Emerging Technologies in Emergency Situations
Call for papers for: International Journal of Operations & Production Management
Emerging Technologies in Emergency Situations
Prof Samuel Fosso Wamba, Toulouse Business School, France
Prof Maciel M. Queiroz, Universidade Paulista, Brazil
Dr. Samuel Roscoe, University of Sussex Business School, UK
Prof Wendy Phillips, University of the West of England, UK
Dr. Dharm Kapletia, University of the West of England, UK
Prof Arash Azadegan, Rutgers Business School, USA
The world is witnessing an unprecedented upheaval in the global operations and supply chains of organizations. Due to COVID-19, companies have been plunged into an emergency situation where they are fighting for their very survival. To find a way out of today’s crisis, managers need guidance on how to redeploy operational resources and build resilience. Industry 4.0 technologies will play an important role in rebuilding and reconfiguring global operations and supply chains (Koh, Orzes and Jia, 2019; Queiroz et al., 2019). Recent scholarly work on emerging technologies such as Blockchain (Wamba and Queiroz, 2020), Artificial Intelligence (AI) (Dwivedi et al., 2019), Big Data Analytics (Kache and Seuring, 2017; Matthias et al., 2017), internet of things (Islam et al., 2018), social media (Ramanathan, Subramanian and Parrott, 2017) and 3D printing (Kapletia et al., 2019; Roscoe et al. 2019), has deepened our understanding of Industry 4.0 in a supply chain context. However, one area that has received limited attention in the literature is the impact of emerging technologies in emergency situations.
Emergency situations occur due to disease outbreaks (e.g., COVID-19, SARS, MERS), climate change, natural disasters, scarcity of resources (e.g. food, water) and man-made crises such as conflict, terrorism and mass migration. Situations such as these require a rapid response from governments, non-governmental organisations and businesses to mitigate threats to life and property. Recent advancements in digital technologies can enhance planning, mobilization and management during emergency situations. For example, AI and business analytics can quickly identify populations in distress. Social media can coordinate the relief efforts of local volunteers during disasters. Distributed manufacturing technologies such as 3D printing offer organisations the potential for point-of-care manufacture of life-saving medicines, implants, equipment and devices within the vicinity of an outbreak or disaster (Phillips et al.,2019).
Scholars have considered the importance of organisational and dynamic capabilities in developing industry 4.0 technologies (Li et al., 2018; Roscoe et al. 2019). Yet, the significance of fostering capabilities for the deployment of emerging technologies in emergency situations is under-researched (Sarkis, 2012; De Giovanni, 2019; Koh, Orzes and Jia, 2019).While scholars have identified the coordination mechanisms needed to provide a synchronised response to disasters (Holguín-Veras et al., 2012; Oloruntoba and Gray, 2006; Van Wassenhove, 2006), the procesess needed to deploy emerging technologies during crises receives limited attention (Dwivedi et al., 2019). To address this gap, the special issue will consider the capabilities and coordination mechanisms required to deploy and utilize emerging technologies in emergency situations. The special issue aims to stimulate debate and discussion with scholars and practitioners on the latest advances in emerging technologies and their application in the context of natural and man-made disasters, conflict situations and disease outbreaks including Covid 19.
This special issue invites scholars and practitioners to provide insights and contributions to the Operations and Supply Chain Management (O&SCM) field by considering the integration of emerging technologies for emergency situations. We expect that this special issue will bring substantial contributions to the field by answering the following research question: What are the challenges facing operations and supply chain managers when adopting, implementing, and diffusing emerging technologies in emergency situations?
Contributions will be welcome in the following areas:
1. Artificial Intelligence (AI): What organisational and supply chain capabilities are required to effectively utilize Artificial Intelligence in emergency situations? What coordination mechanisms are required to utilize AI in a post-disaster or conflict scenario? What capabilities and skills are needed by managers and field operatives utilizing this technology? How can Artificial Intelligence contribute to O&SCM performance improvement and value creation n emergency situations?
2. Blockchain: What is the role of blockchain in enhancing visibility and transparency in humanitarian supply chains? Which are the relevant blockchain applications in humanitarian operations? How can blockchain be used by operations managers to combat disease outbreaks during crises?
3. Big Data and Business Analytics: How can business analytics support humanitarian operations pre-and post-natural and man-made disasters. How can business analytics minimize human suffering caused by disease outbreaks? How can business analytics help the O&SCM field minimize the disturbances produced by supply chain disruptions?
