Pro-environmental behavior can promote the optimization of the living environment and sustainable social development. This paper constructs a theoretical analysis framework of “environmental consciousness, habitat environment-social capital- pro-environmental behavior”. By using structural equation modeling and 1005 instances of microscopic research data, we analyzed the influence of environmental awareness and habitat environment on the pro-environmental behavior of community residents. The results of the analysis were combined with the Bootstrap method to verify the mediating role of social capital dimensions in the influence of environmental awareness and habitat quality on the pro-environmental behavior of community residents. The results show that: Firstly, environmental awareness, habitat quality, and social capital have positive effects on the pro-environmental behavior of community residents. Secondly, environmental awareness and habitat quality have positive effects on the five dimensions of social capital. Thirdly, among the five dimensions of social capital, four dimensions of social trust, social norms, sense of community belonging, and community voluntarism play a partially mediating role between environmental awareness, habitat quality, and pro-environmental behavior. This paper enriches the research on the influence of environmental awareness and habitat environment on pro-environmental behavior, reveals the mediating effect of each dimension of social capital, and broadens the horizon for the study of pro-environmental behavior. The results of the study can provide a reference for decision making to promote the implementation of pro-environmental behavior among community residents.

Studies on the factors that influence farmers’ pro-environmental behavior could promote environmental management in rural areas. Jinan of China was selected as the case study area in this study. A structural equation model and multiple hierarchical regression analysis were applied to analyze the influence mechanism of ecological value cognition on pro-environmental behavior. Environmental attitudes were set as the mediating variable and place attachment was selected as the moderating variable. The results showed that (1) ecological value cognition exhibited a positive influence on pro-environmental behavior in both direct and indirect ways. The indirect influence was mediated by environmental attitude. (2) Place identity and place dependence showed a positive direct influence on pro-environmental behavior. (3) It is suggested that in order to improve pro-environmental behavior, enhancing ecological value cognition, cultivating farmers’ positive environmental attitude, increasing farmers’ place attachment, and releasing reward and punishment measures are good strategies. The findings in this study are important to the improvement of the rural ecological environment and the quality of life of farmers. Meanwhile, the findings shed light on the construction process of ecological civilization and the improvement of public welfare.

Spatial autocorrelation, cold and hot spot analysis, and standard deviation ellipse analysis were used to analyze the spatial distribution of intangible cultural heritage (ICH). Geodetectors were used to reveal the factors that influenced the distribution in Shandong Province. The results showed that: (1) The ICH in Shandong Province covered most ICH types with the difference in the number of expressions of ICH of a different type. Traditional artistry, traditional art, traditional sports, recreation and acrobatics, and folk literature are the main types of ICH. (2) The spatial distribution of ICH showed a great difference. Multiple concentration areas and deficient areas were presented that followed the direction from southwest to northeast. (3) Man–land relationship-related factors such as population, waters, urban–rural size, and air temperature showed important influence on ICH distribution. The influence of interaction among influence factors is higher than a single factor. In summary, man–land relationships are the key factors that influenced ICH distribution.

