Enhancing Job Performance: The Critical Roles of Well-Being, Satisfaction, and Trust in Supervisor.

This empirical study investigated the associations between psychological well-being, job satisfaction, trust in supervisor, and job performance. Data were collected from 277 company employees in Bahrain through online questionnaires and analyzed using structural equation modeling (SEM). The purpose of the study is to examine the relationships between psychological well-being, job satisfaction, trust in supervisor, and job performance through the use of a theoretical framework that synthesizes prominent models in the field of organizational psychology. The research findings indicate a positive influence of psychological well-being on both job satisfaction and job performance. Notably, job satisfaction plays a mediating role in the relationship between psychological well-being and job performance. The study contributes to the existing body of knowledge by offering an integrated approach to examining the intricate connections between psychological well-being, job satisfaction, trust in supervisor, and job performance, which all are crucial for creating a sustainable workplace environment and outcomes. Practical implications highlight the need for organizations to prioritize employee psychological well-being through initiatives such as wellness programs and supportive work environments, as these initiatives directly influence job satisfaction and performance. Job satisfaction acts as a significant mediator, emphasizing the importance of fair compensation, recognition, and professional development in enhancing job satisfaction.

Supply chain finance and innovation efficiency: An empirical analysis based on manufacturing SMEs.

This paper firstly demonstrates the positive and negative effects of supply chain finance on the innovation efficiency of China's small and medium-sized enterprises (SMEs) in the manufacturing industry from the theoretical point of view. Based on the data of 267 manufacturing companies in China Growth Enterprise Market from 2015 to 2019, the DEA-SBM method was used to measure the comprehensive innovation efficiency of different companies, and it was further decomposed into technological innovation efficiency and organizational innovation efficiency. Afterwards, it conducts an empirical analysis through the double fixed effect model, and explores the difference in the impact of supply chain finance on innovation efficiency in enterprises with different industries and different property rights. The results show that supply chain financial services have a strong positive impact on the comprehensive innovation efficiency, technological innovation efficiency and organizational innovation efficiency of manufacturing SMEs. Further, supply chain finance has the most significant improvement on the technological innovation efficiency of the sample of private traditional enterprises, but it has a significant inhibitory effect on the organizational innovation efficiency of the sample of state-owned high-tech enterprises. Therefore, this paper suggests that the development of supply chain financial services should increase support for traditional manufacturing industries; appropriately tilt resources to private enterprises; improve relevant supply chain financial laws and regulations, establish and improve corresponding institutional arrangements, and encourage state-owned enterprises to participate in market competition.

Air quality and health benefits of increasing carbon mitigation tech-innovation in China.

Most studies on the short-term local benefits of carbon mitigation technologies on air quality improvement and health focus on specific technologies such as biofuels or carbon sequestration technologies, while ignoring the overall role of the growing scale of low-carbon technologies. Based on STIRPAT model and EKC hypothesis, this paper takes 30 provinces in China from 2004 to 2016 as research samples. We builded the panel double fixed effect model to empirical analysis of climate change on carbon mitigation tech-innovation suppressing the influence of haze pollution, on this basis, the mediating effect model was used to explore the mediation function of industrial structure and energy structure. Meanwhile, we drawed on the existing studies on air quality and health benefits, and quantify the co-benefits of carbon mitigation tech-innovation on health through the equivalent substitution formula. It shows that a 1% increase in the number of low-carbon patent applications can reduce haze pollution by 0.066%. According to this estimate, to 2029, China's carbon mitigation tech-innovation could reduce PM2.5 concentration to 15 µg/m3 preventing 5.597 million premature deaths. Moreover, carbon mitigation tech-innovation can also indirectly inhibit haze pollution by triggering more systematic economic structure changes such as energy and industrial structure. Additionally, we found that the role of gray tech-innovation (GT) related to improving the efficiency of fossil energy is stronger than that of clean technology (CT) related to the use of renewable energy. This suggests that for a large economy such as China, where coal is still the dominant source of energy consumption, the short-term local benefits of improving air quality and health through the use of gray tech-innovation to improve energy and industrial structure are still important to balance the cost of carbon mitigation.

The General Public Knowledge, Attitude, and Practices Regarding COVID-19 During the Lockdown in Asian Developing Countries.

The recent outbreak of coronavirus disease (COVID-19) is the worst global crisis. Since no successful treatment and vaccine have been reported, efforts to improve the public's knowledge, attitudes, and practices are critical to reducing the spread of COVID-19. This study aims to investigate the general public knowledge, attitude, and practices regarding COVID-19. A cross-sectional online survey was conducted in three developing countries (China, India, and Pakistan). The reason for choosing only three countries is to identify the cross-border effect statistically and data collection constraints. The IBM SPSS version 23.0 was used for descriptive, univariate, and multivariate analysis of the study. One thousand one hundred and sixty participants completed the study, one-quarter of them were female, and three-quarters were male. The study's findings evidenced that the knowledge and attitude correlation was 58.4% and between knowledge and practices 18.2%. Furthermore, the knowledge was found lower in females, among India and Pakistan, and people aged less and equivalent to 30 years. The attitudes among respondents were found poorer among unmarried females and India and Pakistan residents. While the practices found lower among employed, unemployed and, respondents had a bachelor's degree, and females reside in India. And future studies should focus on factors that influence the government regarding the imposition of lockdown, boost the economy in the pandemic, and motivate the general public to follow the health institution's instructions.

