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How ecosystems coordinate architectures and AI in humanitarian operations? A configurational view

Author

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  • Guo, Yuanyuan
  • Chen, Yilang
  • Wu, Liang
  • Li, Longzhen
  • Li, Ruoxi

Abstract

Recent research in crisis management indicates that business ecosystems are increasingly incorporating artificial intelligence (AI) into humanitarian operations. This integration is designed to coordinate a diverse range of actors and ensure the quick and efficient delivery of aid. One of the key operational issues identified with this undertaking is communal coordination in that the effectiveness of these humanitarian efforts largely hinges on the ability of the actors to foster a sense of community within the architecture of the AI-enabled ecosystem, i.e., a community characterized by trust and cooperation. This architecture is deemed critical for effective humanitarian operations. Yet some studies indicate that AI might impede coordination, potentially obstructing how communal relations develop between actors. Unfortunately, the literature does not adequately explain how ecosystems and architectures should be designed to promote communal coordination among the actors involved. Hence, with this research, we conducted a configurational analysis of humanitarian operations, referencing data from 73 ecosystems observed during the catastrophic floods in China in 2023. Using v4.1 of the fuzzy-set qualitative comparative analysis (fsQCA) tool, we identified correlations between the architectures of various AI-enabled ecosystem configurations and the performance of the humanitarian operations they supported. From our research, we identified two exemplary architectures that led to superior humanitarian performance: one featuring loosely coupled coordination within an AI-enabled architecture, and the other emphasizing aligned coordination within more regulated homogeneity. The key distinction between the two architectural models lies in how the AI deployed influences the dynamics of coordination between the community and the governance bodies. This study reveals that, despite AI's significant potential to enhance humanitarian performance, effective communal coordination depends on aligning the ecosystem architecture with AI-driven coordination. This research contributes to the humanitarian literature by clarifying the complicated interactions between AI and ecosystem architectures in humanitarian scenarios.

Suggested Citation

  • Guo, Yuanyuan & Chen, Yilang & Wu, Liang & Li, Longzhen & Li, Ruoxi, 2025. "How ecosystems coordinate architectures and AI in humanitarian operations? A configurational view," Technological Forecasting and Social Change, Elsevier, vol. 211(C).
    • Handle: RePEc:eee:tefoso:v:211:y:2025:i:c:s0040162524007005
    DOI: 10.1016/j.techfore.2024.123902
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