In recent years, the market pattern of infant formula in China has changed dramatically. The market share of domestic infant formula has exceeded that of imports. The essence of the market share change of domestic and foreign brands is the change of consumers’ brand preferences. To explore which factors affected consumers’ brand preferences, our study conducted a qualitative research method based on the grounded theory, through in-depth interviews with 60 mothers in the Beijing-Tianjin-Hebei region, systematically identifying the factors which affect consumers’ brand preferences for infant formula, which allowed us to establish a theoretical model for them. We found that product characteristics and external environmental factors could directly affect the formation of consumers’ brand preferences, or indirectly through the two intermediary factors of buyers and users. In addition, in the consumption of infant formula, buyers and users were separated, and infants, as actual users, were an important factor that could not be ignored in brand preference.

China’s raw milk production is confronted with problems such as high production costs, stringent environmental constraints, weak industrial interest linkages, etc. The extensive and inefficient operation mode seriously restricts the further development of China’s dairy industry. How to increase the production efficiency of raw milk and realize the transition from “a country with high milk production” to “a country with high-efficiency milk production” has become the key to further developing China’s dairy industry. In order to explore the upgrading path of the raw milk industry in China, this study used the DEA-Malmquist model to estimate the production efficiency of raw milk in China and analyze its spatial and temporal distribution characteristics based on raw milk production input and output data at four scales (i.e., free-range, small-scale, medium-scale, and large-scale) from 2004 to 2020. It then adopted the SFA model to explore the relationship between raw milk input and output factors and the driving factors of production efficiency. Finally, robustness was discussed according to the existing research differences. The study draws several valuable conclusions. First, the production efficiency of raw milk in China from 2004 to 2020 fluctuated upward and showed specific regular regional distribution characteristics, but the spatial–temporal differences were minor. Second, raw milk production efficiency is significantly influenced by various factors, including the proportion of concentrate to roughage consumption, medical and epidemic prevention investment, the price of raw milk, the wage level, and fixed assets. Third, the spatial–temporal distribution and driving factors of raw milk production efficiency are less robust, so efficiency analysis and improvement measures should fully consider analytical methods, scale heterogeneity, indicator systems, and temporal heterogeneity.

Clarifying the key driving factors behind the adoption of manure resource utilization technology and promoting its widespread application are crucial for achieving the high-quality development of animal husbandry. This study analyses survey data from 412 large-scale dairy farms across 23 provinces in China. The Cov-AHP method is used to measure the adoption intensity of technology and analyse its mechanisms and underlying logic. The results indicate that value perception, particularly economic value perception, is the strongest driver of adoption intensity. Although the direct effect of environmental regulation is limited, it significantly amplifies the influence of value perception—particularly economic value perception—on technology adoption intensity, especially in large-scale farms. Furthermore, incentive-based regulations (e.g., government subsidies) markedly promote the adoption of manure resource utilization technologies, whereas constraint-based measures (e.g., fines) exert stronger effects on small-scale farms. Additionally, demonstration farms serve as critical catalysts for disseminating best practices and accelerating technology adoption. This study suggests that policies should integrate value perception with targeted financial subsidies and regulatory measures to improve technology adoption, especially with support for small-scale farms. By leveraging demonstration farms to promote successful experiences, the comprehensive adoption of manure resource utilization technologies across the industry can be further improved.

Facilitating the comprehensive adoption of manure and sewage resources (MSR) technologies to establish a business model centred on reduction, reuse, and low pollution has become an urgent priority for achieving high-quality development in the animal husbandry industry. This study analyzes survey data from 412 large-scale dairy farms across 23 provinces in China. The CovAHP method is used to measure the adoption intensity of technology and analyze its mechanisms and underlying logic. The results indicate that value perception, particularly economic value perception, is the strongest driver of adoption intensity. While the direct effect of environmental regulation is limited, it can significantly amplify the influence of value perception on adoption intensity, especially in large-scale farms. The study further finds that incentive-based regulations, such as government subsidies, significantly promote the improvement of manure resource utilization technologies, whereas constraint-based regulations (e.g., fines) have a greater impact on small-scale farms. Additionally, demonstration farms play a key role in promoting best practices and accelerating technology adoption. The study suggests that policies should integrate value perception with targeted financial subsidies and regulatory measures to improve technology adoption, especially with support for small-scale farms. By leveraging demonstration farms to promote successful experiences, the comprehensive adoption of manure resource utilization technologies across the industry can be further improved.