Roles of Innovation Leadership on Using Big Data Analytics to Establish Resilient Healthcare Supply Chains to Combat the COVID-19 Pandemic: A Multimethodological Study
Journal
IEEE Transactions on Engineering Management
Date Issued
2021
Author(s)
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. IEEE
Subjects
Big data analytics (BDA); COVID-19; COVID-19; healthcare supply chain; Leadership; Medical services; multi-methods research; Organizations; Pandemics; responsive supply chain; supply chain innovation; supply chain resilience; Supply chains; Technological innovation
Other Subjects
Big data; Data Analytics; Health care; Least squares approximations; Supply chains; Surveys; Empirical research; Healthcare industry; Information processing theories; Innovation leadership; Moderating effect; Partial least square (PLS); Structural equation modeling; Supply chain resiliences; Advanced Analytics
Publisher
Institute of Electrical and Electronics Engineers Inc.
Type
journal article