IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v22y2020i1d10.1007_s10796-019-09943-9.html
   My bibliography  Save this article

The Productivity Vampires

Author

Listed:
  • John Leslie King

    (University of Michigan)

  • Andrew J. Ehrenberg

    (University of Michigan)

Abstract

The four decade old Productivity Puzzler (sometimes called the Productivity Paradox) asks why the massive investment in information technology (IT) is not accompanied by equally massive productivity improvements. The belief that IT does improve productivity is foiled by faulty measurement, but improved measurement will, at some point, demonstrate conclusively that IT improves productivity. Another view is that “Productivity Vampires” use IT to suck productivity out of organizations through mechanisms such as moving the goalposts, making things not forbidden required, and increasing cognitive load on workers.

Suggested Citation

  • John Leslie King & Andrew J. Ehrenberg, 2020. "The Productivity Vampires," Information Systems Frontiers, Springer, vol. 22(1), pages 11-15, February.
    • Handle: RePEc:spr:infosf:v:22:y:2020:i:1:d:10.1007_s10796-019-09943-9
    DOI: 10.1007/s10796-019-09943-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-019-09943-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-019-09943-9?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "The Economics of Artificial Intelligence: An Agenda," NBER Books, National Bureau of Economic Research, Inc, number agra-1, May.
    2. Robert J. Gordon, 2016. "Perspectives on The Rise and Fall of American Growth," American Economic Review, American Economic Association, vol. 106(5), pages 72-76, May.
    3. Janeway,William H., 2018. "Doing Capitalism in the Innovation Economy," Cambridge Books, Cambridge University Press, number 9781108471275.
    4. David, Paul A, 1990. "The Dynamo and the Computer: An Historical Perspective on the Modern Productivity Paradox," American Economic Review, American Economic Association, vol. 80(2), pages 355-361, May.
    5. Agrawal, Ajay & Gans, Joshua & Goldfarb, Avi (ed.), 2019. "The Economics of Artificial Intelligence," National Bureau of Economic Research Books, University of Chicago Press, number 9780226613338, December.
    6. Hammer, Michael & Champy, James, 1993. "Reengineering the corporation: A manifesto for business revolution," Business Horizons, Elsevier, vol. 36(5), pages 90-91.
    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. R. Ramesh & H. R. Rao, 2020. "ISF Editorial 2020," Information Systems Frontiers, Springer, vol. 22(1), pages 1-9, February.

    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. Yingying Lu & Yixiao Zhou, 2021. "A review on the economics of artificial intelligence," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1045-1072, September.
    2. repec:gdk:wpaper:67 is not listed on IDEAS
    3. Stefan Schweikl & Robert Obermaier, 2020. "Lessons from three decades of IT productivity research: towards a better understanding of IT-induced productivity effects," Management Review Quarterly, Springer, vol. 70(4), pages 461-507, November.
    4. Ferschli, Benjamin & Rehm, Miriam & Schnetzer, Matthias & Zilian, Stella, 2021. "Labor-saving technological change? Sectoral evidence for Germany," ifso working paper series 14, University of Duisburg-Essen, Institute for Socioeconomics (ifso).
    5. Björn Döhring & Atanas Hristov & Christoph Maier & Werner Roeger & Anna Thum-Thysen, 2021. "COVID-19 acceleration in digitalisation, aggregate productivity growth and the functional income distribution," International Economics and Economic Policy, Springer, vol. 18(3), pages 571-604, July.
    6. Colin Wessendorf & Alexander Kopka & Dirk Fornahl, 2021. "The impact of the six European Key Enabling Technologies (KETs) on regional knowledge creation," Papers in Evolutionary Economic Geography (PEEG) 2127, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Sep 2021.
    7. Oliver Falck & Johannes Koenen, 2020. "Rohstoff „Daten“: Volkswirtschaflicher Nutzen von Datenbereitstellung – eine Bestandsaufnahme," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 113.
    8. Christian Rammer & Gastón P Fernández & Dirk Czarnitzki, 2021. "Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data," Working Papers of Department of Economics, Leuven 674605, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    9. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
    10. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    11. DUERNECKER Georg & SANCHEZ MARTINEZ Miguel, 2021. "Structural change and productivity growth in the European Union: Past, present and future," JRC Working Papers on Territorial Modelling and Analysis 2021-09, Joint Research Centre.
    12. Ekaterina Prytkova, 2021. "ICT's Wide Web: a System-Level Analysis of ICT's Industrial Diffusion with Algorithmic Links," Jena Economics Research Papers 2021-005, Friedrich-Schiller-University Jena.
    13. Combes, Pierre-Philippe & Gobillon, Laurent & Zylberberg, Yanos, 2022. "Urban economics in a historical perspective: Recovering data with machine learning," Regional Science and Urban Economics, Elsevier, vol. 94(C).
    14. Thomsen, Stephan L, 2018. "Die Rolle der Computerisierung und Digitalisierung für Beschäftigung und Einkommen," Hannover Economic Papers (HEP) dp-645, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    15. Vasiliki Koniakou, 2023. "From the “rush to ethics” to the “race for governance” in Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(1), pages 71-102, February.
    16. Andrea Szalavetz, 2019. "Artificial Intelligence-Based Development Strategy in Dependent Market Economies - Any Room amidst Big Power Rivalry?," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 40-54.
    17. Gries, Thomas & Naudé, Wim, 2022. "Modelling artificial intelligence in economics," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 56, pages 1-12.
    18. Fossen, Frank M. & Sorgner, Alina, 2021. "Digitalization of work and entry into entrepreneurship," Journal of Business Research, Elsevier, vol. 125(C), pages 548-563.
    19. Mario Benassi & Elena Grinza & Francesco Rentocchini & Laura Rondi, 2022. "Patenting in 4IR technologies and firm performance [Robots and jobs: evidence from US labor markets]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 31(1), pages 112-136.
    20. Charles M. A. Clark & Aleksandr V. Gevorkyan, 2020. "Artificial Intelligence and Human Flourishing," American Journal of Economics and Sociology, Wiley Blackwell, vol. 79(4), pages 1307-1344, September.
    21. Nicholas Crafts, 2022. "Slow real wage growth during the Industrial Revolution: productivity paradox or pro-rich growth? [Engels’ pause: technical change, capital accumulation, and inequality in the British industrial rev," Oxford Economic Papers, Oxford University Press, vol. 74(1), pages 1-13.

    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:spr:infosf:v:22:y:2020:i:1:d:10.1007_s10796-019-09943-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.