Publication Type
Editorial
Version
acceptedVersion
Publication Date
10-2016
Abstract
The recent advent of remote sensing, mobile technologies, novel transaction systems, and high performance computing offers opportunities to understand trends, behaviors, and actions in a manner that has not been previously possible. Researchers can thus leverage 'big data' that are generated from a plurality of sources including mobile transactions, wearable technologies, social media, ambient networks, and business transactions. An earlier AMJ editorial explored the potential implications for data science in management research and highlighted questions for management scholarship, and the attendant challenges of data sharing and privacy (George, Haas & Pentland, 2014). This nascent field is evolving rapidly and at a speed that leaves scholars and practitioners alike attempting to make sense of the emergent opportunities that big data holds. With the promise of big data come questions about the analytical value and thus relevance of this data for theory development -- including concerns over the context-specific relevance, its reliability and its validity.
Discipline
Management Sciences and Quantitative Methods | Strategic Management Policy
Research Areas
Marketing; Strategy and Organisation
Publication
Academy of Management Journal
Volume
59
Issue
5
First Page
1493
Last Page
1507
ISSN
0001-4273
Identifier
10.5465/amj.2016.4005
Publisher
Academy of Management
Citation
GEORGE, Gerard; Ernst C. OSINGA; LAVIE, Dovev; and SCOTT, Brent A..
Big data and data science methods for management research: From the Editors. (2016). Academy of Management Journal. 59, (5), 1493-1507.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/4964
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.5465/amj.2016.4005
Included in
Management Sciences and Quantitative Methods Commons, Strategic Management Policy Commons