Accounting perspectives on the business value of big data during and beyond the Covid-19 pandemic

Abstract

Research Question: How can business organizations develop accounting practices to use big data to create competitive intelligence advantages to survive during and beyond the Covid19 conditions? Motivation: We aim to provide new accounting perspectives for using big data techniques in business organizations beyond the covid-19. Idea: We argue that the massive reduction in business capacity and operations will interpose the accounting and financial practices beyond the COVID-19 pandemic. There is a crucial need to uncover the underlying business practices and market circumstances toward the radical shifts in business and society. Data: Our paper uses a desk study method to investigate companies' possible challenges and opportunities to use big data analytics as a survival method during and beyond the Covid-19 conditions. Tools: Critical contingencies represent one of the leading business strategies to manage the shift in customer demand and business risks. Big data can be used in this sense as a valuable intangible asset to create these critical contingencies and help a business survive beyond this pandemic. Findings: This study provides policy and practitioner implications in relation to establishing new accounting perspectives on big data analytics in the context of achieving economic sustainability for corporations during and beyond the Covid-19 pandemic. It offers new forms of trust, accountability and governance practices to integrate big data into accounting practices to create more competitive intelligence for businesses. Contribution: This study extends previous accounting literature by offering unique insights and critical developmental thoughts about accounting perspectives of big data applications, opportunities and challenges beyond the Covid-19 pandemic. It provides a critical understanding of the predictive analytics of big data from an accounting perspective as an intangible asset.

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DOI

https://doi.org/10.24818/jamis.2022.02002

Repository URI

https://eprints.gla.ac.uk/321182/