4. Social Media. Is social media a useful technology in responding to supply chain disruptions? How can social media support O&SCM scholars in addressing natural and man made disasters? How are practitioners using social media to support healthcare operations in post-disaster situations?
5. 3D printing/Additive Manufacturing. How can 3D printing address the scarcity of medical supplies in disaster relief operations? What novel applications of 3D printing can be used to combat resource scarcity (water, food, etc.)? Is 3D printing a suitable emerging technology in refugee operations? What systems and processes are needed to support point-of-care manufacture of healthcare devices and medicines?
6. Internet of things: How can the internet of things be used to minimize human suffering during humanitarian operations, disease outbreaks and mitigation? How can the internet of things be used to address issues of resources scarcity in emergency situations?
7. Drones - How can drones use the smart cities infrastructure to respond to post-disaster situations? How can drones can be used in humanitarian operations? What are the ethical issues related to the usage of the drones in disaster relief operations?
8. Medical diagnostics, medicines and advanced therapies – How can advances in diagnostics address the need for rapid and accurate evaluation and/or monitoring/tracking of patient health? How can emerging technologies alleviate pressure on the availability of pharmaceuticals and vaccines in emergency scenarios? How are leading-edge advanced therapies being pioneered to address a range of injuries and health conditions associated with humanitarian support..
Types of papers to be published
In this special issue, we expect influential articles dealing with a range of emerging technologies for emergency situations using empirical quantitative and qualitative methodologies including (but not limited to) case studies, surveys, design science, action research, mixed-methods, etc. The papers must provide new insights and theoretical contributions to the O&SCM field and the sub-discipline of humanitarian and disaster relief operations. Moreover, we expect papers to utilize novel frameworks and theories to shed new light on the interplay between capabilities, coordination mechanisms, emergent technologies and emergency situations
Submission and review process
Papers must adhere to the normal author guidelines of the International Journal of Operations and Production Management, which can be found at https://www.emeraldgrouppublishing.com/journal/ijopm#author-guidelines. Submission must be made via Manuscript Central (https://mc.manuscriptcentral.com/ijopm) with clear selection indicating that the submission is for this Special Issue. Papers submitted to the Special Issue will be subjected to the normal thorough double-blind review process.
Deadline for paper submission: 30/11/2020
First review outcome by: 31/01/2021
Revised manuscript to be submitted by: 31/03/2021
Second review outcome by: 31/04/2021
Expected publication date of this Special Issue: 30/07/2021
Special Issue Editorial Team
Prof Samuel Fosso Wamba ([email protected]) lead guest editor), Ph.D., HDR, is a Professor at Toulouse Business School. His current research focuses on business value of IT, inter-organizational systems adoption and use, SCM, electronic commerce, blockchain, artificial intelligence in business, social media, business analytics, and big data. He has published papers in a number of journals including: Academy of Management Journal, European Journal of Information Systems, International Journal of Production Economics, International Journal of Production Research, Technological Forecasting and Social Change, Journal of Business Research, Production Planning & Control, Information Systems Frontiers, Electronic Markets, Proceedings of the IEEE. He is an Associate Editor of International Journal of Logistics Management information and The Electronic Markets. He is the Coordinator of the Artificial Intelligence & Business Analytics Cluster of Toulouse Business School, France.
Prof. Maciel M. Queiroz ([email protected]), Ph.D., is a Professor and Researcher of Operations and Supply Chain Management at Universidade Paulista – UNIP. His current research focuses on Digital supply chain capabilities, Industry 4.0, AI, blockchain, big data, and IoT. He has published papers in top-tier international journals and conferences, including IJIM, IJLM, SCMIJ, BIJ, EQM, among others. Also, his research appeared in the Proceedings of the IFAC-MIM, IMAM, TMS, ISL. He serves as a reviewer for top-tier international journals and AOM. Dr. Maciel has been serving as a Guest Co-Editor for the International Journal of Information Management, on the topic “Blockchain in the Operations and Supply Chain Management”, Production Planning and Control on the topic “Industry experiences of Artificial Intelligence (AI): benefits and challenges in operations and supply chain management”. Also, he served as a co-chair in Artificial Intelligence topics for various conferences, including itAIS & MCIS 2019 and IFIP WG8.6 2020.
