期刊信息

Decision Support Systems (DSS)

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影响因子:
6.8
出版商:
Elsevier
ISSN:
0167-9236
浏览:
36998
关注:
24
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征稿

Decision Support Systems (DSS) is an academic journal published by Elsevier. (ISSN 0167-9236, impact factor 6.8, CCF C).

The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs). Manuscripts may draw from diverse methods and methodologies, including those from decision theory, economics, econometrics, statistics, computer supported cooperative work, data base management, linguistics, management science, mathematical modeling, operations management, cognitive science, psychology, user interface management, and others. However, a manuscript focused on direct contributions to any of these related areas should be submitted to an outlet appropriate to the specific area. Examples of research topics that would be appropriate for Decision Support Systems include the following: 1. DSS Foundations e.g. principles, concepts, and theories of enhanced decision making; formal languages and research methods enabling improvements in decision making. It is important that theory validation be carefully addressed. 2. DSS Functionality e.g. methods, tools, and techniques for developing thefunctional aspects of enhanced decision making; solver, model, and/or data management in DSSs; rule formulation and management in DSSs; DSS development and use in computer supported cooperative work, negotiation, research and product. 3. DSS Interfaces e.g. methods, tools, and techniques for designing and developing DSS interfaces; development, management, and presentation of knowledge in a DSS; coordination of a DSS's interface with its functionality. 4. DSS Implementation - experiences in DSS development and utilization; DSS management and updating; DSS instruction/training. A critical consideration must be how specific experiences provide more general implications. 5. DSS Evaluation and Impact e.g. evaluation metrics and processes; DSS impact on decision makers, organizational processes and performance.
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