The efficient and green use of urban land is essential for achieving sustainable urban development. However, local protectionism often undermines the allocative efficiency of market mechanisms and the implementation of top-down environmental regulations. By treating China's 2018 environmental tax legislation as an exogenous policy shock, we examine how strengthened regulatory enforcement enhances urban green land-use efficiency (UGLUE) by curbing local protectionism. The findings indicate that this policy curtails protection for incumbent firms, forcing them to either upgrade or exit, thereby promoting industrial upgrading. Simultaneously, it restrains protection for new polluting projects, as evidenced by a reduction in land allocation to high-pollution industries. These mechanisms collectively elevate UGLUE by optimizing the use of both existing and newly allocated urban land. Furthermore, the effects of the environmental tax legislation vary with the intensity of local protectionism. By adopting the lens of local protectionism, this research broadens the analytical framework for policy evaluation and provides practical insights for more targeted urban growth management.
Homeless populations face multiple and intersecting vulnerabilities in rapidly urbanizing cities; however, the lived experiences of individuals residing beneath flyovers in Dhaka remain underexplored. This study explores their lived experiences, with particular attention to shelter, food security, safety, and personal identity, and challenges related to food, income, housing, safety risks, extreme weather, and sexual violence. By employing a qualitative design, data collection was conducted with 20 in-depth interviews (IDIs) using purposive sampling. The study used Interpretative Phenomenological Analysis (IPA) to facilitate an in-depth exploration of participants' lived experiences of homelessness. Themes were developed inductively from the raw data and subsequently interpreted within the study's theoretical framework. Data were analyzed using Braun and Clarke's six-stage thematic approach and NVivo 15 to facilitate systematic data coding. The findings reveal that people residing under flyovers face informal housing, food shortages, unstable informal incomes, exposure to harsh weather, dependence on begging, security risks, and experiences of sexual violence. Future large-scale mixed-methods research involving women, children, and people with disabilities is needed to provide a more comprehensive understanding of homelessness and vulnerability in urban Bangladesh. The findings provide evidence to inform more inclusive urban policies that integrate temporary shelter, accessible healthcare, livelihood support, and community safety for people experiencing homelessness beneath flyovers in Dhaka, Bangladesh.
Real estate stock companies’ price fluctuations have been analysed extensively, particularly in terms of regional focus and investment type. However, the activities on which the real estate stock corporations focus have not yet been thoroughly analysed. The intensity to which these companies participate in various real estate segments of the value chain and within different sectors may lead to differing capital market performances. This is because individual activities may be more susceptible to shocks or valued differently by capital markets. This study clusters real estate stock companies in the German-speaking region (DACH region) according to their revenue structures along two dimensions: business segments (along the value chain) and sectors (real estate asset classes). Based on a novel dataset, the analysis identifies four statistically robust clusters among real estate stock companies. These four clusters can be viewed as different business models. Stock indices are then computed for these four clusters, and their performance during crises is analysed. Granger causality tests, changepoint analysis and three volatility measures are employed to investigate these reactions. The results underscore that these clusters react differently to the selected shocks. These insights serve as a basis for systematic benchmarking and enrich the understanding of stock market performances and resilience of different real estate business models across market phases.
Noise generation along Mass Rapid Transit (MRT) corridors is an emerging environmental concern in densely populated cities. It has adverse effects on public health and urban livability. This study analyses field noise measurements from 99 locations along MRT-6 corridor in Dhaka, Bangladesh. Upon utilizing the collected noise data, a regression-based noise prediction model is developed for estimating maximum noise levels (Lmax). The model is statistically significant (p=0.000) and the three predictors are able to explain 65.4% of the variation of Lmax along the MRT corridor (R2=0.654). The standardized beta coefficients from the resulting prediction model reveal that Lmax along the corridor is significantly influenced by distance from the MRT track (β = −0.637), followed by land use and lastly, train speed (β = 0.133). These results indicate that noise exposure along the corridor is primarily dictated by proximity to the track but is also influenced by the surrounding urban land use. By quantifying how specific urban land uses alter noise propagation, this predictive model provides urban planners and policymakers with an evidence-based tool to establish statutory setback distances and guide future development along transit routes in Dhaka.
Existing multidimensional housing affordability assessments have yet to adequately explain how neighborhood physical-spatial conditions, residents' priorities, and residential satisfaction are interrelated. This study investigates the sustainability of housing affordability by developing an integrated conceptual framework that recognizes financial affordability and neighborhood livability as two interrelated dimensions of sustainable housing affordability. Grounded in housing affordability, neighborhood design, and residential satisfaction scholarship, the framework integrates six criteria and twenty-four indicators. Employing a mixed-methods comparative approach, the research examines two planned neighborhoods in Khulna, Bangladesh, through morphological mapping and built-environment analysis, 200 semi-structured household interviews, Residents' Preference and Satisfaction Indices (RPI and RSI), and separate multiple linear regression models. The physical-spatial analysis reveals contrasting neighborhood qualities: mixed land use and interconnected streets support accessibility and social interaction but are constrained by congestion, inadequate pedestrian infrastructure, and limited public spaces; conversely, more controlled residential layouts provide spatial order and greenery but restrict access to everyday services and informal social spaces. Residents assigned high importance to housing price/rent in both neighborhoods, alongside differing priorities concerning walkability, infrastructure connectivity, and environmental quality. Overall residential satisfaction with neighborhood livability varied between the neighborhoods, with contrasting patterns across income groups. The regression models exhibited substantial within-sample explanatory fit, identifying significant associations between neighborhood satisfaction and the perceived importance of commuting-related attributes, natural elements, social space, sense of place, and crime rates. By integrating physical-spatial evidence with residents’ priorities and satisfaction, the study advances multidimensional housing affordability assessment and provides an empirical basis for context-sensitive neighborhood design and planning guidelines that promote neighborhood livability and sustainable residential development.
