dc.rights.license | Kūrybinių bendrijų licencija / Creative Commons licence | en_US |
dc.contributor.author | Stukalina, Yulia | |
dc.contributor.author | Zervina, Olga | |
dc.date.accessioned | 2024-03-14T10:33:04Z | |
dc.date.available | 2024-03-14T10:33:04Z | |
dc.date.issued | 2023 | |
dc.date.submitted | 2023-01-29 | |
dc.identifier.isbn | 9786094763335 | en_US |
dc.identifier.issn | 2029-4441 | en_US |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/153935 | |
dc.description.abstract | The purpose of the paper is to explore cutting-edge AI-based solutions applied for providing a multi-business company with the capability to increase business value in the agenda of digital transformation. The main elements of a scale-up business strategy, where AI creates business value, are identified and described. The methodology includes secondary research involving reviewing and interpretation of secondary data, analysis of publicly available statistical data, and a case study for providing factual evidence from a specific example – the company, which is one of the best illustrations of business digital transformation. The conducted research shows that today, data has become key resource for data-driven business model innovation and maximizing business value. The results are supposed to contribute to the debate what AI means for business leaders in the agenda of developing a scale-up strategy, and how they would benefit from building an AI-powered company. | en_US |
dc.format.extent | 9 p. | en_US |
dc.format.medium | Tekstas / Text | en_US |
dc.language.iso | en | en_US |
dc.relation.isreferencedby | Scopus | en_US |
dc.relation.uri | https://etalpykla.vilniustech.lt/handle/123456789/153869 | en_US |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.source.uri | https://bm.vgtu.lt/index.php/verslas/2023/schedConf/presentations | en_US |
dc.subject | digital economy | en_US |
dc.subject | data | en_US |
dc.subject | business value | en_US |
dc.subject | Artificial Intelligence (AI) | en_US |
dc.title | Business digital transformation in the data-driven economy: enhancing value with ai services | en_US |
dc.type | Konferencijos publikacija / Conference paper | en_US |
dcterms.accessRights | Laisvai prieinamas / Openly available | en_US |
dcterms.accrualMethod | Rankinis pateikimas / Manual submission | en_US |
dcterms.alternative | Advanced economic development | en_US |
dcterms.dateAccepted | 2023-03-17 | |
dcterms.issued | 2023 | |
dcterms.license | CC BY | en_US |
dcterms.references | 51 | en_US |
dc.description.version | Taip / Yes | en_US |
dc.type.pubtype | P1d - Straipsnis recenzuotame konferencijos darbų leidinyje / Paper published in peer-reviewed conference publication | en_US |
dc.contributor.orcid | https://orcid.org/0000-0002-2660-4975, Stukalina Yulia | |
dc.contributor.orcid | https://orcid.org/0000-0002-3323-9443, Zervina Olga | |
dc.contributor.institution | Transport and Telecommunication Institution, Riga, Latvia | en_US |
dcterms.sourcetitle | 13th International Scientific Conference “Business and Management 2023” | en_US |
dc.description.volume | I | en_US |
dc.identifier.eisbn | 9786094763342 | en_US |
dc.identifier.eissn | 2029-929X | en_US |
dc.publisher.name | Vilnius Gediminas Technical University | en_US |
dc.publisher.name | Vilniaus Gedimino technikos universitetas | en_US |
dc.publisher.country | Lithuania | en_US |
dc.publisher.country | Lietuva | en_US |
dc.publisher.city | Vilnius | en_US |
dc.date.firstonline | 2023-05-25 | |
dc.identifier.doi | https://doi.org/10.3846/bm.2023.955 | en_US |