Abstract
Hard laddering is a kind of a semi structured interview in a quantitative means-end chain (MEC) approach that yields a summary implication matrix (SIM). The SIM is based on pairwise associations between attributes (A), consequences (C), and personal values (V), and constitutes a base for developing hierarchical value maps (HVM). A new summary data presentation of the A-C-V triplets that form a summary ladder matrix (SLM) is presented. The structure of the SLM is examined with the use of non-symmetrical correspondence analysis. This approach permits us to identify the dependence structure in the SLM as well as the ladders that contribute most to the system’s inertia.
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Notes
- 1.
NSCA has been performed using Kroonenberg’s Asymtab 2.0c and XLSTAT 2006 packages.
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© 2013 Springer International Publishing Switzerland
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Kaciak, E., Sagan, A. (2013). Non-symmetrical Correspondence Analysis of Abbreviated Hard Laddering Interviews. In: Lausen, B., Van den Poel, D., Ultsch, A. (eds) Algorithms from and for Nature and Life. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-00035-0_46
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DOI: https://doi.org/10.1007/978-3-319-00035-0_46
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