Chen Yu-Ping, Nelson Leif D, Hsu Ming
Haas School of Business, University of California, Berkeley; Helen Wills Neuroscience Institute, University of California, Berkeley.
Haas School of Business, University of California, Berkeley.
J Mark Res. 2015 Aug 1;52(4):453-466. doi: 10.1509/jmr.14.0606.
Considerable attention has been given to the notion that there exists a set of human-like characteristics associated with brands, referred to as brand personality. Here we combine newly available machine learning techniques with functional neuroimaging data to characterize the set of processes that give rise to these associations. We show that brand personality traits can be captured by the weighted activity across a widely distributed set of brain regions previously implicated in reasoning, imagery, and affective processing. That is, as opposed to being constructed via reflective processes, brand personality traits appear to exist a priori inside the minds of consumers, such that we were able to predict what brand a person is thinking about based solely on the relationship between brand personality associations and brain activity. These findings represent an important advance in the application of neuroscientific methods to consumer research, moving from work focused on cataloguing brain regions associated with marketing stimuli to testing and refining mental constructs central to theories of consumer behavior.
人们已经相当关注这样一种观念，即存在一组与品牌相关的类人特征，称为品牌个性。在这里，我们将新出现的机器学习技术与功能性神经成像数据相结合，以描述产生这些关联的一系列过程。我们表明，品牌个性特征可以通过广泛分布的一组先前与推理、意象和情感处理有关的大脑区域的加权活动来捕捉。也就是说，与通过反思过程构建不同，品牌个性特征似乎先验地存在于消费者的头脑中，以至于我们能够仅根据品牌个性关联与大脑活动之间的关系来预测一个人正在思考的品牌。这些发现代表了神经科学方法在消费者研究应用中的一项重要进展，从专注于对与营销刺激相关的大脑区域进行编目的工作，转向对消费者行为理论核心的心理结构进行测试和完善。
