IDEAS home Printed from https://ideas.repec.org/a/inm/orijds/v1y2022i1p23-26.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/ijds.2022.0013
    Download Restriction: no

    File URL: https://libkey.io/10.1287/ijds.2022.0013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Philipp Schwarz & Oliver Schacht & Sven Klaassen & Daniel Grunbaum & Sebastian Imhof & Martin Spindler, 2024. "Management Decisions in Manufacturing using Causal Machine Learning -- To Rework, or not to Rework?," Papers 2406.11308, arXiv.org.
    3. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. William L. Cooper & Tito Homem-de-Mello & Anton J. Kleywegt, 2015. "Learning and Pricing with Models That Do Not Explicitly Incorporate Competition," Operations Research, INFORMS, vol. 63(1), pages 86-103, February.
    2. Soonhui Lee & Tito Homem-de-Mello & Anton Kleywegt, 2012. "Newsvendor-type models with decision-dependent uncertainty," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 76(2), pages 189-221, October.
    3. Adam J. Mersereau & Dan Zhang, 2012. "Markdown Pricing with Unknown Fraction of Strategic Customers," Manufacturing & Service Operations Management, INFORMS, vol. 14(3), pages 355-370, July.
    4. Song‐Hee Kim & Ward Whitt, 2014. "Choosing arrival process models for service systems: Tests of a nonhomogeneous Poisson process," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(1), pages 66-90, February.
    5. Biyu He & Franklin Dexter & Alex Macario & Stefanos Zenios, 2012. "The Timing of Staffing Decisions in Hospital Operating Rooms: Incorporating Workload Heterogeneity into the Newsvendor Problem," Manufacturing & Service Operations Management, INFORMS, vol. 14(1), pages 99-114, January.
    6. Opher Baron & Iman Hajizadeh & Joseph Milner, 2011. "Now Playing: DVD Purchasing for a Multilocation Rental Firm," Manufacturing & Service Operations Management, INFORMS, vol. 13(2), pages 209-226, April.
    7. Omar Besbes & Assaf Zeevi, 2015. "On the (Surprising) Sufficiency of Linear Models for Dynamic Pricing with Demand Learning," Management Science, INFORMS, vol. 61(4), pages 723-739, April.
    8. Gerardo Berbeglia & Agustín Garassino & Gustavo Vulcano, 2022. "A Comparative Empirical Study of Discrete Choice Models in Retail Operations," Management Science, INFORMS, vol. 68(6), pages 4005-4023, June.
    9. Ossi Ylijoki, 2018. "Guidelines for assessing the value of a predictive algorithm: a case study," Journal of Marketing Analytics, Palgrave Macmillan, vol. 6(1), pages 19-26, March.
    10. Naveed Chehrazi & Thomas A. Weber, 2015. "Dynamic Valuation of Delinquent Credit-Card Accounts," Management Science, INFORMS, vol. 61(12), pages 3077-3096, December.
    11. So Yeon Chun & Miguel A. Lejeune, 2020. "Risk-Based Loan Pricing: Portfolio Optimization Approach with Marginal Risk Contribution," Management Science, INFORMS, vol. 66(8), pages 3735-3753, August.
    12. Yi-Hao Kao & Benjamin Van Roy, 2014. "Directed Principal Component Analysis," Operations Research, INFORMS, vol. 62(4), pages 957-972, August.
    13. Felipe Caro & Jérémie Gallien, 2012. "Clearance Pricing Optimization for a Fast-Fashion Retailer," Operations Research, INFORMS, vol. 60(6), pages 1404-1422, December.
    14. Lejeune, Miguel A. & Dehghanian, Payman & Ma, Wenbo, 2024. "Profit-based unit commitment models with price-responsive decision-dependent uncertainty," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1052-1064.
    15. Adam N. Elmachtoub & Paul Grigas, 2022. "Smart “Predict, then Optimize”," Management Science, INFORMS, vol. 68(1), pages 9-26, January.
    16. Aydın Alptekinoğlu & John H. Semple, 2021. "Heteroscedastic Exponomial Choice," Operations Research, INFORMS, vol. 69(3), pages 841-858, May.
    17. Max Biggs & Rim Hariss & Georgia Perakis, 2023. "Constrained optimization of objective functions determined from random forests," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 397-415, February.
    18. den Boer, Arnoud V. & Sierag, Dirk D., 2021. "Decision-based model selection," European Journal of Operational Research, Elsevier, vol. 290(2), pages 671-686.
    19. Michael J. Davis & Yingdong Lu & Mayank Sharma & Mark S. Squillante & Bo Zhang, 2018. "Stochastic Optimization Models for Workforce Planning, Operations, and Risk Management," Service Science, INFORMS, vol. 10(1), pages 40-57, March.
    20. Erkip, Nesim Kohen, 2023. "Can accessing much data reshape the theory? Inventory theory under the challenge of data-driven systems," European Journal of Operational Research, Elsevier, vol. 308(3), pages 949-959.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orijds:v:1:y:2022:i:1:p:23-26. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.