Table 2

Bibliographic coupling clusters

New clusterMain articlesCluster (colour)Number of documentsTimespanMain topics
A (AI adoption and benefits)Spanaki et al. (2021)
Tassiello et al. (2021) 
1 (red)152019–2022Customer engagement (Alfalih, 2022), boosting entrepreneurship and innovation (Secinaro et al., 2022; Lachman and Ló pez, 2019); sustainable practices in agriculture (Abban and Abebe, 2022; Morales and Elkader, 2020)
B (AI for efficiency and productivity)Richards et al. (2009) 2 (green)122009–2022Crop yield (Fenu and Malloci, 2021; Jain and Choudhary, 2022); Boosting farming practices (Alam et al., 2020); Support sustainable digital transformation (Lugonja et al., 2022); Crop disease prediction (Anand et al., 2022; Khan et al., 2022)
Skvortsov (2020) 4 (yellow)82020–2022
Kumar et al. (2015) 5 (purple)62015–2022
C (AI for Logistics and Supply Chain Management)Ting et al. (2014)
Priyadarshi et al. (2019) 
3 (blue)102010–2021Food delivery (Bocewicz et al., 2017); supply chain management (Sitek et al., 2017); inventory management (Basljan et al., 2021; Lao et al., 2010b)
D (AI for supporting decision making process for firms and consumers)Olan et al., 2022
Dora et al. (2022) 
6 (light blue)52017–2022Healthy food choices (Kim et al., 2021; Fiore et al., 2017); Sales forecasting (Dellino et al., 2018)
E (AI for risk mitigation)Camaréna (2020) 7 (light orange)42020–2022Supply chain risk management (Nayal et al., 2022); Agriculture risk management (Vuppalapati, 2022); Addressing agricultural and food industry challenges (Camaréna, 2020; Dadi et al., 2021)
Nayal et al. (2022) 8 (brown)42010–2022
F (AI Marketing aspects)Zhu and Chang (2020) 9 (pink)32020–2022consumer perception of food quality (Zhu and Chang, 2020); price forecasting (Chu et al., 2019); enhancing sales and promoting sustainability (Yang et al., 2022 
Chu et al. (2019) 10 (light pink)22019–2021

Source(s): Authors' elaboration

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