Manuscript Topics

There has been a rapid development of new technologies and innovative uses of existing and emerging technologies that hold rapid promise for enhanced logistics and supply chain solutions. The movement of goods has always been aided by technology, whether by early adoptions of barcodes and information systems to track locations of goods in warehouse management systems, through to radio frequency identification (RFID) applications, through to enhancements in predictive analytics using big data for fulfilment and e-commerce.

The wide use of these technologies provides new opportunities to large scale businesses to extend their competitive advantages. However, they also provide smaller firms with new capabilities and the opportunity to achieve outcomes once that domain of dominant firms and scale these technologies rapidly. Further, they provide the opportunity for niche specialist firms to develop and provide new services to clients.

The aim of this Special Issue is to provide an overview of the state-of-the-art research and engineering developments that outline how big data analytics applications can address emerging logistics and supply chain issues. Submissions should embrace and extend big data analytics applications to resolve issues various issues that may include efficiencies, risk mitigation, and sustainability. Given this context, we welcome systematic reviews, case studies, surveys, simulation models, and mathematical models that address implementation, management, assessment, and optimization in big data analytics for smart logistics & supply chains.

Keywords:
Big data; Predictive analytics; Applied industrial technology; Artificial intelligence; Internet of things; Industry 4.0; Smart logistics; Natural language processing; smart business models; Big data and sustainability

Instructions for authors
https://www.aimspress.com/mbe/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
https://aimspress.jams.pub/