Dr. Samuel Roscoe ([email protected]) is a Senior Lecturer in Operations Management and teaches in the areas of Operations and Supply Chain Management. Sam has published in the Journal of Operations Management on digital manufacturing in the aerospace sector. He has also published on dynamic supply chain capabilities in the International Journal of Operations and Production Management (IJOPM) and local volunteerism in disaster relief situations with the International Journal of Production Research (IJPR). Sam received funding from the EPSRC to investigate how 3D printing in reconfiguring pharmaceutical supply chains; moving production closer to patients and consumers. Sam's research interests are on how emerging technologies (3D printing, Blockchain, Artificial Intelligence) are reconfiguring global supply chains. He is the research leader for the Supply Chain 4.0 Hub at the University of Sussex Business School.
Prof Wendy Phillips ([email protected]), Ph.D., is Professor of Innovation at the University of the West of England. She has a multi-disciplinary background in science and management and have spent over 15 years advancing the disciplines of innovation studies and supply chain management. Her research impacts policy and practice. Wendy’s experience includes leading and contributing to large scale collaborative research projects such as EPSRC funded RiHN (www.RiHN.org.uk); HEFCE study of Strategic Sourcing in UK Higher Education Institutions; EPSRC and ESRC funded research on innovation in supply networks. She has published papers in a number of journals and conferences including: Journal of Business Ethics, International Journal of Production Research, Production Planning and Control and the International Journal of Operations and Production Management.
Dr Dharm Kapletia ([email protected]) is Senior Research Fellow at the University of the West of England, specialising in Technology and Innovation Management. He is also a Fellow of the Schumacher Institute for Sustainable Systems in Bristol. Dharm has worked in various research, analytical and consulting roles, for organisations such as Jisc, ADS Group, Hewlett–Packard Laboratories and the UK Ministry of Defence. He has contributed to UK and European innovation and transformation programmes and agendas in healthcare, defence and cyber security. He holds an industry-sponsored PhD from the Engineering Department at the University of Cambridge and his main research interests include managing innovation in complex systems, as well as science and engineering policy and industrial transformation.
Prof Arash Azadegan ([email protected]), Ph.D., is a Professor at Rutgers Business School. Dr. Azadegan focuses on research related to supply chain disruptions, response and recovery from disruptions and inter-organizational creativity and innovation. Dr. Azadegan manages the Supply Chain Disruption Research Laboratory (SCDrl) at the Center for Supply Chain Management. Dr. Azadegan's work is published in the Journal of Operations Management, Production and Operations Management Journal, Journal of Supply Chain Management, R&D Management Journal, Journal of Purchasing and Supply Management and International Journal of Operations and Production Management. He is currently working on several projects related to disruption recovery and response management practices of supply chains.
For further information or queries regarding the special issue, please do not hesitate to contact the lead editor via e-mail and cc the other editors.
Baryannis, G. et al. (2019) ‘Supply chain risk management and artificial intelligence: state of the art and future research directions’, International Journal of Production Research, 57(7), pp. 2179–2202. doi: 10.1080/00207543.2018.1530476.
Dubey, R. et al. (2019) ‘Big data analytics and organizational culture as complements to swift trust and collaborative performance in the humanitarian supply chain’, International Journal of Production Economics. Elsevier B.V., 210(January), pp. 120–136. doi: 10.1016/j.ijpe.2019.01.023.
Dwivedi, Y. K. et al. (2019) ‘Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy’, International Journal of Information Management. Elsevier, (July), p. 101994. doi: 10.1016/j.ijinfomgt.2019.08.002.
De Giovanni, P. (2019) ‘When feature-based production capabilities challenge operations: Drivers, moderators, and performance’, International Journal of Operations and Production Management. doi: 10.1108/IJOPM-04-2019-0309.
Islam, N. et al. (2018) ‘Here there be dragons, a pre-roadmap construct for IoT service infrastructure’, Technological Forecasting and Social Change, 5(3), p. 119073. doi: 10.1016/j.techfore.2017.09.016.
Ivanov, D. (2019) ‘“A blessing in disguise” or “as if it wasn’t hard enough already”: reciprocal and aggravate vulnerabilities in the supply chain’, International Journal of Production Research, pp. 1–11. doi: 10.1080/00207543.2019.1634850.
