Toward a Comprehensive Framework for the Design and Evaluation of Intelligent Decision-making Support Systems (i-DMSS)

TLDR

Design and evaluation frameworks for DMSS and i‑DMSS have been proposed over the past two decades, yet the full realization of i‑DMSS capabilities remains a long‑term goal. The paper seeks to advance the development of i‑DMSS by extending existing frameworks. The authors extend prior work by integrating Chandrasekaran’s task‑structure concept from AI to present an updated framework combining Decision‑Making and Computational Mechanism perspectives. The updated framework aligns i‑DMSS capabilities with decision phases across managerial levels, offers theoretical and practical benefits for design and evaluation, and identifies limitations and future research directions.

Abstract

Design and evaluation frameworks for Decision-making Support Systems (DMSS) and Intelligent DMSS (i-DMSS) have been posed in last 20 years. Useful findings to match the required general system’s capabilities with decision phases and steps in several managerial levels have been also generated. However, current status of i-DMSS capabilities suggests that the full realization of them is still a long-term aim. This paper seeks to advance in it. By extending a previous work and integrating the Chandrasekaran’s task-structure concept from Artificial Intelligence (AI) discipline, an updated framework based on the Decision Making (DM) and Computational Mechanism (CM) views is reported. Its theoretical and practical benefits and other implications for a better design and evaluation process of i-DMSS are also discussed. Finally, limitations of current study and recommendations for further research are reported.