Decision-making in business operations is crucial for the success and sustainability of an organization. It involves analysing various factors and data to make informed choices that affect the growth, profitability, and reputation of the business. Effective decision-making can increase efficiency, productivity, and innovation, while poor decision-making can result in financial losses, reduced market share, and reputational damage.

Effective decision-making in business operations is essential for businesses to align their operations with sustainable development goals set by the United Nations. By making informed decisions based on data-driven insights, businesses can improve their efficiency, reduce waste, and contribute to a more sustainable future, positively impacting the environment, social responsibility, and economic growth. Incorporating United Nations goals into decision-making processes can also help businesses address global challenges such as poverty, hunger, climate change, and inequality, creating a positive impact on society and the environment.

AI-powered technologies have the potential to automate business processes, recognise patterns and trends in data, and forecast outcomes. This can lead to increased efficiency, reduced costs, and improved profits. Furthermore, AI can enable businesses to identify and react to risks and opportunities in real time, enabling them to remain competitive in the constantly evolving business environment.

The primary objective of this special session is to offer guidance on how businesses can use big data and AI techniques to make informed decisions, improve their operations, and achieve their objectives. The session will highlight innovative methods and practical examples that can assist businesses in staying competitive in the ever-changing digital world.

This special session topics include (but are not limited to):

  • Natural language processing for business operations
  • Business intelligence
  • AI and big data for fraud detection in business operations
  • Data-driven decision-making
  • Optimisation of pricing strategies using big data and AI
  • Clinical decision support systems using AI and big data
  • Cybersecurity and data privacy
  • AI-enabled risk management in business operations
  • Medical image analysis and computer-aided diagnosis
  • AI supporting sustainable development

Important Dates

  • Special Session Papers Submission: 29 July 2023
  • Acceptance Notification: 15 September 2023
  • Author Registration: 1 October 2023
  • Camera-Ready Submission: 1 October 2023

Paper submission instruction

Paper submission system is available at: https://easychair.org/conferences/?conf=besc2023.

All papers will be reviewed by the Program Committee on the basis of technical quality, relevance to BESC 2023, originality, significance and clarity.

Please note:

  • All submissions should use IEEE two-column style. Templates are available from here.
  • All papers must be submitted electronically through the paper submission system in PDF format only. BESC 2023 accepts special session papers (6 pages).
  • The page count above excludes the references.
  • Paper review will be double-blind, and submissions not properly anonymized will be desk-rejected without review.
  • Submitted papers must not substantially overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings.
  • Papers must be clearly submitted in English and will be selected based on their originality, timeliness, significance, relevance, and clarity of presentation.
  • Submission of a paper should be regarded as a commitment that, should the paper be accepted, at least one of the authors will register and attend the conference to present the work.
  • Accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore’s scope and quality requirements and indexed by EI. Top quality papers after presented in the conference will be selected for extension and publication in several special issues of international journals, e.g., World Wide Web Journal (Springer), Web Intelligence (IOS Press), and Social Network Analysis and Mining (Springer), Human-Centric Intelligent Systems (Springer), Information Discovery and Delivery (Emerald Publishing).
  • (NEW) The use of artificial intelligence (AI)–generated text in an article shall be disclosed in the acknowledgements section of any paper submitted to an IEEE Conference or Periodical. The sections of the paper that use AI-generated text shall have a citation to the AI system used to generate the text.


Abdul Wahid, University of Galway, Ireland (abdul.wahid[at]universityofgalway.ie)

Jitesh Pradhan, National Institute of Technology Jamshedpur, India (jiteshpradhan.cse[at]nitjsr.ac.in)

Prasun Chandra Tripathi, University of Sheffield, UK (p.c.tripathi[at]sheffield.ac.uk)

Program Committee Members (TBC)

  • Rafik BELLOUM, Université Polytechnique Hauts-de-Franc, France
  • Sandeep Singh Senger, Cardiff Metropolitan University, UK
  • Pratik Dutta, STONY BROOK University, USA
  • Bimal Mandal, Indian Institute of Technology Jodhpur, India
  • Oumaima Jrad, Universite de Haute-Alsace, Mulhouse, France
  • Rakesh Kumar Sanodiya, Indian Institute of Information Technology Sri City, India
  • Prabhat Dhansena, Siksha o Anusandhan Institute, India
  • Aryan M. P, University of Sheffield, UK
  • Ajay Pratap, Indian Institute of Technology Varanasi, India
  • Gurjot Singh Gaba, Linköping University, Sweden
  • Himanshu Sharma, Aalborg University, Denmark
  • Ramesh Kumar, SRM University, AP