An investigation of information alignment and collaboration as complements to supply chain agility in humanitarian supply chain

Our study examines the relationship between information alignment (IA), collaboration (CO) and supply chain agility (SCAG) under the moderating effects of artificial intelligence-driven big data analytics capability (AI-BDAC) and intergroup leadership (IGL). We have grounded our theoretical model in...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of production research 2021-03, Vol.59 (5), p.1586-1605
Hauptverfasser: Dubey, Rameshwar, Bryde, David J., Foropon, Cyril, Tiwari, Manisha, Dwivedi, Yogesh, Schiffling, Sarah
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Our study examines the relationship between information alignment (IA), collaboration (CO) and supply chain agility (SCAG) under the moderating effects of artificial intelligence-driven big data analytics capability (AI-BDAC) and intergroup leadership (IGL). We have grounded our theoretical model in the resource-based view (RBV) and contingency theory and further tested our research hypotheses using multi-informant data collected using a web-based pre-tested instrument from 613 individuals working in 193 humanitarian organisations drawn from 24 countries located on various continents across the globe. We tested our research hypotheses using variance-based structural equation modelling (PLS-SEM). Our study offers interesting results which help to advance the theoretical debates surrounding technology-driven supply chain agility in the context of humanitarian settings. We further provide some directions to managers engaged in disaster relief operations, who are contemplating using emerging technologies to enhance collaboration and supply chain agility. Finally, we have outlined the limitations of our study and offer some future research directions.
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2020.1865583