Abstract Emotions have been largely acknowledged as important drivers of many consumers' behaviors. They are usually recognized through particular facial expressions, body language and gesture. However, the increasing integration of automatic systems in retailing is pushing researchers to understand the extent to which these systems can support employees to better understand consumers' shopping experience. In this vein, the present research aims at investigating the extent to which it is possible to systematically evaluate retail service encounters through consumers' facial expression. To this end, the research provides a machine learning algorithm to detect the six fundamental (human) emotions based on facial expressions associated with consumers' shopping experience in the 19 biggest shopping centers in UK, and (ii) investigates consumers' response to the usage of this system to automatically collect their evaluation of the retail service encounters. Findings reveal that a facial expression recognition system would uncover consumers’ evaluation of retail service encounters, and that consumers would accept the usage of facial expression identification systems to automatically evaluate the retail service encounters.

中文翻译：

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通过消费者面部表情对零售服务遭遇的非语言评估

摘要 情绪已被广泛认为是许多消费者行为的重要驱动因素。他们通常通过特定的面部表情、肢体语言和手势来识别。然而，自动化系统在零售业的日益集成促使研究人员了解这些系统在多大程度上可以支持员工更好地了解消费者的购物体验。在这方面，本研究旨在调查通过消费者的面部表情系统地评估零售服务遭遇的可能程度。为此，该研究提供了一种机器学习算法，可根据与英国 19 家最大购物中心的消费者购物体验相关的面部表情来检测六种基本（人类）情绪，(ii) 调查消费者对使用该系统的反应，以自动收集他们对零售服务体验的评价。研究结果表明，面部表情识别系统将揭示消费者对零售服务遭遇的评价，并且消费者会接受面部表情识别系统来自动评估零售服务遭遇。