dc.contributor.author | Pabedinskaitė, Arnoldina | |
dc.contributor.author | Davidavičienė, Vida | |
dc.contributor.author | Milišauskas, Paulius | |
dc.date.accessioned | 2024-07-03T12:41:10Z | |
dc.date.available | 2024-07-03T12:41:10Z | |
dc.date.issued | 2014 | |
dc.identifier.isbn | 9786094576508 | en_US |
dc.identifier.issn | 2029-4441 | en_US |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/154551 | |
dc.description.abstract | The development of information technology and growing amount of information and scientists rethink the models and strategies of communication as well as information ma lneadg beumseinnet sasneds
usage possibilities. Businesses compete in the fulfilled markets and need to increase efficiency of business
performance as well as market share, atract more customers and minimize operating costs by implementing
new digital and business technologies. Modern technologies providing digital marketing tools,
which could help automate marketing processes, extract data for analysis etc. One of new trend is use of
bwiigth d mataa rikne tminagr.k eTthineg e. mTphhisa spiasp iesr b beeinggin bs rwouitghh at no na nea-lcyosmism oef rbcieg a dsa ata p arinoarliytyti cms etahne oorfi ebsu asninde sitss. cAo nrincehc tliionnk
between e-commerce and online marketing allows big data analytics to bring additional value to the process
and its participants. Based on literature analysis a theoretical online marketing model is being presented.
The aim of the article is to analyse and present use of big data analytics for marketing purposes in
electronic commerce. Following methods are employed: the comparative analysis of the scientific litera ture,
the systems analysis, data analysis. | en_US |
dc.format.extent | 10 p. | en_US |
dc.format.medium | Tekstas / Text | en_US |
dc.language.iso | en | en_US |
dc.relation.uri | https://etalpykla.vilniustech.lt/handle/123456789/154365 | en_US |
dc.source.uri | http://old.konferencijos.vgtu.lt/bm.vgtu.lt/public_html/index.php/bm/bm_2014/paper/view/321 | en_US |
dc.subject | big data | en_US |
dc.subject | e-commerce | en_US |
dc.subject | marketing | en_US |
dc.title | Big data driven e-commerce marketing | 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 | Information and communication technologies in business | en_US |
dcterms.issued | 2014-05-16 | |
dcterms.references | 55 | en_US |
dc.description.version | Taip / Yes | en_US |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | en_US |
dc.contributor.institution | Vilnius Gediminas Technical University | en_US |
dc.contributor.faculty | Verslo vadybos fakultetas / Faculty of Business Management | en_US |
dcterms.sourcetitle | 8th International Scientific Conference “Business and Management 2014” | en_US |
dc.identifier.eisbn | 9786094576492 | 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.identifier.doi | http://dx.doi.org/10.3846/bm.2014.079 | en_US |