Does education matter in China? Myths about financial inclusion and energy consumption

Does Environmental Education Always Contribute to Remanufacturing Supply Chain Development?

Remanufacturing, as an effective way to save resources and alleviate environmental pollution, has gradually become a sustainable practice. Environmental education contributes to the development of remanufacturing by increasing the number of consumers willing to purchase remanufactured products (RPs). However, the incumbent manufacturer usually has limited remanufacturing capability together with yield uncertainty, making a third-party remanufacturer (3PR) an alternate channel choice. This study develops an analytical model to examine the effects of environmental education on a retailer's choice of remanufacturing channels under in-store competition. Results show that consumer environmental education has the potential to significantly improve the retailer and supply chain profits, and temperate environmental education is always desirable for 3PR. The introduction of 3PR benefits the consumer when the retailer's remanufacturing technology level is low. Furthermore, when the environmental impact of defective RPs is relatively high, and environmental education is temperate, selecting a 3PR will enhance environmental sustainability. This study also shows that 3PR can help achieve a win-win situation when environmental education and consumer acceptance of RPs are both in a certain range.

A PLS-SEM approach to determine farmers' awareness about climate change mitigation and adaptation strategies: pathway toward sustainable environment and agricultural productivity

This research was conducted in a significant agricultural region to gauge farmers' knowledge of climate change adaption strategies. We employed a semi-structured questionnaire based on the literature; it was broken up into sections, and used certain statistical techniques (PLS-SEM) to examine the results. Farmers who had sufficient assets and resources thought they were safer and could withstand the adverse effects of climate change. A total of 900 completed questionnaires were gathered to investigate the link between the control, moderator, and DV variables in the future. As a consequence, the PLS-SEM path analysis findings showed that our model is fit. PLS-SEM direct path analysis revealed AM > FACC, UA- > FACC, SA- > FACC, FS- > FACC, PR- > FACC, and SI- > FACC are significant. The established hypotheses H1-H6 are strengthened by these findings. We also examined the respondents' ages and genders to use as controls; whereas gender showed no correlation with FACC, there was a strong link between age and the dependent variable. There is no statistically significant correlation between gender and climate change awareness, but older people tend to have a broader understanding of the topic and its consequences. Education significantly moderates the relationship of farmer's awareness (climate change) associated with AM, UA, SA, FS, PR, and SI. depicts the moderation role of education on the relationship between AM*Education- > FACC, UA*Education- > FACC, SA*Education- > FACC, FS*Education- > FACC, PR*Education- > FACC, and SI*Education- > FACC. H2a and H5a in this study showed significant correlations with education as a moderator; however, H1a, H3a, H4, and H6a did not demonstrate any moderator relationships. There is a medium to strong correlation between various factors, and the correlation values of a few chosen variables are significant when compared to all other variables in the current study. Highly significant correlations were found between PR, SA, SI, and UA with FACC. Governmental policies and effective monitoring systems will be developed as a result of the research to enable integrated and sustainable water development.

An SEM-ANN approach to evaluate public awareness about COVID, A pathway toward adaptation effective strategies for sustainable development

This study was conducted to evaluate public awareness about COVID with aimed to check public strategies against COVID-19. A semi structured questionnaire was collected and the data was analyzed using some statistical tools (PLS-SEM) and artificial neural networks (ANN). We started by looking at the known causal linkages between the different variables to see if they matched up with the hypotheses that had been proposed. Next, for this reason, we ran a 5,000-sample bootstrapping test to assess how strongly our findings corroborated the null hypothesis. PLS-SEM direct path analysis revealed HRP -> PA-COVID, HI -> PA-COVID, MU -> PA-COVID, PM -> PA-COVID, SD -> PA-COVID. These findings provide credence to the acceptance of hypotheses H1, H3, and H5, but reject hypothesis H2. We have also examined control factors such as respondents' age, gender, and level of education. Age was found to have a positive correlation with PA-COVID, while mean gender and education level were found to not correlate at all with PA-COVID. However, age can be a useful control variable, as a more seasoned individual is likely to have a better understanding of COVID and its effects on independent variables. Study results revealed a small moderation effect in the relationships between understudy independent and dependent variables. Education significantly moderates the relationship of PA-COVID associated with MU, PH, SD, RP, PM, PA-COVID, depicts the moderation role of education on the relationship between MU^*Education->PA-COVID, HI^*Education->PA.COVID, SD^*Education->PA.COVID, HRP^*Education->PA.COVID, PM^*Education -> PA.COVID. The artificial neural network (ANN) model we've developed for spreading information about COVID-19 (PA-COVID) follows in the footsteps of previous studies. The root means the square of the errors (RMSE). Validity measures how well a model can predict a certain result. With RMSE values of 0.424 for training and 0.394 for testing, we observed that our ANN model for public awareness of COVID-19 (PA-COVID) had a strong predictive ability. Based on the sensitivity analysis results, we determined that PA. COVID had the highest relative normalized relevance for our sample (100%). These factors were then followed by MU (54.6%), HI (11.1%), SD (100.0%), HRP (28.5%), and PM (64.6%) were likewise shown to be the least important factors for consumers in developing countries struggling with diseases caused by contaminated water. In addition, a specific approach was used to construct a goodness-of-fit coefficient to evaluate the performance of the ANN models. The study will aid in the implementation of effective monitoring and public policies to promote the health of local people.

