Leveraging Emerging Technologies in Supply Chain Management
Guest Editors
Imran Razzak (Lead guest editor)
Course Director, Grad Cert. Supply Chain
Senior Lecturer of Machine Learning
Deakin University, Victoria, Australia.
Email: imran.razzak@deakin.edu.au
Roberto Perez-Franco
Senior Research Fellow - Supply Chain Strategy
Centre for Supply Chain and Logistics
Deakin University, Victoria, Australia.
Email: roberto.perezfranco@deakin.edu.au
Peter Eklund
Professor of AI and Blockchain,
School of Information Technology,
Deakin University, Victoria, Australia.
Email: peter.eklund@deakin.edu.au
The Industrial sector is going through a transformational wave of automation and digitization. The supply chain and logistics industry is confronting similar circumstances. New, emerging technologies are being introduced in the industry. Taking data use one step further, the same technologies can anticipate future behavior and enable businesses to be proactive. By enabling machine learning capabilities and predictive analytics, businesses can ensure that demand can be met with minimal costs. For example, it is possible to anticipate the demand through historical data. It could be seasonal, or even more ad-hoc – based on predicted environmental conditions. With the right inventory systems in place, it’s possible to identify if sufficient inventory is available to meet the expected rise in demands, and if not, the system automatically starts adjusting the orders with suppliers to source the raw materials to overcome the anticipated future high demand.
Traditional ways of managing the supply chain are gradually being replaced by innovative ones – many of which feature emerging technologies, such as Big Data analytics, social media, Internet of Things (IoT), Machine Learning, and Blockchain. With the use of emerging technologies, organizations can prepare to meet the expected demand. This can prevent a surplus of inventory and prove to be a vital cost-saving measure in the long term.
Topics of Interest:
This special issue will focus on development of novel emerging technologies to improve the current methodologies in logistics and supply chain sector. We aim to gain a deeper understanding of how the adoption of emerging technologies helps companies to enhance responsiveness, resilience, and restoration in supply chains. We invite researchers working on practical use-cases of emerging technologies in supply chain. We are looking for research papers based on experimental or theoretical novel contributions related to supply chain management including, but not limited to, the following:
- Machine Learning for supply chain
- Big Data analytics in supply chain
- Product forecasting
- Planning product assortments and recommendation
- Dynamic resource allocation
- Using browsing and/or sensor data to manage inventory and replenishment
- Strategies to improve supply chain operations
- Vehicle loading, routing, and monitoring safety (optimization that incorporates real-time data)
- Managing and mitigating supply chain risk
- Supplier risk assessment, evaluation, and supplier portfolio development
- Managing after-sales service
All manuscripts submitted must be original, not under consideration elsewhere, and not previously published. The peer-review process is designed to avoid bias and conflict of interest on the part of reviewers and is composed of experts in the relevant field of research. A key criterion in publication decisions will be the manuscript’s fit for the special issue. Papers will be published online as soon as accepted.
Deadline for submissions: February 26, 2022
Submission Guidelines
Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. Paper submissions for this special issue should follow the submission format and guidelines. Paper submissions for this special issue should follow the submission format and guidelines.