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Business & Management - Operations Research & Decision Theory | Decision Analytics - a SpringerOpen journal

Decision Analytics

Decision Analytics

Editor-in-Chief: Madjid Tavana

ISSN: 2193-8636 (electronic version)

Journal no. 40165

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Decision Analytics is a peer-reviewed open access journal published under the brand SpringerOpen.
 
Decision Analytics promotes the applications of computer technology, operations research, statistics, and simulation to decision-making and problem-solving in all organizations and enterprises within the private and public sectors. The journal focuses on predictive as well as prescriptive analytics taking organizations to a higher degree of intelligence and competitive advantage. While predictive analytics, such as forecasting, emphasize the future, prescriptive analytics, such as optimization, enable organizations to choose the best course of action. The combination of predictive and prescriptive analytics can help organizations achieve both efficiency and effectiveness.
 
The principal objective of Decision Analytics is to establish a forum among academic researchers, policy-makers, and practitioners concerned with the development of new methodologies to formulate and solve organizational problems by applying decision analytics methods. The journal provides a publication vehicle for theoretical, empirical, and analytical research as well as real-world applications and case studies. Papers published in Decision Analytics should not only meet high standards of research rigor and originality in decision analysis, but they should also embrace predictive and prescriptive analytics.
 
The journal is a forum for exchange of research findings, analysis, information, and knowledge in areas including but not limited to Data Mining, Predictive Modeling, Simulation Modeling, Optimization Modeling, Prescriptive Methods, and Business Intelligence.

Related subjects » Business & Management - Operations Research & Decision Theory

Abstracted/Indexed in 

Google Scholar, DBLP, DOAJ, EBSCO Applied Science & Technology Source, EBSCO Discovery Service, EBSCO STM Source, OCLC, Summon by ProQuest

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  • Aims and Scope

    Aims and Scope

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

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