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Sustainable livelihoods are those that are able to cope with and recover from stress and shocks, and that maintain or strengthen livelihood capacity and livelihood capital, without damaging the foundations of the natural environment. In this paper, the IPHACT framework was constructed by improving the classic IPAT equation, and the key factors affecting production output and livelihood sustainability, as well as the factor differences among different livelihood strategy groups, were analyzed. We took 24 counties and districts of Ankang, Shangluo and Hanzhong in the Qin-Ba Mountain area of southern Shaanxi Province as examples, using a survey of farmers’ livelihood status and livelihood capital accounting. The results show that the amplification effect of population size on the environmental impact of livelihood output is widespread and generally significant. Both livelihood sustainability and livelihood benefit passed the significance test in the multi-model analysis, and the negative effect of livelihood sustainability proved the negative correlation between the environmental impact of livelihood output and livelihood sustainability, that is, the higher the livelihood output dependent on natural capital, the greater the environmental impact. The livelihood transformation of Hanzhong City is developing in the direction of reducing the environmental impact of livelihood output, and farmers have successfully practiced green livelihood transformation by changing their livelihood strategies. On the road to common prosperity, livelihood demand will inevitably increase. Reducing the dependence on natural capital is the key to effectively enhancing the sustainability of livelihoods.

The ability of the food industry to practice a high degree of corporate social responsibility is related to whether national food safety can be effectively guaranteed. By taking the food enterprises in China’s A-share listed companies from 2009–2018, this paper probes into the influence of China’s macroeconomic policy uncertainty on corporate social responsibility, and depicts the differencent impact of enterprise’s practice of social responsibility under government association and market association, respectively. The results firstly show that, the uncertainty of economic policy has a negative effect on the social responsibility of food enterprises, with a regression coefficient of -0.013. Secondly, nonstate-owned enterprises are more vulnerable to macroeconomic fluctuations in the practice of social responsibility. Thirdly, in the case of greater economic policy uncertainty, enterprises with stronger market connections in the food industry tend to be more conservative in their CSR. The above research results not only verify the path of transmission of economic policy uncertainty to corporate social responsibility, but also provide important ideas and references for improving the level of corporate social responsibility in the food industry and ensuring food safety.

The interaction process between farmers’ livelihood and land use is a core link between the interaction and the coupling of the human–land system. It is a complex evolutionary process that involves several issues such as resource-intensive utilization and economic development. This study first constructs a dynamic model of the coupling system of farmers’ livelihood efficiency and land use and designs two types of 31 scenarios based on the farmer’s livelihood mode and land use. This study further simulates the coupling coordination relationship in different scenarios and then proposes suggestions for sustainable development. The findings of our study show that with the development of time, the livelihood capital, livelihood output, and land use level first showed a decline and then an increase. The results also reveal that livelihood efficiency and coordination degree are related to the livelihood mode and land use mode of farmers, while the land use level is not significantly associated with the livelihood mode of farmers. Pure-agriculture farmers have the lowest livelihood efficiency and coordination degree when they have no planting and breeding poultry, while part-time farmers have the highest land use level and coordination degree when they plant cash crops and breeding livestock. Besides, non-agriculture farmers have the highest livelihood efficiency and the lowest land use level when they neither plant crops nor breed livestock. To improve the level of coupling coordination, it is necessary not only to flexibly adjust the farmer’s livelihood and land use mode but also to optimize the allocation of various resources to promote the coordinated and sustainable development of farmers.

This study aims to find out the strategic priorities of the technical factors to have sustainable low carbon industry. For this purpose, a hybrid multi-criteria decision-making (MCDM) is proposed that contains three different stages. First, the economic criteria required for sustainable development and the technical needs of the low carbon industry are defined by making a comprehensive literature review. After that, economic criteria are weighted by using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) methodology. Finally, technical factors are ranked with the help of the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach. Moreover, another analysis is also performed by considering fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to evaluate the consistency of the analysis results. The main motivation of this study is to define the primary technical factors to minimize carbon emission problem by proposing a hybrid MCDM model. The findings indicate that research and development for renewable sources has the greatest importance for low-carbon industry. In addition, the analysis results of fuzzy TOPSIS and fuzzy VIKOR are quite similar. This situation demonstrates the consistency and coherency of the ranking results. Hence, it is recommended that countries should mainly give importance to the research and development investments so that the costs of renewable energy problems can be minimized. This situation can attract the attentions of the companies to invest in these projects. In this way, it will be possible to use a cleaner energy in industrial production.

