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

IF 7.1 2区管理学 Q1 MANAGEMENT

International Journal of Operations & Production Management Pub Date : 2021-08-05 DOI:10.1108/ijopm-12-2020-0871

Denis Dennehy, J. Oredo, Konstantina Spanaki, S. Despoudi, M. Fitzgibbon

引用次数: 26

Abstract

PurposeThe 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/approachThe 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.FindingsThe findings demonstrate that organizational mindfulness is key to enabling resilient humanitarian relief supply chains, as opposed to just big data analytics.Originality/valueThis is the first study to examine organizational mindfulness and big data analytics in the context of humanitarian relief supply chains.

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人道主义援助组织的供应链弹性:大数据分析的作用

目的本文的目的是了解集体正念和大数据分析之间的关联的法理网络，以促进有弹性的人道主义救援供应链。设计/方法论/方法作者根据文献概念化了一个研究模型，并使用从非洲和欧洲人道主义援助组织的线人那里收集的调查数据来检验假设。发现表明，组织正念是实现有弹性的人道主义救援供应链的关键，而不仅仅是大数据分析。原创性/价值这是第一项在人道主义救援供应链背景下研究组织正念和大数据分析的研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Operations & Production Management MANAGEMENT-

CiteScore

13.30

自引率

17.20%

发文量

期刊介绍： The mission of the International Journal of Operations & Production Management (IJOPM) is to publish cutting-edge, innovative research with the potential to significantly advance the field of Operations and Supply Chain Management, both in theory and practice. Drawing on experiences from manufacturing and service sectors, in both private and public contexts, the journal has earned widespread respect in this complex and increasingly vital area of business management. Methodologically, IJOPM encompasses a broad spectrum of empirically-based inquiry using suitable research frameworks, as long as they offer generic insights of substantial value to operations and supply chain management. While the journal does not categorically exclude specific empirical methodologies, it does not accept purely mathematical modeling pieces. Regardless of the chosen mode of inquiry or methods employed, the key criteria are appropriateness of methodology, clarity in the study's execution, and rigor in the application of methods. It's important to note that any contribution should explicitly contribute to theory. The journal actively encourages the use of mixed methods where appropriate and valuable for generating research insights.