Emotions Effect on Shopper Behavioral Responses in AI-Powered Retail Stores: An Abstract

Abstract

The border between the real and digital worlds is blurring as a result of technology-driven commerce. In retail, websites are behaving like stores, and stores are mimicking websites. Artificial intelligence (AI) is vital at this crossroads of offline and online (Grewal et al., 2021). However, retailers spend a lot of time and money installing AI technology, and the predicted satisfying outcomes aren’t always assured (Moore, 2018). Therefore, it is important to figure out how shoppers perceive AI technologies. While some AI technologies focus on transactional moments like price checking to improve the utilitarian side of the shopping experience, other AI applications enrich both utilitarian and hedonic aspects (Kelly, 2020). Consumer emotions might be more relevant when focusing on hedonic experiences. However, the interaction level between shoppers and AI technologies is crucial to determine the importance of considering emotions (Huang & Rust, 2021). Based on that, the current study considers retail AI technologies that include higher levels of interaction with shoppers (like touch screens and smart mirrors). This research, first, plans a pilot study to identify two positive and two negative influential emotional states when consumer-AI interaction moments occur, and then it conducts a survey-based study to examine the effect of these four emotional states on shopper attitude, behavioral and positive WoM intentions. The pilot study recommended that emotional states of interest, enjoyment, sadness, and anger are easily triggered when consumers interact with AI in retail stores. However, the survey-based study demonstrated a significant path only from the positive emotional states to shoppers’ attitudes and behavioral responses. Specifically, the study suggested that both interest and enjoyment directly impact on shopper attitude, indirectly on behavioral intention through both hedonic and utilitarian sources of attitude, and indirectly on positive WoM via the hedonic source of attitude only. Theoretically, the research notifies a significant relationship between positive emotional states, shopper attitude, and behavioral and positive WoM intentions (through attitude). Managerially, this study provides several suggestions for retailers and marketers; to enhance the emotional shopping experience, AI technologies applied in retail stores (1) should be emotion-aware by reading and evaluating consumer emotions, (2) should be useful by enhancing the utilitarian side of shoppers’ attitudes, for example by showing that AI technology features have high utility value like saving time or facilitating transactions, and (3) should be joyful by enhancing the hedonic side of the shoppers’ attitude, for example by keeping up with new trends.