The use of virtual reality (VR) technology in the context of retail is a significant trend in current consumer research, as it offers market researchers a unique opportunity to measure purchase behavior more realistically. Yet, effective methods for assessing the virtual shopping experience based on consumer’s demographic characteristics are still lacking. In this study, we examine the validity of behavioral biometrics for recognizing the gender and age of customers in an immersive VR environment. We used behavior measures collected from eye-tracking, body posture (head and hand), and spatial navigation sources. Participants (n = 57) performed three tasks involving two different purchase situations. Specifically, one task focused on free browsing through the virtual store, and two other tasks focused on product search. A set of behavioral features categorized as kinematic, temporal, and spatial domains was processed based on two strategies. First, the relevance of such features in recognizing age and gender with and without including the spatial segmentation of the virtual space was statistically analyzed. Second, a set of implicit behavioral features was processed and demographic characteristics were recognized using a statistical supervised machine learning classifier algorithm via a support vector machine. The results confirmed that both approaches were significantly insightful for determining the gender and age of buyers. Also, the accuracy achieved when applying the machine learning classifier (> 70%) indicated that the combination of all metrics and tasks was the best classification strategy. The contributions of this work include characterizing consumers in v-commerce spaces according to the shopper’s profile.
There is increasing interest in studies analyzing the influence of technologies that integrate virtual and real-world components on consumer behavior. These technologies include augmented reality, virtual reality and mixed reality. Mixed reality is a user environment in which physical reality and digital content are combined in a way that enables interaction with and among real-world and virtual objects. In spite of previous works related with MR and retails spaces, little is known about how consumers respond to MR features and which elements of the MR-based experience, such as vividness and novelty, impact behavior. In this study, we have explored the relative advantage of mixed reality in retail shopping practices over a traditional-based purchase. Implicit reactions of shoppers when interacting with products with and without MR glasses were compared. The results reveal that participants wearing MR glasses exhibited different patterns of interaction (i.e., frequency and interaction with product duration) that differed from those indicated by participants who did not wear the MR technology. At the level of purchase decision, our results show that the use of MR smart glasses has an impact on decision times that relates to a utilitarian purchase type. Based on participants’ explicit answers to questionnaires, the reported findings further show that the perceived hedonic and utilitarian values of the purchase experience were higher when MR was used, which also affected future purchase intentions and perceived emotional state as reported by consumers’ experience and satisfaction in the context of retail.
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