Perceptions on F/OSS Adoption

  • Bulent Ozel
  • Uros Jovanovic
  • Beyza Oba
  • Manon van Leeuwen
Part of the IFIP — The International Federation for Information Processing book series (IFIPAICT, volume 234)


This paper aims to reveal results of a survey run by the tOSSad1 project. The majority of survey variables devised to capture perception of public administrators around Europe regarding the importance they attach to the factors such as F/OSS product quality, availability of support, expertise and documentation, TCO, vendor lock-in, political influence, administrative attitudes, productivity, and training costs, all of which intermingle with financial, technical, legal, and personal issues. The analysis consist of depiction of respondents’ administration profile in terms of their F/OSS usage and adoption, descriptive summary and analyses of factors mentioned above, and statistical inferential analyses of survey items. Some valid statistical tests are conducted to understand, to discuss and to see the extend and significance of any F/OSS adoption generalizations for Europe based on the findings of this particular survey.


Survey Item Political Influence Personal Attitude Provision Contract Administrative Attitude 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. [1]
    Likert, R. (1932). “A Technique for the Measurement of Attitudes” Archives of Psychology 140, 55.Google Scholar
  2. [2]
    Ross, K. C. (1996). Air University Sampling and Surveying Handbook. University Press of the Pacific.Google Scholar
  3. [3]
    Ghosh, R. et al. (2002) “Free/Libre and Open Source Software: Survey and Study. Part 2B: Open Source Software in the Public Sector”Google Scholar
  4. [4]
    Rogers, E. M. (2003). Diffusion of Innovation, Fifth Edition. New York, NY: Free Press.Google Scholar
  5. [5]
    Welch, B. L. (1947). The generalization of “student’s” problem when several different Population variances are involved. Biometrika. Vol. 34, pp. 28–35.MATHGoogle Scholar
  6. [6]
    Best, D. J. and Roberts, D. E. (1975). Algorithm AS 89: The Upper Tail Probabilities of Spearman’s rho. Applied Statistics, 24, 377–379.CrossRefGoogle Scholar
  7. [7]
    Hollander, M. and Wolfe, D. A. (1973). Nonparametric statistical inference. New York: John Wiley & Sons. Pages 185–194.Google Scholar

Copyright information

© International Federation for Information Processing 2007

Authors and Affiliations

  • Bulent Ozel
    • 1
  • Uros Jovanovic
    • 2
  • Beyza Oba
    • 3
  • Manon van Leeuwen
    • 4
  1. 1.Carnegie Mellon UniversityPittsburghUSA
  2. 2.XLABLjubljanaSlovenia
  3. 3.Istanbul Bilgi UniversityIstanbulTurkey
  4. 4.FUNDECYTBadajozSpain

Personalised recommendations