The Chinese government has issued a new “Plastic Restriction Ban” requiring that, by the end of 2020, the food and beverage industry across the country bans the use of single-use, nondegradable plastic drinking straws. The governance of plastic drinking straws is a multi-dimensional and complex process. Therefore, based on the heterogeneity of consumers, this paper constructs a tripartite game model (the government, retailers, and consumers) for the governance of plastic drinking straws in China. Under this model, this research derives an optimal strategy in both monopoly and competitive markets, assuming the government has access to two policy tools, fines and subsidies. The research results suggest the following. (1) In monopoly markets, when (a) the fine or subsidy fee is high or (b) the fine or subsidy fee is low and the number of environment-conscious consumers is high, retailers are more inclined to provide biodegradable drinking straws. (2) Consumer heterogeneity has a certain impact on policy results; when there are enough environment-conscious consumers, policy costs can be reduced. (3) For high-quality products, the policy costs in competitive markets is lower than in monopoly markets; for low-quality products, the policy costs in competitive markets is higher than in monopoly markets. Based on the conclusions, this work suggests the government should focus on cultivating consumers’ environmental awareness and tighter control of products quality, in addition to the two policy tools, i.e., fines and subsidies, because these can reduce policy costs. Consumers should be aware of their own importance to China’s Plastic Drinking Straws Ban and adopt a refusal to accept plastic drinking straws and reduce the consumption of disposable plastics to support the policy. Retailers should also realize that proactively catering to consumer and government expectations can bring higher benefits to themselves; this can be achieved by providing high-quality biodegradable straws to support China’s Plastic Drinking Straws Ban. The model of this work could be applied to other corporate activities related to sustainability, such as plastic bags, plastic bottles, etc., and their connection to government policies.

Because of incomplete information on pre-sold products, consumers face uncertainty about the value of what they have purchased, which leads to a mismatch between supply and demand and a large number of returns. By developing appropriate return policies and effectively managing and handling consumer returns, retailers can not only reduce waste but also ensure better resource utilization, which is essential for sustainable development. In this paper, we analyze the full-refund and full-and-freight-refund policies of retailers and develop a game model based on binary competition for selecting the optimal return policy for the pre-sold products of two retailers. The study shows that when both retailers have low capacity, there is no pre-sale stage. However, when their combined capacity is high and exceeds the demand of non-strategic consumers, equilibrium depends on their combined capacity and the proportion of strategic consumers who choose to keep the pre-purchased product under both return policies. When the number of strategic consumers who retain pre-order products is low under the full-refund policy and both retailers have moderate capacity, equilibrium is achieved when an asymmetric return policy is followed rather than a symmetric return policy. Specifically, when the percentage of strategic consumers who keep their reserved products under the product return strategy is small and the capacity of the two retailers is moderate, the maximum benefit is achieved if one of the retailers adopts the policy of a full refund and the other adopts the policy of a full-and-freight refund. Otherwise, when one retailer adopts the policy of a full refund or a full-and-freight refund, its competitor should adopt the same strategy to gain maximum revenue. The research on retailers’ pre-sale and return strategies in this paper helps to optimize the operational strategies and operational processes of e-retailers, further improve the management and decision making of their joint pre-sale and return strategies, and help optimize retailers’ profits.