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In recent years, entrepreneurship has been gaining more prominence as a potential tool for solving poverty in developing countries. This paper mainly examines the relationship between farmer entrepreneurship and rural poverty alleviation in China by assessing the contribution of farm entrepreneurs towards overcoming poverty. Data were collected from 309 employees of farmer entrepreneurships in Guangxi Province through survey questionnaires. Structural equation modeling was used to conduct an analysis of the effects of three identified capabilities of farm entrepreneurs—economic, educational and knowledge, and socio-cultural capabilities—on attitude towards farmer entrepreneurship growth and the qualitative growth of farmer entrepreneurship and how these in turn affect rural poverty, using AMOS 21. The findings show that socio-cultural capability has the greatest influence on farmer entrepreneurship growth (β = 0.50, p<0.001). The qualitative growth of farmer entrepreneurship also more significantly impacts rural poverty (β = 0.69, p<0.001) than attitude towards farmer entrepreneurship growth. This study suggests that policy makers in China should involve more rural farmers in the targeted poverty alleviation strategies of the government by equipping rural farmers with entrepreneurial skills. This can serve as a sustainable, bottom-up approach to alleviating rural poverty in remote areas of the country. The study also extends the literature on the farmer entrepreneurship-rural poverty alleviation nexus in China, and this can serve as a lesson for other developing countries in the fight against rural poverty.

Purpose -There is a recent growing interest to find a lasting intervention to rural poverty (RP) in developing countries based on farmer entrepreneurship and innovation. The purpose of this paper, therefore, is to examine the relation between entrepreneurship and RP alleviation in two resource-constrained provinces of China. This paper assesses the influence of three capabilities of farm entrepreneurseducational, economic and socio-culturalon farmer entrepreneurship growth and how these, in turn, impact alleviation of RP. Design/methodology/approach -Household survey data comprising 363 respondents were taken from four deprived communities in two provinces of China. The paper employed structural equation modeling (SEM), using AMOS 21.0 alongside SPSS 20.0 to test the relations between the constructs. Findings -The results show that a statistically significant and positive relation exists between entrepreneurship and RP alleviation in China. The findings of the study further reveal that qualitative growth of entrepreneurship has a stronger positive influence on RP alleviation than on quantitative growth, and socio-cultural capabilities of respondents significantly and positively affect entrepreneurial growth of farmers, rather than education and economic capabilities.Research limitations/implications -The use of data from four communities in two provinces tends to limit the ability to generalize the findings of the study. Furthermore, the survey did not collect information on non-farm entrepreneurs, making it impossible to compare the findings from farm entrepreneurs with non-farm entrepreneurs. Practical implications -The findings have practical implications for policy makers in rural China toward addressing targeted RP. This paper, therefore, suggests that entrepreneurship should be pursued vigorously among farmers in rural areas of China to help solve poverty. The paper also presents a useful lesson for various stakeholders in poverty alleviation programs in other developing countries. Originality/value -This paper contributes to the academic literature on the entrepreneurship-RP alleviation nexus by combining the theory of capability and SEM in the analysis of an emerging economy such as China.

With China's rapid economic growth over the past three decades, the emission of greenhouse gases (GHG) has become more serious to the environment, with debilitating effects on both flora and fauna. This paper mainly investigates the relationship among economic growth, energy intensity, and CO 2 emission in China using static and dynamic regressions, Granger causality, and impulse response function.The results show that by comparing the values of different energy intensities, coal consumption is the highest with mean value of 4.296, which is followed by oil (0.817), electricity (0.226), and gas (0.098). Thus, China's heavy reliance on coal consumption is possibly a dominant cause for the increase in carbon dioxide emissions. The results also indicate that CO 2 emissions have an inverted U-shaped link with per capita income, and this supports the existence of the environmental Kuznets curve (EKC) hypothesis in China. Furthermore, economic growth has a bidirectional relationship with coal energy consumption, while coal consumption also has a bidirectional link with CO 2 emissions. Based on the findings, we suggest that environmental technologies should be improved through efficiency-enhancing strategies to reduce CO 2 emissions.Finally, China's Ministry of Environmental Protection should strictly enforce existing laws and regulations on the environment, and also encourage a shift from the use of fossil fuels to clean energy sources such as ethanol gas, as well as promote the use of eco-friendly vehicles such as electric cars and motors.

Sustainable economic prosperity has become a major policy initiative for economies worldwide. To accomplish this objective, it is imperative to reduce CO 2 emissions, which makes attaining sustainable development goals problematic. In this regard, improving economic growth without disastrously hampering the environment is a key factor in the fight against climate change. As such, many nations and multinational organizations have promulgated laudable and sound policy initiatives to achieve CO 2 emission reduction targets. One such policy directive is the reduction of CO 2 emission drastically by the end of the 21st century formulated by the intergovernmental panel on climate change (IPCC) in 1996. 1

The present study intends to scrutinize the asymmetrical influence of economic growth, industrial production, CPI (consumer price index) and oil price on the trade deficit for the People’s Republic of China’s economy. The Toda–Yamamoto causality, non-linear ARDL method, and quarterly data for 1995Q1 to 2021Q4 have been utilized to investigate the results. The estimated results confirm the uni-directional causality and presence of non-linear co-integration among variables under discussion. However, bound test analysis also reveals the long-run asymmetrical association among TD (trade deficit), IP (industrial production), oil price, and GDP growth, but not the CPI (consumer price index). Further, long-run asymmetrical outcomes highlight that a decrease (increase) in industrial production and an increase (decrease) in oil price and GDP growth rate increase (decrease) the trade deficit. Short-run asymmetrical outcomes reveal a similar trend to the long run, but the impact of all variables in the short run is insignificant, which means that linkages between the trade deficit and the explanatory variables are a long-run phenomenon in People’s Republic of China. Thus, in terms of policy, to reduce the trade deficit, it is necessary to focus on attaining standardized GDP growth, increasing industrial-sector production using advanced technology, and replacing oil-using energy sources with green technology (solar panels, wind farm energy).

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Digital humanistic knowledge production emphasises the importance of a strong knowledge production community and differentiates from traditional knowledge production models, which include aspects such as online and cooperative knowledge development. The digital humanities knowledge production community model is already widely acknowledged. However, the features and characteristics of digital humanistic knowledge production under natural language processing are controversial. This research presents a wordVEA digital humanistic knowledge production feature mining approach based on a word2vec and variational self-encoder (VAE). The knowledge production characteristics of digital humanistic are primarily defined by the coexistence of a knowledge production structure and boundary blurring, as well as interdisciplinary collaboration thematic cohesiveness and broad horizon, as determined by the research results which effectively address the question of the characteristics of digital humanistic knowledge production through application of the word VAE method.