What to buy, Pepper? – Bridging the Physical and the Digital World with Recommendations from Humanoid Robots

ABSTRACT

While e-commerce has flourished in the past decades, brick-and-mortar retail stores face increasing challenges in attracting customers. Prior research indicates that humanoid robots may constitute a promising means to counteract this development. However, their capability to acquire and make use of rich information from the physical world (e.g. regarding customers’ physical characteristics) in combination with knowledge from (online) databases has not been adequately exploited yet. Thus, we aim at bringing together the best of the physical and the digital world by supplementing the traditional consultation process in brick-and-mortar retail stores with humanoid robots. Following a design-oriented approach, we propose a novel knowledge-based humanoid robot recommender process. We demonstrate our approach in cooperation with an optician and evaluate it using a customer survey and expert interviews. Results show that the approach achieves the design objectives and yields high customer satisfaction.

KEYWORDS:

• Humanoid robots
• recommender systems
• brick-and-mortar retail stores
• knowledge-based recommender process

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data that support the findings of this study are available from the corresponding author, M.K., upon reasonable request.

Notes

1. https://www.softbankrobotics.com/emea/en/pepper

2. https://github.com/ageitgey/face_recognition

3. https://www.cedefop.europa.eu/en/events-and-projects/projects/european-qualifications-framework-eqf