Editor in Chief

  • Madjid Tavana, La Salle University

Articles

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Aims & scope

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The Decision Analytics journal is a forum for exchange of research findings, analysis, information, and knowledge in areas which include but are not limited to:

  • Data Mining - Decision Analytics journal seeks research articles that show how to utilize a wide range of statistical methods, data visualization techniques, and pattern recognition approaches to help decision-makers leverage the knowledge hidden within organizational data.
  • Predictive Modeling - Decision Analytics journal encourages research endeavors that identify organizational risks and opportunities by exploiting patterns found in historical and transactional data.
  • Simulation Modeling - Decision Analytics journal promotes application of simulation in enterprise and organizational context for examining and comparing options and scenarios prior to implementation.
  • Optimization Modeling - Decision Analytics journal promotes research that can help decision-makers make the best choice by means of various optimization models.
  • Prescriptive Methods - Decision Analytics journal invites research that supports the joint application of predictive models and optimization technology to create better solutions for decision-makers.
  • Business Intelligence - Decision Analytics journal invites research that utilizes the latest techniques in data mining, analysis, and performance management to help decision-makers gain and sustain a competitive edge.

Editor profile

Madjid Tavana

Madjid Tavana

Editor-in-Chief

Madjid Tavana is a Professor of Business Systems and Analytics and the Lindback Distinguished Chair of Information Systems and Decision Sciences at La Salle University where he served as Chairman of the Management Department and Director of the Center for Technology and Management. He has been a Distinguished NASA Research Fellow at Kennedy Space Center, Johnson Space Center, Naval Research Laboratory - Stennis Space Center, and Air Force Research Laboratory.
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ISSN: 2193-8636