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Journal of Business Analytics - New Journal Announcement

We are delighted and excited to announce the launch of the Journal of Business Analytics, an official journal of the Operational Research Society.  With this announcement, we the co-editors of this journal are inviting you to submit one of your best analytics works for the consideration in the inaugural issue of the journal, which is scheduled to be released in June 2018.

Online Access

 
Members can LOGIN AT THE TOP OF THE SCREEN,
to see the new edition, which is scheduled to be released in June 2018.

 

Full papers are only accessible to paying members of the Society. If you are a member and do not yet have your username and password please click here. If you have forgotten your login details, please click here.

Non-members who have registered with the website (e.g. as part of submitting an abstract, or booking a conference) do not have access to full Journal of Business Analytics papers. Membership subscription details can be found here.

Journal of Business Analytics - Scope

The mission of the Journal of Business Analytics is to serve the emerging and rapidly growing community of business

analytics both in academia and industry. The journal aims to do this by publishing solutions to business problems, developing innovative business analytics methods and methodologies, and by using real-world data to show the how the problems in business analytics can be solved.

Contributions can include addressing an important problem in a new and innovative way, repurposing existing heterogeneous data, and/or developing and demonstrating the use of new analytics tools, techniques, methods and methodologies.  A representative list of topic areas includes:

  • AI, Deep Learning, and machine learning in business analytics
  • Statistical approaches in business analytics
  • Econometrics in business analytics
  • Emerging areas of network science and large scale graph analysis for business problems
  • Field Experiments and Field studies combining prediction and prescriptive analyses
  • Integrating Statistical and machine learning for business analytics
  • Data quality issues and innovative solutions
  • Innovative business analytics development methodologies
  • Organizational and behavioral aspects of business analytics
  • Use of other types of data science techniques in business analytics, as long as they are evaluated rigorously using real-world datasets

Our editorial philosophy is to publish papers that contribute to theory and practice. Once your paper has been assessed for suitability by the editor, it will then be peer-reviewed by independent, expert referees. You can find more information on our editorial policies at Instructions for Authors page.

For questions, comment, and suggestions, please feel free to contact the Editors:

Dr. Sudha Ram (ram@eller.arizona.edu)
Dr. Dursun Delen (dursun.delen@okstate.edu)