The chloride migration coefficient (CMC) of concrete is crucial for evaluating its durability. This study develops ensemble models to predict the CMC of concrete, addressing the limitations of traditional, labor-intensive laboratory tests. We developed three ensemble models: an inverse variance-based model, an Artificial Neural Network (ANN)-based model, and a tree-based model using the random forest regression algorithm. These models were trained on a dataset comprising 843 concrete mix proportions from existing literature. Results indicate that ensemble models outperform single models such as ANN and Support Vector Regression (SVR) in predicting CMC, with the combined random forest and ANN model showing the highest accuracy. Sensitivity analysis using Shapley Additive Explanations (SHAP) reveals that the CMC is most influenced by the water-to-cement ratio and curing age. Additionally, we designed a graphical user interface (GUI) to facilitate the practical application of our models. This research offers a robust methodology for evaluating concrete durability and potential for extending the prediction to other concrete properties.

Numerous organizational researchers have acknowledged that COVID-19 reduced the profit in the tourism industry. Some tourism firms decreased the cost by reducing the investment of CSR in order to increase the profit. However, the relevant literature remains scarce. The main purpose of this study is to explore the effect of COVID-19 on CSR investment in the tourism industry. This study fills the gap between stakeholder and cost stickiness theories. Based on a quasi-experiment of listed Chinese tourism companies from 2017 to 2021, the study finds that COVID-19 caused tourism firms to increase strategic CSR and decrease a responsive one. In addition, tourism firms that adopted cost leadership strategies trimmed responsive CSR more than strategic CSR. Tourism firms with differentiation leadership strategies increased strategic and decreased responsive CSR. Tourism firms with higher levels of political connections increased responsive CSR, while tourism firms with higher organizational resilience increased strategic CSR. At the theoretical level, this study reveals the theoretical mechanism of COVID-19 on tourism firms’ adjustment of CSR from the perspective of cost stickiness. On a practical level, it helps inform tourism firms’ decision-making regarding CSR adjustments for sustainable development when they face widespread crisis scenarios.

In China, new-energy vehicles are viewed as the ultimate goal for the automobile industry, given the current focus on the “dual-carbon” target. Therefore, it is important to promote the sustainable development of this new-energy market and ensure a smooth transition from fuel-driven vehicles to new-energy vehicles. This study constructs a tripartite evolutionary game model involving vehicle enterprises, consumers, and the government. It improves the tripartite evolutionary game through the mechanisms of dynamic and static rewards and punishments, respectively, using real-world data. The results show the following. (1) A fluctuation is present in the sales of new-energy vehicles by enterprises and the active promotional behavior of the government. This fluctuation leads to instability, and the behavior is difficult to accurately predict, which is not conducive new-energy vehicles’ promotion and sales. (2) A static reward and punishment mechanism can change the fluctuation threshold or peak value. Nevertheless, the stability of the system’s strategy is not the main reason that the government has been actively promoting it for a long time. However, enterprises are still wavering between new-energy and fuel vehicles. (3) The linear dynamic reward and punishment mechanism also has its defects. Although they are considered the stability control strategy of the system, they are still not conducive to stability. (4) The nonlinear dynamic reward and punishment mechanism can help the system to achieve the ideal stabilization strategy.

The education policy of the Macao Special Administrative Region is a driving factor in the investment of educational resources and the construction of a comprehensive education system. At the same time, the Macao Special Administrative Region Government closely integrates its education policy with the overall national development strategy, focuses on the training of teachers with a strong sense of national responsibility, and attaches importance to the needs of young people in national education, information technology education, and vocational education. Taking the policy addresses of the Macau Special Administrative Region over the past 25 years as the research sample, this study pioneered the use of policy modeling consistency index modeling combined with text mining to construct an evaluation system featuring the development of education policies. This approach provides a more in-depth quantitative analysis of the evolution and effectiveness of specific education policies. The results show that the MSAR has made significant progress in strengthening educational resources and aligning educational goals with national priorities. However, there is still room for improvement in areas such as information technology and vocational training. Based on this, the study recommends that these areas be targeted for strengthening, providing a reference basis for the future formulation or adjustment of existing education policies.