Retail Managers’ Preparedness to Capture Customers’ Emotions: A New Synergistic Framework to Exploit Unstructured Data with New Analytics
研究通过机器学习分析顾客静态图像中的情绪（快乐与悲伤），并调查零售经理对情绪识别系统的态度，发现应用需求与伦理担忧并存，为零售管理提供新框架。
Abstract Although emotions have been investigated within strategic management literature from an internal perspective, managers’ ability and willingness to understand consumers’ emotions, with emphasis on the retail sector, is still a scarcely explored theme in management research. The aim of this paper is to explore the match between the supply of new analytical tools and retail managers’ attitudes towards new tools to capture customers’ emotions. To this end, Study 1 uses machine learning algorithms to develop a new system to analytically detect emotional responses from customers’ static images (considering the exemplar emotions of happiness and sadness), whilst Study 2 consults management decision‐makers to explore the practical utility of such emotion recognition systems, finding a likely demand for a number of applications, albeit tempered by concern for ethical issues. While contributing to the retail management literature with regard to customers’ emotions and big data analytics, the findings also provide a new framework to support retail managers in using new analytics to survive and thrive in difficult times.