Polytechnic University of Valencia Congress, CARMA 2020 - 3rd International Conference on Advanced Research Methods and Analytics

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High order PLS path modeling to evaluate well-being merging traditional and big data: A longitudinal study
Francesca De Battisti, Elena Siletti

Last modified: 11-05-2020


We propose using high order partial least squares path modeling (PLS-PM) to
define a synthetic Italian well-being index merging traditional data,
represented by the Quality of Life index proposed by “Il Sole 24 Ore”, and
information provided by big data, represented by a Subjective Well-being
Index (SWBI) performed extracting moods by Twitter. High order constructs,
which allow to define a more abstract higher-level dimension and its more
concrete lower-order sub-dimensions, have gained wide attention in
applications of PLS-PM, and many contributions in literature proposed their
use to build composite indicators. The aim of the paper is to underline some
critical issues in the use of these models and to suggest the implementation of
a new spurious repeated indicator approach. Furthermore, following some
recommendations proposed on the use of PLS-PM in longitudinal studies, we
compare the situation in 2016 and 2017.

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