International Journal of Urban Management and Energy Sustainability

International Journal of Urban Management and Energy Sustainability

Spatial Configuration Analysis and Identification of Blind Spots in Large-Scale Shopping Centres Using Space Syntax (Case Study: Floor G2 of Iran Mall, Tehran, Iran)

Articles in Press

Document Type : Case Study

Authors
Shahla Naderi Delpak
Azadeh Shahcheraghi
Zahra Sadat Saeideh Zarabadi
Department of Architecture, SR.C, Islamic Azad University, Tehran, Iran
10.22034/ijumes.2026.2107623.1412
Abstract
The marked decline of footfall on the upper floors of large-scale shopping centres is a fundamental challenge of contemporary architectural design. Despite advances in space-syntax theory for analysing spatial behaviour, the systematic use of this toolset to diagnose configurational weaknesses in multi-purpose commercial complexes has received limited attention. This study quantitatively analyses the spatial configuration of Floor G2 of Iran Mall in Tehran and identifies its blind spots using three complementary analytical toolsets axial analysis, visibility graph analysis, and network analysis and, through reverse engineering, derives design rules from five leading global projects to remedy the identified weaknesses. VGA over more than 3,000 points yielded a mean connectivity of 1.00, a mean isovist area of 35 m², and a visual permeability of 0.28. In the network analysis of 166 nodes and 250 edges, 55% of nodes had zero betweenness centrality and only 6 nodes played a strategic role. Integrating the three analyses identified 28 blind spots with a cumulative area of about 450 m², mainly on the eastern, western, and northern fronts, and four spatial categories: strategic cores, latent central spaces, low-access through-paths, and blind spots. On this basis, six soft design rules were derived. A deep tree-like structure, the absence of movement loops, and visual isolation are the main causes of reduced footfall. Combining the three spatial-analysis tools enables precise diagnosis of configurational weaknesses, and the design rules derived by reverse-engineering global exemplars provide an objective basis for redesign and can serve as input to optimization in future research.

Graphical Abstract

Spatial Configuration Analysis and Identification of Blind Spots in Large-Scale Shopping Centres Using Space Syntax (Case Study: Floor G2 of Iran Mall, Tehran, Iran)

Highlights

·         Three complementary space-syntax tools axial analysis, visibility graph analysis (VGA), and network analysis are combined to diagnose configurational weaknesses of Floor G2 of Iran Mall.

·         Floor G2 has a deep, unbalanced, tree-like structure: mean integration 16.77, mean spatial depth 6.06 steps, mean connectivity 1.00, and visual permeability 0.28.

·         Twenty-eight blind spots were identified, with a cumulative area of about 450 m² (3.75% of the floor), concentrated on the eastern, western, and northern fronts.

·         Network analysis of 166 nodes and 250 edges shows 55% of nodes with zero betweenness centrality and only 6 strategic through-nodes, confirming the absence of movement loops.

·         Reverse engineering of five leading global projects yields six operational soft design rules that translate the diagnosis into an evidence-based basis for redesign.

