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

Zaitsava, M, Marku, E, Chiara Di Guardo, M and Shahgholian, A Busting the Black Box of Big Data: Dimensions, Effects, and Insights Creation. In: Annual Meeting of the Academy of Management . (80th Annual Meeting of the Academy of Management, August 7-11, 2020, Vancouver, British Columbia, Canada). (Accepted)

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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.

Item Type: Conference or Workshop Item (Paper)
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Divisions: Leadership & Organisational Development (from Sep 19)
Date Deposited: 15 Apr 2020 10:06
Last Modified: 13 Apr 2022 15:17
URI: https://researchonline.ljmu.ac.uk/id/eprint/12730
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