Next-Generation Decision Support Systems: Integrating Artificial Intelligence, Machine Learning, Big Data Analytics, and Intelligent Information Systems

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Khan Khilji N., Safaei M., Alamassi S., Quispemamani N. U., Al-Shaybani A., Israilova I.

Computer and Decision Making, cilt.3, sa.1s, ss.275-286, 2026 (Scopus)

Özet

Decision support systems are moving from model-and data-driven systems to integrated intelligent environments where complex, dynamic and information-rich decisions can be supported.  This  integrative  review  examines  the  combined  contribution  of  artificial intelligence,  machine  learning,  big  data  analytics,  and  intelligent  information  systems  to the  development  of  next-generation  decision  support  systems.  The  literature  reviewed indicates that AI and machine learning can enhance prediction, reasoning, automation and adaptive learning, and big data analytics can facilitate the processing of large-scale, real-time  and  heterogeneous  data.  Information  systems  with  intelligence  play  a  role  in  the organization,  contextualization  and  integration  of  knowledge  in  the operational  and strategic  decision-making  process.  The  review  also  emphasizes  the  need  to  integrate  all these features in a single architecture for connecting data acquisition, analytics, intelligent modelling, contextual information, user interaction, andhuman oversight. Advanced DSS has  strategic  applications  in  sectors  such  as  healthcare,  finance,  manufacturing,  supply chains,   transportation,   and   agriculture,   to   name   a   few.   Significant   difficulties   in explainability, data quality, interoperability, scalability, trust and organizational readiness persist. Future research should focus on more integrated, human-centered, and adaptive DSS, using more robust evaluation frameworks, and more standardized and cross-domain validation. The general trend of next-generation DSS technologies should be a focus on not only computational abilities but also clarity, relevance, and decision value.