadi, S. (2016). The proposed architecture of the Internet of Things‌ـ based recommender systems for intelligent building in Tehran. Iranian Journal of Information Processing and Management, 32(1), 275–295. https://doi.org/10.35050/JIPM010.2016.028
Henneron, L., Kardol, P., Wardle, D. A., Cros, C., & Fontaine, S. (2020). Rhizosphere control of soil nitrogen cycling: A key component of plant economic strategies. New Phytologist, 228(4), 1269–1282. https://doi.org/10.1111/nph.16760
Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2–20. https://doi.org/10.1108/IMDS‌ـ 09‌ـ 2015‌ـ 0382
Hollands, R. G. (2020). Will the real smart city please stand up?: Intelligent, progressive or entrepreneurial?. In The Routledge companion to smart cities (pp. 179‌ـ199). Routledge. https://doi.org/10.1080/13604810802479126
Huh, J. H., Choi, J. H., & Seo, K. (2021). Smart trash bin model design and future for smart city. Applied Sciences, 11(11), 4810. https://doi.org/10.3390/app11114810
Khan, M. I., Asfand, F., & Al‌ـ Ghamdi, S. G. (2023). Progress in research and technological advancements of commercial concentrated solar thermal power plants. Solar Energy, 249, 183–226. https://doi.org/10.1016/j.solener.2022.10.041
Kreno, L. E., Leong, K., Farha, O. K., Allendorf, M., Van Duyne, R. P., & Hupp, J. T. (2012). Metal–organic framework materials as chemical sensors. Chemical Reviews, 112(2), 1105–1125. https://doi.org/10.1021/cr200324t
Kumar, V. (2020). Smart environment for smart cities. Springer. https://doi.org/10.1007/978‌ـ 981‌ـ 13‌ـ 6822‌ـ 6_1
Lazaroiu, G. C., & Roscia, M. (2012). Definition methodology for the smart cities model. Energy, 47(1), 326‌ـ 332. https://doi.org/10.1016/j.energy.2012.09.028
Lederman, N. G., & Abell, S. K. (Eds.). (2014). Handbook of research on science education (Vol. 2, pp. 600–620). Routledge. https://doi.org/10.4324/9780367855758
Lemke, L. K. G., Sakdapolrak, P., & Trippl, M. (2023). Unresolved issues in regional economic resilience: Conceptual ways forward. Progress in Human Geography, 47(5), 699–717. https://doi.org/10.1177/03091325231191242
Mirzaii, H., & Shabestari, S. H. (2020). Feasibility study of a low‌ـ carbon house in Tabriz, Iran. In Green buildings and renewable energy: Med Green Forum 2019—Part of World Renewable Energy Congress and Network (pp. 401–412). Springer International Publishing. https://doi.org/10.1007/978‌ـ 3‌ـ 030‌ـ 30841‌ـ 4_28
Mishra, P., & Singh, G. (2023). Energy management systems in sustainable smart cities based on the internet of energy: A technical review. Energies, 16(19), 6903. https://doi.org/10.3390/en16196903
Mohammadi Vosough, M., & Hanaee, T. (2023). Evaluation of the quality of the third place for young people with an emphasis on promoting social resilience. Space Ontology International Journal, 46(3), 15. https://doi.org/10.22094/soij.2023.1987978.1555
Mou, J., Gao, K., Duan, P., Li, J., Garg, A., & Sharma, R. (2022). A machine learning approach for energy‌ـ efficient intelligent transportation scheduling problem in a real‌ـ world dynamic circumstances. IEEE Transactions on Intelligent Transportation Systems, 24(12), 15527–15539. https://doi.org/10.1109/TITS.2022.3183215
Neirotti, P., De Marco, A., Cagliano, A. C., Mangano, G., & Scorrano, F. (2014). Current trends in Smart City initiatives: Some stylised facts. Cities, 38, 25‌ـ 36. https://doi.org/10.1016/j.cities.2013.12.010
Piprani, A. Z., Ali, A., & Shah, A. (2022). Big data analytics: Applications and barriers in supply chain. In Integrating blockchain technology into the circular economy (pp. 184–202). IGI Global. https://doi.org/10.4018/978‌ـ 1‌ـ 7998‌ـ 7642‌ـ 7.ch011
Piro, G., Cianci, I., Grieco, L. A., Boggia, G., & Camarda, P. (2014). Information centric services in smart cities. Journal of Systems and Software, 88, 169‌ـ 188. https://doi.org/10.1016/j.jss.2013.10.029
Radvanovsky, R., & McDougall, A. (2023). Critical infrastructure: Homeland security and emergency preparedness. CRC Press. https://doi.org/10.4324/9781003346630
Ramezanpour Karizaki, M., Saraie, M., Esteghlal, A., Almodaresi, S. A., & Hataminasab, S. H. (2023). Explanation of physical and spatial indicators of a smart city (Case study: Torbat Heydarieh city). Urban Space and Social Life, 2(4), 73–92. https://doi.org/10.4324/9781003346630
Rezaei, N., Haghparast, F., & Mohammadzade, R. (2023). The feasibility of smartening Grand Bazaar of Tabriz. Urban Space and Social Life, 2(6), 1–18. https://doi.org/10.22034/jprd.2023.57396.1054
Saberifar, R. (2020). Determination and identification of influential factors in the design of smart organization for urban management (Case study: Mashhad Municipality). Urban Planning Geography Research, 8(2), 445–467. https://doi.org/10.22111/gaij.2023.44065.3072
Saeed, S. (2023). A customer‌ـ centric view of E‌ـ commerce security and privacy. Applied Sciences, 13(2), 1020. https://doi.org/10.3390/app13021020
Sarker, A. K., Azad, A. K., Rasul, M. G., & Doppalapudi, A. T. (2023). Prospect of green hydrogen generation from hybrid renewable energy sources: A review. Energies, 16(3), 1556. https://doi.org/10.3390/en16031556
Sun, L., Chen, J., Li, Q., & Huang, D. (2020). Dramatic uneven urbanization of large cities throughout the world in recent decades. Nature Communications, 11, 5366. https://doi.org/10.1038/s41467‌ـ 020‌ـ 19158‌ـ 1
Talaat, F. M., & ZainEldin, H. (2023). An improved fire detection approach based on YOLO‌ـ v8 for smart cities. Neural Computing and Applications, 35(28), 20939–20954. https://doi.org/10.1007/s00521‌ـ 023‌ـ 08809‌ـ 1
Tang, K., & Yang, G. (2023). Does digital infrastructure cut carbon emissions in Chinese cities? Sustainable Production and Consumption, 35, 431–443. https://doi.org/10.1016/j.spc.2022.11.022
Vanolo, A. (2014). Smartmentality: The smart city as disciplinary strategy. Urban studies, 51(5), 883‌ـ 898. https://doi.org/10.1177/0042098013494427
Vinodh, S., Antony, J., Agrawal, R., & Douglas, J. A. (2021). Integration of continuous improvement strategies with Industry 4.0: A systematic review and agenda for further research. The TQM Journal, 33(2), 441–472. https://doi.org/10.1108/TQM‌ـ 07‌ـ 2020‌ـ 0157
White, G., Zink, A., Codecá, L., & Clarke, S. (2021). A digital twin smart city for citizen feedback. Cities, 110, 103064. https://doi.org/10.1016/j.cities.2020.103064
Urban Economics and Planning
Volume 6, Issue 1
Winter 2025
Pages 58-75

  • Receive Date 22 January 2025
  • Revise Date 10 March 2025
  • Accept Date 12 March 2025