Aims and Scope

This journal publishes peer-reviewed contributions on the full lifecycle of Decision Support Systems, from foundational theory and methodological innovation to system development, empirical evaluation, and real-world application, with emphasis on technical rigor, interdisciplinary collaboration, practical impact, and societal relevance.

The journal welcomes work in the following areas (including but not limited to):

• Model-Driven DSS
  e.g. MCDM, AHP/ANP, optimization, simulation, and other quantitative decision methods

• Data- & Knowledge-Driven DSS
  e.g. data mining, predictive analytics, expert systems, fuzzy/neural approaches, and emerging AI techniques

• Intelligent & Emerging DSS
  e.g. reinforcement learning, metaheuristics (GA, PSO), cognitive architectures, explainable AI, and other novel algorithms

• Document & Communication-Driven DSS
  e.g. NLP, text mining, visualization, collaborative/group decision systems, and other interaction-based tools

• Domain-Specific & Spatial DSS
  e.g. GIS-based systems, clinical decision support, supply-chain/logistics, smart cities, environmental management, and other application domains

• Innovative Technologies in DSS
  e.g. IoT-enabled decision engines, digital twins, blockchain-based DSS, crowdsourcing platforms, and other technological trends

• Other Relevant Topics
  Any research advancing DSS theory, methods, evaluation, or practice not explicitly listed above