{"title":"Intelligent Decision Support Systems: An Analysis of the Literature and a Framework for Development","authors":"Gerald Onwujekwe, Heinz Roland Weistroffer","doi":"10.1007/s10796-024-10571-1","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"131 1","pages":""},"PeriodicalIF":6.9000,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Systems Frontiers","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10796-024-10571-1","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍：
The interdisciplinary interfaces of Information Systems (IS) are fast emerging as defining areas of research and development in IS. These developments are largely due to the transformation of Information Technology (IT) towards networked worlds and its effects on global communications and economies. While these developments are shaping the way information is used in all forms of human enterprise, they are also setting the tone and pace of information systems of the future. The major advances in IT such as client/server systems, the Internet and the desktop/multimedia computing revolution, for example, have led to numerous important vistas of research and development with considerable practical impact and academic significance. While the industry seeks to develop high performance IS/IT solutions to a variety of contemporary information support needs, academia looks to extend the reach of IS technology into new application domains. Information Systems Frontiers (ISF) aims to provide a common forum of dissemination of frontline industrial developments of substantial academic value and pioneering academic research of significant practical impact.
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