A multistage risk decision making method for normal cloud model considering behavior characteristics

Risk assessment for supply chain based on Cloud model

In recent years, supply chain risk management has been followed with interest due to the short life cycle of products. How to identify risk indicators can help evaluate risks on supply chains. Commonly adopted methods such as Fuzzy to determine the level of risks have limitations. In this paper, a framework of supply chain risk evaluation is first proposed and risk indicators are identified by theoretical surveys from 35 keywords and empirical analysis from 448 questionnaires. Moreover, both linguistic risk assessment model and Cloud model are used to evaluate risks of supply chain. The Cloud model evaluation results are between general risk and high risk but closer to high risk. In addition, Cloud expected value of risk is 6.54 which is within the high-risk range, and evaluation results are also high risk. It is shown that when the weights are the same, the cloud model can determine the priority of risk indicators, and reflect volatility and randomness comparing with other evaluation methods.

Dynamic early warning of regional atmospheric environmental carrying capacity

Economic development cannot exceed the maximum amount that the environment can support. Therefore, atmospheric environmental policy should be formulated based on the scientific assessment of regional atmospheric environmental carrying capacity. The establishment of an early warning model of atmospheric environmental carrying capacity can dynamically analyse regional atmospheric environmental carrying capacity, which contributes to discerning the change trend of the regional atmospheric environmental carrying capacity and the risk issue of the regional atmospheric environment. Additionally, it can provide theoretical reference for the formulation of relevant binding and restrictive policies. In this study, according to the daily monitoring data of atmospheric pollutants, we established a dynamic early warning model of regional atmospheric environmental carrying capacity based on the cloud model and Markov chain. The research results show that this model has an excellent early warning capability. Moreover, many regions in China have exceeded the atmospheric environmental carrying capacity, especially in North China and Central China. By 2020, North China and Central China for prediction of region with non-overloading are only 9.09% and 12.50%, respectively. China's regional atmospheric environmental carrying capacity is gradually improving. It is predicted that by 2024, regions with non-overloading in North China and Central China will reach 40.91% and 37.50%, respectively. From the overall aspect, there is currently no risk of serious overload in any region.

Applicability Evaluation of China’s Retail Electricity Price Package Combining Data Envelopment Analysis and a Cloud Model

With the reform of the power system, the retail electricity market in China has gradually been liberalized. The mechanism of freely selling electricity have been set up. To grab market share and increase profits, electricity retail companies have introduced a series of retail electricity price packages. To evaluate the applicability of these retail electricity price packages, an adaptive evaluation index system that takes into account the interests of both the power company and the users is first established. Furthermore, an integrated evaluation model that combines data envelopment analysis (DEA) and the cloud model is proposed. In this model, DEA is used to process quantitative indicators and the cloud model is employed to quantify qualitative problems. A case study of Tianjin is conducted to verify the effectiveness of the proposed evaluation system and model. The empirical study shows that qualitative indicators can also affect the applicability of the retail electricity price packages, and the applicability of the retail electricity price package was different in different seasons. Finally, several reliable suggestions on how to design retail electricity price packages are given based on the research. This study provides useful support for customers to choose the price package to increase the competitiveness of power selling companies and ultimately promote the reform of power selling.