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. Contents:- scopus_corpus_371.csv: Final screened corpus (N=371 documents), Scopus, search executed 2026-08-07- prisma_pipeline.py: Document-type restriction, de-duplication, and title/abstract screening script- keyword_cooccurrence.py: Keyword co-occurrence network construction and Louvain community detection (seed=42, min_freq=5, resolution=1.0)- cooccurrence_results.json: Cluster assignments and keyword frequencies- keyword_network.gexf: Full network file (importable in Gephi/Cytoscape for independent verification) 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).