dc.contributor.author | Singh, Shubham Udairaj | |
dc.contributor.author | Banelienė, Rūta | |
dc.date.accessioned | 2023-12-22T07:07:12Z | |
dc.date.available | 2023-12-22T07:07:12Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/xmlui/handle/123456789/153785 | |
dc.description.abstract | While living under rapidly changing conditions innovation, flexibility and readiness to change are grounding prosperity of the firm. But any changes for companies should be reasoned and made on the basis of analytical approach. Big data usually could help in this situation without spending time and money on expensive research activities. Therefore, this paper is focused on big data application on customers’ behavior switching from one product to new its look. Modeling is based on few monthsˈ daily data with application of regression analysis and the least squares method. The major finding comes up with the estimation output that the new webpage is more popular among IOS and WEB users, although Android systems showing negative impact on switching to new website. | eng |
dc.format | PDF | |
dc.format.extent | p. 97-103 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.ispartofseries | Vilnius University Proceedings t. 37 2669-0233 | |
dc.relation.isreferencedby | Dimensions | |
dc.relation.isreferencedby | Scilit | |
dc.source.uri | https://www.zurnalai.vu.lt/proceedings/article/view/33503/32144 | |
dc.title | Big data application for traffic estimation on a website: Big daddy case | |
dc.type | Straipsnis kitoje DB / Article in other DB | |
dcterms.accessRights | This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | |
dcterms.license | Creative Commons – Attribution – 4.0 International | |
dcterms.references | 11 | |
dc.type.pubtype | S3 - Straipsnis kitoje DB / Article in other DB | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Mechanikos fakultetas / Faculty of Mechanics | |
dc.subject.researchfield | T 007 - Informatikos inžinerija / Informatics engineering | |
dc.subject.researchfield | S 003 - Vadyba / Management | |
dc.subject.studydirection | B02 - Informacijos sistemos / Information system | |
dc.subject.studydirection | J09 - Informacijos paslaugos / Information services | |
dc.subject.vgtuprioritizedfields | EV02 - Aukštos pridėtinės vertės ekonomika / High Value-Added Economy | |
dc.subject.ltspecializations | L103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society | |
dc.subject.en | big data | |
dc.subject.en | customersˈ behavior | |
dc.subject.en | new product | |
dcterms.sourcetitle | 17th Prof. Vladas Gronskas International Scientific Conference, Vilnius University Kaunas Faculty, 2nd of December, 2022 : reviewed selected papers | |
dc.publisher.name | Vilnius University Press | |
dc.publisher.city | Vilnius | |
dc.identifier.doi | 10.15388/VGISC.2023.14 | |
dc.identifier.elaba | 180215200 | |