De structuur en het belang van werkwaarden: een vergelijking tussen drie analysetechnieken | Amsterdam University Press Journals Online
Volume 20, Issue 3
  • ISSN: 0921-5077
  • E-ISSN: 1875-7235


Structure and importance of work values: a comparison between three data analysis techniques

Structure and importance of work values: a comparison between three data analysis techniques

J.W.M. van Breukelen, B. Zandbergen & F.M.T.A. Busing, Gedrag & Organisatie, volume 20, September 2007, nr. 3, pp. 272-302

Work values refer to the importance people attribute to the various aspects of a job, such as work content, salary, and colleagues. Generally, in studies on work values two questions are being answered: a) How important are the various aspects of a job for a certain sample of respondents as a whole or for certain subgroups, and b) What is the structure underlying the total set of work values under study? In this study three data analytic techniques are being investigated in analysing the answers of 417 respondents (299 men and 118 women).

The three data analytic methods were principal component analysis (PCA), multidimensional scaling (MDS), and multidimensional unfolding (MDU). Of these three, PCA and MDS give information about the structure of the work values, whereas MDU shows the importance of the various work values in a visual plot. We describe and discuss the pro's and cons of these techniques using the data set mentioned above as an illustration. Our conclusion is that MDU is a welcome addition to both PCA and MDS in studies on work values. Firstly, MDU makes visible the importance of work values for the group respondents as a whole and for subgroups, if needed. At the same time, MDU gives indications about the structure of the work values under study.


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