Pervaiz Akhtar
Coordination and collaboration for humanitarian operational excellence : big data and modern information processing systems
Akhtar, Pervaiz; Osburg, Victoria-Sophie; Kabra, Gaurav; Ullah, Subhan; Shabbir, Haseeb; Kumari, Sushma
Authors
Victoria-Sophie Osburg
Gaurav Kabra
Subhan Ullah
Haseeb Shabbir
Dr. Sushma Kumari S.Kumari@hull.ac.uk
Senior Lecturer and Programme Director- MSc Logistics and Supply Chain Management and Education Lead Logistics and Supply Chain Management
Abstract
Humanitarian operational excellence depends on effective coordination and collaboration not only between supply chain partners but also among other actors such as host government, local and international non-government organizations (NGOs), and donors. Importantly, effective coordination and collaboration are facilitated by big data and modern information processing (BDMIP) systems that are complex and interlocked with contemporary information and communication technology (ICT). This study simplifies BDMIP systems by using a comprehensive methodology (literature review and a multicriteria decision-making approach, called the analytic network process) and explores its key determinants and other interconnected factors. The data were collected from humanitarian managers, working in horizontally (e.g., governments, local and international humanitarian organizations) and vertically (e.g., supply chain partners) collaborated organizations. Three systems (manual, semi-automated, and fully automated) are investigated, which depend on various determinants for operational excellence interlinked with modern big data technology and its components. The results indicate that dynamic compatibility is the most important determinant for such systems to support operational excellence, followed by real-time response, cost, end-to-end visibility, and operational service quality. The implementation of fully automated systems is less cost-effective. This attributes to contemporary dimensions and enablers (e.g. the internet of things, big data collection and analytics, effective data and information sharing, modern unmanned aerial vehicles (called drones), skills for mining structured and unstructured data, among others). Semi-automated systems are also imperative for certain enablers (e.g. data accuracy, data reliability, and personalized data exchange). This study concludes by discussing these findings and their implications for practitioners; how they can combine these technical and operational foundations to execute humanitarian operational excellence and to build effective coordination and collaboration among involved parties. It further provides suggestions for future research.
Citation
Akhtar, P., Osburg, V.-S., Kabra, G., Ullah, S., Shabbir, H., & Kumari, S. (in press). Coordination and collaboration for humanitarian operational excellence : big data and modern information processing systems. Production planning & control, https://doi.org/10.1080/09537287.2020.1834126
Journal Article Type | Article |
---|---|
Acceptance Date | Apr 19, 2020 |
Online Publication Date | Oct 26, 2020 |
Deposit Date | Jul 17, 2020 |
Publicly Available Date | Oct 27, 2021 |
Journal | Production planning & control |
Print ISSN | 0953-7287 |
Publisher | Taylor and Francis |
Peer Reviewed | Peer Reviewed |
DOI | https://doi.org/10.1080/09537287.2020.1834126 |
Keywords | Coordination and collaboration; Humanitarian operational excellence; ICT and big data applications in humanitarian operations; Big data and information processing systems; Analytic network process |
Public URL | https://hull-repository.worktribe.com/output/3541406 |
Publisher URL | https://www.tandfonline.com/doi/full/10.1080/09537287.2020.1834126 |
Related Public URLs | http://eprints.whiterose.ac.uk/160006/ |
Files
Article
(965 Kb)
PDF
Copyright Statement
©2020 University of Hull
You might also like
Embracing supply chain agility: an investigation in the electronics industry
(2016)
Journal Article
Supervision environments and performance of UK dairy warehouses: A path analysis
(2014)
Journal Article
Downloadable Citations
About Repository@Hull
Administrator e-mail: repository@hull.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search