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The United Nations’ Sustainable Development Goals for 2030 provide a foundation for this study. These SDGs encompass crucial targets pertaining to sustainable development (SDG-8), responsible energy consumption (SDGs 11 and 12), access to clean and affordable energy (SDG-7), and environmental sustainability action (SDG-13) and among others. To this end, the research employs advanced panel methodologies to investigate the heterogeneous effects of energy resources and financial development on a sustainable environment. The study adopts second-generation econometric tools to evaluate the model’s cross-sectional dependence, and the cointegration methodology proves the long-run correlation between the indicators. Additionally, the ordinary least square and the panel quantile regression results reveal long-run estimations. These long-run studies provide reliable information on environmental sustainability dynamics in the E-7 economies. The analysis reveals that the effects of the high financial development, rapid economic growth and fast-growing nonrenewable energy resources significantly impact environmental sustainability from 2000–2020 within the E-7 bloc. Furthermore, the results from both the OLS and the PQR indicate that the coefficients for renewable energy resources and globalization are negative across all quantiles (Q25to Q95quantiles) with regard to CO2 emissions. These findings advocate for a policy framework that aligns with the SDGs. The study also proposes a comprehensive policy framework for the E-7 nations to promote progress toward SDGs (7, 8, 9, 11, 12, 13, and 16).

ABSTRACTEnvironmental sustainability is a pressing global concern that demands urgent attention from policymakers and researchers. The objective of our research is to investigate the influence of economic policy uncertainty (determined by the world uncertainty index) and financial development on carbon emissions, followed by green technological innovation, institutional quality, economic growth, foreign direct investment, energy consumption, and trade in Organization of Economic Co-operation and Development, for the period 2003–2019, to analyse the data, the second-generation econometric techniques are used. We applied the two-stage sequential techniques of the linear panel data model and generalised method of moments approach to tackle the endogeneity problem and report robust findings. The findings of the study revealed that economic policy uncertainty, financial development, economic growth, energy consumption, and trade decrease environmental quality by increasing CO2 emissions, while green technological innovation and institutional quality increase environmental degradation by reducing CO2 emissions. Our evidence-based study provides significant outcomes for green technological innovation and institutional quality conditioning’s role in reducing carbon emissions in OECD economies.

Energy plays a very important role more or less in every aspect of human life as well as economic activities. It is one of the sectors that play a pivotal role in the development of every county as it helps in easing or reducing poverty through job creation and manufacturing and supports infrastructural development. Renewable energy resources particularly hydropower remain one of the main sources of energy in recent times to overcome energy demand globally and reduce CO2 emissions and other Greenhouse gases from energy generation. The energy produced from sources such as coal, geothermal, burning of fossil fuels, and thermal have a negative impact on the environment as they release pollutants that affect aquatic life and other parts of the environment. Generating energy from hydroelectric power using a pump operating in reverse as turbine serves as the best and cheapest way to operate. This is due to its numerous advantages such as cheater installment and operation and low environmental hazards. This study examines the role of Pump as turbine for energy generation in reducing emission generation. Considering pump as turbine performance at different flow conditions for selection to be used for small hydro energy generation. Both numerical and experimental studies have been conducted and the results are discussed in this study. A literature survey has also been conducted to analyze data on global emission generation from energy generation. This study offers valuable information which supports the reduction of CO2 emissions and other Greenhouse gases from power generation through the provision of appropriate methods for the generation

The study aims to examine the impact of various behavioral biases such are overconfidence, representativeness, availability, anchoring and herding, and their effects on individual investment decisions in the case-developed country context of China. To achieve this, data was meticulously gathered from 362 participants active in the Shanghai stock market. Employing advanced analytical tools, particularly the Smart PLS 3.3.2 software and structural equation modelling (SEM), this study rigorously scrutinized the intricate relationships between behavioral biases and investment decisions. The findings of this study notably reveal that all examined behavioral biases exert a significant positive impact on investment decisions within the Anxin, Haitong, Shanxi, and China Galaxy stock markets. Remarkably, no substantial disparities in the effects of these biases on stock market trading were observed among these markets. Importantly, these findings bear exceptional significance within the context of a developed country like China. The implications extend to a wide spectrum of stakeholders, including government entities, regulatory bodies, practitioners, the academic community, industry professionals, and researchers. Regulatory authorities can leverage these insights to refine their strategies, practitioners can fine-tune their investment advisory approaches, and academia and researchers can build upon these findings to deepen the understanding of behavioral finance in the realm of stock market investments.

