The Lancaster mutual teaching model originated in late 18th century England and quickly spread to the American colonies after receiving positive responses in Europe. In the 1820s, renowned Spanish physician, educator, and publisher Manuel Codorniú Ferreras brought it to Mexico, making outstanding contributions to the newly independent nation in educational philosophy, system, and methods. In the mid-19th century, with the absence of a centralized institution for public education in Mexico, the Lancaster Company took on the significant responsibility of guiding the direction of national public education development. Although this function did not persist for too long due to political changes in Mexico, the educational system continued to play an important role in the Mexican education sector. The Lancaster Company and its teaching system exerted a positive and profound influence on the democratization and secularization of education in Mexico, laying important foundations for the modernization and reform of Mexican education.

The MENA region, known for its significant oil and gas production, has been widely acknowledged for its reliance on fossil fuels. The dependence on fossil fuels has led to significant environmental pollution. Therefore, the shift towards a more environmentally friendly and enduring future is crucial. Thus, the current study tries to investigate the effect of green technology innovations on green growth in MENA region. Specifically, we examine whether the effect of green technology innovations on green growth depend on the threshold level of income. To this end, a panel threshold model is estimated for a sample of 10 MENA countries over the period 1998–2022. Our main findings show that only countries with income level beyond the threshold can benefit significantly from green technology innovations in term of green growth. Nevertheless, our findings indicate a substantial and adverse impact of green technology innovation on countries where income levels fall below the specified threshold.

Technology development in the agricultural sector is important in the development of Thailand’s economy. The purpose of this research was to study the approach of guidelines for future agricultural technology development to increase productivity in the Agricultural sector in order to develop a structural equation model. The research applied mixed-methodology. Qualitative research by in depth interview from 9 experts and focus group with 11 successful businesspersons for approve this model. The quantitative data gather from firm, in the 500 of agricultural sector by using questionnaire, using statistical tests of descriptive analysis, inferential analysis, and multivariate analysis. The research found guidelines for future agricultural technology development to increase productivity in the Agricultural sector composed of 4 latent. The most important item of each latent were as following: 1) Agrobiology Technology (= 4.41), in important item as choose seeds that for disease resistance and tolerate the environment to suit the cultivation area, 2) Environmental Assessment (= 4.37),, in important item as survey of cultivated areas according to topography with geographic information system, 3) Agricultural Innovation (= 4.30), in important item as technology reduces operational procedures, reduce the workforce and can reduce operating costs, and 4) Modern Management Systems (= 4.13), in important item as grouping and manage as a cooperative to mega farms. In addition, the hypothesis test found that the difference in manufacturing firm sizes. Medium and Small size and large size revealed overall aspects that were significantly different at the level of 0.05. The analysis of the developed structural equation model found that there was in accordance and fit with the empirical data and passed the evaluation criteria. Its Chi-square probability level, relative Chi-square, the goodness of fit index, and root mean square error of approximation were 0.062, 1.165, 0.961, and 0.018, respectively.

Compared with their fellow citizens in the city, rural residents are more likely to be affected by ecological restoration programs and policies. Yet no one has conducted a large-scale study of how ecological conservation impacts rural livelihoods and the economic status of rural households, especially in China. To fill that knowledge gap, I collected and analyzed relevant data from 2007 to 2018 for western and eastern China. I found that the relationship between western China’s green coverage rate and rural income followed an inverted U curve whereas that between its green coverage rate and urban-rural income gap was instead U-shaped, suggesting that ecological restoration has come to eventually negatively impact the economic welfare of rural residents in western China; however, the complete opposite was found in eastern China. Greater urbanization, financial support, and infrastructure such as education, medical, and Internet services would help to improve the current situation in western China. This suggests the government should take actions—such as improving the quality of farmer training to the rural residents and improving infrastructure construction—to help farmers acquire a new source of income and narrow the urban-rural income gap in parallel to implementing ecological restoration projects.

Analysis of the factors influencing the price of carbon emissions trading in China and its time-varying characteristics is essential for the smooth operation of the carbon trading system. We analyse the time-varying effects of public concern, degree of carbon regulation, crude oil price, international carbon price and interest rate level on China’s carbon price through SV-TVP-VAR model. Among them, the quantification of public concern and the degree of carbon emission regulation is based on microblog text and government decisions. The results show that all the factors influencing carbon price are significantly time-varying, with the shocks of each factor on carbon price rising before 2019 and turning significantly thereafter. The short-term shock effect of each factor is more significant compared to the medium- and long-term, and the effect almost disappears at a lag of six months. Thanks to public environmental awareness, low-carbon awareness and the progress of carbon market management mechanisms, public concern has had the most significant impact on carbon price since 2019. With the promulgation of relevant management measures for the carbon market, relevant regulations on carbon emission accounting, financing constraints, and carbon emission quota allocation for emission-controlled enterprises have become increasingly mature, and carbon price signals are more sensitive to market information. The above findings provide substantial empirical evidence for all stakeholders in the market, who need to recognize that the impact of non-structural factors on the price of carbon varies over time. Government intervention also serves as a key aspect of carbon emission control and requires the introduction of relevant constraints and incentives. In particular, emission-controlling firms need to focus on the policy direction of the carbon market, and focus on the impact of Internet public opinion on business production while reducing carbon allowance demand and energy dependence.

Based on digital technology, the digital economy has typical characteristics of high efficiency, greenness, intelligence, innovation, strong penetration and so on, which can promote the sporting goods manufacturing industry (SGMI) to realize the goal of green development. This study selects panel data from 30 provinces in China over the period of 2011 to 2022. And the green total factor productivity of the sporting goods manufacturing industry (SGTFP) is used to reflect the green development of SGMI. The level of digital economy development (DIG) and the SGTFP are measured by using the entropy method and the Super-SBM model with undesirable outputs. Based on the method of coupling coordination degree model, the coordinated development degree of DIG and SGTFP is analyzed first. Then, by making use of the fixed effect model, intermediary effect model and spatial Durbin model, the influence of DIG on the green development of SGMI and its mechanism are empirically studied. The results show that DIG, SGTFP and the degree of their coupling and coordination are generally on the rise. The benchmark regression results show that the coefficient of DIG on SGTFP is 0.213; that is, the digital economy can significantly promote the improvement of green development in SGMI. According to the analysis of the spatial Durbin model, the impact of the digital economy on SGTFP has a certain spatial spillover, that is, the development of digital economy in the region will have a certain promoting effect on the green development of SGMI in the surrounding region. The intermediary effect model analyzes the influence mechanism and finds that the digital economy mainly boosts SGTFP through green innovation technology and energy consumption structure.