The Impact of Big Data Analytics on Supply Chain Resilience and Performance during the COVID-19 Pandemic: an Empirical Investigation in the Chinese Manufacturing SectorTools zhu, luquan (2020) The Impact of Big Data Analytics on Supply Chain Resilience and Performance during the COVID-19 Pandemic: an Empirical Investigation in the Chinese Manufacturing Sector. [Dissertation (University of Nottingham only)]
AbstractIn recent years, many organisations are preparing to develop and utilise Big Data Analytics (BDA) to improve performance. This research examines the impact of BDA on supply chain resilience (SCR) and performance based on the Resource-based View (RBV), Organisational information processing theory (OIPT) and the latest literature on BDA. This research used survey approach to collect data. The findings are derived from structural equation modelling using partial least squares after collecting data from 112 manufacturing industries in China. The positive effect of BDA on SCR and the positive effect of BDA on firm performance are demonstrated. Then, SCR is partially involved as a mediator, meaning that BDA has a positive impact on firm performance regardless of whether SCR mediates the process of BDA's impact on firm performance. Furthermore, this study elucidates the moderating effect of the crisis on the relationship between BDA and SCR. This effect diminishes the positive impact of BDA on SCR. The purpose of introducing COVID-19 as a moderator is to provide more experience on how to deal with future companies after they encounter epidemics. This research combines the two theories, RBV and OIPT, to highlight the importance of the BDA in handling information for firms during turbulence. It also extends RBV and OIPT to provide a better understanding of the application of resources and information processing, as well as making a practical contribution to business managers in developing BDA in their companies.
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