The partial least squares (PLS) method has increasingly been used in a
variety of fields of research, particularly in the context of PLS-based
structural equation modeling (SEM). As an emerging method, its users
often face challenges in successfully publishing PLS-based research,
hence the theme of this year's Symposium.
The focus of this Symposium is on the application of PLS-based methods,
from a multidisciplinary perspective. As such, we encourage empirical
submissions employing PLS as the main data analysis approach from a
diverse range of disciplines. We welcome
submissions from beginner, intermediate and advanced PLS users.
Submissions with practical
examples of research issues and solutions are particularly welcome,
whether they are based on data from actual studies or Monte Carlo
simulations. We
envision presentations in which both presenters and audience
collaboratively learn how to successfully address PLS-based research
issues.
Target PLS-based research issues include, but are not restricted to, the
following: minimum sample size requirements, data and instrument
validation criteria, collinearity, moderating effects, indirect and
total effects, nonlinear effects, formative versus reflective schemes, resampling techniques and their use,
plotting results, expressing results in standardized and unstandardized
terms, and causality assessment.
There are great opportunities and challenges associated with
employing PLS methods in data analytics applications,
including applications involving “big data” issues.
This applies to many fields, such as business analytics,
where PLS methods and software tools hold great promise. We also welcome
submissions that address such opportunities and challenges.
http://plsas.net/
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