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Economic Shocks of Covid-19: Can Big Data Analytics Help Connect the Dots

Hakimah Yaacob, Qaisar Ali*, Nur Anissa Sarbini, Abdul Nasir Rani, Zaki Zaini, Nurul Nabilah Ali, Norliza Mahalle

Faculty of Islamic Economics and Finance (FEKIM), Universiti Islam Sultan Sharif Ali, BE1310, Brunei Darussalam

* Corresponding Author: Qaisar Ali. Email:

(This article belongs to this Special Issue: Soft Computing Technologies for COVID 19 Assessment, Analysis and Control)

Intelligent Automation & Soft Computing 2021, 27(3), 653-668.


Since the beginning of the Covid-19 pandemic, big data analytics (BDA) remains a signatory medium in the battle against it. Governments and policymakers alike are yet to leverage on this scalable technology in an attempt to curb the economic effects of Covid-19. The primary objective of this study is to leverage on BDA to identify economic shocks, and propose a strategic solution for economic recovery in ASEAN member states (AMS). The findings of this study suggest that BDA techniques, frameworks, and architectures are effective tools in predicting and tracking economic shocks, as well as in designing and implementing an effective economic recovery plan. This study proposes a guideline to governments and policymakers scrambling for resources and considering different options to start an economic recovery process. Our findings draw a roadmap for complex AMS economies struggling to explore options for economic recovery in the response of Covid-19. This study has extended and confirmed the knowledge and perception about harnessing BDA as a tool as well as proposed a scientific approach to design economic policies. The findings outlined in this study contribute to the pipeline of BDA’s theoretical frameworks which is expected to strengthen its novelty in data science.


Cite This Article

H. Yaacob, Q. Ali, N. Anissa Sarbini, A. Nasir Rani, Z. Zaini et al., "Economic shocks of covid-19: can big data analytics help connect the dots," Intelligent Automation & Soft Computing, vol. 27, no.3, pp. 653–668, 2021.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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