The low-carbon economy has become the focus of global attention and scientific measurement standards with the concepts of low energy consumption, low pollution, and sustainable development. More and more attentions are paid to the research of low-carbon supply chains. Based on a two-level low-carbon supply chain in the context of carbon trading, a Stackelberg game model was established for government subsidies to determine a coordinated and balanced solution for supply chains in situations dominated by manufacturers. The optimal strategies for low-carbon technology innovation are analyzed within the context of governmental subsidies. This study’s conclusions are as follows: (1) When government subsidies are in place, regardless of who the government subsidies are meant for, manufacturers and retailers that do not generate carbon emissions will transfer the subsidies to the companies that generate carbon emissions by adjusting wholesale prices and retail prices to maximize their own profits. (2) When consumer prices are sensitive, the government’s optimal subsidy intensity increases as consumers’ low-carbon preferences increase. When consumer prices are not sensitive, the government should not provide any subsidies. (3) When consumers’ low-carbon preferences are weak, the retail price of products will decrease with the increase in subsidies; when consumers’ low-carbon preferences are strong, the opposite dynamic occurs.

With the rapid development of online retail, the drawback of product fit uncertainty in online markets are becoming more and more prominent. In order to alleviate the impact of the product fit uncertainty, online retailers continue to introduce new service strategies. Based on the uncertainty of product matching, this paper constructs and solves the model of direct sales and try-before-you-buy(TBYB) strategy by online retailers under the premise of whether to allow returns. And explore the optimal strategy for the e-retailer in different aiming. The results show that: When the product fit is low, the optimal strategy choice for online retailers is TBYB strategy. When the product fit is high, if products are allowed to be returned, sell the product directly is the optimal strategy choice; if not, both TBYB and direct sales are optimal strategies. When the product fit is moderate, for products that are allowed to be returned, sell products directly when aiming to maximize demand and adopt the TBYB strategy when maximize profits. For products that are not allowed to be returned, Online retailers should sell products directly when aiming to maximize demand.

This study focuses on improving the Weber model to obtain a more optimised solution, by which we can measure effectively the quality of the voting rules. By introducing the voter’s supporting domain and the candidate’s supported degree to depict the emotional factors of voters and the real voting network, we propose the concept of validity for a candidate. Upon the traditional Weber model, two improved models are presented and the corresponding global optimal candidate is used as the evaluation benchmark for the voting rules. The experiments show that the optimal solution of the two models has better robustness in complex voting networks, can be used as a standard to evaluate the voting rules. When the support degree of voter is the main factor, the Condorcet rule is optimal in most cases, and when the validity of the candidate is taken as the main factor, the Approval rule must be the best.