Busting the Black Box of Big Data: Dimensions, Effects, and Insights Creation

M Zaitsava, E Marku, M Chiara Di Guardo, Azar Shahgholian

Research output: Contribution to journalMeeting Abstractpeer-review

Abstract

Based on the case study of the large-scale pilot project run in four European cities, the paper aims at opening up the black box of Big Data dimensions taking a close look at their characteristics, interactions, and effects that influence the ability of Big Data to create different types of insights for enhanced decision-making. Existing literature has mostly focused on the Big Data Analytics role in the valuable and actionable insights creation, neglecting the better understanding of the underlying mechanism of different insights creation at the level of Big Data. To take the challenge, we built a conceptual framework that explains the underlying mechanism of different types of Big Data insights creation based on what we called proliferation and additive effects. In this vein, our study contributes to the strategic management literature by uncovering and busting the black box of Data for enhanced competitive performance; it also adds new insight to technology innovation studies by disentangling the Big Data fine-grained subdimension, their distinct effects, and insight creation. Finally, several managerial implications are highlighted and further discussed."
Original languageEnglish
JournalAcademy of Management Proceedings
Volume2020
Issue number1
Early online date29 Jun 2020
DOIs
Publication statusPublished - 1 Aug 2020

Keywords

  • AOM Annual Meeting Proceedings 2020

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