Author(s): Muhammad Aamir Shafique Khan [sup.1] [sup.2] , Jianguo Du [sup.1] , Farooq Anwar [sup.2] , Sikandar Ali Qalati [sup.1] , Muhammad Waqas [sup.2] , Shuja Iqbal [sup.1] Author Affiliations: [...], This study advances research on workplace romance, employees' work-related attitudes, and discretionary work behaviors by drawing on a positive psychology theory to theorize interrelations between workplace romance, job involvement, and employees' work effort and provide empirical evidence of these interrelations. Data were collected in two waves (three months apart) from 365 supervisor-employee dyads in 64 firms from different Chinese manufacturing sectors. Data were analyzed using structural equation modeling (SEM), bootstrapping, and multigroup techniques. The present study found that workplace romance was positively related to employees' work effort. Moreover, employees' job involvement fully mediates the positive relationship between workplace romance and employees' work effort. Importantly, by using multigroup analysis, the current research found that workplace romance types - hierarchical/lateral and licit/illicit (extramarital) moderate the indirect relationship between workplace romance and employees' work effort. This study offers important implications for managers and policymakers of business organizations in China and elsewhere.

This study explores the relationship between environmental taxation, environmental technologies, energy resources, and consumption-based carbon emissions in five leading green economies from 2000 to 2019. The study applied the Cross-Sectional Auto-Regressive Distributed Lag (CS-ARDL) model to derive benchmark results, with Augmented Mean Group (AMG) and Common Correlated Effect Mean Group (CCEMG) techniques being utilized for conducting robustness analyses. The empirical findings suggest that environmental taxation, environmental innovations, and the consumption of renewable energy are associated with a reduction in consumption-based carbon emissions, thereby contributing to enhanced environmental sustainability. Conversely, the utilization of non-renewable energy is linked to an increase in consumption-based carbon emissions. These results align with the objectives outlined in the Sustainable Development Goals' 2030 agenda, particularly SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 13 (Climate Action), offering valuable policy implications.

This study investigates the effects of financial globalization, trade globalization, and information and communication technology on the ecological footprint in G9 industrial economies (China, the United States, Japan, Germany, India, South Korea, Italy, France, and the United Kingdom) from 2000Q1 to 2018Q4. A distinctive Method of Moments Quantile Regression (MMQR) model was employed to analyze these relationships, and the Bootstrap Quantile Regression (BSQR) model was used to validate the results. The findings reveal that financial globalization (FG), environmental tax (ETAX), and institutional quality (IQ) contribute to environmentally sustainable development by reducing the ecological footprint (ECOFP). In contrast, trade globalization, information and communication technology (ICT), and gross domestic product (GDP) have a significant positive impact on the ecological footprint, leading to increased environmental degradation. The BSQR results corroborate these findings, confirming the roles of financial globalization, institutional quality, environmental tax, trade globalization, information and communication technology, and gross domestic product in shaping the ecological footprint. Based on these results, policymakers in G9 industrial nations should promote financial globalization as a tool to reduce the ecological footprint by encouraging green financing and environmentally sustainable investments. For trade globalization, stricter environmental regulations and sustainable trade practices are essential to mitigate its adverse environmental effects. Also, efforts to minimize the ecological impact of information and communication technology should focus on integrating renewable energy into ICT infrastructure and advancing green technology innovations. [ABSTRACT FROM AUTHOR]

As it has been practiced for many decades, agriculture has had a significant negative impact on the environment. More land, fertiliser, and pesticides had been used to increase the yield to meet the demands of an expanding population. Consequences included deforestation and soil degradation as well as the extinction of biodiversity, irrigation issues, and pollution, among other things. This has resulted in developing a new type of agriculture known as sustainable agriculture to remedy the situation. Specifically, the goal is to “meet the food and textile needs of society in the present without risking the ability of future generations to meet their own needs.” Using appropriate agricultural practices to implement sustainable agriculture is the most effective method of accomplishing this goal. According to research, farmers’ decisions to effectively adopt sustainable agricultural practices are influenced by a variety of factors. In this paper, we firstly give an overview of sustainable agriculture practices. Then, we review the various factors affecting the adoption of these practices, and finally, we highlight the gap found in the literature.

According to contemporary innovation literature, green performance management (GPM) is critical to improving green innovation results. Yet, few researchers have examined the relationship between green organizational innovation and HRM. This study explores the direct and indirect impacts of green recruiting and selection (GRS), green training and development (GTD), green compensation and benefits (GCB), and green innovation performance (GIP), with the function of GPM serving as a mediator and the effect of stakeholder pressure (SP) and green Culture (GC) serving as a moderator, respectively, of these factors on developing market small and medium-sized businesses (SMEs). Using a questionnaire survey, we gathered data from 380 SMEs in the industrial sector. We applied the partial least squares (PLS) path modelling technique (PLS-SEM) to test the study's assumptions. According to the study, GPM mediates the effects of GRS, GTD, and GCB on green innovation performance. Results also point to a moderating effect of GC on the effects of green recruitment and selection, training and development, and remuneration and benefits on green performance management. Moreover, Stakeholder pressure moderates the effect of green performance management on the effectiveness of green innovation. The results point to important implications for theory and practice. [ABSTRACT FROM AUTHOR]