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February 20, 2026Urban Science0 citationsOpen Access

Measuring Retail Resilience Using a Geospatial Multi-Criteria Model: A Case Study of Saida, Lebanon

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NBNour Ahmad El BabaIBIbtihal Y. El BastawissiAAAyman Afify

Key Points

  • The study aims to create a measurable model for assessing retail resilience at the neighborhood level in Saida.
  • Developed a geospatial multi-criteria model producing a composite Urban Retail Resilience Index (URRI).
  • Used indicators related to diversity, spatial proximity, and socioeconomic conditions.
  • Applied two weighting scenarios: baseline and stakeholder-based weights to evaluate model robustness.
  • Identified distinct spatial variations in retail resilience throughout Saida.
  • Showed that walkability and socio-cultural characteristics significantly impact retail resilience.
  • Highlighted hotspots for potential urban interventions based on resilience analysis.

Abstract

Urban retail environments are social and economic manifestations of a city, enhancing economic growth and social cohesion. However, they increasingly face challenges from economic downturns, changing consumer preferences, and spatial dynamics, making their ability to adapt and remain viable a critical concern. In this context, retail resilience refers to the capacity of urban retail environments to absorb disturbances, adapt to change, and sustain their economic and social functions over time. Despite growing interest in urban resilience, the operationalization of retail resilience through spatially explicit and measurable indicators remains limited, as many assessments focus on city or regional scales and overlook variations at the neighborhood level. Thus, this paper aims to develop a geospatial multi-criteria model yielding a composite Urban Retail Resilience Index (URRI) to analyze and interpret retail resilience in Saida’s urban retail environment through an adaptive cycle lens. The URRI combines indicators related to diversity, spatial proximity, and socioeconomic conditions, and is applied using two weighting scenarios—baseline and stakeholder-based weights—to test the model’s robustness and reflect local priorities. The results reveal distinct spatial variations in retail resilience across the study area, enabling the identification of hotspots for interventions and highlighting the role of accessibility and diversity in shaping the adaptive capacity. These findings confirm that Saida’s retail resilience is closely linked to walkability and socio-cultural characteristics. The proposed geospatial multi-criteria model provides a robust and replicable framework for assessing retail resilience, offering practical insights for urban planners and policymakers.

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Cite This Study

Baba et al. (2026) studied this question.

synapsesocial.com/papers/6997fa03ad1d9b11b3452ee7https://doi.org/10.3390/urbansci10020120
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