Multi-objective development path evolution of new energy vehicle policy driven by big data: From the perspective of economic-ecological-social

Abstract

With the sustainable development of new energy vehicle industry, there are problems of policy such as unbalanced policy structure, invalid detailed rules, and lack of objectives. While previous studies are lack of multi-objective development under the complex causal effects of various policies. Based on the paradigm driven by big data, this study deals with the multi-source and heterogeneous data of policy and multi-objective, constructs and trains PSR(Pressure-State-Response)-Bayesian network model. Then it completes the prediction of multi-objective development, cause diagnosis of policy in uncertain environment, and explores the evolution process of policy effect path. Results show that: (1) The multi-objective development of each policy in various stages changes dynamically, and unbalanced policy structure is found through results prediction; (2) Each objective development requires various policy priorities in each stage, and policy bottleneck problem due to invalid detailed rules having identified by cause diagnosis; (3) The effect path of policy mix to multi-objective development evolves dynamically, and exists lack of policy effect path. (4) According to the characteristics of industrial development stage, multi-objective development for sustainability should be realized through the spiral advancement of policies’ dynamic optimization.