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International Journal of Decision Support System Technology - IGI Global | 2024 Impact Factor:0.6 | Cite Score:2.6 | Q3

International Journal of Decision Support System Technology With Cite Score

Cite Score and Journal Rank of International Journal of Decision Support System Technology

  • About: International Journal of Decision Support System Technology (IJDSST) is a peer-reviewed journal that focuses on the development and application of decision support systems (DSS) technologies. It serves as a platform for researchers, practitioners, and professionals to share innovative research, methodologies, and applications in the field of decision support systems.
  • Objective: The primary objective of IJDSST is to advance the theory and practice of decision support systems technology by covering a broad range of topics, including DSS architecture, decision modeling, data analysis, business intelligence, and artificial intelligence applications in decision-making. The journal aims to provide insights into the design, implementation, and evaluation of decision support systems that aid in complex decision-making processes across various domains.
  • Interdisciplinary Approach: The journal adopts an interdisciplinary approach by integrating research from fields such as computer science, information systems, management science, operations research, and artificial intelligence. This approach allows IJDSST to address diverse challenges related to decision support systems, including the integration of advanced technologies, data analytics, and user-centric design. Contributions that explore the intersection of decision support systems with emerging technologies and applications are particularly encouraged.
  • Impact and Significance: The International Journal of Decision Support System Technology holds significant impact in both academic and professional communities. The research published in the journal contributes to the development of innovative DSS technologies and methodologies, helping organizations improve decision-making processes and achieve better outcomes. The journal provides valuable resources for professionals involved in designing and using decision support systems, as well as for researchers seeking to advance the field through theoretical and applied research.

  • Editor-in-Chief:  Shaofeng Liu

  • Scope: The International Journal of Decision Support System Technology focuses on the development, application, and advancement of decision support systems (DSS) and related technologies. The journal covers a broad range of topics, including but not limited to:
  • 1. Decision Support Systems (DSS): Research on the design, implementation, and evaluation of DSS, including tools and methodologies for supporting decision-making processes.
  • 2. Business Intelligence and Analytics: Techniques and technologies for business intelligence, data analysis, and data-driven decision-making.
  • 3. Decision-Making Models: Theoretical and practical models for decision-making, including optimization models, simulation models, and multi-criteria decision analysis.
  • 4. Data Mining and Knowledge Discovery: Methods for extracting valuable information from large datasets, including data mining techniques and knowledge discovery processes.
  • 5. Artificial Intelligence and Machine Learning: Applications of AI and machine learning in decision support systems, including predictive analytics and intelligent decision-making.
  • 6. Human-Computer Interaction (HCI): Design and evaluation of user interfaces and interaction techniques for decision support systems.
  • 7. Geographic Information Systems (GIS) and Spatial Decision Support: Integration of spatial data and GIS technologies in decision support systems for spatial analysis and planning.
  • 8. Decision Support in Specific Domains: Applications of DSS in various fields such as healthcare, finance, logistics, and environmental management.
  • 9. System Integration and Implementation: Challenges and solutions related to the integration and implementation of decision support systems in organizational environments.
  • Latest Research Topics for PhD in Computer Science
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  • Print ISSN:  19416296

    Electronic ISSN:  1941630X

  • Abstracting and Indexing:  Scopus

  • Imapct Factor 2024:  0.6

  • Subject Area and Category:   Computer Science, Computer Science (miscellaneous), Mathematics, Modeling and Simulation

  • Publication Frequency:  Quarterly

  • H Index:  16

  • Best Quartile:

    Q1:  

    Q2:  

    Q3:  Computer Science (miscellaneous)

    Q4:  

  • Cite Score:  2.6

  • SNIP:  0.442

  • Journal Rank(SJR):  0.234