nonparametric method supply chain probability risk

Statistics show that about 40–60% of small businesses never reopen following a disaster (FEMA 2015). Natural disasters like the Thailand flood and Japan’s earthquake and tsunami in 2011 immediately affected the SCs of several products from firms such as Apple, Toshiba, General Motors, Nissan Motor and Toyota Motor causing negative results in these companies’ reputations and earnings (Chongvilaivan 2011). The same phenomenon is observed globally based on the OFDA/CRED International Disaster Database with less than 200 disasters per year in the 1980s and over 300 in the 2010s. The occurrence of costly disasters has mounted. A typical year in the 1980s experienced, on average, 2.7 such disasters in the U.S, 4.6 in the 1990s, 5.4 in the 2000s, and 10.5 in the 2010s. Based on the site of the National Oceanic and Atmospheric Administration (NOAA), which keeps a record regarding the number of disasters and their associated costs in the U.S, there have been 212 disasters since 1980 resulting in approximately $1.2 trillion in damage. Supply chain disruptions may occur due to climate change or human factors. Therefore, the need for designing resilient SCs and preparing contingency plans is of paramount importance. Given that more than 56% of companies globally suffer a SC disruption annually, firms have started taking SC disruptions more seriously (BCI-Business Continuity Institute 2019). These trends place enormous pressure for undistracted operations and stable environments, but also increase their vulnerability to disruptions which consequently increases the operational and financial impact of supply chain (SC) disruptions (Zsidisin et al. Furthermore, the pressure for cost reductions has led to the outsourcing and offshoring of many manufacturing and R&D activities, especially the sourcing from low-cost countries. 2005) calling for continuous flow processing with low inventory volumes, levelled and just-in-time production and accurate scheduling of transport for cross-docking operations leading to more cost-effective and responsive supply chains (SCs). The study summarizes and builds upon the knowledge of other well-cited reviews and surveys in this research area.ĭriven by the globalization of markets and the competitive business environment, lean supply chain management (SCM) practices have become very popular (Blackhurst et al. The aim of this study is to amalgamate knowledge on supply chain disruptions which constitutes an important and timely as the frequency and impact of disruptions increase. Finally, a detailed future research agenda is formed about SC disruptions, which identifies the research gaps yet to be addressed. Our review also examines the most popular modeling approaches on the topic with indicative examples and the IT tools that enhance resilience and reduce disruption risks.

The content analysis of these studies synthesized existing information about the types of disruptions, their impact on supply chains, resilience methods in supply chain design and recovery strategies proposed by the studies supported by cost–benefit analysis. Based on a review process important studies have been identified and analyzed. Our study examines the literature that has been published in important journals on supply chain disruptions, a topic that has emerged the last 20 years, with an emphasis in the latest developments in the field.

Nonparametric method supply chain probability risk