Urban Management
leila sahraei cheshmehsardeh; Alireza Sheikholeslami; Ahmad PourAhmad; Hassan Piriaei
Abstract
Qualitative Analysis of the Mechanisms Shaping Social Resilience in Relation to Urban Governance in the Context of BorujerdLeila Sahraei Cheshmeh Sarde¹, Alireza Sheikh al-Islami²*, Ahmad Pourahmad³, Hassan Piriaei⁴ExtendedabstractIntroductionIn recent years, social resilience has emerged ...
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Qualitative Analysis of the Mechanisms Shaping Social Resilience in Relation to Urban Governance in the Context of BorujerdLeila Sahraei Cheshmeh Sarde¹, Alireza Sheikh al-Islami²*, Ahmad Pourahmad³, Hassan Piriaei⁴ExtendedabstractIntroductionIn recent years, social resilience has emerged as a critical component of sustainable urban development, particularly in cities facing increasing social, economic, and spatial pressures. Medium-sized cities in Iran, such as Borujerd, experience compounded challenges related to unequal access to urban services, weakened institutional trust, and limited citizen participation in decision-making processes. These challenges undermine the capacity of local communities to adapt to, recover from, and collectively respond to urban stresses and disruptions.Urban governance plays a decisive role in shaping social resilience through institutional arrangements, decision-making mechanisms, and the quality of interactions between citizens and public institutions. In particular, spatial justice and institutional trust have been identified as key determinants influencing citizens’ perceptions of fairness, legitimacy, and responsiveness of urban management. Despite growing scholarly attention to social resilience, the mechanisms through which urban governance contributes to resilience—especially in the Iranian urban context—remain insufficiently explored. This study addresses this gap by analyzing the causal mechanisms linking urban governance to social resilience, with a specific focus on spatial justice as a causal driver and institutional trust as a mediating variable in the city of Borujerd.Theoretical FrameworkThe theoretical foundation of this study integrates concepts from social resilience, urban governance, and spatial justice. Social resilience is conceptualized as a multidimensional capacity rooted in social capital, trust, collective learning, and institutional embeddedness. From a governance perspective, “good urban governance” emphasizes participation, transparency, accountability, and equity in urban decision-making processes.Spatial justice serves as a critical causal mechanism through which governance quality becomes socially perceptible. Equitable distribution of urban services, infrastructure, and public spaces shapes citizens’ everyday experiences and directly influences their trust in urban institutions. Institutional trust, in turn, functions as a mediating mechanism that transforms governance practices into collective adaptive capacity. Accordingly, the study proposes a causal pathway in which urban governance influences social resilience primarily through spatial justice and institutional trust, rather than through direct effects alone.MethodologyThis research adopts a sequential exploratory mixed-methods design (qualitative → quantitative) with an applied research orientation. In the qualitative phase, in-depth semi-structured interviews were conducted with 40 experts, including urban planners, municipal managers, sociologists, local activists, and community representatives in Borujerd. The qualitative data were analyzed using thematic content analysis, leading to the identification of key constructs and the development of a context-sensitive conceptual model.Based on the qualitative findings, a researcher-designed questionnaire was developed for the quantitative phase. Data were collected from 384 residents of Borujerd using multi-stage cluster sampling to ensure spatial representation across different urban zones. Structural Equation Modeling (SEM) was employed to test the proposed model using AMOS software.Measurement validity and reliability were confirmed through multiple indicators. Convergent validity was verified with a Content Validity Ratio (CVR = 0.81), and internal consistency reliability was confirmed with a Cronbach’s alpha coefficient of 0.92. Sampling adequacy was supported by a Kaiser–Meyer–Olkin (KMO) value of 0.89. Model fit indices demonstrated satisfactory fit (RMSEA = 0.053, GFI = 0.91, AGFI = 0.87).Results and DiscussionThe results indicate that urban governance has a positive and statistically significant effect on social resilience in Borujerd. However, this effect is substantially strengthened through indirect pathways. Spatial justice emerged as a strong causal mechanism linking governance quality to institutional trust, while institutional trust played a decisive mediating role in enhancing social resilience.The findings confirm that citizens’ perceptions of fair distribution of services and opportunities are foundational to building trust in urban institutions. Governance practices that fail to address spatial inequalities weaken institutional legitimacy and, consequently, reduce social resilience capacity. Conversely, governance that prioritizes equitable access, transparency, and accountability fosters trust, collective engagement, and adaptive capacity at the neighborhood level.These results highlight the importance of indirect governance mechanisms and suggest that resilience-oriented urban management must move beyond formal administrative efficiency toward socially embedded and distributive governance practices.ConclusionThis study demonstrates that social resilience in Borujerd is not merely an outcome of economic or physical conditions but is fundamentally shaped by governance-related social mechanisms. Spatial justice functions as a causal driver, and institutional trust acts as a key mediating mechanism through which urban governance influences social resilience. The proposed model offers a context-specific framework for understanding resilience in medium-sized Iranian cities and underscores the need for participatory, transparent, and equity-oriented governance approaches to enhance urban resilience.KeywordsSocial Resilience; Institutional Trust; Spatial Justice; Neighborhood Networks; Borujerd
Urban Planning
parvaneh jalerajabi; reza ahmadian; Zahra sadat saiedeh Zarabadi
Abstract
This research was conducted mainly to provide a method based on artificial intelligence algorithms in order to obtain optimal urban land use allocation, subjected to mathematical modeling from the perspective of spatial justice using multi-criteria decision analysis concepts, both parcel-based and floor-based. ...
