This volume advocates accurate case outcome prediction that does
not rely on symmetric modeling. To that end, it provides theory
construction and testing applications in several sub-disciplines of
business and the social sciences to illustrate how to move away
from symmetric theory construction. Each chapter constructs case
outcome theory and includes empirical analysis of outcomes. Chapter
1 provides a foundation of symmetric variable
directional-relationship theory construction and null hypothesis
significance testing versus asymmetric case outcome theory
construction and somewhat precise outcome testing, while Chapters
2-6 investigate these principles through a range of applications.
This volume will be very useful to researchers and professionals in
manufacturing, service, consulting, management, marketing,
organizational studies, and more. It will also be an excellent
resource for advanced statistics students in building and testing
case outcome models. Data sets are included so that readers can
replicate findings presented in each chapter, and grow to present
and test additional theories.
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