The purchasing decisions of consumers increasingly incorporate considerations of freshness and the carbon footprint of agri-foods. This study aims to investigate the impact of consumer preferences on decision-making behavior within dual-channel supply chains. Specifically, it classifies the structure of the supply chain channels into two types: producer-led and seller-led online channels, and examines two distinct decision-making scenarios: centralized and decentralized decision-making. The study applies the game theory modeling method to analyze the differences in the selling prices, freshness, low carbon levels, and profits of agri-foods in these scenarios. The findings indicate that as consumer preference for the online channel grows, it becomes more challenging to sell homogeneous agri-foods at higher prices through physical (entity) channels. Moreover, the introduction of online channels by sellers leads to higher selling prices for agri-foods in the supply chain under decentralized decision-making compared to centralized decision-making, and the freshness and low carbon level of agri-foods primarily depend on the cost structure of the supply chain. From the perspective of enhancing produce quality, promoting low carbon development, and attaining high-quality products at a reasonable price, centralized decision-making within the supply chain and seller-led online channels are more advantageous. However, it is important to note that pursuing these benefits may result in a certain amount of sacrifice in terms of supply chain profit.

The onset of the information era has accelerated the transformation of digital governance, establishing it as a critical component in the modernization of governance frameworks and capabilities worldwide. Despite considerable advancements in the field of digital government, regional disparities in development remain pronounced, emphasizing the necessity for a coordinated and effective approach. This study employs a qualitative comparative analysis (QCA) of fuzzy sets to assess 31 provincial capitals in China, aiming to discern the digital governance ecosystems that promote the development of digital governments. It is grounded in the TOE framework, which examines the dynamics among technological, organizational, and environmental factors. The results provide empirical insights into the architecture of digital governance, offering a detailed comprehension of performance levels and recommending specific policy directions to enhance digital government progression.