Assessing the impact of oil and gas trading, foreign direct investment inflows, and economic growth on carbon emission for OPEC member countries.

The exploration of oil and gas contributes to green-house-gas. While exploring countries ensures economic growth, their activities also contribute to environmental pollution through carbon emissions. The 13-member states of the Organization of the Petroleum Exporting Countries (OPEC) are the world's most important oil-producing and exporting countries. Since the safety of a country's oil and gas resources is related to the country's economic growth and environmental protection, this study aims at assessing the impact of oil and gas trading, foreign direct investment inflows, and economic growth on carbon emission for OPEC member countries. Using secondary data from 2000 to 2018, the authors utilized Stata and EViews statistical software for the empirical studies. The fully modified least squares (FMOLS) and the generalized methods of moments estimators were used for the multiple regression. The findings from the multiple regression analysis revealed a positive but statistically insignificant relationship between oil and gas export and carbon emissions. On the contrary, an inverse relationship that is statistically significant was found between foreign direct investment inflows and carbon emissions. Also, a positive and statistically significant relationship was found between economic growth and carbon emissions for OPEC member countries. The research findings contribute to previous literature on petroleum exploration activities and give clues to policy-makers and stakeholders in putting in measures to ensure economic growth while promoting environmental protection for OPEC member countries.

An extension of the theory of planned behavior to understand factors influencing Pakistani households' energy-saving intentions and behavior: a mediated-moderated model.

This study aims to explore the factors influencing households' intentions and actual behavior in relation to saving energy. This study is based on the theory of planned behavior (TPB), extending it by adding descriptive norms and moral responsibility. An online survey was administered to collect data from randomly selected households and data analysis was run using partial least squares structural equation modeling (PLS-SEM). The research findings reveal the positive and significant effect of TPB factors (attitude, subjective norms, and perceived behavior control) and the extended factors (descriptive norms and moral responsibility) on households' intention to save energy, as well as the significant effect of perceived behavior control, moral responsibility, and intention on household's energy-saving behavior. This study also evidences the significant mediating and moderating role of households' intention to save energy and moral responsibility. This study's model explains 70.5% of variations in households' intention to save energy and 63.1% of variations in households' energy-saving behavior. In particular, the extended model explains 11.6% more of the variation in households' intention to save energy compared to the TPB model. This research has several theoretical and practical implications for scholars, environmental protection agencies, and policy-makers.

Effects of Information Overload, Communication Overload, and Inequality on Digital Distrust: A Cyber-Violence Behavior Mechanism.

In recent years, there has been an escalation in cases of cyber violence, which has had a chilling effect on users' behavior toward social media sites. This article explores the causes behind cyber violence and provides empirical data for developing means for effective prevention. Using elements of the stimulus-organism-response theory, we constructed a model of cyber-violence behavior. A closed-ended questionnaire was administered to collect data through an online survey, which results in 531 valid responses. A proposed model was tested using partial least squares structural equation modeling using SmartPLS 3.0, v (3.2.8). Research findings show that information inequality is a strong external stimulus with a significant positive impact on digital distrust and negative emotion. However, the effects of information overload on digital distrust and the adverse effects of communication overload on negative emotions should not be ignored. Both digital distrust and negative emotions have significant positive impacts on cyber violence and cumulatively represent 11.5% changes in cyber violence. Furthermore, information overload, communication overload, information inequality, and digital distrust show a 27.1% change in negative emotions. This study also presents evidence for competitive mediation of digital distrust by information overload, information inequality, and cyber violence. The results of this study have implications for individual practitioners and scholars, for organizations, and at the governmental level regarding cyber-violence behavior. To test our hypotheses, we have constructed an empirical, multidimensional model, including the role of specific mediators in creating relationships.

Effects of Social Media Use on Psychological Well-Being: A Mediated Model.

The growth in social media use has given rise to concerns about the impacts it may have on users' psychological well-being. This paper's main objective is to shed light on the effect of social media use on psychological well-being. Building on contributions from various fields in the literature, it provides a more comprehensive study of the phenomenon by considering a set of mediators, including social capital types (i.e., bonding social capital and bridging social capital), social isolation, and smartphone addiction. The paper includes a quantitative study of 940 social media users from Mexico, using structural equation modeling (SEM) to test the proposed hypotheses. The findings point to an overall positive indirect impact of social media usage on psychological well-being, mainly due to the positive effect of bonding and bridging social capital. The empirical model's explanatory power is 45.1%. This paper provides empirical evidence and robust statistical analysis that demonstrates both positive and negative effects coexist, helping to reconcile the inconsistencies found so far in the literature.