Blockchain technology has brought about profound revolutions in supply chain management. Notably, in the agricultural sector, blockchain-based traceability has become an essential tool to maintain the safety and quality of farm commodities. However, the implementation of blockchain technology in agricultural traceability is not prevalent. In this paper, mathematical modeling and simulation methods were used to investigate the decision making regarding the adoption of blockchain traceability in agriculture, which comprises producers, processors, and governments. This paper provides further analysis of the optimal blockchain-based traceability strategies of the members of the agricultural product supply chain in different scenarios. The results reveal the following: (1) Producers and processors should manage the traceability costs for adopting blockchains to improve their brand image and gain more benefits. (2) The government should encourage supply chain agents to participate in traceability by establishing an effective reward-and-punishment mechanism. In addition, the research will help agricultural supply chain agents to design strategies to implement traceability in agriculture and create a transparent and efficient data-driven agricultural products supply chain. Furthermore, these findings provide guidance to policymakers to develop policies to accelerate the implementation of blockchain-based traceability systems to guarantee fraud-free and sustainable agricultural supply chains.

Global building energy consumption is significantly increasing. Utilizing renewable energy sources may be an effective approach to achieving low-carbon and energy-efficient buildings. A combined system incorporating solar photovoltaic–thermal (PV/T) components with an air-source heat pump (ASHP) was studied for simultaneous heating and power generation in a real residential building. The back panel of the PV/T component featured a novel polygonal Freon circulation channel design. A prototype of the combined heating and power supply system was constructed and tested in Fuzhou City, China. The results indicate that the average coefficient of performance (COP) of the system is 4.66 when the ASHP operates independently. When the PV/T component is integrated with the ASHP, the average COP increases to 5.37. On sunny days, the daily average thermal output of 32 PV/T components reaches 24 kW, while the daily average electricity generation is 64 kW·h. On cloudy days, the average daily power generation is 15.6 kW·h; however, the residual power stored in the battery from the previous day could be utilized to ensure the energy demand in the system. Compared to conventional photovoltaic (PV) systems, the overall energy utilization efficiency improves from 5.68% to 17.76%. The hot water temperature stored in the tank can reach 46.8 °C, satisfying typical household hot water requirements. In comparison to standard PV modules, the system achieves an average cooling efficiency of 45.02%. The variation rate of the system’s thermal loss coefficient is relatively low at 5.07%. The optimal water tank capacity for the system is determined to be 450 L. This system demonstrates significant potential for providing efficient combined heat and power supply for buildings, offering considerable economic and environmental benefits, thereby serving as a reference for the future development of low-carbon and energy-saving building technologies.

The breakthroughs in communication technologies, such as 5G, have significantly accelerated the popularity of high-traffic consumption entertainment activities, including short video live streaming and real-time broadcasting, making them one of the most prevalent social interaction methods today. It is the high activity level of such online engagements that has given rise to diversified online marketing business models, opening up new channels and opportunities for interactions between brands and consumers. This study focuses on the emerging “influencer marketing” strategy rooted in content marketing, employing double-layer network game theory to construct a dual-layer relationship network between “brands” and “influencers” and establish a game-theoretic mechanism between them. During the construction of the influencer network, a novel concept—tunable clustering of influencers’ followers—is specifically introduced, followed by an analysis of how micro-level decision-making factors (from brands and influencers) and network structures influence the evolutionary mechanisms of macro-level cooperative emergence. This study focuses on the emerging “influencer marketing” strategy rooted in content marketing, employing double-layer network game theory to construct a dual-layer relationship network between “brands” and “influencers”, establishing a game-theoretic mechanism between them and analyzing how micro-level decision-making factors (from brands and influencers) influence the evolutionary mechanisms of macro-level cooperative emergence. Specifically, during the construction of the influencer network, the network structural metric—tunable clustering—is integrated with the practical scenario of uneven follower distribution among influencers, thereby investigating the impact of influencer network clustering intensity on the system’s evolutionary dynamics. The research findings reveal that:(1) Influencer marketing represents a win-win cooperative model. (2) Brands’ decision-making outcomes are significantly affected by profit margins, additional costs, and commission rates. (3) Creative incentives and tunable clustering predominantly shape influencers’ decision-making behaviors. (4) Product lifecycles and platform extraction rate impact decisions of both parties, with brands exhibiting higher sensitivity to environmental changes. Followers’ trust levels in influencers have minimal influence on either party’s decisions. Finally, applying reasonable values derived from parameter experiments to the influencer marketing model in the cosmetics industry demonstrates that this approach effectively enhances mutual benefits and stabilizes the overall business environment.

