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The Rise and Fall of an Online Project. Is Bureaucracy Killing Efficiency in Open Knowledge Production?

Author

Listed:
  • Nicolas Jullien

    (LUSSI - Département Logique des Usages, Sciences sociales et Sciences de l'Information - UEB - Université européenne de Bretagne - European University of Brittany - Télécom Bretagne - IMT - Institut Mines-Télécom [Paris], ICI - Laboratoire Information, Coordination, Incitations - UEB - Université européenne de Bretagne - European University of Brittany - UBO - Université de Brest - Télécom Bretagne - IMT - Institut Mines-Télécom [Paris] - IBSHS - Institut Brestois des Sciences de l'Homme et de la Société - UBO - Université de Brest, MARSOUIN - Môle Armoricain de Recherche sur la SOciété de l'information et des usages d'INternet - UR - Université de Rennes - UEB - Université européenne de Bretagne - European University of Brittany - UBS - Université de Bretagne Sud - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - UBO - Université de Brest - Télécom Bretagne - IMT - Institut Mines-Télécom [Paris] - UR2 - Université de Rennes 2)

  • Kevin Crowston

    (iSchool - Syracuse University School of Information Studies)

  • Felipe Ortega

    (URJC - Universidad Rey Juan Carlos [Madrid])

Abstract

In this article we ask whether it is possible to evaluate the efficiency of an online knowledge production project to determine its position in the life-cycle of projects and to identify factors that affect efficiency. To assess efficiency, we used the Data Envelopment Analysis (DEA) modelling methodology, applying it to data from Wikipedia, studying more than 30 Wikipedia language projects over three years. We showed that if the main Wikipedia projects were indeed less efficient that smaller ones, corrected by the decreasing return to scale phenomenon, they were quite as efficient as the other projects.

Suggested Citation

  • Nicolas Jullien & Kevin Crowston & Felipe Ortega, 2015. "The Rise and Fall of an Online Project. Is Bureaucracy Killing Efficiency in Open Knowledge Production?," Post-Print hal-01192596, HAL.
    • Handle: RePEc:hal:journl:hal-01192596
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    Cited by:

    1. Grace Gimon Betancourt & Armando Segnini & Carlos Trabuco & Amira Rezgui & Nicolas Jullien, 2016. "Mining team characteristics to predict Wikipedia article quality," Post-Print hal-01354368, HAL.

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