Intelligent Decision Support Systems: An Analysis of the Literature and a Framework for Development

The spread and impact of decision support systems (DSS) have continued to gain intensity with applications in medical diagnosis, control systems, air traffic control, security systems and executive dashboards that help in strategic decision-making. As the field of machine learning (ML) continues to develop, DSS researchers have been incorporating ML techniques into DSS artifacts and this trend is growing. Though researchers have been talking about intelligent decision support systems for about three decades now, there has not been any recent attempt to provide a comprehensive framework to guide researchers and developers in creating DSS that use machine learning techniques. In this paper we examine the progress that has been made in applying ML techniques for developing DSS, based on a literature analysis of 2093 journal papers published from 2014 – 2024, and propose a framework for future development of intelligent DSS.