The role of Big Data in the business challenge of Covid-19: a systematic literature review in managerial studies


The role of Big Data in the business challenge of Covid-19: a systematic literature review in managerial studies


Objectives. 2020 has been globally affected by the Covid-19 pandemic caused by SARS-CoV-2, which is still today impacting and profoundly changing life globally.

The pandemic has inevitably had consequences at a global economic level, with particular impact on international market and trade (Bailey & Breslin, 2021). Firms are having a hard time and continue to face the dramatic consequences and business challenges that Covid-19 is constantly creating. Firms have had to immediately rethink business models, strategies and forecasting tools to adapt their behavior and activities to the new scenario that has been emerging (Ritter & Pedersen, 2020).

In this context, the need for timely and accurate information has become vital in every area of business management, from strategic planning, to production dynamics, to the relationship with customers (McAfee et al., 2012).

The digital transformation process, which began some years ago (Matt et al., 2015), has seen a need to accelerate, to face and to satisfy the new emerging scenario (Soto-Acosta, 2020).

Furthermore, the spread of the Covid-19 global pandemic has generated an exponential increase and extraordinary volume of data (Sheng et al., 2020) and created the need to manage and monitor these data in order to obtain relevant information and benefits for management (Zhou et al., 2020).

In this domain, Big Data is one of the digital innovation technologies that can support business organizations during these complex times (Javaid et al., 2020).

Even though widely investigated within literature, Big Data still remains an uncertain and abstract topic from various points of view (Chen et al., 2014). The definition of Big Data, for example, is still today a conflicting concept for scholars (i.e. Laney, 2001; Manyika 2011; Beyer & Laney, 2012; Dumbill, 2013) although its characteristics have evolved and expanded over the years, these are issues that certainly require further study (Gandomi & Haider, 2015; De Mauro et al., 2016).

An interesting definition of Big Data is provided by Buhl et al. (2013, p. 68) who consider Big Data “a multidisciplinary and evolutionary fusion of new technologies in combination with new dimensions in data storage and processing (volume and velocity), a new era of data source variety (variety) and the challenge of managing data quality adequately (veracity)”. The authors also highlight the multidisciplinary aspect of Big Data which, like the other enabling technologies of Industry 4.0 (Aquilani et al., 2020), are tools born in the engineering domain that have rapidly expanded to the managerial field, from production techniques to strategies, without neglecting their social impact (Oztemel et al., 2018).

The multidisciplinary nature of Big Data verifies its versatility and ability to support numerous decision-making processes, not only related to the managerial sphere (Sheng et al., 2017). The earliest uses and applications of Big Data in the context of the Covid-19 pandemic were certainly in the medical and biological fields. Indeed, Bragazzi et al. (2020, p. 3176) state that “Big Data can help handle the huge, unprecedented amount of data derived from public health surveillance, real-time epidemic outbreaks monitoring, trend now-casting/forecasting, regular situation briefing and updating from governmental institutions and organisms, and health resources utilization information”.

Looking at the managerial use of Big Data in Covid-19, there are as yet a limited number of studies, also due to the recent emergence of the topic. In particular, there is no precise systematic analysis of the literature that organizes contributions published to date. Only one paper (Sheng et al., 2020) initiates a first joint analysis of the two topics in the managerial field by examining methodological analysis innovations in studying Big Data and how they can be better used to examine contemporary organizational issues.

#big data #Covid-19 #Industry 4.0 #pandemic management #systematic literature review