Moving beyond multiple regression analysis to algorithms: Calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory

Moving beyond multiple regression analysis to algorithms: Calling for adoption of a paradigm... This editorial suggests moving beyond relying on the dominant logic of multiple regression analysis (MRA) toward thinking and using algorithms in advancing and testing theory in accounting, consumer research, finance, management, and marketing. The editorial includes an example of testing an MRA model for fit and predictive validity. The same data used for the MRA is used to conduct a fuzzy-set qualitative comparative analysis (fsQCA). The editorial reviews a number of insights by prominent scholars including Gerd Gigerenzer's treatise that “Scientists' tools are not neutral.” Tools impact thinking and theory crafting as well theory testing. The discussion may be helpful for early career scholars unfamiliar with David C. McClelland's brilliance in data analysis and in introducing business research scholars to fsQCA as an alternative tool for theory development and data analysis. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Business Research Elsevier

Moving beyond multiple regression analysis to algorithms: Calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory

Journal of Business Research, Volume 66 (4) – Apr 1, 2013

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Publisher
Elsevier
Copyright
Copyright © 2013 Elsevier Inc.
ISSN
0148-2963
eISSN
1873-7978
D.O.I.
10.1016/j.jbusres.2012.12.021
Publisher site
See Article on Publisher Site

Abstract

This editorial suggests moving beyond relying on the dominant logic of multiple regression analysis (MRA) toward thinking and using algorithms in advancing and testing theory in accounting, consumer research, finance, management, and marketing. The editorial includes an example of testing an MRA model for fit and predictive validity. The same data used for the MRA is used to conduct a fuzzy-set qualitative comparative analysis (fsQCA). The editorial reviews a number of insights by prominent scholars including Gerd Gigerenzer's treatise that “Scientists' tools are not neutral.” Tools impact thinking and theory crafting as well theory testing. The discussion may be helpful for early career scholars unfamiliar with David C. McClelland's brilliance in data analysis and in introducing business research scholars to fsQCA as an alternative tool for theory development and data analysis.

Journal

Journal of Business ResearchElsevier

Published: Apr 1, 2013

References

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