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 construc...
Table of Content
Matching case identification hypotheses and case-level data analysis.- Constructing algorithms for forecasting high (low) project management performance.- Accu...
About the author
Arch G. Woodside is visiting research professor, Coastal Carolina University, USA; distinguished university professor, Yonsei University, Yonsei Frontier Lab, S...