Paradox-responding in humanitarian temporary supply networks: exploring strategies and enabling mechanisms

Author:

Fernandes Aline RodriguesORCID,Dube NonhlanhlaORCID

Abstract

PurposeThis study investigates paradox-responding strategies and enabling mechanisms in humanitarian temporary supply networks (TSNs). Given the high stakes involved in life-saving supply networks, understanding how diverse, often under-resourced, organisations jointly tackle paradoxical tensions under time pressure is crucial.Design/methodology/approachA qualitative single case study approach is adopted and a TSN deployed to meet shelter needs following the 2015 Nepal earthquake is selected as the case. The authors use diverse secondary data sources to establish how the TSN responded to paradoxical tensions.FindingsResults show that paradox-responding in humanitarian TSNs is ongoing, dynamic and a collective effort. Most strategies entail tackling the paradoxical tensions at the same time, using the same TSN structure, but there are differences in the treatment of the paradoxical elements. Additionally, the authors find that the execution of the responding strategies is enabled by the appropriate types of network-level mechanisms which can vary in novelty, complexity, depth and reach.Research limitations/implicationsThis study provides rich explanations of paradox-responding and develops insights into collective action within TSNs. However, further research is needed to extend and refine insights given the single-case setting design.Practical implicationsThis study develops a framework of paradox-responding strategies and a corresponding mix of enabling mechanisms that can guide decision-makers in the humanitarian sector when deploying TSNs.Originality/valueTo the best of the authors' knowledge, this is the first study that investigates paradox-responding strategies in humanitarian TSNs in particular and enabling mechanisms in general.

Publisher

Emerald

Subject

Management of Technology and Innovation,Strategy and Management,General Decision Sciences

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