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.
Madjid Tavana (January 2017)
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