The enterprise DNA : static and dynamic digital representation of organizations

Detalhes bibliográficos
Autor(a) principal: Trotsyuk, Roman Vladimirovich
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/70662
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
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spelling The enterprise DNA : static and dynamic digital representation of organizationsArtificial LifeCorporate DNACompetitive StrategyEnterprise ArchitectureEnterprise DNAEvolutionary AlgorithmsGenetic AlgorithmsGA RepresentationDissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsThe contemporary business environment become more complex and fast changing during processes of business globalization, technical progress, competition, accumulation and sharing of knowledge. Companies arise, grow, exchange ideas, merge, interact with each other and adapt to the market environment, and, finally, some of them disappear. Their behavior determined by sophisticated laws, that cannot be discovered in isolation, because existence of each entity depends on its specific, internal properties and the interplay with other participants of the market. The complex interactions and enterprise life cycle reminds the life of species in the nature and thus, the mimic of biological entities can be applied as a modelling tool for better understanding how company works and what makes it successful. The broad purpose of this work is to create foundation for applying Artificial Life simulation for business analysis. Artificial Life is a concept that allow to mimic biological evolution and behavior of living creatures for modelling complex systems, forming specific environment with interacting and evolving agents. Thus, the Artificial Life can be applied for the analysis of the enterprise on the competitive market for studying its success factors. Possible combination of factors and their value are company- specific and represent properties that affects performance of the organization. The enterprises can exchange their characteristics with others by means of stuff swap, consulting, merging etc., acquiring best practices and becoming more adapted for specific challenges. The main goal of this paper is the research and suggestion of such characteristics and their representation, which, by analogy with biology, will constitute Enterprise DNA. In this thesis the digital representation of the Enterprise DNA inspired by the biological notion of living organism’s DNA is proposed. As the foundation of important company’s features, the Enterprise Architecture concept was applied. Despite the fact, that it was previously used for an Information Technology architecture, this discipline was evolved to more broad science and became a tool for describing the business architecture of the company. The Zachman Enterprise Architecture framework used as a basis of enterprise representation. Regarding this tool, the artifacts for phenotype representation are proposed and then, their digital XML representation found. The DNA digital representation model (genotype) for artifacts is proposed, which can be used for further evaluation of fitness of the specific company to the competitive environment on the specific market. This representation can be used by means of Genetic Algorithm for further implementation of Artificial Life simulation on real company’s data. The evaluation by the experts showed perspectivity of the idea of applying ALife modelling for solving business problems. As a result, some ideas for model improvement are discovered.Santos, Vitor Manuel Pereira Duarte dosRUNTrotsyuk, Roman Vladimirovich2019-05-24T15:56:34Z2019-05-172019-05-17T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/70662TID:202248828enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:33:31Zoai:run.unl.pt:10362/70662Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:35:09.073760Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv The enterprise DNA : static and dynamic digital representation of organizations
title The enterprise DNA : static and dynamic digital representation of organizations
spellingShingle The enterprise DNA : static and dynamic digital representation of organizations
Trotsyuk, Roman Vladimirovich
Artificial Life
Corporate DNA
Competitive Strategy
Enterprise Architecture
Enterprise DNA
Evolutionary Algorithms
Genetic Algorithms
GA Representation
title_short The enterprise DNA : static and dynamic digital representation of organizations
title_full The enterprise DNA : static and dynamic digital representation of organizations
title_fullStr The enterprise DNA : static and dynamic digital representation of organizations
title_full_unstemmed The enterprise DNA : static and dynamic digital representation of organizations
title_sort The enterprise DNA : static and dynamic digital representation of organizations
author Trotsyuk, Roman Vladimirovich
author_facet Trotsyuk, Roman Vladimirovich
author_role author
dc.contributor.none.fl_str_mv Santos, Vitor Manuel Pereira Duarte dos
RUN
dc.contributor.author.fl_str_mv Trotsyuk, Roman Vladimirovich
dc.subject.por.fl_str_mv Artificial Life
Corporate DNA
Competitive Strategy
Enterprise Architecture
Enterprise DNA
Evolutionary Algorithms
Genetic Algorithms
GA Representation
topic Artificial Life
Corporate DNA
Competitive Strategy
Enterprise Architecture
Enterprise DNA
Evolutionary Algorithms
Genetic Algorithms
GA Representation
description Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
publishDate 2019
dc.date.none.fl_str_mv 2019-05-24T15:56:34Z
2019-05-17
2019-05-17T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/70662
TID:202248828
url http://hdl.handle.net/10362/70662
identifier_str_mv TID:202248828
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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