Thinking Big About Big Data
Amy Wax,
Raquel Asencio and
Dorothy R. Carter
Industrial and Organizational Psychology, 2015, vol. 8, issue 4, 545-550
Abstract:
Guzzo, Fink, King, Tonidandel, and Landis (2015) review important issues—privacy, informed consent, and data/data analysis integrity—that are critical logistical considerations in any program of research with human subjects, including studies utilizing big data. Overall, we agree with the cautionary sentiment conveyed throughout the focal article; industrial and organizational (I-O) psychology researchers and practitioners should not assume that big data is a panacea, and many of our established disciplinary approaches for ensuring ethical and accurate research are applicable—or modifiable—in big data contexts. However, we believe that the conversation about big data in I-O psychology is broader than that reviewed by Guzzo et al., and we would like to further elaborate on the focal article. We present this commentary from our perspective as junior scholars entering the field at a critical time—a time when I-O psychology is becoming increasingly intertwined with big data science.
Date: 2015
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.cambridge.org/core/product/identifier/ ... type/journal_article link to article abstract page (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:cup:inorps:v:8:y:2015:i:04:p:545-550_00
Access Statistics for this article
More articles in Industrial and Organizational Psychology from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Bibliographic data for series maintained by Kirk Stebbing ().