Research Article
Research on the Risk Assessment of New Energy Automobile Industry Based on Entropy Weight-Cloud Model in China’s Jiangsu Province
Table 4
Risk-factor weight of new energy automobile industry in China’s Jiangsu province.
| Risk indicator Risk weight | Primary-indicator-factor layer | Primary-indicator weight | Secondary-indicator-factor layer | Secondary-indicator weight |
| Endogenous risk (0.4111) | Fundamental risk | 0.1666 | Technological-innovation risk | 0.3975 | Production-cost risk | 0.2000 | Production-efficiency risk (output value) | 0.2224 | Financing-ability risk | 0.1801 | Structural risk | 0.1074 | Fuel-source risk | 0.2091 | Market-concentration risk | 0.3277 | Regional-distribution risk | 0.2583 | Industrial-chain risk | 0.2049 | Network risk | 0.1371 | Unfair-competition risk | 0.1423 | Incomplete-contract hazard | 0.2302 | Moral risk | 0.4092 | Risk of excessive policy dependence | 0.2183 |
| Exogenous risk (0.5889) | Policy risk | 0.1582 | Policy-stability risk | 0.2000 | Policy-continuity risk | 0.3773 | Policy-timeliness risk | 0.2107 | Policy-coordination risk | 0.2120 | Market risk | 0.1732 | International-competition risk | 0.1998 | Industry-transformation risk | 0.3014 | Social-cognitive risk | 0.3387 | Overcapacity risk | 0.1601 | Environmental risk | 0.2575 | Legal-environment risk | 0.2188 | Power-battery-environment risk | 0.3209 | Economic-cycle risk | 0.1517 | Zonal-ecological risk | 0.3086 |
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