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Rejoinder to “Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters”

Author

Listed:
  • Carlos Fernández-Loría

    (HKUST Business School, Hong Kong University of Science and Technology, Hong Kong)

  • Foster Provost

    (NYU Stern School of Business, New York University, New York, New York 10012; Compass Inc., New York, New York 10011)

Abstract

We thank Dean Eckles, Edward McFowland III, and Uri Shalit for their valuable commentaries ( Eckles 2022 , McFowland 2022 , Shalit 2022 ). This note takes a closer look at several of the main points they raised, especially those related to future research on data science for businesses and other organizations.

Suggested Citation

  • Carlos Fernández-Loría & Foster Provost, 2022. "Rejoinder to “Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters”," INFORMS Joural on Data Science, INFORMS, vol. 1(1), pages 23-26, April.
    • Handle: RePEc:inm:orijds:v:1:y:2022:i:1:p:23-26
    DOI: 10.1287/ijds.2022.0013
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    References listed on IDEAS

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    1. Rick Lawrence & Claudia Perlich & Saharon Rosset & Ildar Khabibrakhmanov & Shilpa Mahatma & Sholom Weiss & Matt Callahan & Matt Collins & Alexey Ershov & Shiva Kumar, 2010. "Operations Research Improves Sales Force Productivity at IBM," Interfaces, INFORMS, vol. 40(1), pages 33-46, February.
    2. Omar Besbes & Robert Phillips & Assaf Zeevi, 2010. "Testing the Validity of a Demand Model: An Operations Perspective," Manufacturing & Service Operations Management, INFORMS, vol. 12(1), pages 162-183, June.
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    Cited by:

    1. Yu Xia & Ali Arian & Sriram Narayanamoorthy & Joshua Mabry, 2023. "RetailSynth: Synthetic Data Generation for Retail AI Systems Evaluation," Papers 2312.14095, arXiv.org.
    2. Margrét Vilborg Bjarnadóttir & Louiqa Raschid, 2023. "Modeling Financial Products and Their Supply Chains," INFORMS Joural on Data Science, INFORMS, vol. 2(2), pages 138-160, October.

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