Introduction: Environmental protection is an essential issue for sustainable development, and its execution power mainly comes from individual environmental protection behavior. This study investigates the resident environmental protection behaviors and influencing factors in the ecologically fragile areas of western China based on a total of 1062 households by adopting the participatory assessment method. Then, this study used the structural equation model to empirically analyze the impact of social capital, environmental risk perception, and environmental awareness on residents’ environmental protection behavior.Outcomes: The results showed that environmental awareness is the basis for practicing environmental protection behavior, consistent with the existing research; social capital has a significant impact on residents’ environmental protection behavior, with an impact coefficient of 0.347. Hence, environmental risk perception has an indirect influence on environmental protection behavior through environmental awareness. Besides, compared with urban residents, rural residents’ environmental awareness and social capital have a stronger role in environmental protection behavior.Conclusions: The study clarified the influence path of residents’ environmental protection behavior, thus effectively providing a decision-making basis for the government to guide residents in the environmental governance system.

The interaction between livelihood means and land use pattern of households is the core of the interactive coupling of the human-land system. This study focuses on Qinba mountainous area in southern Shaanxi province, a typical poverty-alleviated mountainous area. With the help of the coupling coordination degree model, kernel density estimation, and trend surface analysis, this study constructs the coupling coordination degree of livelihood efficiency and land use for households, and analyzes the differences between households’ livelihood efficiency and land use level, as well as the coupling coordination relationship between households livelihood efficiency and land use in different types and regions. The research conclusions are as follows. (1) For households in the Qinba mountainous area, southern Shaanxi province, the livelihood efficiency is at a medium level of 0.681, the land use is at a low level of 0.127, while the coupling coordination degree 0.526 is at the primary coordination state. (2) With the increase of nonagricultural degree, the coupling coordination degree of households increases first, and then decreases. (3) The coupling coordination degree for households east-to-west is “sagging”, while south-to-north diagram is “hogging”. (4) The distribution of the coupling coordination degree for agriculture-dependent households east-to-west (the “sagging” diagram) is opposite to the other types of households. By analogy, the distribution of the coupling coordination degree for nonagriculture and agriculture-dependent households north-to-south (the “hogging” diagram) is opposite to the other types of households. The coupling coordination between the households’ livelihood efficiency and land use level is affected by the households’ regional development level, natural resources, geographic location, infrastructure availability and many other factors. Making appropriate livelihood development plans based on the types of households and regional space can both effectively improve the livelihood conditions, as well as offer guidance in promoting regional human-land activity coordination and ensuring sustainable development.

This study examined the effect of livelihood risk on the options for livelihood strategies in rural farming communities in China's Shiyang River Basin. Using data collected from semi-structured interviews with 483 households, this study identified the effect of livelihood risk on livelihood strategies. By establishing an index system of livelihood risk (health, environmental, financial, social, and information and connectivity risks) and livelihood strategy (convert assets into cash, use loans, reduce consumption, let children drop out of school, go out to work and wait for government relief), this effect was measured and evaluated using multinomial logistic regression. The results indicated that health risk, environmental risk, and financial risk were significantly correlated with the options for livelihood strategies. Meanwhile, social risk and information and connectivity risk were not significantly correlated with options for livelihood strategies. These findings can support evidence-based policies that induce farmers to not only adopt more effective livelihood strategies and improve their well-being but also to establish specialized associations to improve their capacities and broaden their stock of livelihood strategies to mitigate livelihood risk. [ABSTRACT FROM AUTHOR]

Economic development forecasting allows planners to choose the right strategies for the future. This study is to propose economic development prediction method based on the wavelet kernel-based primal twin support vector machine algorithm. As gross domestic product (GDP) is an important indicator to measure economic development, economic development prediction means GDP prediction in this study. The wavelet kernel-based primal twin support vector machine algorithm can solve two smaller sized quadratic programming problems instead of solving a large one as in the traditional support vector machine algorithm. Economic development data of Anhui province from 1992 to 2009 are used to study the prediction performance of the wavelet kernel-based primal twin support vector machine algorithm. The comparison of mean error of economic development prediction between wavelet kernel-based primal twin support vector machine and traditional support vector machine models trained by the training samples with the 3-5 dimensional input vectors, respectively, is given in this paper. The testing results show that the economic development prediction accuracy of the wavelet kernel-based primal twin support vector machine model is better than that of traditional support vector machine. [ABSTRACT FROM AUTHOR]