data-379.xlsx
收藏DataCite Commons2025-06-01 更新2024-11-06 收录
下载链接:
https://figshare.com/articles/dataset/data-379_xlsx/27614013/1
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资源简介:
This dataset accompanies the research study titled "Evaluating Brand Equity’s Role in Electric Vehicle Adoption: A Structural Equation Modeling Framework Incorporating Attitude and Price Perception." The study investigates how customer-based brand equity (CBBE) components, such as brand associations, perceived quality, and brand loyalty, influence consumers’ purchase intentions for electric vehicles (EVs) in China. The research integrates theoretical frameworks of the Theory of Planned Behavior (TPB) and CBBE, providing a unique perspective on the drivers of EV adoption within emerging markets.The dataset includes quantitative responses collected from a survey of potential EV consumers across six major Chinese cities. Variables covered include consumer attitudes toward EVs, brand loyalty, perceived quality, environmental concerns, perceived price, and other demographic information. Statistical analyses, including structural equation modeling (SEM) using SmartPLS, were employed to assess relationships between these variables.This data is valuable for researchers and practitioners interested in understanding the factors influencing consumer adoption of sustainable technologies, particularly in the context of brand equity and environmentally conscious purchasing decisions. The data is in CSV format and includes labeled columns with a detailed codebook describing each variable.<b>Data Content</b>:Survey responses from 379 participants.CBBE variables: brand awareness, brand associations, perceived quality, and brand loyalty.TPB variables: attitudes, perceived behavioral control, and subjective norms.Moderators: perceived price.Demographic variables: age, income, education, and location.
提供机构:
figshare
创建时间:
2024-11-05
搜集汇总
数据集介绍

背景与挑战
背景概述
该数据集包含来自中国六个主要城市的379名潜在电动汽车消费者的调查数据,用于研究品牌资产、消费者态度和价格感知对电动汽车购买意愿的影响。数据集涵盖客户基础品牌资产(CBBE)、计划行为理论(TPB)变量以及人口统计信息,支持结构方程建模分析,适用于可持续技术和品牌资产相关研究。
以上内容由遇见数据集搜集并总结生成



