The knowledge trajectory and structure of the supply chain integration: a main path and cluster analysis

Abstract

PurposeSupply chain integration (SCI) dominates supply chain strategy and is receiving increasing academic attention. The purpose of this paper is to provide a systematic review of the knowledge trajectory and structure of the SCI field.Design/methodology/approachBased on 3,533 papers extracted from the Web of Science (WoS), this paper adopts the main path analysis (MPA) method to detect three distinct knowledge development trajectories. Coupling-based clustering is combined with MPA to reveal three critical subfields.FindingsThe findings show that the definition, content and dimensions of SCI lack unified conclusions. The influencing factors and performance consequences of SCI are long-standing research elements. Building theoretical models and integrated systems and applying blockchain technology to improve SCI are the key research contents. The intertwining of collaboration and SCI cannot be ignored, and the green SCI may be a hot topic in the future.Research limitations/implicationsThis study explores knowledge in the SCI field based on the limited literature collected by WoS rather than all published papers. The omissions of some relevant papers and books may exist.Practical implicationsThe study methodology provides a framework for similar studies in the future, and the results help researchers to get a comprehensive picture of the knowledge trajectory and structure of the SCI field.Originality/valueCompared to existing reviews, MPA combines cluster analysis to develop a synthetic framework of the knowledge trajectory and structure in the SCI domain. It contributes to a systematic review of the development of SCI.