Abstract

This paper presents an overview of technological prospective studies on selected classes of decision support and intelligent information systems. Technological trends and scenarios were generated from simulation experiments with hybrid models consisting of discrete-time control and discrete-event components. These trends were then merged with the outcomes of an innovative Delphi survey. Both techniques yielded a complex information technology model, capable of describing various factors relevant to the evolution and adsorption of intelligent technologies. Specifically, we investigated the development of intelligent decision support systems, recommenders, and specialized information systems supporting e-commerce, e-science, e-learning, and crisis management. The technological evolution model features software development paradigms such as DevOps, Next Release choice, and competition among system suppliers. Additionally, the survey highlighted customers’ preferences and market prospects. The foresight results are presented in the context of overall progress in information systems, software market needs, and user behavior.

Recommended Citation

Skulimowski, A. M. J. (2021). Future Prospects of Selected Intelligent Decision Technologies and their Deployment in Information Systems. In E. Insfran, F. González, S. Abrahão, M. Fernández, C. Barry, H. Linger, M. Lang, & C. Schneider (Eds.), Information Systems Development: Crossing Boundaries between Development and Operations (DevOps) in Information Systems (ISD2021 Proceedings). Valencia, Spain: Universitat Politècnica de València.

Paper Type

Short Paper

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Future Prospects of Selected Intelligent Decision Technologies and their Deployment in Information Systems

This paper presents an overview of technological prospective studies on selected classes of decision support and intelligent information systems. Technological trends and scenarios were generated from simulation experiments with hybrid models consisting of discrete-time control and discrete-event components. These trends were then merged with the outcomes of an innovative Delphi survey. Both techniques yielded a complex information technology model, capable of describing various factors relevant to the evolution and adsorption of intelligent technologies. Specifically, we investigated the development of intelligent decision support systems, recommenders, and specialized information systems supporting e-commerce, e-science, e-learning, and crisis management. The technological evolution model features software development paradigms such as DevOps, Next Release choice, and competition among system suppliers. Additionally, the survey highlighted customers’ preferences and market prospects. The foresight results are presented in the context of overall progress in information systems, software market needs, and user behavior.