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Causal Machine Learning: An Empirical Approach to Supply Chain Management

In: Emerging Technologies in Supply Chains

Author

Listed:
  • Alfredo Roa-Henriquez

    (North Dakota State University (NDSU), College of Business)

  • Juan Fung

    (National Institute of Standards and Technology (NIST), Applied Economics Office (AEO), Engineering Lab)

  • Ruhaimatu Abudu

    (North Dakota State University (NDSU), College of Business)

  • Jennifer Helgeson

    (National Institute of Standards and Technology (NIST), Applied Economics Office (AEO), Engineering Lab)

  • Douglas Thomas

    (National Institute of Standards and Technology (NIST), Applied Economics Office (AEO), Engineering Lab)

Abstract

Over the past two decades, artificial intelligence (AI) has revolutionized industries, with machine learning (ML) at its core. While ML has enhanced supply chain management (SCM) in efficiency and resilience, it often relies on correlations, risking decisions based on spurious relationships. Causal machine learning (CML) offers a solution by focusing on cause-and-effect relationships, promising accuracy and better decision-making. Leading companies like Amazon and Walmart are beginning to harness CML for predictive modeling and AI-driven pricing strategies. Despite its potential, CML in SCM remains nascent, with limited empirical research. This chapter delves into the integration of causal inference in SCM, emphasizing methods that avoid pre-selecting covariates. It reviews foundational causal estimation techniques, surveys CML algorithms, and showcases their application through a simulation. By connecting theoretical advancements with practical implementations, the chapter underscores CML’s transformative potential for SCM research and practice, and outlines future directions for its development.

Suggested Citation

  • Alfredo Roa-Henriquez & Juan Fung & Ruhaimatu Abudu & Jennifer Helgeson & Douglas Thomas, 2026. "Causal Machine Learning: An Empirical Approach to Supply Chain Management," International Series in Operations Research & Management Science, in: Yacob Khojasteh & S.M. Mousavi Jahan Abadi (ed.), Emerging Technologies in Supply Chains, chapter 0, pages 327-358, Springer.
    • Handle: RePEc:spr:isochp:978-3-032-01218-0_13
    DOI: 10.1007/978-3-032-01218-0_13
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