Anais
Resumo do trabalho
Marketing · Marketing e Sociedade
Título
A SYSTEMATIC REVIEW ON THE IMPACT OF ARTIFICIAL INTELLIGENCE IN RETAIL
Palavras-chave
Artificial Intelligence
Marketing
Retail
Autores
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Lucas DamasioPONTIFÍCIA UNIVERSIDADE CATÓLICA DO PARANÁ (PUCPR)
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Ricardo GomesPONTIFÍCIA UNIVERSIDADE CATÓLICA DO PARANÁ (PUCPR)
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Heitor Takashi KatoPONTIFÍCIA UNIVERSIDADE CATÓLICA DO PARANÁ (PUCPR)
Resumo
Introdução
Objective: This study aims to provide a systematic review of the scientific literature published between 2008 and 2023 related to the application of artificial intelligence (AI) technology in retail activities.
Problema de Pesquisa e Objetivo
Originality/Value: The research extends the observation period compared to previous studies and contributes to the analysis of aspects related to companies' managerial capabilities in using AI.
Fundamentação Teórica
Design/Methodology/Approach: The research is characterized as a systematic review in which bibliometric analysis techniques of co-authorship, keyword co-occurrence, and co-citation were applied, following the five-step flow recommended by Zupic and Čater (2015). The Web of Science (WOS) database was used, from which 433 documents were selected, of which 390 studies, 230 citations, 75 authors, and 54 journals were relevant to the research.
Discussão
The study reveals the growing application of AI in retail, its impacts on customer experience and operational efficiency, and highlights theoretical gaps—such as ethics, privacy, and consumer acceptance—while suggesting avenues for future research.
Conclusão
Results: Four major thematic groups of concentration of research around AI application in retail activities were delineated. These areas are related to economic base, game theory and prices; administration, information, and model quality; anthropomorphism, engagement, and social networks; and artificial intelligence, deep learning, and machine learning.
Contribuição / Impacto
Contribution/Implication: The research organized the scientific production in the area, demonstrating the thematic groups of study concentration and proposing a less fragmented view of the findings and the relationship between the analyzed documents. Based on the findings, it was possible to identify gaps and themes that should be further explored, such as the consumer acceptance process, the use of AI for managerial decision-making, and cost optimization.
Referências Bibliográficas
Key references include Heins (2023), who mapped AI themes in retail; Dwivedi et al. (2021), offering a multidisciplinary overview of AI’s challenges and research agenda; and Pillai et al. (2020), analyzing consumer behavior in AI-powered stores. Other notable studies address AI’s role in personalization (Chopra, 2019), in-store technology (Grewal et al., 2020), and trust in AI influencers (Alboqami, 2023), collectively highlighting AI’s transformative impact on retail operations and consumer engagement.