IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-02303982.html
   My bibliography  Save this paper

La quantification des données qualitatives : intérêts et difficultés en sciences de gestion

Author

Listed:
  • Isabelle Royer

    (Laboratoire de Recherche Magellan - UJML - Université Jean Moulin - Lyon 3 - Université de Lyon - Institut d'Administration des Entreprises (IAE) - Lyon)

  • Lionel Garreau

    (DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

  • Thomas Roulet

    (Judge Business School - CAM - University of Cambridge [UK])

Abstract

Dans cet article introductif du numéro spécial sur la quantification des données qualitatives, nous présentons l'intérêt et l'ampleur du sujet pour le champ des sciences de gestion. Quantifier implique l'association de valeurs numériques – via la mesure ou le comptage – à des jeux de données pour lesquels ces valeurs ne sont pas évidentes – comme par exemple du texte ou des images. En premier lieu nous explorons les raisons qui justifient la quantification des données qualitatives. La transparence et la possibilité de comparer les jeux de données de manière formelle figurent parmi les principaux avantages de la quantification. La crédibilité et la facilité de communication en sont d'autres. Nous discutons ensuite des précautions à prendre. En particulier, il est important de sélectionner avec attention le matériau à quantifier, et de réfléchir à la production des valeurs numériques. Enfin nous notons la responsabilité du chercheur et le recul nécessaire pour une quantification rigoureuse.

Suggested Citation

  • Isabelle Royer & Lionel Garreau & Thomas Roulet, 2019. "La quantification des données qualitatives : intérêts et difficultés en sciences de gestion," Post-Print hal-02303982, HAL.
  • Handle: RePEc:hal:journl:hal-02303982
    DOI: 10.4000/fcs.3312
    Note: View the original document on HAL open archive server: https://hal.science/hal-02303982
    as

    Download full text from publisher

    File URL: https://hal.science/hal-02303982/document
    Download Restriction: no

    File URL: https://libkey.io/10.4000/fcs.3312?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. Picault, Matthieu & Renault, Thomas, 2017. "Words are not all created equal: A new measure of ECB communication," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 136-156.
    2. Renault, Thomas, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 25-40.
    3. Frédérique Déjean & Jean-Pascal Gond & Bernard Leca, 2004. "Measuring the unmeasured : An institutional entrepreneur strategy in an emerging industry," Post-Print halshs-00151270, HAL.
    4. Thomas Renault, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205113, HAL.
    5. Isabelle Royer, 2011. "La responsabilité des chercheurs en gestion," Post-Print halshs-00726123, HAL.
    6. Thomas Roulet, 2015. "“What Good is Wall Street?” Institutional Contradiction and the Diffusion of the Stigma over the Finance Industry," Journal of Business Ethics, Springer, vol. 130(2), pages 389-402, August.
    7. Yvonne Giordano, 2003. "Conduire un projet de recherche. Une perspective qualitative," Post-Print halshs-00440011, HAL.
    8. repec:dau:papers:123456789/13762 is not listed on IDEAS
    9. Rodrigo Bandeira-De-Mello & Lionel Garreau, 2011. "L'utilisation d'Atlas.ti pour améliorer les recherches dans le cadre de la Méthode de la Théorisation Enracinée (MTE) : panacée ou mirage?," Post-Print hal-00638508, HAL.
    10. Andrew Abbott, 1990. "A Primer on Sequence Methods," Organization Science, INFORMS, vol. 1(4), pages 375-392, November.
    11. repec:dau:papers:123456789/4803 is not listed on IDEAS
    12. Matthieu Picault & Thomas Renault, 2017. "Words are not all created equal: A new measure of ECB communication," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205121, HAL.
    13. repec:dau:papers:123456789/1478 is not listed on IDEAS
    14. Eva Boxenbaum & Candace Jones & Renate E. Meyer & Silviya Svejenova, 2018. "Towards an articulation of the material and visual turn in organization studies," Post-Print hal-01802981, HAL.
    15. Florence Allard-Poesi, 2003. "Coder les données," Post-Print hal-01495063, HAL.
    16. Ababacar Mbengue & Isabelle Vandangeon-Derumez & Lionel Garreau, 2014. "Construire un modèle," Post-Print halshs-01026208, HAL.
    Full references (including those not matched with items on IDEAS)

