Search results

This chapter embarks on a cross-Asian comparison to glean valuable insights from various regions and religious contexts. By examining family planning practices and challenges in different parts of Asia, valuable lessons are uncovered that can inform policies, programs, and initiatives aimed at achieving family planning-related sustainable development goals (SDGs). The complexities and nuances of family planning across diverse cultural, social, and religious landscapes are delved into, shedding light on both common threads and unique challenges faced by marginalized communities. Through this comparative analysis, the aim is to contribute to a holistic understanding of family planning in Asia and provide actionable recommendations to enhance access, equity, and outcomes in pursuit of family planning-related SDGs.

In this final chapter, we explore the ever-evolving 21st century landscape where ethics drive community development toward resilience and progress. Drawing inspiration from the subheadings mapping our journey, we traverse international case studies spanning Canada, Brazil, Sweden, Kenya, China, Australia, Antarctica, and India. Through these global insights, we uncover the impacts of dynamic forces on communities worldwide, navigating ethical dilemmas and opportunities. We present strategies tailored to diverse continent-specific needs, explore inclusive governance models, and highlight the transformative power of ethical engagement. This journey underscores the vital role of resilience and concludes with a global call to embrace ethical approaches for inclusive community development and a sustainable future.

The purpose of this study is to examine the relationship between the productive structure and the size of the informal economy in Latin American countries.

The study employs econometric techniques for panel data covering the period from 2002 to 2017 and considering 17 Latin American countries. The evidence presented is based on the informal economy data generated by Medina and Schneider (2018) who estimate the size of the informal economy using a structural equation model and the share of manufacturing in total employment as a measure of the size of the manufacturing sector. Also, the study addresses the possible endogeneity bias in the relationship studied and makes the conclusions more robust, thus avoiding spurious correlations that weaken the findings.

The results indicate that most industrialized Latin American countries are associated with a smaller size of the informal economy.

The findings have important policy implications, as they suggest that Latin American economies need to switch the structure of the economy toward more sophisticated productive structures if they want to reduce the size of the informal economy. Thus, more efforts should be deployed to policies to diversify and upgrade economies.

The study contributes to the literature on the informal economy by connecting the country’s productive structure and informality. Specifically, the results show that the productive structure of countries is a plausible explanation for the size of the informal economy.

This chapter provides a comprehensive exploration of global demographic trends and challenges, specifically focusing on Asian countries and the demographic landscape of Bangladesh. This chapter highlights the implications of rapid population growth, aging populations, and urbanization, analyzing their socioeconomic impacts on education, healthcare, and employment. By contextualizing these trends within the broader framework of sustainable development, this chapter sets the stage for understanding the intricate relationship between population dynamics and the empowerment of marginalized communities through family planning strategies.

The fundamental aim of the study is to investigate the implications of labor housing designs in Dubai, with a focus on courtyards and the governing building regulations, on daylight performance as an underlying factor impacting laborers’ indoor environmental quality. Several studies shed light on the subject of labor camps and labor migration in Dubai, but few have focused on the subject from the perspective of the environmental performance of these camps. A model that represents one of the labor camps was built using Rhinoceros 7.0 and Grasshopper software packages. Annual daylighting and glare simulations were carried out using the lighting modeling engine RADIANCE 5.0 in conjunction with the “ClimateStudio”.

The construction sector has emerged as a significant economic development driver, attracting a diverse labor force from a variety of countries to Dubai. As a result, Dubai authorities have implemented several measures to ensure the provision of suitable housing facilities for its labor force. These measures contribute to the reduction of energy costs in labor housing by encouraging the use of renewable energy. While several studies shed light on the subject of labor camps and labor migration in Dubai, few have focused on the subject from the perspective of the environmental performance of these camps.

The study provided statistical evidence that the current regulations governing courtyards in labor housing resulted in significant changes in daylight levels across different floor levels of the labor housing units. It is suggested that both 2:3 and 3:4 Court Width-to-Height ratios would further contribute to a more consistent daylight Illuminance with marginal statistical differences between floor levels (p > 0.05). The 3:4 ratio, on the other hand, offers a consistent distribution across all floor levels in the North and South with negligible variances, although weakly significant differences can be yet expected between the first and fourth floors in the East and West orientations (p < 0.05). The results of Annual Sunlight Exposure (ASE) suggest excessive solar incidence and a high probability of glare, which remains a problem that must be addressed under the governing building regulations.

This study could serve as a framework for analyzing and contrasting the findings of other studies on labor accommodation, notably in the Gulf Cooperation Council (GCC) countries. Such an approach has the potential to enhance living conditions in labor accommodations in Dubai and other areas. It is necessary to meet people' physical and psychological well-being while also addressing sustainability and regulatory compliance.

This study aims to investigate the spatial distribution of housing prices and identify the affecting factors (independent variable) on the cost of residential units (dependent variable).

The method of the present study is descriptive-analytical and has an applied purpose. The used statistical population in this study is the residential units’ price in Tehran in 2021. For this purpose, the average per square meter of residential units in the city neighborhoods was entered in the geographical information system. Two techniques of ordinary least squares regression and geographically weighted regression have been used to analyze housing prices and modeling. Then, the results of the ordinary least squares regression and geographically weighted regression models were compared by using the housing price interpolation map predicted in each model and the accurate housing price interpolation map.

Based on the results, the ordinary least squares regression model has poorly modeled housing prices in the study area. The results of the geographically weighted regression model show that the variables (access rate to sports fields, distance from gas station and water station) have a direct and significant effect. Still, the variable (distance from fault) has a non-significant impact on increasing housing prices at a city level. In addition, to identify the affecting variables of housing prices, the results confirm the desirability of the geographically weighted regression technique in terms of accuracy compared to the ordinary least squares regression technique in explaining housing prices. The results of this study indicate that the housing prices in Tehran are affected by the access level to urban services and facilities.

Identifying factors affecting housing prices helps create sustainable housing in Tehran. Building sustainable housing represents spending less energy during the construction process together with the utilization phase, which ultimately provides housing at an acceptable price for all income deciles. In housing construction, the more you consider the sustainable housing principles, the more sustainable housing you provide and you take a step toward sustainable development. Therefore, sustainable housing is an important planning factor for local authorities and developers. As a result, it is necessary to institutionalize an integrated vision based on the concepts of sustainable development in the field of housing in the Tehran metropolis.

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

Land value varies at a micro level depending on the location’s economic, geographical and political determinants. The purpose of this study is to present a comprehensive assessment of the determinants affecting land value in the Indian city of Thiruvananthapuram in the state of Kerala.

The global influence of the identified 20 explanatory variables on land value is measured using the traditional hedonic price modeling approach. The localized spatial variations of the influencing parameters are examined using the non-parametric regression method, geographically weighted regression. This study used advertised land value prices collected from Web sources and screened through field surveys.

Global regression results indicate that access to transportation facilities, commercial establishments, crime sources, wetland classification and disaster history has the strongest influence on land value in the study area. Local regression results demonstrate that the factors influencing land value are not stationary in the study area. Most variables have a different influence in Kazhakootam and the residential areas than in the central business district region.

This study confirms findings from previous studies and provides additional evidence in the spatial dynamics of land value creation. It is to be noted that advanced modeling approaches used in the research have not received much attention in Indian property valuation studies. The outcomes of this study have important implications for the property value fixation of urban Kerala. The regional variation of land value within an urban agglomeration shows the need for a localized method for land value calculation.

This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability.

Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index.

U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO₂ emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO₂ reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality.

This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.