Overview

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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9783030268206

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​Arch G. Woodside is visiting research professor, Coastal Carolina University, USA; distinguished university professor, Yonsei University, Yonsei Frontier Lab, Seoul, ROK; and honorary professor of marketing, Curtin University, Australia. He is the editor in chief of the Journal of Global Scholars of Marketing Science and editor of Advances in Culture, Tourism, and Hospitality Research. Research articles (co)authored by Dr. Woodside appear in 55 hospitality, management, marketing, psychology, and tourism journals. His book publications include Brand Choice Revealing Customers' Unconscious-Automatic and Strategic Thinking Processes (with Randolph J. Trappey III, Palgrave 2004); The Complexity Turn (ed., Springer 2017); and Incompetency and Competency Training: Improving Executive Skills in Sensemaking, Framing Issues, and Making Choices (with Rouxelle de Villiers and Roger Marshall, Springer 2016).

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