Abstract
This article empirically examines the effect of big data analytics (BDA) on healthcare supply chain (HSC) innovation, supply chain responsiveness, and supply chain resilience under the moderating effect of innovation leadership in the context of the COVID-19 pandemic. The scanning interpretation-action-performance model and organization information processing theory are used to explain BDA, HSC innovation, responsiveness, and resilience relationships. First, the hypotheses were tested using data collected from 190 experienced respondents working in the healthcare industry. Our structural equation modeling analysis using the partial least squares (PLS) method revealed that BDA capabilities play a pivotal role in building a responsive HSC and improving innovation, which has contributed to resilience during the current pandemic situation. High innovation leadership strengthens the effect of BDA capabilities on HSC innovation. High innovation leadership also increases the effect of BDA capabilities on responsiveness. Second, we validated and supplemented the empirical research findings using inputs collected in 30 semistructured qualitative questionnaires. Our article makes a unique contribution from the perspective of innovation leaderships. In particular, we argue that the role of innovative leadership in the COVID-19 pandemic situation is critical as it indirectly affects HSC resilience when BDA is in place.
| Original language | English |
|---|---|
| Pages (from-to) | 13213-13226 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Engineering Management |
| Volume | 71 |
| DOIs | |
| Publication status | Published - 2024 |
| Externally published | Yes |
Keywords
- Big data analytics (BDA)
- COVID-19
- healthcare supply chain
- multi-methods research
- responsive supply chain
- supply chain innovation
- supply chain resilience
ASJC Scopus subject areas
- Strategy and Management
- Electrical and Electronic Engineering