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Business Intelligence in Supply Chain Management

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Management".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 466

Special Issue Editor

Faculty of Technical Sciences, University of Kragujevac, 32000 Cacak, Serbia
Interests: supply chain management; B2B; business intelligence; data mining; machine learning; big data

Special Issue Information

Dear Colleagues,

Due to globalization and other market factors, supply chains are one of the key business systems. They not only need to be economically efficient, but also need to be sustainable and improve social and environmental impact. This creates many supply chain management (SCM) challenges that can only be resolved with more intelligent decision-making. This involves incorporating the advanced big data analytical systems capable to integrate, store, process, and analyze large volumes of data, with different formats and speeds.

During the past two decades, organizations have made large investments in SCM and business-to-business (B2B) enterprise systems to improve their businesses and to achieve sustainability. However, these systems usually provide only transaction-based functionality and mostly maintain an operational view of the business. They lack the sophisticated analytical capabilities required to provide an integrated view of the supply chain networks.

Supply chains networks are complex systems with silos of information that are very difficult to integrate and analyze. The best way to effectively analyze and manage such complex business networks is the use of business intelligence (BI). Traditional BI and analytical systems face many challenges that include processing of vast data volumes, demand for real-time analytics, enhanced decision making, insight discovery, and optimization of supply chain processes. Data science, machine learning, and big data initiatives promise to answer these challenges by incorporating various methods, tools, and services for more agile and flexible analytics and decision making.

Nevertheless, the potential value of BI in supply chain management and B2B has not yet been fully realized and requires establishing new BI infrastructures, architectures, models, and tools.

The aim of this Special Issue is to explore state-of-the-art research and developments in SCM business intelligence and analytics, and to advance methods, platforms, models, and tools for more intelligent and proactive decision making that can lead to more efficient and sustainable supply chains.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not be limited to) the following:

  • Business intelligence in SCM and B2B processes;
  • CRM (customer relationship management) analytics;
  • Big data analytics in SCM;
  • Data science applications in SCM/B2B;
  • Application of data mining and machine learning in SCM and B2B processes;
  • Advanced analytics in plan, source, make, deliver, and return supply chain processes;
  • Cloud-based analytics in SCM and B2B;
  • Real-time analytics in SCM and B2B based on IoT technologies;
  • Performance monitoring and intelligent decision making;
  • Data visualization and reporting;
  • Digital assistants and bots in SCM/B2B;
  • Blockchain and analytics for sustainable SCM;
  • Analytics in sustainable and green SCM.

I look forward to receiving your contributions.

Prof. Dr. Nenad Stefanovic
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • business intelligence
  • supply chain management
  • green supply chain
  • sustainable supply chains
  • big data
  • data mining
  • machine learning
  • data science

Published Papers

There is no accepted submissions to this special issue at this moment.
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