A Study on Selection Strategies for Battery Electric Vehicles Based on Sentiments, Analysis, and the MCDM Model

Under the goal of carbon peak and neutrality, developing battery electric vehicles (BEVs) is an important way to reduce emissions in transportation sector. To popularize BEVs as soon possible, it necessary study selection strategies for from perspective consumers. Therefore, Latent Dirichlet Allocation (LDA) model based on fine-grained sentiment analysis combined with multi-criteria decision-making (MCDM) assess ten types BEV alternatives. Fine-grained applied find vehicle attributes that consumers care about most word-of-mouth data. The LDA suggested divide topics construct indicator system. MCDM used rank put forward corresponding optimization path increase consumer purchases China. results show (a) via analysis, are divided into five topics: dynamics, technology, safety, comfort, cost; (b) DEMATEL technique, dimensions order importance follows: (c) price criteria affect customers’ satisfaction by DANP model; (d) VIKOR model, present Aion S highlighted best choice, discussed promote performance satisfaction. findings can provide a reference improving sustainable development automobile industry proposed framework serves basis further discussion BEVs.