Using Knowledge Graphs and Human-Centric Artificial Intelligence for Reconfigurable Supply Chains: A Research Framework
Benjamin Rolf, Nasser Mebarki, Sebastian Lang, Tobias Reggelin, Olivier Cardin, Harold Mouchère, Alexandre Dolgui
Abstract
Reconfigurable supply chains received increasing interest from academia and industry in the past years, especially because recent events such as the COVID-19 pandemic revealed the vulnerability of present supply chains. Especially the rapid digitalization and the emergence of artificial intelligence in supply chain management create new opportunities for implementing reconfigurable supply chains. In this paper, we propose a concept that uses a knowledge graph and graph-based artificial intelligence to recommend reconfigurations of the supply chain. Due to the importance of these strategic decisions, the concept considers a human-centric approach using a recommender system. The knowledge graph exploits the inherent graph structure of supply chains to create a machine-readable and human-understandable database that also supports reasoning. Finally, we provide three research hypotheses and examine the integration of open-source knowledge graphs and news monitoring tools.