https://ue.ui.ac.ir/ Urban Economics en daily 1 Sat, 21 Mar 2026 00:00:00 +0330 Sat, 21 Mar 2026 00:00:00 +0330 https://ue.ui.ac.ir/article_30205.html The objective of this study is to identify innovative financing tools for implementing urban projects in the Hamadan Municipality. Given the instability of traditional municipal revenues and the need for sustainable financial resources, this research adopted a qualitative approach. Initially, modern financing methods and examples of implemented projects were identified through library resources and reviews of Iranian municipal websites. Subsequently, semi-structured interviews were conducted with 60 experts, including representatives from investment and public participation organizations, investment companies, urban investors, faculty members from Bu-Ali Sina University, staff from the Hamadan Department of Economy and Finance, and capital market specialists. These interviews resulted in the identification of 24 innovative financing methods, categorized into three main groups: asset-based (e.g., public-private partnerships), debt-based (e.g., Islamic financial bonds), and equity-based (e.g., specialized funds). The findings also provided practical insights for implementing these methods and strategies for creating sustainable urban revenues. By focusing on Hamadan's characteristics, such as its medium scale and specific infrastructure needs, this research offers a practical model for sustainable development in similar Iranian cities. It contributes to filling the research gap on innovative financial tools for medium-sized cities. https://ue.ui.ac.ir/article_30072.html This study examines the spatio-temporal patterns of urban development in the centers of 31 Iranian provinces during the period 2001-2023 using spatial econometric methods. The study employs the spatio-temporal autoregression (STAR) model to analyze spatial dependencies and temporal dynamics affecting the composite urban development index. The findings show that urban development in Iran exhibits strong spatial dependence (ρ = 0.351), indicating that each province is significantly affected by neighboring provinces' conditions. The temporal inertia (φ = 0.285) demonstrates the persistent effects of development policies over time. Among the influential factors, the development budget and provincial gross domestic product have the greatest impact on urban development. Infrastructure variables, particularly road density, show the strongest spatial spillover effects, while population growth has a weakly negative effect. The results reveal the formation of spatial development clusters, with central provinces emerging as advanced poles and eastern/southern border provinces as less-developed areas. Through spatio-temporal analyses, this study proposes three policy categories: regional integration based on spatial dependencies, smart resource allocation emphasizing high-spillover projects, and data-driven governance for spatio-temporal monitoring of development indicators. These findings provide a scientific basis for designing Iran's smart regional development roadmap. https://ue.ui.ac.ir/article_30238.html Neighborhood economic sustainability is central to ensuring justice, welfare, and developmental opportunities for children. This study aims to identify and prioritize economic indicators contributing to the realization of sustainable child-friendly neighborhoods. The guiding question is: which economic indicators most strongly influence child-friendly neighborhood sustainability, and how do their priorities vary across three urban scales (metropolis, medium-sized city, small town)? The research adopted a mixed and applied methodology. First, a systematic review of scientific literature and domestic and international policy documents was conducted, followed by systematic content analysis (open coding independently by two researchers) to extract economic indicators. Next, the relative importance of each indicator was assessed using the Analytic Hierarchy Process (AHP) and expert input from 20 specialists. Findings identified nine key indicators: family, occupational, and livelihood welfare, child-centered economic participation, family-based entrepreneurship and employment, financial sustainability of child-related services, reduction of child-related costs, equitable economic access to services, forward-looking economic planning for children, economic justice in children’s benefits, and family economic capacity to support children. Comparative analysis revealed that family welfare consistently ranked first. In metropolises, emphasis was placed on economic justice and cost reduction; in medium-sized cities, human capital and local economy were more prominent; and in small towns, local financial resources, household economic capacity, and family entrepreneurship were prioritized. These results underscore the need for scale-sensitive policies that integrate short-term livelihood measures with long-term mechanisms of financing and justice. https://ue.ui.ac.ir/article_30310.html Buildings contribute significantly to energy production and carbon dioxide emissions, and experts are looking for ways to reduce this, focusing on eco-friendly design strategies. In this regard, the present study aims to systematically analyze energy consumption optimization strategies in urban environments as a framework for the development management of Isfahan. The present study is a review type, and a systematic literature review method was used to collect data, and a content analysis method was used to analyze them. The statistical population includes sources from 2011 to 2023. The present research method is based on a systematic literature review, which consists of five stages: definition, search, selection, analysis, and synthesis. Based on the research findings, a total of 17 components regarding energy consumption optimization solutions in urban environments, including double-skin facade; building orientation; building form; optimizing wall insulation thickness; optimizing wall-to-window ratio; optimizing window thickness; wireless network sensor; Wall height; existence of adjacent buildings; roofing materials; thermal comfort; passive cooling and heating; energy-based planning for a site; alternative energy sources; multi-objective optimization; light and canopy have been extracted. Additionally, this research investigates the orientation of Group C residential buildings as a key factor influencing energy efficiency in the city of Isfahan. The results of the research show that the energy saving potential with the appropriate orientation of Group C residential apartment buildings in the Isfahan region for total energy consumption is 32 percent, and the optimal building orientation in the city of Isfahan in terms of energy consumption is the southern orientation. https://ue.ui.ac.ir/article_30467.html This article aimed to analyze the spatial differences in housing prices in the Tehranpars neighborhood and their relationship with 12 spatial factors. Housing data, which served as the dependent variable, were obtained from 54 real estate offices to create a point layer in GIS. Information on the 12 independent variables was gathered through field observations and calculations based on shapefile data from the 2016 Iranian National Census. To analyze the data, zoning maps were created using the Interpolation-IDW (Inverse Distance Weighting) function. The Moran index and Pearson correlation were calculated, and a geographically weighted regression (GWR) model was implemented. Findings showed that housing prices follow a clustered distribution pattern, with higher prices in the geometric center of the neighborhood and decreasing prices toward the east and west. Among the 12 independent variables, three factors—per capita residential infrastructure, the percentage of resilient houses, and [third factor]—showed a strong positive correlation, while one factor (the percentage of housing with an area of 75 square meters or less) showed a strong negative correlation with housing prices. The weighted regression analysis showed that three independent variables—population density, distance from the nearest park, and per capita residential infrastructure—have a significant spatial relationship with housing prices.