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This research was conducted mainly to provide a method based on artificial intelligence algorithms in order to obtain optimal urban land use allocation, subjected to mathematical modeling from the perspective of spatial justice using multi-criteria decision analysis concepts, both parcel-based and floor-based. For that purpose, objective functions were considered for land use allocation, including mixed use, suitability, dependency, compatibility, and access to services, in terms of both floors and neighbors. For achievement of the main purpose, parameters effective on urban land use planning were examined to optimize urban land use allocation from the spatial justice perspective. This led to a presentation and classification of the spatial parameters effective on land use allocation based on sustainability and, more specifically, spatial justice concerns. The main part of the research, named “land use allocation modeling with NSGA-II” focused on development of a land use allocation model and its optimization. The main stage in the modeling procedure was to adapt multi-objective optimization algorithms to land use allocation and, then, to define it as desired. The adaptation of the multi-objective optimization algorithm involved the definition of the solution structure, objective functions, and problem constraints and their calculation for use in the second version of the Non-dominant Genetic Ranking Algorithm (NSGA-II). The objective functions were defined based on criteria and indexes extracted in the second part of the research, including maximization of accessibility to the facilities, of service efficiency (compatibility), of mixed uses, of land suitability, and of spatial dependency. Moreover, seven constraints were introduced for land use allocation, including avoidance of allocating wasteland to the first floor of the parcel, allocation of a land use to the third floor provided that the second one already has a defined land use, possibility of land use allocation to various floors of the same parcel, consideration of maximum and minimum land parceling, avoidance of exceeding the per capita standards in neighborhoods and districts, and, finally, allocation of the necessary land uses to each of the neighborhoods. The models were then implemented, where the main purpose was to optimize urban land use allocation according to all the criteria and constraints. In other words, these criteria had to be defined in terms of the model objectives and with an extensive search space (many of the possible land use allocations) at the same time. Therefore, a set of solutions, which included Pareto front, i.e. optimal, solutions, was obtained rather than a single solution to the problem. As decision-makers prefer to examine the corresponding scenarios after introducing their own decision priorities, the AHP method was used finally after the optimal Pareto solutions were obtained for selection of one of the four possible land use allocations and its presentation in a land use plan given spatial justice concerns. For that purpose, weights were assigned to the objective functions based on spatial justice. Once the objective function values were normalized, the desired weights were multiplied by the normal values. After the calculation of total weight, the solutions corresponding to the objective functions being addressed were converted to land use plans in ArcGIS. The results of land use allocation in floors were compared to the actual conditions. It could be stated in general that the most important achievement of the study involved the introduction and presentation of an efficient model that was appropriate for addressing multi-criteria decision-making problems for allocation of urban land use. The presented model performs simultaneous optimization, and helps decision makers to select one desired solution from among multiple optimized ones according to their priorities, although it is in contradiction with some of the objective functions. The results of the model designed for land use allocation given spatial justice concerns improved the spatial distribution of facilities at the level of the area under study. Moreover, a quantitative evaluation of the allocation results demonstrated that the commercial, academic, health, sport, and cultural land uses were allocated properly per capita, increasing the level of enjoyment in neighborhoods across the area under investigation. Land use allocation, Spatial justice, Multi-objective optimization method, NSGA-II.
