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Big data in humanitarian supply chain management: a review and further research directions

Author

Listed:
  • Shivam Gupta

    (Montpellier Business School)

  • Nezih Altay

    (DePaul University)

  • Zongwei Luo

    (Southern University of Science and Technology of China)

Abstract

Humanitarian organizations work diligently to save lives using scarce resources, competing for donor money, and operating in complex environments. It is no surprise that they need information to effectively execute their task. As there have been tremendous developments in data analytics it is imperative that the domain of humanitarian supply chain management leverage the benefits offered by the advancement of big data. In this study, we have conducted a systematic literature review in the field of big data and humanitarian supply chain. The data was collected using Scopus which is the largest digital database. After careful screening, only 28 journal papers were selected for literature review. These papers have been classified and grouped into various categorizations. Future research directions in this field have been suggested that are based on various organizational theories.

Suggested Citation

  • Shivam Gupta & Nezih Altay & Zongwei Luo, 2019. "Big data in humanitarian supply chain management: a review and further research directions," Annals of Operations Research, Springer, vol. 283(1), pages 1153-1173, December.
    • Handle: RePEc:spr:annopr:v:283:y:2019:i:1:d:10.1007_s10479-017-2671-4
    DOI: 10.1007/s10479-017-2671-4
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    Cited by:

    1. George S. Atsalakis & Elie Bouri & Fotios Pasiouras, 2021. "Natural disasters and economic growth: a quantile on quantile approach," Annals of Operations Research, Springer, vol. 306(1), pages 83-109, November.
    2. Josip Marić & Carlos Galera-Zarco & Marco Opazo-Basáez, 2022. "The emergent role of digital technologies in the context of humanitarian supply chains: a systematic literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1003-1044, December.
    3. Sudhanshu Joshi & Manu Sharma & Rashmi Prava Das & Kamalakanta Muduli & Rakesh Raut & B. E. Narkhede & Himanshu Shee & Abhishek Misra, 2022. "Assessing Effectiveness of Humanitarian Activities against COVID-19 Disruption: The Role of Blockchain-Enabled Digital Humanitarian Network (BT-DHN)," Sustainability, MDPI, vol. 14(3), pages 1-22, February.
    4. Taiga Saito & Shivam Gupta, 2022. "Big Data Applications with Theoretical Models and Social Media in Financial Management," CIRJE F-Series CIRJE-F-1205, CIRJE, Faculty of Economics, University of Tokyo.
    5. Surajit Bag & Shivam Gupta & Lincoln Wood, 2022. "Big data analytics in sustainable humanitarian supply chain: barriers and their interactions," Annals of Operations Research, Springer, vol. 319(1), pages 721-760, December.
    6. Taiga Saito & Shivam Gupta, 2022. "Big data applications with theoretical models and social media in financial management," CARF F-Series CARF-F-550, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    7. Sarah Schiffling & Claire Hannibal & Matthew Tickle & Yiyi Fan, 2022. "The implications of complexity for humanitarian logistics: a complex adaptive systems perspective," Annals of Operations Research, Springer, vol. 319(1), pages 1379-1410, December.
    8. Rameshwar Dubey & David J. Bryde & Cyril Foropon & Gary Graham & Mihalis Giannakis & Deepa Bhatt Mishra, 2022. "Agility in humanitarian supply chain: an organizational information processing perspective and relational view," Annals of Operations Research, Springer, vol. 319(1), pages 559-579, December.
    9. Sachin Modgil & Rohit Kumar Singh & Cyril Foropon, 2022. "Quality management in humanitarian operations and disaster relief management: a review and future research directions," Annals of Operations Research, Springer, vol. 319(1), pages 1045-1098, December.
    10. Sabari R. Prasanna, 2022. "The role of supplier innovativeness in the humanitarian context," Annals of Operations Research, Springer, vol. 319(1), pages 1359-1377, December.
    11. Aniruddh Nain & Deepika Jain & Shivam Gupta & Ashwani Kumar, 2023. "Improving First Responders' Effectiveness in Post-Disaster Scenarios Through a Hybrid Framework for Damage Assessment and Prioritization," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(3), pages 409-437, September.
    12. Guo Fuli & Cyril Foropon & Ma Xin, 2022. "Reducing carbon emissions in humanitarian supply chain: the role of decision making and coordination," Annals of Operations Research, Springer, vol. 319(1), pages 355-377, December.
    13. M. Ali Ülkü & James H. Bookbinder & Nam Yi Yun, 2024. "Leveraging Industry 4.0 Technologies for Sustainable Humanitarian Supply Chains: Evidence from the Extant Literature," Sustainability, MDPI, vol. 16(3), pages 1-26, February.
    14. Jimei Yang & Hanping Hou & Hanqing Hu, 2024. "Exploring the Intelligent Emergency Management Mode of Rural Natural Disasters in the Era of Digital Technology," Sustainability, MDPI, vol. 16(6), pages 1-21, March.
    15. Rodolfo Modrigais Strauss Nunes & Susana Carla Farias Pereira, 2022. "Intellectual structure and trends in the humanitarian operations field," Annals of Operations Research, Springer, vol. 319(1), pages 1099-1157, December.
    16. Jaya Priyadarshini & Rajesh Kr Singh & Ruchi Mishra & Surajit Bag, 2022. "Investigating the interaction of factors for implementing additive manufacturing to build an antifragile supply chain: TISM-MICMAC approach," Operations Management Research, Springer, vol. 15(1), pages 567-588, June.
    17. Meriem Riad & Mohamed Naimi & Chafik Okar, 2024. "Enhancing Supply Chain Resilience Through Artificial Intelligence: Developing a Comprehensive Conceptual Framework for AI Implementation and Supply Chain Optimization," Logistics, MDPI, vol. 8(4), pages 1-26, November.
    18. Peiyu Zhang & Yankui Liu & Guoqing Yang & Guoqing Zhang, 2022. "A multi-objective distributionally robust model for sustainable last mile relief network design problem," Annals of Operations Research, Springer, vol. 309(2), pages 689-730, February.

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