Artifıcial Intelligence in Enterprise Resource Planning Systems: A Bibliometric Study
0
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
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.
Abstract
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.
참고문헌 (25)
- Al-Mashari, M., "Enterprise resource planning : A taxonomy of critical factors", European Journal of Operational Research, 146, pp.352~364 (2003)
- Ardito, L., "A bibliometric analysis of research on big data analytics for business and management", Management Decision, 57, pp.1993~2009 (2019)
- Azevedo, P. S., "Success factors for using ERP(enterprise resource planning)systems to improve competitiveness in the hospitality industry", Tourism & Management Studies, 10, pp.165~168 (2014)
- Bahssas, D. M., "Enterprise resource planning(ERP)systems : Design, trends and deployment", The International Technology Management Review, 5, pp.72~81 (2015)
- Cadersaib, B. Z., "A review of skills relevant to enterprise resource planning implementation projects", Proceedings of the 2020 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS) (2020)
- Ç iftçi, Ö, "An artificial intelligence application at the alternative supplier medium for the selection of supplier", Electronic Letters on Science and Engineering, 1, pp.1~6 (2005)
- Cong, W., "Heterogeneity of industrial development and evolution of cleaner production : Bibliometric analysis based on JCLP", Journal of Cleaner Production, 212, pp.822~836 (2019)
- Gibson, N., "Enterprise resource planning: A business approach to systems development", Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences (1999)
- Gür, Y. E., "Yapay zekâ alanindaki gelişmelerin insan kaynakları yönetimine etkisi", Fırat Üniversitesi Uluslararası İktisadi ve İdari Bilimler Dergisi, 3, pp.137~158 (2019)
- Inacio, H., "Analysis of the research on internal control in enterprise resource planning systems", Proceedings of the 2018 13th Iberian Conference on Information Systems and Technologies (CISTI) (2018)
- Ivanov, D., "Researchers’ perspectives on Industry 4. 0 : Multi-disciplinary analysis and opportunities for operations management", International Journal of Production Research, 59, pp.2055~2078 (2020)
- Janssens, G., "An expert-based taxonomy of ERP implementation activities", Journal of Computer Information Systems, 60, pp.175~183 (2020)
- Korkmaz, G., "Yapay zekâ yöntemleriyle sınıflandırma ve finans sektöründe bir uygulama", Akademik Yaklaşımlar Dergisi, 11(2), pp.91~109 (2020)
- Lizano-Mora, H., "The evolution of business process management : A bibliometric analysis", IEEE Access, 9, pp.51088~51105 (2021)
- Mladenova, T., "Open-source ERP systems : An overview", Proceedings of the 2020 International Conference Automatics and Informatics (ICAI) (2020)
- Mourao, P. R., "Forest entrepreneurship : A bibliometric analysis and a discussion about the co-authorship networks of an emerging scientific field", Journal of Cleaner Production, 256, pp.120413~ (2020)
- Nabiyev, V. V., "Yapay Zeka: Insan-Bilgisayar Etkileşimi" (2012), Seçkin Yayıncılık
- Ö ztürk, K., "Yapay sinir ağları ve yapay zekâ’ya genel bir bakış", Takvim-i Vekayi, 6, pp.25~36 (2018)
- Pirim, A. G. H., "Yapay zeka", Journal of Yaşar University, 1, pp.81~93 (2006)
- Prashar, A., "A bibliometric and content analysis of sustainable development in small and medium-sized enterprises", Journal of Cleaner Production, 245, pp.118665~ (2020)
- Pulat, M., "Gezgin satıcı probleminin genetik algoritmalar kullanarak çözümünde çaprazlama operatörlerinin örnek olaylar bazlı incelenmesi", İzmir İktisat Dergisi, 34, pp.225~243 (2019)
- Schlichter, B. R., "A comprehensive literature review of the ERP research field over a decade", Journal of Enterprise Information Management, 23, pp.486~520 (2010)
- Tektaş, M., "Yapay zekâ tekniklerinin trafik kontrolünde kullanilmasiüzerine bir inceleme" (2002), Uluslararası Trafik ve Yol Güvenliği Kongresi
- Türk, E., "Yapay sinir ağları ile talep tahmini yapma : Beyaz eşyaüretim planlamasıörneği", İstanbul Sabahattin Zaim Ü niversitesi Fen Bilimleri Enstitüsü Dergisi, 1, pp.30~37 (2019)
- Ünver, M., "Medikal endüstride yapay zeka ve uzman sistemlerin sürekli iyileştirmeye etkisi", Proceedings of the 8th International Symposium on Innovative Technologies in Engineering and Science (ISITES2020) (2020)