Application of Artificial Intelligence (AI) in the Drinks & Beverages (D&B) industry is becoming increasingly important for the competitiveness of companies in the sector. AI application for Marketing 5.0 in the D&B industry is of growing interest to both researchers and companies. AI-tools allow to create extremely precise market segmentations and satisfy increasingly differentiated consumer preferences or even influence them. However, at present, research on AI for Marketing of companies in the D&B industry is still at an early stage. Furthermore, to the best of our knowledge, there is a lack of systematic and quantitative reviews mapping the scholarly landscape at the intersection of these topics of research. Therefore, in order to help fill this gap, this review is the first study that aims to provide a comprehensive and detailed bibliometric analysis of the scientific literature published to date on the topics of AI for marketing and consumer studies in the D&B sector; in addiction, this study highlights the most discussed connecting themes among the main topics. Scientific cooccurrence maps were provided and Time Series analysis was carried out. Results showed limited number of scientific documents whose primary objective is the study of AI for Beverages' Marketing, despite the likely increase in academic interest in these topics. Machine Learning is the most widely used technology for customer profiling and preference prediction. Findings suggest an interdisciplinary approach for future AI-based marketing research and consumer studies, to provide open tools for personalized marketing tactics and strategies for SMEs.

Chinnici, P., Bacarella, S., Chironi, S., Naselli, V., Ingrassia, M. (2025). How will artificial intelligence drive marketing in the beverage industry? - A bibliometric literature review. FUTURE FOODS, 12 [10.1016/j.fufo.2025.100704].

How will artificial intelligence drive marketing in the beverage industry? - A bibliometric literature review

Chinnici P.
Primo
;
Bacarella S.
Secondo
;
Chironi S.;Naselli V.
Penultimo
;
Ingrassia M.
Ultimo
2025-01-01

Abstract

Application of Artificial Intelligence (AI) in the Drinks & Beverages (D&B) industry is becoming increasingly important for the competitiveness of companies in the sector. AI application for Marketing 5.0 in the D&B industry is of growing interest to both researchers and companies. AI-tools allow to create extremely precise market segmentations and satisfy increasingly differentiated consumer preferences or even influence them. However, at present, research on AI for Marketing of companies in the D&B industry is still at an early stage. Furthermore, to the best of our knowledge, there is a lack of systematic and quantitative reviews mapping the scholarly landscape at the intersection of these topics of research. Therefore, in order to help fill this gap, this review is the first study that aims to provide a comprehensive and detailed bibliometric analysis of the scientific literature published to date on the topics of AI for marketing and consumer studies in the D&B sector; in addiction, this study highlights the most discussed connecting themes among the main topics. Scientific cooccurrence maps were provided and Time Series analysis was carried out. Results showed limited number of scientific documents whose primary objective is the study of AI for Beverages' Marketing, despite the likely increase in academic interest in these topics. Machine Learning is the most widely used technology for customer profiling and preference prediction. Findings suggest an interdisciplinary approach for future AI-based marketing research and consumer studies, to provide open tools for personalized marketing tactics and strategies for SMEs.
2025
Settore AGRI-01/A - Economia agraria, alimentare ed estimo rurale
Settore AGRI-08/A - Microbiologia agraria, alimentare e ambientale
Chinnici, P., Bacarella, S., Chironi, S., Naselli, V., Ingrassia, M. (2025). How will artificial intelligence drive marketing in the beverage industry? - A bibliometric literature review. FUTURE FOODS, 12 [10.1016/j.fufo.2025.100704].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/689683
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