Abstract
New energy products (NEPs) are important driving forces for promoting economic transformation and green development. The current trend of NEPs development is propelled by consumers, spurred by governmental regulations, and implemented by manufacturers. However, the previous studies rarely discussed the behavioral strategies of consumers. The relationships among consumers, manufacturers, and governments need to be researched in depth. In this paper, we focus on analyzing the impact factors of these three groups strategic selection of NEPs. In bounded rationality, by jointly considering the interactions among the customers’ purchases, the manufacturers’ product strategies, and the regulation policies, we develop three scenarios based on the evolutionary game model. The equilibrium results show that the production cost of NEPs and the profit from NEPs, government subsidies, and the taxation imposed on the manufacturers are the key influencing factors of the manufacturers’ strategy. The critical factors affecting the consumers’ purchase behavior are the benefits obtained from NEPs, government subsidies to consumers, and taxation on traditional energy products (TEPs). The influencing factors of governmental regulations include consumer satisfaction with the government, the environmental loss caused by TEPs, the cost of regulations, the coefficient of taxation, and subsidies. According to the research results, the countermeasures put forward will be more helpful for government to regulate the development of NEPs.
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Acknowledgements
The authors gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the presentation. This study was funded by Shandong Provincial Natural Science Foundation (Grant Nos. ZR2017QG003, ZR2016GM10), Shandong Provincial Social Science Foundation (Grant No. 17DGLJ09), and China Postdoctoral Science Foundation (Grant No. 2017M622265).
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Liu, C., Xia, T. Strategy analysis of governments and new energy product manufacturers and consumers based on evolutionary game model. Soft Comput 24, 6445–6455 (2020). https://doi.org/10.1007/s00500-019-04571-6
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DOI: https://doi.org/10.1007/s00500-019-04571-6