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COVID-19 Pandemic in the New Era of Big Data Analytics: Methodological Innovations and Future Research Directions

Sheng, Jie, Amankwah-Amoah, Joseph, Khan, Zaheer, Wang, Xiaojun (2020) COVID-19 Pandemic in the New Era of Big Data Analytics: Methodological Innovations and Future Research Directions. British Journal of Management, . ISSN 1045-3172. E-ISSN 1467-8551. (doi:10.1111/1467-8551.12441) (KAR id:83010)

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Official URL:
https://doi.org/10.1111/1467-8551.12441

Abstract

Although scholars in management recognise the value of harnessing big data to understand, predict and respond to future events, there remains little or very limited overview of how various analytics techniques can be harnessed to provide the basis for guiding scholars in studying contemporary management topics and global grand challenges raised by the COVID19 pandemic. In this

Methodology Corner, we present a review of the methodological innovations in studying big data analytics and how they can be better utilised to examine contemporary organisational issues. We provide insights on methods in descriptive/diagnostic, predictive, and prescriptive analytics, and how they can be leveraged to study “black swan” events such as the COVID-19 related global crisis and its aftermath’s implications for managers and policymakers.

Item Type: Article
DOI/Identification number: 10.1111/1467-8551.12441
Uncontrolled keywords: Big Data Analytics; Methodological Innovations; COVID-19; Coronavirus
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Divisions > Division of Human and Social Sciences > School of Politics and International Relations
Divisions > Kent Business School - Division > Department of Marketing, Entrepreneurship and International Business
Depositing User: Joseph Amankwah-Amoah
Date Deposited: 18 Sep 2020 14:11 UTC
Last Modified: 05 Nov 2024 12:48 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/83010 (The current URI for this page, for reference purposes)

University of Kent Author Information

Amankwah-Amoah, Joseph.

Creator's ORCID: https://orcid.org/0000-0003-0383-5831
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