Can big data be used to handle big disaster of COVID-19? AIM professor Yeming (Yale) Gong addressed a research question: How do logistics firms improve the supply chain performance in COVID-19 through big data and supply chain integration (SCI)? Yeming Gong and his team used a mixed-method approach with four rounds of data collection. A three-round survey of 323 logistics firms in 26 countries in Europe, America, and Asia was first conducted. The authors then conducted in-depth interviews with 55 logistics firms.
In the first quantitative study, the authors find mediational mechanisms through which big data analytics technology capability (BDATC) and SCI influence supply chain performance. The results of the follow-up qualitative analysis not only confirm the inferences from the quantitative analysis but also provide complementary insights into #organizational #culture and the #institutional #environment.
The authors contribute to supply chain risk management by developing a three-level hierarchy of capabilities framework and finding a mechanism with the links between big data and big disaster. The authors also provide managerial implications for logistics firms to address the new management challenges posed by COVID-19.
Yeming GONG (corresponding author) 2022. Big data and big disaster: A mechanism of supply chain risk management in global logistics industry. International Journal of Operations and Production Management. With L. Li, Z. Wang, L. Liu