The Impact of the Coronavirus Pandemic on Supply Chains and Their Sustainability: A Text Mining Approach

The coronavirus pandemic is an unprecedented event, putting global supply chains (SC) into the focus of a wider public. Yet, it is unclear, what is communicated about this and how and what consequences supply chain management (SCM) would take away. This research aims at analyzing how text mining can provide insights on the impact of the coronavirus pandemic on supply chains, focusing on the implications of the pandemic for the supply chain constructs related to risk, resilience and sustainability. As method applies text mining of general newspapers as well as supply chain and logistic newspaper articles employing the open-source software R. This paper shows that certain supply chain topics like risk, resilience, disruption and sustainability vary in their news coverage on the type of newspaper and the number of COVID-19 infections. It reassures trends and observations from individual experiences on a broader and global picture and discusses the limitations and possibilities of using text mining in this field. The time period was split into three phases regarding the course of the number of infections and differences in the news coverage of the phases can be distinguished already: (1) the onset of the crisis, (2) the peak and lockdown, (3) managing supply chains during the crisis. As this pandemic is highly dynamic, new and not yet ended, research implications are too early to make. This research rather serves as a base for further, more detailed research into certain topics and identifies limitations and improvements of the applied method. Due to the method chosen and the timeliness of data, this empirical research is unique and can be of great help to see trends and patterns to further deep dive into specific areas.