Predictive analytics: The power to predict who will click, buy, lie, or die

By Richard Boire. 2013

396 citations recorded by the source corpus.

Subfields: Management Information Systems

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In Management Information Systems

Citations in the corpus

"Wrong side of the tracks": Big Data and Protected Categories (2014, background): “ the world with in unexpected accuracy. Over and above advances reported in the peer-reviewed literature, recent popular accounts provide a sense for the growing use of these tools beyond the academy [12, 18], and their use seems likely to accelerate in both scale (number of domains) and scope (rang”
Active Fairness in Algorithmic Decision Making (2018, background): “ng systems (ADMs) have become increasingly ubiquitous—e.g., in criminal justice [17], medical diagnosis and treatment [16], human resource management [5], social work [10], credit [13], and insurance [24]—there is widespread concern about how these can deepen social inequalities and systematize disc”
Geospatial Big Data: Challenges and Opportunities (2015, background): “The executives at Walmart decided to adopt one of big data technologies—predictive analytics [27].”
Online Social Influence and the Convergence of Mass and Interpersonal Communication (2017, methodology): “Additionally, the use of predictive analytics, whereby data mining techniques are used to forecast individual behaviors, are now routinely invoked to harvest individuals’ data and exploit specific user characteristics, often by using algorithmically derived mass appeals to attract individuals on a s”
Internet of Things, Real-Time Decision Making, and Artificial Intelligence (2017, background): “…and because of a hedging assumption, does not depend on the expected return of the underlying share) that won them a Nobel Prize in 1997; Siegel [18] is convinced that Big Data analytics is driving millions of decisions, determining who to call, mail, investigate, incarcerate, match with a…”
Digitization capability and the digitalization of business models in business-to-business firms: Past, present, and future (2020, background): “…amount of attention, as illustrated in the widespread discussions surrounding data scientists (e.g., Davenport & Patil, 2012), predictive and prescriptive analytics (e.g., Bertsimas, O'Hair, & Pulleyblank, 2016; Siegel, 2013), and artificial intelligence (e.g., Brynjolfsson & McAfee, 2014).”
The Threat of Algocracy: Reality, Resistance and Accommodation (2016, background): “Any new algorithm is likely to be grafted on top of others, collectively authored by teams of coders using pre-existing coded architectures and then woven into increasingly complex algorithmic ecosystems (Seaver 2013; Kitchin 2014a, 2014b).”