Combining the Intangible Cultural Heritage and sustainable development has been an important effort of UNESCO since the new century. This study discusses the suitability of educational tourism development of intangible cultural heritage. On the one hand, it was beneficial to improve the comprehensive quality of students; on the other hand, it was conducive to protecting and rationally developing the cultural heritage and avoiding its loss. In this study, an evaluation index system was established according to the analytic hierarchy process, which included two aspects (i.e., intrinsic value and extrinsic conditions) and 16 indices from four criterion layers (e.g., educational value, recreational value, environmental conditions, and relevant facilities and services). Furthermore, we calculated the development suitability and spatial distribution patterns of intangible cultural heritage for educational tourism. At the same time, using the obstacle degree model, the obstacle degrees of each indicator factor were screened and identified to explore the source of obstacles that restrict the suitability of educational tourism development of ICH. Results showed that: (1) The development suitability of intangible cultural heritage for educational tourism was divided into high suitability, middle suitability, and low suitability. A total of 186 intangible cultural heritages were found in Shandong Province, China. Among these intangible cultural heritages, 60 of 186 (32.26%) were low suitability, with values ranging from 0.326 to 0.460; 86 of 186 (46.24%) were middle suitability, with values of 0.460–0.543, and 40 of 186 (21.50%) were high suitability with a range of 0.543–0.689. (2) The spatial distribution patterns of suitability showed that the development suitability of intangible cultural heritage for educational tourism in Shandong Province exhibited a significantly positive spatial correlation that projects with similar suitability levels were clustered into a group and generally distributed with a direction of “southwest to the northeast”. (3) According to the diagnostic results of obstacle factor analysis, from the perspective of the first level indicator, the obstacle degree of the intrinsic value (A1) of the three levels of suitability of ICH was the highest. Among the second-level indicators, educational value (B1) has always been the biggest obstacle factor affecting the educational tourism of ICH, and the relevance of cultural content (C2), representativeness and typicality of the phenomenon (C3), applicability of teaching cases (C4), and uniqueness or rarity (C5) were the greatest among the three suitability factors.

The pig-breeding industry is one of the pillar industries of China’s agriculture. Improving the green total factor productivity of pig breeding is the basis for ensuring the stable supply of pork, and is also the key to the green transformation of the pig industry. The existing studies about the green total factor productivity of pig breeding lack an analysis of regional coordination and the spillover of spatial technology efficiency at the macro level, and most studies focus on the impact of agricultural production’s environment pollution and other undesirable outputs. Based on the input–output index system of the pig-breeding industry’s green production, the DDF directional distance function model and the Malmquist–Luenberger (ML) productivity index were combined to measure the green total factor productivity of the pig-breeding industry. Moran’s I-Theil index model was used to measure and reveal the technical efficiency differences among the dominant regions of the pig-breeding industry in China and the σ-convergence test was adopted to reveal the convergence trend of green total factor productivity. The results showed that: (1) The growth level of green total factor productivity of pig breeding in China was generally low from 2006 to 2018, and there were obvious regional and scale differences. (2) The green total factor productivity of pig breeding in each province had spatial autocorrelation; that is, there was technology spillover. From 2006 to 2018, with the advance of time, a pattern of gradual evolution from low-level equilibrium to high-level imbalance was formed. (3) Through the convergence test, the convergence trend of large and medium-scale development between different regions fluctuated, while the convergence trend of small-scale development between different regions was not obvious. Therefore, it is necessary to increase investment in technological innovation, promote the large-scale and standardized development of the pig-breeding industry, and strengthen the promotion of technology in producing areas with advantages in pig breeding.

Actively promoting the orderly and voluntary withdrawal of idle rural house bases and effectively activating “sleeping” land assets are considered important measures to accelerate the modernization of agriculture and rural areas, as well as promoting the integrated development of urban and rural areas. However, few studies have focused on the superimposed effects of negative psychological and social environmental factors on the willingness of farmers to withdraw from their homestead. Therefore, we conducted this study in order to clarify the logical ideas of rural home base withdrawal, analyze the factors that influence the decision of home base withdrawal behavior of interest subjects, and provide a scientific decision basis for promoting rural home base withdrawal and accelerating the process of transferring citizens of agricultural population in terms of policies, measures, and paths, so as to design and develop an incentive mechanism for home base withdrawal of citizens of agricultural transfer population. The results of the study show that: (1) the findings indicate that social deprivation, economic deprivation, and emotional deprivation all significantly and negatively affect farmers’ willingness to withdraw from their homesteads; (2) social trust plays a mediating role between relative deprivation and farmer homestead withdrawal behavior; and (3) urban integration plays a moderating role between social and emotional deprivation and the social trust of farmers, but does not have a significant moderating role in the relationship between economic deprivation and social trust. Furthermore, it plays a moderating role between all deprivation factors (i.e., economic, social, and emotional deprivation) and farmer homestead withdrawal behavior. This study aims to provide useful guidance and policy suggestions for optimizing policies related to farmer homestead withdrawal behaviors, and for scientifically designing the homestead withdrawal mechanism and policy system.