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Submit a Manuscript to the Journal
International Journal of Logistics Research and Applications

For a Special Issue on
Data Mining and Data Warehousing for Logistics & Supply Chain Management

Manuscript deadline
05 April 2022

Cover image - International Journal of Logistics Research and Applications

Special Issue Editor(s)

Jerry Chun-Wei Lin (Lead Guest Editor), Western Norway University of Applied Sciences, Norway
[email protected]

Gautam Srivastava, Brandon University, Canada
[email protected]

Yu-Dong Zhang, University of Leicester, UK
[email protected]

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Data Mining and Data Warehousing for Logistics & Supply Chain Management

Data mining and Data warehousing are the two most prominent technologies that can make sense only if they are thoughtfully implemented. In logistics and supply chain management, these two techniques have emerged as an essential tool to integrate complex networks associated with the supply chain (inventory, production management, etc.) and improve their core value and abilities. In general, the modern supply chain and logistics require an efficient flow of data all the time. Practically speaking, big data has made an immense impact on logistics and supply chain by changing the way how the business operates and effectively controlling the numerous processes associated with it. This is mainly because the complex and dynamic nature of the logistics, together with many moving parts, can create a bottleneck at any point of the supply chain. Further, when the business starts to scale, many of the challenges they encounter are mainly due to added operational complexity and lack of visibility. To effectively mitigate these challenges, many business organizations rely on key performance indicators (KPI) to make informed decisions about the entire business process. However, operational data becomes useless in its raw state, and data mining and data warehousing are crucial to make the data informative and actionable.

The process of collecting, sorting, and analyzing a sheer volume of data from various sources all at once helps organizations discover valuable patterns and trends in logistics and supply chain management. Data warehousing and data mining are strategically crucial in enterprise decision making as they help build a more robust supply chain network. It allows businesses to compile and organize data from multiple sources into one common database. It then assesses large data sets and databases using algorithms to extract meaningful patterns from the data and build a reserve of actionable information. These techniques have become more important for manufacturing companies as they need to fulfil the needs and expectations of their customers.  If effectively implemented, it can keep up with rapidly changing customer demands, effectively deal with delays and disruptions, provide well-defined planning, improve automation, reduce the cost for transportation, remove the diversity among the sales channels, manage the complex data efficiently, and offer more visibility. More advanced research is required in this background to find out the more opportunities that data mining and data warehousing provides for logistics and supply chain. In this special issue, we briefly examine data warehousing and data mining techniques and their application in logistics and supply chain to efficiently review data, improve services, reduce costs, and streamline logistics and supply chain operations. Researchers working in this discipline are most invited to present their findings.

This special issue invites research on following themes, but not limited to:

  • Innovations in data mining and data warehousing for logistics and supply chain management
  • Role of data warehousing and data mining in supply chain operations
  • Data mining for optimization of supply chain
  • Applications and emerging trends in data warehousing and data mining for logistics and supply chain management
  • Data mining for business intelligence and demand forecasting
  • Financial business forecasts with data mining algorithms
  • Data warehousing and data mining in procurement and contract management
  • Data mining for optimization of warehouse operations
  • Data mining for shipment tracking and transportation maintenance
  • Data warehousing and data mining for order and inventory management
  • Data warehousing and data mining and its revolutionary impact on logistics and supply chain management
  • Intelligent decision making in supply chain management with data mining and data warehousing

Submission Instructions

Full manuscript submission by: 05 April 2022

Screening and review process will begin once the submission has been made.
Final manuscript decision: As soon as the manuscript has been accepted for publication, it will become available online. The final volume and issue number will be assigned after the deadline of the submission as stated above.

Manuscripts will be subject to a rigorous review process under the supervision of the Guest Editors and Editor-in-Chief, and accepted papers will be published online before print publication. Regarding the submission guidelines and other details, authors should refer to the details on the journal website.

Please make sure you select the SI you are submitting to when prompted in the submission portal.

Instructions for AuthorsSubmit an Article