Azzam, Mark and Beckmann, Rasmus (2022) How AI Helps to Increase Organizations' Capacity to Manage Complexity - A Research Perspective and Solution Approach Bridging Different Disciplines. IEEE Transactions on Engineering Management, 71, pp. 2324-2337. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/TEM.2022.3179107. ISSN 0018-9391.
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Official URL: https://dx.doi.org/10.1109/TEM.2022.3179107
Abstract
A major challenge for organizations and their strategic management today is the increasingly complex internal and external information and knowledge environment. To tackle this problem, we want to provide a fresh perspective on how to construct a modern AI-based socio-technical support system for strategic management. Methodologically, we provide a deep problem analysis and use the resulting insights to provide a solution approach drawing on different disciplines and bridging the gap between social science and computer science. Starting from challenges for strategic analysis in the age of information-overload, we analyze organizations as social communication systems. This yields a deeper understanding of organizations processing strategic information and their complex information environment. Based on the resulting insights, we propose our framework design by building on text mining and knowledge graph technology and give some guidance for its implementation. The novel system generates strategic intelligence by tapping into qualitative data: defining constantly changing information needs, interpreting information in its context as well as in reflection to the organization and making new knowledge promptly available to the right people. Throughout, we give illustrating examples from the domain of strategic research management.
| Item URL in elib: | https://elib.dlr.de/205589/ | ||||||||||||
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| Document Type: | Article | ||||||||||||
| Title: | How AI Helps to Increase Organizations' Capacity to Manage Complexity - A Research Perspective and Solution Approach Bridging Different Disciplines | ||||||||||||
| Authors: |
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| Date: | 29 June 2022 | ||||||||||||
| Journal or Publication Title: | IEEE Transactions on Engineering Management | ||||||||||||
| Refereed publication: | Yes | ||||||||||||
| Open Access: | Yes | ||||||||||||
| Gold Open Access: | No | ||||||||||||
| In SCOPUS: | Yes | ||||||||||||
| In ISI Web of Science: | Yes | ||||||||||||
| Volume: | 71 | ||||||||||||
| DOI: | 10.1109/TEM.2022.3179107 | ||||||||||||
| Page Range: | pp. 2324-2337 | ||||||||||||
| Publisher: | IEEE - Institute of Electrical and Electronics Engineers | ||||||||||||
| ISSN: | 0018-9391 | ||||||||||||
| Status: | Published | ||||||||||||
| Keywords: | Artificial intelligence, knowledge graph, natural language processing, research management, social systems theory, strategic intelligence, strategic management | ||||||||||||
| HGF - Research field: | other | ||||||||||||
| HGF - Program: | other | ||||||||||||
| HGF - Program Themes: | other | ||||||||||||
| DLR - Research area: | no assignment | ||||||||||||
| DLR - Program: | no assignment | ||||||||||||
| DLR - Research theme (Project): | no assignment | ||||||||||||
| Location: | Köln-Porz | ||||||||||||
| Institutes and Institutions: | Executive Board Division Innovation, Technology Transfer and Scientific Infrastructures > Technology Transfer | ||||||||||||
| Deposited By: | Beckmann, Rasmus | ||||||||||||
| Deposited On: | 09 May 2025 10:09 | ||||||||||||
| Last Modified: | 06 Oct 2025 09:41 |
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