This paper investigates the impacts of cap-and-trade (CAT) regulation on a three-echelon closed-loop supply chain network (CLSCN) that consists of suppliers, high-emission and low-emission manufacturers, demand markets and carbon trading centers. The presented CLSCN model includes both product trading and carbon trading subnets. Combining variational inequality theory (VI) with complementary theory, we first characterize the optimal conditions for members in each tier first, and then derive that of the entire CLSCN. In addition, we focus on the effects of carbon caps and EOL collection rate target on CLSCN performances with numerical examples. The results reveal that, in some cases, there is a consistency between carbon emission reduction target of the government and the profit target of enterprises. The government should choose reasonable and moderate carbon caps for all the enterprises to balance the CLSCN members’ economic interests, carbon emissions, as well as resources utilization rate. Moreover, the government should not blindly pursue a high collection rate target. The above conclusions can provide practical guidance for governments and enterprises in a CLSCN under CAT regulation.

The continuous decrease in the number of women of childbearing age and the consequent decrease in reproductive willingness have contributed to the continuous decrease in labor participation among Chinese women, which has negatively affected the stable socioeconomic development in terms of health. This paper deeply explores the intrinsic relationship between the number of children and women’s labor participation based on 2016 data from China Labor-force Dynamic Survey (CLDS). Our results show that there is an “inverted U-shaped” relationship between the number of children and the rate of women’s labor involvement; in other words, women’s labor participation shows a trend with the increase in the number of children, first rising and then falling; meanwhile, the relationship is more pronounced among women in eastern and central regions and towns. To this end, this study provides a theoretical research basis to effectively alleviate women’s selective pressure at home and work, and has a certain reference value for the Chinese government to improve women’s employment environment.

Under the background of a circular economy, this paper examines multi-tiered closed-loop supply chain network competition under carbon emission permits and discusses how stringent carbon regulations influence the network performance. We derive the governing equilibrium conditions for carbon-capped mathematical gaming models of each player and provide the equivalent variational inequality formulations, which are then solved by modified projection and contraction algorithms. The numerical examples empower us to investigate the effects of diverse carbon emission regulations (cap-and-trade regulation, mandatory cap policy, and cap-sharing scheme) on enterprises’ decisions. The results reveal that the cap-sharing scheme is effective in coordinating the relationship between system profit and carbon emission abatement, while cap-and-trade regulation loses efficiency compared with the cap-sharing scheme. The government should allocate caps scientifically and encourage enterprises to adopt green production technologies, especially allowing large enterprises to share carbon quotas. This study can also contribute to the enterprises’ decision-making and revenue management under different carbon emissions reduction regulations.

Expanding green consumption market and precise data promotion advantages make the platform economy have a significant effect on influencing manufacturers to carry out green R&D and production activities, and government subsidies have a positive incentive effect. In this context, for the studies about platform supply chain management with manufacturer’s green production and the platform’s marketing activities simultaneously are rare, we consider that a manufacturer invests in green technologies to produce products and sell them through a smart platform supply chain by an agency selling or reselling strategy, in which the platform provides data-driven marketing technology to promote green products. Four game models are constructed to study the operational efficiency of the platform supply chain considering selling strategy difference and government subsidy. The results show that: (1) The manufacturer’s green technology and the platform’s data-driven marketing levels, as well as all member’s profits are all influenced by the potential market demand of green products, the sensitivities of consumers to green product attributes, and data analysis technology. (2) The service commission rate charged by the platform plays a main role on the manufacturer’s selling strategy choice, when the service commission rate is low, the manufacturer chooses an agency selling strategy and can obtain more profit, but now the green technology level is not necessarily better than that in the reselling system. With the service commission rate increases, a manufacturer that chooses the reselling strategy can obtain more profit, and the green technology level is better than in the agency selling system. (3) Government subsidy can effectively encourage the manufacturer to improve the green technology level, and now the platform will improve the data-driven marketing level. There is a threshold range of the service commission rate charged by the platform in which the government can guide the manufacturer and the platform to reach an equilibrium selling strategy by regulating the subsidy level.