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. With the promise of big data come questions about the analytical value and thus relevance of these data for theory development—including concerns over the context-specific relevance, its reliability and its validity. In this editorial, we address both the collection and handling of big data and the analytical tools provided by data science for management scholars. This primer can guide management scholars who wish to use data science techniques to reach better answers to existing questions or explore completely new research questions.

Big data and data science methods for management research

Lavie, Dovev;
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. With the promise of big data come questions about the analytical value and thus relevance of these data for theory development—including concerns over the context-specific relevance, its reliability and its validity. In this editorial, we address both the collection and handling of big data and the analytical tools provided by data science for management scholars. This primer can guide management scholars who wish to use data science techniques to reach better answers to existing questions or explore completely new research questions.
2016
George, Gerry; Osinga, Ernst C.; Lavie, Dovev; Scott, Brent A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4000565
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