The consumer social network plays an important role in the formation of price premiums for agricultural foods. This study focuses on organic milk products and addresses the following questions: First, how does the consumer social network influence the formation of the price premium for organic milk? Second, what is the underlying mechanism of the consumer social network’s effect on this price premium? Despite existing research on social networks and consumer behavior, there is a limited understanding of the specific mechanisms by which social networks impact price premiums for organic goods. To investigate these issues, we utilized a consumption dataset of organic milk provided by CTR Market Research Co., Ltd. (2015–2021) and employed a two-way fixed effects econometric model that incorporates consumer social network density. The findings revealed that the consumer social network has a significant positive impact on the price premium of organic milk products, potentially accelerating the dissemination of knowledge about these products among consumer groups. Furthermore, feedback from friends has a greater influence on the formation of this price premium compared to input from family and relatives. Notably, the price premium exhibits a “U-shaped” relationship with an increase in the distance within the consumer social network. Overall, this paper is likely to contribute to the existing literature and provide marketers with valuable practical insights.

Industrial digitalization reshapes production processes and can potentially improve carbon productivity by optimizing factor allocation and energy efficiency. Using panel data for 30 Chinese provinces from 2012 to 2022, this study constructs a comprehensive industrial digitalization index with four dimensions and 13 indicators using the entropy method and examines its impact on carbon productivity (GDP per unit of CO₂ emissions). We employ the Dagum Gini coefficient and kernel density estimation to describe regional disparities and their evolution, a dynamic panel threshold model to test the nonlinear role of industrial transformation and upgrading, and a spatial Durbin model to identify spatial spillover effects. The results indicate that industrial digitalization has risen nationwide but remains uneven; industrial digitalization significantly enhances carbon productivity, with stronger effects in the eastern and western regions and in plain areas; the effect exhibits a double-threshold pattern with respect to industrial transformation and upgrading, implying a U-shaped relationship; and industrial digitalization generates positive spatial spillovers. These findings suggest that policy should coordinate digital infrastructure investment with industrial upgrading and regional collaboration to accelerate low-carbon, high-efficiency growth.