    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. Jonne Lehtimäki & Marianne Palmu, 2022. "Who Should You Listen to in a Crisis? Differences in Communication of Central Bank Policymakers," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 11(3), pages 33-57.
    2. Shen, Yiran & Liu, Chang & Sun, Xiaolei & Guo, Kun, 2023. "Investor sentiment and the Chinese new energy stock market: A risk–return perspective," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 395-408.
    3. repec:hal:spmain:info:hdl:2441/3mgbd73vkp9f9oje7utooe7vpg is not listed on IDEAS
    4. Beckmann, Joscha & Czudaj, Robert L., 2023. "Perceived monetary policy uncertainty," Journal of International Money and Finance, Elsevier, vol. 130(C).
    5. Thomas Renault, 2020. "Sentiment analysis and machine learning in finance: a comparison of methods and models on one million messages," Digital Finance, Springer, vol. 2(1), pages 1-13, September.
    6. Gianluca Anese & Marco Corazza & Michele Costola & Loriana Pelizzon, 2023. "Impact of public news sentiment on stock market index return and volatility," Computational Management Science, Springer, vol. 20(1), pages 1-36, December.
    7. Martin Baumgaertner & Johannes Zahner, 2021. "Whatever it takes to understand a central banker - Embedding their words using neural networks," MAGKS Papers on Economics 202130, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    8. Paweł Baranowski & Wirginia Doryń & Tomasz Łyziak & Ewa Stanisławska, 2020. "Words and deeds in managing expectations: empirical evidence on an inflation targeting economy," NBP Working Papers 326, Narodowy Bank Polski.
    9. Béatrice BOULU-RESHEF & Catherine BRUNEAU & Maxime NICOLAS & Thomas RENAULT, 2022. "An Experimental Analysis of Investor Sentiment," LEO Working Papers / DR LEO 2940, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    10. Geng, Yuedan & Ye, Qiang & Jin, Yu & Shi, Wen, 2022. "Crowd wisdom and internet searches: What happens when investors search for stocks?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    11. Albina Latifi & Viktoriia Naboka-Krell & Peter Tillmann & Peter Winker, 2023. "Fiscal Policy in the Bundestag: Textual Analysis and Macroeconomic Effects," MAGKS Papers on Economics 202307, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    12. Seok, Sangik & Cho, Hoon & Ryu, Doojin, 2022. "Scheduled macroeconomic news announcements and intraday market sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    13. Mikael Apel & Marianna Blix Grimaldi & Isaiah Hull, 2022. "How Much Information Do Monetary Policy Committees Disclose? Evidence from the FOMC's Minutes and Transcripts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1459-1490, August.
    14. Youngjoon Lee & Soohyon Kim & Ki Young Park, 2018. "Deciphering Monetary Policy Committee Minutes with Text Mining Approach: A Case of South Korea," Working papers 2018rwp-132, Yonsei University, Yonsei Economics Research Institute.
    15. Chen, Haozhi & Zhang, Yue, 2023. "Research on the effect of firm-specific investor sentiment on the idiosyncratic volatility anomaly: Evidence from the Chinese market," Pacific-Basin Finance Journal, Elsevier, vol. 81(C).
    16. Gaoshan Wang & Guangjin Yu & Xiaohong Shen, 2020. "The Effect of Online Investor Sentiment on Stock Movements: An LSTM Approach," Complexity, Hindawi, vol. 2020, pages 1-11, December.
    17. Baranowski, Paweł & Doryń, Wirginia & Łyziak, Tomasz & Stanisławska, Ewa, 2021. "Words and deeds in managing expectations: Empirical evidence from an inflation targeting economy," Economic Modelling, Elsevier, vol. 95(C), pages 49-67.
    18. Paul Hubert & Fabien Labondance, 2019. "Central bank tone and the dispersion of views within monetary policy committees," Sciences Po publications 2019 – 08, Sciences Po.
    19. Picault, Matthieu & Pinter, Julien & Renault, Thomas, 2022. "Media sentiment on monetary policy: Determinants and relevance for inflation expectations," Journal of International Money and Finance, Elsevier, vol. 124(C).
    20. Smita Roy Trivedi, 2024. "Into the Unknown: Uncertainty, Foreboding and Financial Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(1), pages 1-23, March.
    21. Tillmann, Peter, 2021. "Financial markets and dissent in the ECB’s Governing Council," European Economic Review, Elsevier, vol. 139(C).

    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:hal:journl:hal-02303982. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.