Missing data has become an increasingly serious problem in credit risk classification. A one-hot encoding-based data preprocessing method is proposed to solve the missing data problem in credit classification. In this paradigm, the proposed missing-data preprocessing method is first used to deal with missing values to fill in the incomplete dataset. Then the classification and regression tree (CART) model is applied on the completed dataset to measure performances of different preprocessing methods. The experimental results indicate that the proposed one-hot encoding method performs the best when the missing rate is high. When missing rate is low, random sample (RS) imputation method performs better though it entails a greater computational cost than other imputation methods listed in this study. In particular, for high-missing-rate coupled with data-imbalance issue, the proposed one-hot encoding based imputation method shows not only high accuracy, but also great robustness and needs less of computational time.

The constantly increasing CO₂ emissions are threatening the environment tremendously. Facing the pressure of environmental activists and public opinion, businesses and governments are taking action to reduce carbon emissions. Among these endeavors, carbon tax and subsidy policies proposed by governments are widely adopted. Remanufacturing is believed to save manufacturing costs and reduce carbon emissions from the process of enterprise operation, and it is increasingly being accepted by enterprises. However, different consumers’ willingness to pay for remanufactured products and the durability of new products will also affect consumers’ willingness to buy remanufactured products. Therefore, considering the discrepancy between consumer willingness to pay and product durability, we established the trade-old-for-remanufactured (TOR) model for a scenario of carbon tax and government subsidies. Through the analysis of the model, we obtained the optimal pricing and production decisions of manufacturers (remanufacturers) in the case of carbon tax and government subsidies. Our results show that, when there is no carbon tax constraint, the increase in consumer willingness to pay and the adjustment in product durability can stimulate consumers to participate in TOR projects and augment enterprises’ profits. However, it can also lead to a carbon rebound that increases corporate carbon emissions. When there is a carbon tax constraint, the introduction of carbon tax contributes to a reduction in carbon emissions, while enterprises tend to lose profits. In order to achieve a “win-win” between corporate profits and carbon emissions, we considered government subsidy policies. Our numerical examples illustrate that appropriate carbon tax and government subsidies can curb carbon emissions and also increase profits for enterprises.

Global warming has become a growing concern for countries around the world. Currently, the direct way to solve this issue is to curb carbon emissions. Governments and enterprises should assume the social responsibility to conserve the environment. Under the background of carbon emission constraint, this article investigates the optimal decisions of closed-loop supply chains in the context of social responsibility, explores the impacts of constraints of carbon emissions and corporate social responsibility on recycling and remanufacturing decisions, and introduces the model of maximizing social welfare for further comparison and analysis. The results show that the coefficient of remanufacturing and emission reduction and the coefficient of government reward and punishment are inversely proportional to recycling rates and the total carbon emissions. Governments should formulate rational carbon emission caps for enterprises with different coefficients of remanufacturing and emission reduction. Additionally, corporate social responsibility has a positive effect on recycling rates, and a rise in its strength can lead to a fall in carbon emissions per unit product. In terms of product recycling and profit sources, the model of maximizing social welfare is superior to that of maximizing the manufacturer’s total profits, which provides new managerial insights for decision-makers.

Closed-loop supply chain is an important path to realize the sustainable development of supply chain, and cap-and-trade and carbon tax policies further promote closed-loop supply chain to invest in low-carbon technologies. This paper combines Economic Production Quantity with Economic Order Quantity models and designs multiple carbon policies. Abatement rate and collection rate are the key variables used to explore the mechanism of the interaction between carbon tax and cap-and-trade, inventory dynamics of closed-loop supply chain and impact of multiple carbon policies on closed-loop supply chain. Construct and analyze benchmark model, investment model under multiple carbon policies, remanufacturing model under multiple carbon policies and mixed strategies model under multiple carbon policies, and the results show that there is a non-linear complementary relationship between carbon price and carbon tax, and both remanufacturing and low-carbon investment can optimize cost and carbon emissions when carbon price is distributed at a certain interval. Furthermore, mixed strategies combining remanufacturing and low-carbon investment can optimize cost and carbon emissions simultaneously. The main contribution of this paper is to build a low-carbon circular system, which can help balance cost and carbon emissions of closed-loop supply chain.