The Enterprise DNA: Static and Dynamic Digital Representation of Organizations
Roman Trotsyuk1, Vítor Santos2
1Roman Trotsyuk, Nova Information Management School, Lisbon, Portugal.
2Vítor Santos, Nova Information Management School, Lisbon, Portugal.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 5034-5038 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9544088619/2019©BEIESP | DOI: 10.35940/ijeat.B5552.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The contemporary business environment become more complex and fast changing. The complex interactions and enterprise life cycle reminds the life of s species in the nature and , thus ,the mimic of biological entities can be applied as a modelling tool for better understanding how company operates and what makes it s successful. The broad purpose of this article is to propos e a foundation for applying Artificial Life s simulations for business analyse. Artificial Life is a concept that allow to mimic biological evolution and behaviour of living creatures for modelling complex systems , forming specific environment with interacting and evolving agents. The main goal of this paper is the research and suggestion of such characteristics and their representation, which will constitute Enterprise DNA. As the foundation of important company’s features, the Enterprise Architecture concept was applied. The Zach man Enterprise Architecture framework used as a base is of enterprise representation. Accordingly, the artefacts for phenotype representation are proposed and then, their digital XML representation found. The DNA digital representation model (genotype) for artefacts is proposed. This representation can be used by means of Genetic Algorithm for further implementation of Artificial Life’s simulation on real company’s data.
Keywords: Artificial Life, A Life, Corporate DNA, Competitive Strategy, Enterprise Architecture, Enterprise DNA, Evolutionary Algorithms, Genetic Algorithms, Genetic Algorithm Representation.