China is a country highly vulnerable to natural disasters, resulting in significant losses in terms of human casualties, injuries, property damage, economic losses, infrastructure destruction, and so on each year. We propose a conceptual model based on the Data Envelopment Analysis model to evaluate regional vulnerability in mainland China using the annual data of Chinese official statistics from 2006 to 2021. The proposed model includes five input variables: regional total population, per capita GDP, population density, GDP per square kilometer, and regional total fixed investment in water conservancy, environment, and public facilities management. Additionally, it incorporates two output variables: affected people and direct economic loss. The results indicate that the vulnerability level generally decreases from West China through Central China to East China. Based on the new classification method proposed in this study, the regions are divided into five areas. These findings can serve as a reference for policymakers in enhancing disaster planning and improving the efficiency of natural disaster prevention.
Carbon policies and consumer environmental consciousness are effective motivators that drive enterprises to adopt sustainability technology. To provide enterprises insights into sustainable investment and inventory-transportation decision-making and governments insights into policy-making, this study investigates integrated inventory-transportation scheduling considering consumer environmental consciousness and sustainability technology under carbon cap, tax, and cap-and-trade policies. We first examined sustainability that extends the economic order quantity (EOQ) models, simultaneously taking into account the comprehensive emission model, consumer environmental consciousness, and carbon policies. We then optimized the sustainability level and EOQ using the simulation method. Furthermore, we performed a regression analysis on the carbon policy effects on sustainability level, profit, and emission. Moreover, using the regression models, we estimated and discussed the optimal policy parameters from the perspective of social welfare maximization. The results indicate that the carbon cap-and-trade policy is superior to carbon cap and tax policies. Under carbon cap and tax policies, the tougher the carbon policy, the higher the sustainability level and the lower the profit and carbon emission. Meanwhile, under the carbon cap-and-trade policy, the carbon trading price is the decisive factor that affects the sustainability level, enterprises’ profit, and carbon emission; the carbon cap has a positive regulatory effect on profit.
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