Replication data and code for "AI-Driven Decision Making in Supply Chain Operations: A Phase Space Framework for Organizational Resilience and Strategic Navigation" — Scopus bibliometric corpus and keyword co-occurrence analysis

Replication package for the bibliometric component of a manuscript proposing the Phase Space Strategic Framework (PSSF) for AI-driven supply chain decision-making and organizational resilience. Version 2.0 (revision). Main changes from version 1.0: (1) keyword clustering now uses consensus clustering (1,000 Louvain runs with randomised node and edge order; medoid partition reported, 3 clusters, mean ARI = 0.57), triangulated with the Leiden algorithm (mean ARI with the medoid = 0.63), replacing the single Louvain run of v1, which was sensitive to node ordering; (2) the synonym map has been extended; (3) a de-duplication error affecting records without a DOI has been corrected (Stage 3: 507 records; final corpus unchanged at 371 documents); (4) new outputs have been added: keyword centrality and participation coefficients, keyword emergence by period, document lists by cluster, the network figure, and a content-analysis coding sheet. The original v1 files are kept in the folder v1_original. See README.md and CHANGELOG.md for full details. Search protocol (Scopus, TITLE-ABS-KEY, executed 2026-08-07): ("artificial intelligence" OR "machine learning" OR "AI") AND ("supply chain" OR "supply chain management") AND ("resilience" OR "resilient" OR "disruption" OR "risk management") AND ("decision making" OR "decision support" OR "strategic decision"). Filters: Document type = Article/Review; Language = English; Years = 2019–2026. This dataset accompanies a manuscript submitted to the Special Issue "Emerging Perspectives on Technology Enabled Global Operations and Supply Chain Resilience", Journal of Global Operations and Strategic Sourcing (Emerald).