Artificial Intelligence (AI) as a Decision-Making Tool to Control Crisis Situations

Crisis Management

According to Coombs (2014), a crisis can be defined as “an unpredictable event that threatens important expectancies of stakeholders relating to health, safety, environmental, and economic issues, which can seriously impact an organisation’s performance and generate negative comments” (p.3). Examples of crises involving multinational companies, governments, etc. can be found in the media around the world on a regular basis. For instance, the recent impact of the coronavirus (COVID-19) on the global economies, tourism, and virtually all aspects of human endeavour. In the multinational organisations, some prominent crises over time are the falsification of metal quality reports by Kobe steel (Mitchell, 2002), the disappearance of Malaysia Airlines Flight 370, the BP oil spill in the Gulf region, unexplainable acceleration in Toyota cars, or the collapse of the building in Bangladesh. Due to globalisation resulting from technological advancement, there will be even more increased impacts of crises on organisations due to the complexity and depth of supply chains in multinationals today. For instance, consider the suppliers identifiable in the Nike supply chain, or the composition of the agricultural food supply chains. Crisis management is becoming an interesting topic of research having many implications for both academicians and practitioners, which has led to the development and promulgation of various articles in the area of crisis management. For instance, a systematic literature by Cleeren et al., (2017) highlighted the need for an enhanced understanding of product harm crises considering an international perspective. The findings from that study reveal the overwhelming number of studies on product harm crises in developed countries, however, with little or close to nothing of such being conducted in emerging economies.