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Intelligent process-aware information systems to support agility in disaster relief operations: a survey of emerging approaches

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  • Mohammad Reza Rasouli

Abstract

Agility is a key characteristic in disaster relief operations. Intelligent process-aware information systems (IPAISs) can support agility in disaster relief operations through providing information and process reach and richness to manage dynamic inter-operations. In this research, based on relevant reference architectures, a conceptual overview of an IPAIS to support agility in disaster relief operations is described. This conceptual overview includes the dynamic partnering, the collaborative process composition, the collaborative ontology management, the global workflow engine, the run-time coordination, the dynamic rule management, the run-time process proposer, and the dynamic interoperability adaptor components. Based on this conceptual overview, a systematic literature review is conducted to explore emerging approaches that can be applied to realise intelligent process-centred collaborative inter-operations to respond disasters. The findings of the conducted review show the applicability of the emerging multi-agent service-oriented modelling and analysis approaches, optimal control theory based methodologies, social network analysis techniques, data-driven inductive methods, resilient-centred approaches for robustness and agility, self-organisation mechanisms based on cyber physical systems and systems of systems perspectives, simulation methods, and trust management procedures to support the realisation of the components of an IPAIS in the context of disaster relief operations.

Suggested Citation

  • Mohammad Reza Rasouli, 2019. "Intelligent process-aware information systems to support agility in disaster relief operations: a survey of emerging approaches," International Journal of Production Research, Taylor & Francis Journals, vol. 57(6), pages 1857-1872, March.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:6:p:1857-1872
    DOI: 10.1080/00207543.2018.1509392
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    Cited by:

    1. Núñez-Merino, Miguel & Maqueira-Marín, Juan Manuel & Moyano-Fuentes, José & Castaño-Moraga, Carlos Alberto, 2022. "Industry 4.0 and supply chain. A Systematic Science Mapping analysis," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    2. George Mutugu Mwangi & Stella Despoudi & Oscar Rodriguez Espindola & Konstantina Spanaki & Thanos Papadopoulos, 2022. "A planetary boundaries perspective on the sustainability: resilience relationship in the Kenyan tea supply chain," Annals of Operations Research, Springer, vol. 319(1), pages 661-695, December.
    3. Abirami Raja Santhi & Padmakumar Muthuswamy, 2022. "Pandemic, War, Natural Calamities, and Sustainability: Industry 4.0 Technologies to Overcome Traditional and Contemporary Supply Chain Challenges," Logistics, MDPI, vol. 6(4), pages 1-32, November.
    4. Merve Cengiz Toklu, 2023. "A fuzzy multi-criteria approach based on Clarke and Wright savings algorithm for vehicle routing problem in humanitarian aid distribution," Journal of Intelligent Manufacturing, Springer, vol. 34(5), pages 2241-2261, June.
    5. Gillani, Fatima & Chatha, Kamran Ali & Jajja, Shakeel Sadiq & Cao, Dongmei & Ma, Xiao, 2024. "Unpacking Digital Transformation: Identifying key enablers, transition stages and digital archetypes," Technological Forecasting and Social Change, Elsevier, vol. 203(C).

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