Kache, F. and Seuring, S. (2017) ‘Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management’, International Journal of Operations & Production Management, 37(1), pp. 10–36. doi: 10.1108/IJOPM-02-2015-0078.
Kapletia, D. et al. (2019) ‘Redistributed manufacturing – challenges for operations management’, Production Planning & Control, 30(7), pp. 493–495. doi: 10.1080/09537287.2018.1540057.
Koh, L., Orzes, G. and Jia, F. (Jeff) (2019) ‘The fourth industrial revolution (Industry 4.0): technologies disruption on operations and supply chain management’, International Journal of Operations & Production Management, 39(6/7/8), pp. 817–828. doi: 10.1108/IJOPM-08-2019-788.
Lam, H. K. S. et al. (2019) ‘The impact of 3D printing implementation on stock returns: A contingent dynamic capabilities perspective’, International Journal of Operations and Production Management, 39, pp. 935–961. doi: 10.1108/IJOPM-01-2019-0075.
Li Da Xu, Eric L. Xu & Ling Li (2018) Industry 4.0: state of the art and future trends, International Journal of Production Research, 56:8, 2941-2962, DOI: 10.1080/00207543.2018.1444806
Lima-Junior, F. R. and Carpinetti, L. C. R. (2019) ‘Predicting supply chain performance based on SCOR ® metrics and multilayer perceptron neural networks’, International Journal of Production Economics. Elsevier B.V., 212(January), pp. 19–38. doi: 10.1016/j.ijpe.2019.02.001.
Matthias, O. et al. (2017) ‘Making sense of Big Data – can it transform operations management?’, International Journal of Operations & Production Management, 37(1), pp. 37–55. doi: 10.1108/IJOPM-02-2015-0084.
Nosek, J. T. and McNeese, M. D. (1997) ‘Augmenting group sense making in ill‐defined, emerging situations’, Information Technology & People, 10(3), pp. 241–252. doi: 10.1108/09593849710178216.
Phillips, W., Medcalf, N., Dalgarno, K., Makatoris, H., Sharples, S., Srai, J., Kapletia, D. (2018) White Paper: Redistributed manufacturing in healthcare: Creating new value through disruptive innovation. UWE: Bristol, UK
Queiroz, M. M. et al. (2019) ‘Industry 4.0 and digital supply chain capabilities’, Benchmarking: An International Journal, ahead-of-p(ahead-of-print). doi: 10.1108/BIJ-12-2018-0435.
Ramanathan, U., Subramanian, N. and Parrott, G. (2017) ‘Role of social media in retail network operations and marketing to enhance customer satisfaction’, International Journal of Operations and Production Management, 37(1), pp. 105–123. doi: 10.1108/IJOPM-03-2015-0153.
Roscoe S., Cousins, P., Handfield, R. (2019). “The Microfoundations of an Operational Capability in Digital Manufacturing “. Journal of Operations Management. 65 (8) pp. 774-793
Ryman-tubb, N. F., Krause, P. and Garn, W. (2018) ‘Engineering Applications of Artificial Intelligence How Artificial Intelligence and machine learning research impacts payment card fraud detection : A survey and industry benchmark’, 76(July), pp. 130–157.
Sarkis, J. (2012) ‘Models for compassionate operations’, International Journal of Production Economics, 139, pp. 359–365. doi: 10.1016/j.ijpe.2012.06.018.
Syam, N. and Sharma, A. (2018) ‘Waiting for a sales renaissance in the fourth industrial revolution: Machine learning and artificial intelligence in sales research and practice’, Industrial Marketing Management, 69(January), pp. 135–146. doi: 10.1016/j.indmarman.2017.12.019.
Teece, D. J., Pisano, G. and Shuen, A. M. Y. (1997) ‘Dynamic Capabilities and Strategic Management’, Strategic Management Journal, 18(7), pp. 509–533.
Wamba, S. F. and Queiroz, M. M. (2020) ‘Blockchain in the operations and supply chain management: Benefits, challenges and future research opportunities’, International Journal of Information Management, p. 102064. doi: 10.1016/j.ijinfomgt.2019.102064.
Zhu, Q., Krikke, H. and Caniëls, M. C. J. (2018) ‘Supply chain integration: value creation through managing inter-organizational learning’, International Journal of Operations and Production Management, 38(1), pp. 211–229. doi: 10.1108/IJOPM-06-2015-0372.