Abstract
Virtual reality (VR) in retailing (V-commerce) has been proven to enhance the consumer experience. Thus, this technology is beneficial to study behavioral patterns by offering the opportunity to infer customers’ personality traits based on their behavior. This study aims to recognize impulsivity using behavioral patterns. For this goal, 60 subjects performed three tasks—one exploration task and two planned tasks—in a virtual market. Four noninvasive signals (eye-tracking, navigation, posture, and interactions), which are available in commercial VR devices, were recorded, and a set of features were extracted and categorized into zonal, general, kinematic, temporal, and spatial types. They were input into a support vector machine classifier to recognize the impulsivity of the subjects based on the I-8 questionnaire, achieving an accuracy of 87%. The results suggest that, while the exploration task can reveal general impulsivity, other subscales such as perseverance and sensation-seeking are more related to planned tasks. The results also show that posture and interaction are the most informative signals. Our findings validate the recognition of customer impulsivity using sensors incorporated into commercial VR devices. Such information can provide a personalized shopping experience in future virtual shops.
Highlights
Imagine that you can go shopping, walk down the aisles, look at the products, interact with them, and purchase them without ever leaving your house
The kinematic category became dominant because the margin between the kinematic and temporal categories was slim in the general features
The results showed that POS & INT features were the best signal for predicting impulsivity with a kappa equal to 0.64 in the exploration task
Summary
Imagine that you can go shopping, walk down the aisles, look at the products, interact with them, and purchase them without ever leaving your house. The first virtual system was presented by Morton Heilig in the early 1960s using a recorded colored film and the ambient properties of sound and scent, but no interaction with the environment [3]. In recent years, this technology has been improved in several aspects such as interactive graphics, head tracking, and interactions between individuals [2]. These technological advancements have resulted in using different kinds of VR apparatus in behavioral studies [4], since this technology provides researchers with the possibility of studying scenarios under controlled laboratory conditions [5], and it permits time- and cost-efficient manipulation of behavioral variables in comparison with real situations [6]
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