With the increasing global concern for environmental protection and sustainable development, the low-carbon transformation of the manufacturing industries has become a top priority. The rapid development of green digital technology (GDT) provides new opportunities and a strong impetus for the low-carbon transformation of the manufacturing industries. Meanwhile, green credit, as an important financial tool to promote the development of the green economy, plays a key role in guiding resource allocation. In order to respond to the urgent global demand for environmental protection and sustainable development and to accelerate the pace of the low-carbon transformation of manufacturing industries, based on evolutionary game theory, this paper constructs a three-party evolutionary game model of commercial banks (CBs), digital businesses (DBs) and manufacturing industries (MIs); further subdivides the MIs into two categories of non-polluting MIs and polluting Mis; and performs a numerical simulation using Python to analyze the influence of the main parameters on the evolutionary stabilization strategy. The results of the study are as follows: (1) Changes in the interest rate of the green credit have a greater impact on the strategic evolution process of polluting MIs than non-polluting MIs. The green credit model contributes to the introduction of GDT for the low-carbon transformation by non-polluting MIs, although for polluting MIs, the model hinders, to some extent, their introduction of GDT for the low-carbon transformation. (2) Polluting MIs are more sensitive to the investment cost of introducing GDT than non-polluting MIs. When the support benefits of GDT are too low, polluting MIs are more inclined to choose independent innovation to realize the low-carbon transition. (3) Government subsidies to DBs in terms of GDT innovation are crucial to the DBs’ strategy choices. High subsidies can significantly accelerate the cooperation process between DBs and Mis. The findings reveal the challenges and opportunities faced by both non-polluting and polluting manufacturing industries in the process of the low-carbon transformation. In addition, the study provides theoretical references for the behavioral decisions of commercial banks, digital businesses, and manufacturing industries, and proposes corresponding management suggestions to promote the sustainable development of the manufacturing industries.

In the context of rapid development of social networks, users gather together through social network platforms (SNPs) to form social circles, which become the main carriers for users to disseminate public opinion information and emotions, and it is easy to form the phenomenon of network public opinion polarization in social circles. To prevent the polarization of network public opinions in social circles, the application of blockchain technology to SNPs can provide a credible database for the traceability of public opinions and avoid the spread of false information in social circles. Based on blockchain traceability, this paper establishes a three‐party evolutionary game model consisting of government, SNPs, and social circle managers (SCMs). Through model solving and numerical simulation, the influencing factors of each party’s strategy are analyzed. The findings suggest: (1) Although the rising cost of building blockchain platforms may undermine the government’s incentive to regulate, the government will still prioritise support for their construction if they can significantly enhance social welfare. (2) The government could boost SNPs’ willingness to adopt blockchain technology through subsidy measures, but increased privacy risks could undermine this willingness. (3) Blockchain technology realizes the traceability of public opinion and improves the rational guidance tendency of SCMs. Therefore, in order to promote and strengthen the collaborative governance of network public opinion in social circles, SNPs should enhance the use of blockchain technology, while the government should give full play to its regulatory and supervisory roles. This study introduces blockchain technology for public opinion traceability; explores a collaborative network public opinion governance system based on strict regulation by the government, introduction of blockchain technology by SNPs, and rational guidance by SCMs; expands the related research on network public opinion governance; and provides a new idea for the study of network public opinion governance of social circles based on blockchain traceability.