Examining the effects of information and communications technology on green growth and environmental performance, socio-economic and environmental cost of technology generation: A pathway toward environment sustainability

Human capital and ICT have a significant role in determining human development. The impacts of ICT and human capital on green growth and environmental sustainability should be explored for sustainable economic development. This research contributes to the literature on the role of ICTs and human capital in the determination of green growth and environmental performance. Based on time-series data 1990-2019, the study intends to investigate the impact of ICTs and human capital on environmental and green growth performance for China. The study reports that ICTs tend to reduce CO2 emissions and improve green growth in the long-run. However, education reduces CO2 emissions in the long-run but does not produce any significant impact on green growth in the long-run. It is suggested that government should invest in environmental efficiency and environmental technologies simultaneously with human capital that could significantly contribute to pollution reduction. Lastly, policies to increase human capital should be implemented simultaneously with policies to promote ICTs contribution in order to confirm green growth and environmental protection.

Environmental concern in the era of digital fiscal inclusion: The evolving role of human capital and ICT in China

To achieve environmental sustainability, the role of human capital and financial inclusion has been debated in limited empirical studies. Employing a reliable ARDL model approach, this study examines the dynamic link between human capital and ICT, financial inclusion, and CO2 emissions using the China economy dataset over the period 1998–2020. The vivacious side of human capital shows that literacy rate and average year of schooling curb CO2 emissions in long run. The results of human capital are also based on facts in magnitude as well as in direction. Also, empirics unfold that digital financial inclusion significantly increases CO2 emissions. Based on these novel findings, a wide set of economic policies are repaired for environmental quality. Environmental education should be considered at early levels of education. The authorities and policymakers should fix energy-related issues through education. The China government should stimulate the educational sector to conduct a clean and green revolution that acts as a mechanism for a green and clean economy. This study's finding is more effective than the previous unlike empirical studies for policy-making because of the advanced econometric method.

A systematic PLS-SEM approach on assessment of indigenous knowledge in adapting to floods; A way forward to sustainable agriculture

The present study was conducted in one of the major agriculture areas to check farmers indigenous knowledge about the impacts of floods on their farming lives, food security, sustainable development, and risk assessment. In the current study, primary data was used to analyze the situation. A semi-structured questionnaire was distributed among farmers. We have collected a cross-sectional dataset and applied the PLS-SEM dual-stage hybrid model to test the proposed hypotheses and rank the social, economic, and technological factors according to their normalized importance. Results revealed that farmers' knowledge associated with adaption strategies, food security, risk assessment, and livelihood assets are the most significant predictors. Farmers need to have sufficient knowledge about floods, and it can help them to adopt proper measurements. A PLS-SEM dual-stage hybrid model was used to check the relationship among all variables, which showed a significant relationship among DV, IV, and control variables. PLS-SEM direct path analysis revealed that AS (b = -0.155; p 0.001), FS (b = 0.343; p 0.001), LA (b = 0.273; p 0.001), RA (b = 0.147; p 0.006), and for FKF have statistically significant values of beta, while SD (b = -0.079NS) is not significant. These results offer support to hypotheses H1 through H4 and H5 being rejected. On the other hand, age does not have any relationship with farmers' knowledge of floods. Our study results have important policy suggestions for governments and other stakeholders to consider in order to make useful policies for the ecosystem. The study will aid in the implementation of effective monitoring and public policies to promote integrated and sustainable development, as well as how to minimize the impacts of floods on farmers' lives and save the ecosystem and food.

Digital Students' Satisfaction With and Intention to Use Online Teaching Modes, Role of Big Five Personality Traits

During the COVID-19 pandemic, online teaching modes were found vital to continue students' learning process, but sustainable implementation of online teaching models is an area of concern for policymakers. Psychiatrists are also eager to know students' behavior toward learning and modes of teaching during COVID-19. We have drawn a model based on the big five personality traits to study students' satisfaction with online teaching modes and their adoption intentions toward online teaching modes. We have collected data from 718 bachelor's and master's level students from four different universities. We have applied the SEM-ANN dual-stage approach to test personality traits' influence and ranked them based on their normalized importance. The results revealed that agreeableness, conscientiousness, neuroticism, and openness positively influence students' satisfaction with online teaching models, but that extraversion negatively influences their satisfaction. Agreeableness, extraversion, and neuroticism positively impact, but openness negatively influences. Conscientiousness does not affect adoption intention. Furthermore, agreeableness is the most significant, and conscientiousness is the least important factor for students to adopt online teaching modes. The findings of the study have useful perceptiveness for educational policymakers, academics, and psychiatrists.

Revealing the Effects of Corporate Governance on Green Investment and Innovation: Do Law and Policy Matter?

Green investment (GI) and innovation performance are key factors of sustainable green development. GI and innovation have become a trendy solution to minimize environmental issues in the previous few decades. We investigate the effects of corporate governance, environmental law, and environmental policy stringency on GI and environmental innovation (EI) using Chinese time-series data from 1998 to 2020. Short and long-run findings indicate that corporate governance has a positive and significant impact on GI and innovation in China. However, environmental law has positive and significant effects on GI and innovation in the short run and long run. Furthermore, environmental policy stringency has an insignificant impact on GI but stimulates green innovation both in the short and long run. The study also reveals that education has a significant positive impact on green innovation both in the short and long-run. The short and long-run results propose essential policy implications.