基于QFD的场景化新能源汽车满意度提升研究

Research on the Improvement of New Energy Vehicle Satisfaction based on Scene Features and QFD Model

随着近年来新能源汽车的迅猛发展,消费者对新能源汽车的使用场景更加多样化,随之而来则引发了消费者在不同使用场景下对新能源汽车飭诸多不满和多种需求.文章从搜索到的车评语句出发,选取评价指标并构建用车场景,对车评语句进行指标划分归类;然后利用情感算法和语句指标提及率分别计算满意度和重视度,并通过减法模型获取待优化改进指标;最后利用QFD模型研究用户在不同场景下的新能源汽车满意度情况和潜在需求,输出优化提升的改进方向=文章的研究成果在一定程度上反映了当前新能源汽车行业的满意度发展趋势,深度挖掘了新能源汽车消费者在不同使用场景下的车辆痛点,并准确把握其需求,对车企改进提升靳能源汽车产品满意度以及未来开发新产品提供参考性建议.

With the fast development of new energy vehicles in recent years,consumers drive their new energy vehicles in more and more diverse scenes.This has led to users dissatisfaction and various demands for new cnergy vehicles in different driving scene.Starting at the car review sentences,then this article defines evaluation indicators and vehicle scenes,and classifies the review sentences.Next,using the sentiment algorithm and the mention rate calculates user satisfaction and the importance of the indicators respectively,and obtain the indicators to be optimized and improved through the subtraction model.Finally,the QFD model is used to research the user's satisfaction and potential demands for new energy vehicles in different driving scene,and output the improvement direction for optimization and improvement.The research results of this article reflect the current development trend of the new energy vehicle satisfaction industry to a certain extent,deeply excavate the pain points and diverse needs of new energy vehicle consumers in different driving scene,and provide reference suggestions for car companies to improve their satisfaction with new energy vehicle products and to develop new products in the future.