The transition from a linear economic model to a circular economy (CE) marks a profound change, driving toward better resource management and ecological robustness. Although much previous investigation has concentrated on specific industries, this research takes a broader, multi - sector approach. It delves into how circular economy principles are being incorporated across crucial industries such as textiles, construction, energy, chemical production and agriculture in Uzbekistan. Employing a qualitative research methodology, which involved synthesizing existing literature and scrutinizing policies, the study pinpoints the primary forces driving this change, the obstacles encountered and the connections between different sectors that influence the move toward a circular economy. The results highlight that shared circular practices - like industrial symbiosis, optimizing resource use, adopting renewable energy and developing circular business models - are essential for boosting both environmental sustainability and economic viability. Nevertheless, this transition faces hurdles due to inadequate infrastructure, disjointed governance structures and insufficient skilled personnel, especially within developing nations. Examining Uzbekistan specifically, we observe both growing policy dedication and ongoing structural difficulties, underscoring the need for synchronized governance, investment in green initiatives and robust innovation systems. This work adds to the existing body of knowledge by introducing a conceptual framework that spans multiple sectors. This framework illustrates how industrial systems are interconnected and how these connections contribute to achieving sustainable development goals. Moreover, it offers practical policy suggestions aimed at speeding up circular economy adoptions in Uzbekistan and comparable developing countries.
Read MoreDoi: https://doi.org/10.54216/JSDGT.060201
Vol. 6 Issue. 2 PP. 01–11, (2026)
Realizing the carbon reduction capabilities of deploying renewable energy. is core to the constructive plan of effective climate policy in heterogenous national. contexts. Even though there is an accumulating corpus of panel econometric and machine learning. literature dealing with this relationship, methodological inconsistencies and limited geographic scope leave important empirical questions unanswered. This paper put forward a mixed analytical model combining a within-group Fixed Effects. country-clustered standard errors estimator and a Random Forest ensemble. model to measure the combined effect of renewable energy penetration, economic growth, energy consumption and reliance on fossil fuels per capita carbon. emissions. Findings affirm that the growth of renewable energy has a statistically significant impact. strong and economically significant negative impact on carbon intensity, which remains. following the elimination of country-specific unobserved heterogeneity. Economic structure and energy efficiency are shown to be co-dominant determinants, highlighting. that the energy transition is not decoupled of larger structural. transformation. Articulated income-group and regional heterogeneity issues. single-coefficient policy prescriptions, which propose decarbonization. plans have to be aligned to the national development levels. The machine learning complement validates econometric variable rankings and proves. good cross-country generalizability with country-stratified. cross-validation.
Read MoreDoi: https://doi.org/10.54216/JSDGT.060202
Vol. 6 Issue. 2 PP. 12–33, (2026)
