New Strategies for Data Analysis by Dimension Reduction, of Resource Combinations and Benchmarking
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Beschreibung
This cumulative dissertation comprises three research articles.
This cumulative dissertation comprises three research articles. All
articles have one thing in common: The attempt to model and empirically
analyse complex interrelations between (aggregates of) not
directly measurable constructs, traditional approaches can not cope
with. While the first two articles use Partial-Least-Squares Pathmodeling
(PLS-PM) as statistical tool, the third paper is carried out with
Fuzzy Set Qualitative Comparative Analysis (fsQCA). The applications
are quite different and reflect the universal applicability and flexibility
these approaches offer. Topics vary from developing a modelbased,
data-driven benchmark (Chapter 1), over reducing dimensions
of variables and testing hypothesis on the relation of these latent constructs
(Chapter 2), to identifying combinations of resources leading
to a successful outcome (Chapter 3).
Autor*in
Frank Pelzel
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