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 |
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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) |
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