This book pulls together robust practices in Partial Least Squares
Structural Equation Modeling (PLS-SEM) from other disciplines and shows
how they can be used in the area of Banking and Finance. In terms of
empirical analysis techniques, Banking and Finance is a conservative
discipline. As such, this book will raise awareness of the potential of
PLS-SEM for application in various contexts. PLS-SEM is a non-parametric
approach designed to maximize explained variance in latent constructs.
Latent constructs are directly unobservable phenomena such as customer
service quality and managerial competence. Explained variance refers to
the extent we can predict, say, customer service quality, by examining
other theoretically related latent constructs such as conduct of staff
and communication skills.
Examples of latent constructs at the microeconomic level include
customer service quality, managerial effectiveness, perception of market
leadership, etc.; macroeconomic-level latent constructs would be found
in contagion of systemic risk from one financial sector to another, herd
behavior among fund managers, risk tolerance in financial markets, etc.
Behavioral Finance is bound to provide a wealth of opportunities for
applying PLS-SEM. The book is designed to expose robust processes in
application of PLS-SEM, including use of various software packages and
codes, including R.
PLS-SEM is already a popular tool in marketing and management
information systems used to explain latent constructs. Until now,
PLS-SEM has not enjoyed a wide acceptance in Banking and Finance. Based
on recent research developments, this book represents the first
collection of PLS-SEM applications in Banking and Finance. This book
will serve as a reference book for those researchers keen on adopting
PLS-SEM to explain latent constructs in Banking and Finance.