The rising global competition and uncertainty in business environment has led logistics firms to redesign supply chain strategies which boost disaster immunity. Therefore, the current study develops an integrated research framework that combines big data analytics capability, HR practices, resilience and resource reconfiguration to investigate logistic firm disaster immunity. In addition to that, the moderating effect of data-driven culture is tested between disaster immunity and supply chain performance.
The research design of this study is based on quantitative techniques and followed by positivist research paradigm. Data are collected through structured questionnaires. Overall, 219 managers have participated in this logistics research survey. Data are computed with structural equation modeling approach.
Statistical findings have revealed that collectively HR practices, innovation capability, proactive capability, reactive capability, resource configuration and supply chain resilience explained R2 71.5% variance in disaster immunity. Therefore, in the extended model, disaster immunity and data-driven culture have depicted R2 49.2% variance in manufacturing firm supply chain performance.
The integration of big data analytics capability factors with HR practices, supply chain resilience and resource configuration has enriched logistic literature in the disaster immunity setting. Practically, this study has concluded that factors such as data analytics capabilities, resource reconfiguration, supply chain resilience and HR practices need policymakers’ attention to boost disaster immunity and supply chain performance.
This research is original as it unveils three core factors of big data analytics capability, namely proactive, reactive and innovative capability, and examines firm disaster immunity. Similarly, research is unique as it combines capability factors with resilience, HR practices and resource reconfiguration and investigates logistic firm disaster immunity.
