In this study, the influence of various factors on CO2 emissions in Uzbekistan during the period 1992-2020 was studied. The study examines the effect of forest area, urban population growth, renewable energy consumption, fossil fuel energy consumption, per capita energy consumption and industrial activity on observed CO2 emissions. Data were analyzed using multivariate linear regression, the D'Agostino skewness test, and the Anscombe-Glynn kurtosis tests. The results show that forest area has a significant negative correlation with CO2 emissions, suggesting that increased forest cover helps reduce emissions. Urban population growth shows a positive correlation with CO2 emissions, emphasizing the need for sustainable urbanization practices. Renewable energy consumption has been found to have a negative impact on emissions, promoting the adoption of clean energy sources. Fossil fuel energy consumption reveals a complex relationship, with different fuels contributing differently to emissions. Per capita energy consumption and industrial activity contribute significantly to emissions, requiring the adoption of energy-efficient technologies and sustainable industrial practices.

This article analyzed the impact of agriculture on the regional economy, population employment and export potential. Studies show that the volume of agricultural production and its export has a significant impact on the region's gross regional product, employment and income. Also, the study shows that the coefficient of elasticity of the volume of agricultural products is high, and the development of agriculture has a significant impact on the growth of the regional economy. In addition, the article emphasized the importance of developing agriculture-related industries and services for sustainable growth. In the article, regression and correlation analyzes were used to determine the relationship between agriculture and other economic indicators.

This study investigates the intricate interplay between the utilization of renewable energy sources and the fluctuations in unemployment rates in Uzbekistan during the period from 2000 to 2022, utilizing the Autoregressive Distributed Lag model. The analysis leverages World Bank data to explore both short-term and long-term impacts, offering critical insights for policymakers and stakeholders. The findings reveal that an increase in renewable energy consumption has a statistically significant and negative impact on unemployment rates in the long run, with a 1% rise in renewable energy usage leading to a 1.86% decrease in unemployment. In addition, gross fixed capital formation and government expenditure significantly contribute to job creation, while domestic credit to the private sector shows a positive association with unemployment, suggesting inefficiencies in credit allocation. The results emphasize the crucial role of strategic investments in renewable energy as a pathway to address economic and environmental challenges. By promoting renewable energy initiatives, Uzbekistan can align its economic growth with sustainability goals, reduce carbon emissions, and create employment opportunities. This study provides empirical evidence supporting the expansion of renewable energy infrastructure as a means to foster economic development and social well-being. It also underscores the necessity of enhancing financial policy frameworks to ensure efficient credit distribution and maximize the employment benefits of renewable energy projects. The policy recommendations derived from this study advocate for targeted investments, financial sector reforms, and the development of specialized training programs to cultivate a skilled workforce in renewable energy sectors.

In this study, the relationships between Uzbekistan's economic growth, renewable energy use, rural electricity use, and greenhouse gas emissions were investigated using an ARDL model based on data from 2000 to 2022. The long-term results showed that renewable energy production had a significant positive impact on economic growth (coefficient: 0.608, P0.05). However, rural electricity use had a negative impact on economic growth (coefficient: -6.815, P<0.01). The short-term analysis shows that renewable energy production has a rapid and significant positive impact on economic growth (coefficient: 0.0001, P<0.05). In addition, the previous period's economic growth rate (coefficient: 0.643, P<0.05) and greenhouse gas emissions (coefficient: 0.0001, P<0.05) have a positive impact on economic growth in the short term.

The paper deals with the growing importance of understanding energy consumption patterns and their relationship with export performance in developing economies. The study aims to analyze the bidirectional relationship between commodity exports and energy consumption in Uzbekistan from 1992 to 2023. A vector autoregression (VAR) model is employed as the primary methodology, incorporating four main variables: commodity exports, GDP per capita, renewable energy consumption, and renewable electricity generation. Unit root tests (ADF and PP) were conducted, revealing that all variables are stationary in their first differences, which necessitated cointegration analysis. The Johansen test results confirm the existence of a single long-run cointegration vector among the variables. Granger causality tests identify a bidirectional causal relationship between GDP per capita and exports, with changes in GDP per capita having a significant impact on exports (p < 0.001) and vice versa. The results demonstrate that renewable electricity has a positive effect on exports (coefficient = 0.055, p = 0.01), while GDP per capita shows a negative effect on exports (coefficient = –0.0002, p = 0.039). Additionally, VAR analysis reveals that past values of exports significantly influence current export levels, with a lagged coefficient of 0.883 (p < 0.05). These findings have practical implications for policymakers in Uzbekistan seeking to balance economic growth objectives with sustainable energy development strategies.

Type of the article: Research ArticleAbstractInnovation marketing has emerged as a critical research domain due to rapid digital transformation, evolving consumer behaviors, and increasing sustainability demands that fundamentally reshape modern business strategies. However, the intellectual structure and thematic evolution of this interdisciplinary field remain fragmented, with terminological ambiguities and isolated knowledge silos hindering theoretical development and practical advancement. This study systematically maps the intellectual structure and thematic evolution of innovation marketing research through comprehensive bibliometric analysis spanning 1972-2025. Data were retrieved from the Scopus database, yielding 10,453 scholarly documents after filtering duplicates and irrelevant materials, analyzed using the “Bibliometrix” package in R Studio with productivity metrics, citation analysis, co-word analysis, and cluster analysis techniques. The results reveal exponential growth with an annual growth rate of 11.04, particularly accelerating after 2000, with four distinct research clusters emerging: digital transformation technologies (23.4%), sustainable marketing innovations (19.8%), consumer-centric methodologies (21.2%), and strategic innovation management (18.6%). The United States leads publication volume with 1,048 documents (17.26%), followed by China with 681 documents (11.22%), while Belgium demonstrates highest citation impact with 66.15 citations per article. Notably, 67% of highly-cited articles appear in non-marketing journals, confirming interdisciplinary influence, with the most cited work by Pushpakom et al. (2018) receiving 3,064 citations. Innovation marketing has evolved from product-focused approaches toward integrated, technology-driven, and sustainability-oriented strategies, establishing itself as a distinct research domain with significant cross-disciplinary impact for marketing practitioners and policymakers.