Supply chain resilience in mindful humanitarian aid organizations:the role of big data analytics

Abstract

Purpose: The purpose of this paper is to understand the nomological network of associations between collective mindfulness and big data analytics in fostering resilient humanitarian relief supply chains. Design/methodology/approach: The authors conceptualize a research model grounded in literature and test the hypotheses using survey data collected from informants at humanitarian aid organizations in Africa and Europe. Findings: The findings demonstrate that organizational mindfulness is key to enabling resilient humanitarian relief supply chains, as opposed to just big data analytics. Originality/value: This is the first study to examine organizational mindfulness and big data analytics in the context of humanitarian relief supply chains.

Publication DOI: https://doi.org/10.1108/IJOPM-12-2020-0871
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences > Aston Business School
Additional Information: Copyright © 2021, Denis Dennehy, John Oredo, Konstantina Spanaki, Stella Despoudi and Mike Fitzgibbon. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode.
Uncontrolled Keywords: Big data analytics,Humanitarian aid,Mindfulness,Resilience,Supply chain,General Decision Sciences,Strategy and Management,Management of Technology and Innovation
Publication ISSN: 1758-6593
Last Modified: 23 Dec 2024 08:30
Date Deposited: 10 Aug 2021 14:21
Full Text Link:
Related URLs: https://www.eme ... -0871/full/html (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2021-10-12
Published Online Date: 2021-08-05
Accepted Date: 2021-07-01
Authors: Dennehy, Denis
Oredo, John
Spanaki, Konstantina
Despoudi, Stella (ORCID Profile 0000-0002-8377-6407)
Fitzgibbon, Mike

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