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The study’s objective is to measure the importance consumers attach to AI-based attributes, namely, chatbots, face recognition, virtual fitting room, smart parking and cashier-free station in retail stores. The study also examines the specific purpose of using these attributes for shopping.

A conjoint experiment was conducted using fractional factorial design. Consumers were given 14 profiles (AI attributes and its levels) to rank according to their visiting preferences.

The results revealed that the retail chatbot was considered the most important attribute, followed by face recognition, virtual fitting room, smart parking system and cashier-free station. Moreover, consumers prefer to use chatbots for in-store shopping assistance over alerts and updates, customer support and feedback. Similarly, consumers wish a face recognition facility for greetings while entering the store over other services. In addition, cluster analyses revealed that customer groups significantly differ in their preferences for AI-based attributes.

The study guides retail managers to invest in AI technologies to provide consumers with a technology-oriented shopping experience.

Our results provide an insight into the receptivity of AI technologies that consumers would like to experience in their favorite retail stores. The present study contributes to the literature by investigating consumer preferences for various AI technologies and their specific uses for shopping.

In a consumer-driven world, captivating experiences are increasingly vital and retailers prioritise them for consumers. This study aims to develop a comprehensive theoretical framework that explores the impact of a consumer's multi-sensory and atmospheric experiences on their intention and commitment to a mall, with perceived value acting as a mediating factor.

The study employed a descriptive quantitative research approach and utilised a self-administered mall-intercept survey. A total of 380 shoppers participated in and responded to the survey administered at the mall. The collected responses are analysed using partial least squares structural equation modelling (PLS-SEM).

Study findings show that experiences significantly influence consumers' intentions to patronise shopping malls, leading to their commitment. The study reveals a strong impact of atmospheric experience on multi-sensory experiences. Furthermore, perceived value mediates the relationship between consumers' experiences and their mall patronage intention.

The research sheds light on the significance of atmospheric elements in creating sensory experiences for consumers. Additionally, the study introduces the concept of “props” as essential components of the atmospheric experiences in retail stores and malls. Furthermore, the study advances inference theory by exploring the effects of these sensory and atmospheric experiences within the shopping mall environment.