Data, analytical techniques and collaboration between researchers and practitioners in humanitarian health supply chains: a challenging but necessary way forward

K. De Boeck, M. Besiou, C. Decouttere, Sean Rafter, N. Vandaele, L. V. Van Wassenhove, P. Yadav
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引用次数: 1

Abstract

Purpose This paper aims to provide a discussion on the interface and interactions between data, analytical techniques and impactful research in humanitarian health supply chains. New techniques for data capturing, processing and analytics, such as big data, blockchain technology and artificial intelligence, are increasingly put forward as potential “game changers” in the humanitarian field. Yet while they have potential to improve data analytics in the future, larger data sets and quantification per se are no “silver bullet” for complex and wicked problems in humanitarian health settings. Humanitarian health supply chains provide health care and medical aid to the most vulnerable in development and disaster relief settings alike. Unlike commercial supply chains, they often lack resources and long-term collaborations to enable learning from the past and to improve further. Design/methodology/approach Based on a combination of the authors’ research experience, interactions with practitioners throughout projects and academic literature, the authors consider the interface between data and analytical techniques and highlight some of the challenges inherent to humanitarian health settings. The authors apply a systems approach to represent the multiple factors and interactions between data, analytical techniques and collaboration in impactful research. Findings Based on this representation, the authors discuss relevant debates and suggest directions for future research to increase the impact of data analytics and collaborations in fostering sustainable solutions. Originality/value This study distinguishes itself and contributes by bringing the interface and interactions between data, analytical techniques and impactful research together in a systems approach, emphasizing the interconnectedness.
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人道主义卫生供应链中的数据、分析技术和研究人员与从业人员之间的合作:一条具有挑战性但必要的前进道路
本文旨在讨论人道主义卫生供应链中数据、分析技术和有影响力的研究之间的接口和相互作用。数据捕获、处理和分析的新技术,如大数据、区块链技术和人工智能,越来越多地被认为是人道主义领域潜在的“游戏规则改变者”。然而,尽管它们有可能在未来改进数据分析,但更大的数据集和量化本身并不是解决人道主义卫生环境中复杂和棘手问题的“灵丹妙药”。人道主义保健供应链向发展和救灾环境中最脆弱的群体提供保健和医疗援助。与商业供应链不同,它们往往缺乏资源和长期合作,无法从过去学习并进一步改进。设计/方法学/方法根据作者的研究经验、在整个项目中与从业人员的互动以及学术文献,作者考虑了数据和分析技术之间的相互作用,并强调了人道主义卫生环境固有的一些挑战。作者运用系统方法来表示影响研究中数据、分析技术和协作之间的多重因素和相互作用。在此基础上,作者讨论了相关的争论,并提出了未来研究的方向,以增加数据分析和合作在促进可持续解决方案方面的影响。原创性/价值本研究通过将数据、分析技术和有影响力的研究以系统方法结合在一起,强调相互联系,从而脱颖而出。
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来源期刊
CiteScore
6.40
自引率
20.00%
发文量
20
期刊介绍: The Journal of Humanitarian Logistics and Supply Chain Management (JHLSCM) is targeted at academics and practitioners in humanitarian public and private sector organizations working on all aspects of humanitarian logistics and supply chain management. The journal promotes the exchange of knowledge, experience and new ideas between researchers and practitioners and encourages a multi-disciplinary and cross-functional approach to the resolution of problems and exploitations of opportunities within humanitarian supply chains. Contributions are encouraged from diverse disciplines (logistics, operations management, process engineering, health care, geography, management science, information technology, ethics, corporate social responsibility, disaster management, development aid, public policy) but need to have a logistics and/or supply chain focus. JHLSCM publishes state of the art research, utilizing both quantitative and qualitative approaches, in the field of humanitarian and development aid logistics and supply chain management.
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