Retailer servicebots – a reassuring service relation and an efficient counterpart
Short description
'Bots' are becoming an increasingly common feature in retail, in both digital customer interactions (chatbots) and physical encounters with customers. While we already know quite a lot about how consumers respond to robots as counterparts — for instance, that we can be both attracted to and put off by 'human' traits in a robot — much remains unknown. This project will experimentally explore how consumers react to one specific way of 'humanising' robots: giving them human facial expressions.
The project will experimentally test robots' facial expressions in different contexts, where consumers have different expectations of their interaction with the retailer. One such context is the exchange of information, which is relatively free of emotional elements and where consumers want to obtain specific information. Another context is based on a mistake; for example, when a customer wants to exchange an item or is dissatisfied with something that has gone wrong. In this scenario, there is greater emotional content, with negative feelings such as disappointment and dissatisfaction, and perhaps even anger.
The project will also examine how the type of goods purchased by the customer affects the robot's facial expressions. Purchases that are emotionally 'important', such as clothes with a certain signalling value, may result in a different interaction to more routine purchases.
Digitalisation, automation and the use of robots in customer interaction will play an increasingly important role for companies. Companies benefit from learning about consumer reactions. For instance, the significance of employees in customer interactions has impacted how companies organise and inform their staff internally, and the design of stores has given rise to extensive literature on the subject. Similarly, the project predicts that knowledge about consumer reactions to all aspects of robots, including their appearance, behaviour, and facial expressions, will be crucial for retail companies to understand their customers in the future.
Researchers in the project
Jeanette Hauff, University of Gothenburg
Jonas Nilsson, University of Gothenburg
Eunmi Jeon, University of Gothenburg