Improving business processes provides companies with advantages in terms of efficiency and profitability, as well as competitiveness against other companies in the market. Companies that integrate business processes with enterprise resource planning (ERP) systems into digital platforms also have the opportunity to strengthen their weaknesses by recognizing disruptions and bottlenecks in inefficient business processes thanks to this digital transformation. Descriptive and bibliometric analyses were performed in this study for a systematic evaluation of studies on artificial intelligence (AI) in the ERP literature. The studies in which the keywords determined from the AI literature were firstly used together with ERP were investigated from the Scopus database. 837 publications meeting the search criteria were reached and a descriptive analysis of these publications was presented. Then, bibliometric analysis was performed using common author, common citation, and common keyword analysis methods for 296 publications in the article type. Tsinghua University and Obuda University have the most publications according to the results. The most commonly used AI keywords in the ERP studies were “genetic algorithm”, “fuzzy logic”, and “machine learning”. This study aims to guide future studies by providing a systematic and new perspective to researchers and experts working on ERP-AI.
Aktürk, C. (2021), "Artifıcial Intelligence in Enterprise Resource Planning Systems: A Bibliometric Study", Journal of International Logistics and Trade, Vol. 19 No. 2, pp. 69-82. https://doi.org/10.24006/jilt.2021.19.2.069
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Copyright © 2021 Jungseok Research Institute of International Logistics and Trade
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