Adaptive Enterprise Architecture: Complexity Metrics in a Mixed Evaluation Method

TitreAdaptive Enterprise Architecture: Complexity Metrics in a Mixed Evaluation Method
Publication TypeJournal Article
Year of Publication2022
AuthorsDaoudi, W, Doumi, K, Kjiri, L
JournalLecture Notes in Business Information Processing
Volume455 LNBIP
Pagination505-523
Mots-clésAdaptation, Adaptive enterprise, Complexity, Complexity measurement, Complexity metrics, Dynamic environments, enterprise architecture, Evaluation methods, Global warming, Memory architecture, Mixed approach, Social responsibilities
Abstract

Classically, enterprises future is intertwined with the needs and demands of society. Nowadays, in addition to those two elements, challenges are becoming more and more numerous and unavoidable. Saying a few, global warming, social responsibilities, Covid 19, digital transformation… We are living in a new era that is highly volatile and unpredictable. We don’t have anymore the privilege to choose threats and opportunities that we want to adapt to. In fact adaptation becomes a necessity to survive in this highly competitive and dynamic environment. Factors coming from those challenges externally on top of internal ones can impact various parts of the enterprise in the form of changes. Thus, Adaptive Enterprise Architecture (EA) is leveraged to assist the continuous adaptation to the evolving transformation. On the other hand, one of the criteria of Adaptive EA is the ability to monitor and control the complexity of changes. In this paper, we suggest a mixed approach of EA complexity measurement based on quantitative and qualitative analysis. First, we begin with a recap of the criteria shaping our Adaptive Enterprise Architecture approach and we give an overview of the model that we worked on in previous work. Then we investigate related work about complexity and subjective measurement. Finally, we describe our mixed approach of assessment of complexity and we focus on the calculation of some objective and subjective metrics. © 2022, Springer Nature Switzerland AG.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85135013677&doi=10.1007%2f978-3-031-08965-7_26&partnerID=40&md5=0f86e1df30e1a710a67e90c0238de8f1
DOI10.1007/978-3-031-08965-7_26
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