Artificial intelligence in retail – a systematic literature review

Abstract

Purpose The purpose of this study is to present a systematic literature review of academic peer-reviewed articles in English published between 2005 and 2021. The articles were reviewed based on the following features: research topic, conceptual and theoretical characterization, artificial intelligence (AI) methods and techniques. Design/methodology/approach This study examines the extent to which AI features within academic research in retail industry and aims to consolidate existing knowledge, analyse the development on this topic, clarify key trends and highlight gaps in the scientific literature concerning the role of AI in retail. Findings The findings of this study indicate an increase in AI literature within the field of retailing in the past five years. However, this research field is fairly fragmented in scope and limited in methodologies, and it has several gaps. On the basis of a structured topic allocation, a total of eight priority topics were identified and highlighted that (1) optimizing the retail value chain and (2) improving customer expectations with the help of AI are key topics in published research in this field. Research limitations/implications This study is based on academic peer-reviewed articles published before July 2021; hence, scientific outputs published after the moment of writing have not been included. Originality/value This study contributes to the in-depth and systematic exploration of the extent to which retail scholars are aware of and working on AI. To the best of the author’s knowledge, this study is the first systematic literature review within retailing research dealing with AI technology.