Keywords
Blind spots
DepthmapX
Iran Mall
reverse engineering
Space syntax
Altafini, D., Salardi-Jost, M., & Cutini, V. (2024). Decoding small-worlds networks in a regional context: Unveiling local-local and local-global centrality logics with space syntax. In Proceedings of the 14th Space Syntax Symposium (pp. 1625–1656). Tab Edizioni.
Altafini, D., & Cutini, V. (2020). Homothetic behavior of betweenness centralities: A multiscale alternative approach to relate cities and large regional structures. Sustainability, 12(19), 7925. https://doi.org/10.3390/su12197925
Altuwaijri, H. A., Hossain, S. T., Al-Ramadan, B., & Bilal, M. (2025). Enhancing accessibility in public spaces: A computational study of Hatirjheel lakefront using space syntax. ISPRS International Journal of Geo-Information, 14(1), 29. https://doi.org/10.3390/ijgi14010029
Bier, H., & Knight, T. (2024). Data-driven design in architecture: A systematic review. Journal of Architectural Computing, 22(1), 15–38.
Carpo, M. (2017). The second digital turn: Design beyond intelligence. MIT Press.
Chen, Y., Wang, L., & Zhao, M. (2023). Amazon Go: The future of retail space design. Journal of Retailing, 99(2), 189–204.
Davis, M. (2013). Reverse engineering in architecture. Architectural Design, 83(4), 88–95.
Deutsch, R. (2015). Data-driven design and construction. John Wiley & Sons.
El-Ghandour, W., & Al-Huss, M. (2004). Productivity in the construction industry: A review. Journal of Construction Engineering and Management, 130(5), 718–727. https://doi.org/10.1061/(ASCE)0733-9364(2004)130:5(718)
Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. https://doi.org/10.2307/3033543
Freeman, L. C. (1978). Centrality in social networks: Conceptual clarification. Social Networks, 1(3), 215–239. https://doi.org/10.1016/0378-8733(78)90021-7
Gath-Morad, M., Thrash, T., Schöninger, C., Hölscher, C., & Granić, A. (2023). The DesignMind toolkit: Integrating empirical evidence into architectural design. In Proceedings of CAADRIA 2023.
Hillier, B. (1996). Space is the machine. Cambridge University Press.
Hillier, B., & Hanson, J. (1984). The social logic of space. Cambridge University Press.
Hillier, B., & Iida, S. (2005). Network and psychological effects in urban movement. In Spatial information theory (COSIT 2005), Lecture Notes in Computer Science (Vol. 3693, pp. 475–490). Springer. https://doi.org/10.1007/11556114_30
Hillier, B., Penn, A., Hanson, J., Grajewski, T., & Xu, J. (1993). Natural movement: Or, configuration and attraction in urban pedestrian movement. Environment and Planning B: Planning and Design, 20(1), 29–66. https://doi.org/10.1068/b200029
Hosseini, Z., Yeganeh, M., & Jalali, S. (2024). Exploring the impact of vertical access elements on visual richness and space quality within shopping mall atriums. Buildings, 14(9), 2724. https://doi.org/10.3390/buildings14092724
Jalalian-Hoseini, S. (2020). Space syntax in architectural design. University of Tehran Press. [in Persian]
Jalalian-Hoseini, S. (2022). Analysis of bazaars and shopping centers as urban spaces via space-syntax software (Case studies: Iranian bazaars and Tehran shopping centers). Journal of Iranian Architecture Studies. [in Persian]
Khachouch, M. K., Korchi, A., & Lakhrissi, Y. (2023). Architecture-driven modernization: A review on reverse-engineering techniques based on models' approach. WSEAS Transactions on Information Science and Applications, 20, 293–302.
Li, J., & Bian, K. (2024). Construction of an urban spatial intelligent planning and design system under the background of big data. International Journal of Information Technology and Systems, 17(1).
Lian, H., & Li, G. (2023). Correlation analysis of retail space and shopping behavior in a commercial street based on space syntax: A case of Shijiazhuang, China. Buildings, 13(11), 2674. https://doi.org/10.3390/buildings13112674
Loyola, M. (2018). The productivity gap in the AECO industry. Building Research & Information, 46(5), 489–504.
Manum, B. (2009). AGraph: A tool for spatial analysis. In Proceedings of the 7th International Space Syntax Symposium.
Manum, B., Rusten, E., & Benze, P. (2005). AGraph: A tool for spatial analysis. In Proceedings of the 5th International Space Syntax Symposium.
Najafpour, I., & Haghlesan, M. (2023). Optimizing the spatial design of urban metro stations using the space-syntax method. Journal of Architect, Urban Design & Urban Planning, 16(44), 49–67. [in Persian]
Penn, A. (2003). Space syntax and spatial cognition: Or why the axial line? Environment and Behavior, 35(1), 30–65. https://doi.org/10.1177/0013916502238864
Penn, A., Hillier, B., Banister, D., & Xu, J. (1998). Configurational modelling of urban movement networks. Environment and Planning B: Planning and Design, 25(1), 59–84. https://doi.org/10.1068/b250059
Sajadzadeh, H., Arianpour, S., & Talischi, G. (2023). A comparative study of behavioral camps in the traditional bazaar and the Diplomat shopping center of Boroujerd based on spatial-configuration analysis. Journal of Researches in Islamic Architecture, 11(1). [in Persian]
Space Syntax. (2018). Broadgate Arena: Post-occupancy evaluation report. UCL Space Syntax Lab.
Turner, A. (2001). Depthmap: A program to perform visibility graph analysis. In Proceedings of the 3rd International Space Syntax Symposium.
Turner, A. (2007). From axial to road-centre lines: A new representation for space syntax and a new model of route choice for transport-network analysis. Environment and Planning B: Planning and Design, 34(3), 539–555. https://doi.org/10.1068/b32067
van Nes, A. (2021). The impact of the ring roads on the location pattern of shops in town and city centres: A space-syntax approach. Sustainability, 13(7), 3927. https://doi.org/10.3390/su13073927
Varoudis, T. (2020). DepthmapX: A cross-platform software for space-syntax analysis. Journal of Space Syntax, 11(1), 45–62.
Varoudis, T., & Hanna, S. (2024). Beyond axial lines: High-resolution geometric analysis of London's urban fabric using LIDAR scans. UCL Discovery.
Wang, Y. (2024). Research on urban traffic congestion using a dual-modal model of space syntax based on big data. In Proceedings of ICAICE '24 (pp. 1–6). ACM.
Yurtseven, M. (2024). The verticality challenge in shopping malls. Journal of Urban Design, 29(3), 301–318.
Zaleckis, K., Chmielewski, S., Kamičaitytė, J., Grazuleviciute-Vileniske, I., & Lipińska, H. (2022). Walkability compass: A space-syntax solution for comparative studies. Sustainability, 14(4), 2033. https://doi.org/10.3390/su14042033
Zhang, J., Song, J., & Fan, Z. (2023). The study of historical progression in the distribution of urban commercial space locations—Example of Paris. Sustainability, 15(19), 14499. https://doi.org/10.3390/su151914499
Zhou, W., Guo, H., Hou, X., Lai, W., & Yao, L. (2024). A statistical study of the pedestrian distribution in a commercial wholesale centre based on the traffic spatial structure. Buildings, 14(6), 1782. https://doi.org/10.3390/buildings14061782
International Journal of Urban Management and Energy Sustainability

Articles in Press, Accepted Manuscript
Available Online from 22 October 2026

  • Receive Date 02 July 2026
  • Revise Date 01 October 2026
  • Accept Date 22 October 2026