Enhancing Collaborative Shopping Experience Through Interactive Personalized Avatars and Shared Gaze in a Multi-User Augmented Reality Environment

Abstract

Augmented Reality (AR) has been used to enhance the shopping experience. However, existing AR shopping systems mainly focus on the solo user’s experience, while lacking multi-user experience. To address the gap, we propose a novel approach to collaborative shopping in a multi-user AR environment. By integrating the interactive personalized avatars of customers and shared gaze cues between shopping companions, we aim to understand how these technologies can enhance the collaborative shopping experience. We recruited thirty participants to conduct a 2 (personalized avatar: static vs. interactive) times 2 (shared gaze: without vs. with) within-subject repeat user study. The quantitative results from questionnaires showed that both interactive personalized avatars and shared gaze cues had positive effects on participants’ perceptions of enjoyment, usefulness, communication, co-presence, and future use. The combination of two features further enhanced the communication and perceived co-presence between shoppers and was preferred by participants. The qualitative results showed that interactive personalized avatars and shared gaze cues can enhance the shopping experience and promote efficiency which is consistent with quantitative results.

Keywords:

• Collaborative shopping
• augmented reality
• interactive personalized avatar
• shared gaze
• multi-user augmented reality experience
• shopping experience

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 https://youtu.be/wrMuyrzcHFs

Additional information

Funding

Shihui Xu holds a China Scholarship Council Studentship with Waseda University (No.202008050224).

Notes on contributors

Shihui Xu

Shihui Xu received her B.Eng degree from Southeast University, Nanjing, China, in 2018 and her Master’s degree from the Graduate School of Information, production, and Systems, Waseda University, Fukuoka, Japan, in 2019. She is currently a PhD student at Waseda University. Her research interest is human-computer interactions.

Like Wu

Like Wu received a B.Eng degree in computer science from the Hubei University of Education, Hubei, China, and a Master’s in Engineering from the Waseda University, Fukuoka, Japan, in 2018 and 2022. He is currently a PhD student at Waseda University. His research interest is Human-computer Interaction.

Wenjie Liao

Wenjie Liao received a B.Eng degree from Sichuan University, Chengdu, China, in 2021 and a Master’s degree from the Graduate School of Information, production, and Systems, Waseda University, Fukuoka, Japan, in 2022. He is currently a PhD student at Waseda University.

Shigeru Fujimura

Shigeru Fujimura completed his education at Waseda University, earning a doctorate in Engineering in 1995. He worked at Yokogawa Electric Corporation and its subsidiary before becoming a professor at Waseda University, specializing in software engineering and production management.