Abstract
Management Science (MS) is the broad interdisciplinary study of problem-solving and decision-making in human organizations. Scientific research is conducted to improve an organization’s rational management decisions by determining optimal or near-optimal solutions to complex decision problems. With the focus on MS, this paper presents a brief description of the sixteenth ICMSEM proceedings Volume I. First, the key MS research areas are reviewed; dynamic analysis, machine learning, and supply chain management; after which the most prominent concerns in the sixteenth ICMSEM proceedings Volume I are discussed. Finally, CiteSpace is used to analyze the MS developments in the future. Overall, the ICMSEM continues to provide an invaluable platform for academic interaction and communication to ensure future Management Science and Engineering Management (MSEM) innovations.
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The author gratefully acknowledges Jiaxin Jiang and Min Tang’s efforts on the paper collection and classification, Keru Fan and Liqing Yao’s efforts on data collation and analysis, and Xingyu Chen and Zongze Wu’s efforts on the chart drawing.
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Xu, J. (2022). Advancement of Dynamic Analysis, Machine Learning, and Supply Chain Management Based on the Sixteenth ICMSEM Proceedings. In: Xu, J., Altiparmak, F., Hassan, M.H.A., García Márquez, F.P., Hajiyev, A. (eds) Proceedings of the Sixteenth International Conference on Management Science and Engineering Management – Volume 1. ICMSEM 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 144. Springer, Cham. https://doi.org/10.1007/978-3-031-10388-9_1
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DOI: https://doi.org/10.1007/978-3-031-10388-9_1
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