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dc.contributor.authorWoodside, Arch
dc.date.accessioned2017-01-30T10:43:22Z
dc.date.available2017-01-30T10:43:22Z
dc.date.created2014-03-09T20:00:39Z
dc.date.issued2013
dc.identifier.citationWoodside, Arch. 2013. 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. 66 (4): pp. 463-472.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/5040
dc.identifier.doi10.1016/j.jbusres.2012.12.021
dc.description.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.

dc.publisherElsevier
dc.titleMoving Beyond Multiple Regression Analysis to Algorithms: Calling for Adoption of a Paradigm Shift from Symmetric to Asymmetric Thinking in Data Analysis and Crafting Theory
dc.typeJournal Article
dcterms.source.volume4
dcterms.source.startPage463
dcterms.source.endPage472
dcterms.source.issn01482963
dcterms.source.titleJournal of Business Research
curtin.department
curtin.accessStatusFulltext not available


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