Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на этот документ:
https://elib.bsu.by/handle/123456789/322951
Полная запись метаданных
Поле DC | Значение | Язык |
---|---|---|
dc.contributor.author | Wang, H. | - |
dc.date.accessioned | 2024-12-12T10:13:16Z | - |
dc.date.available | 2024-12-12T10:13:16Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | E3S Web of Conf.2024; 537: 02022 | ru |
dc.identifier.uri | https://elib.bsu.by/handle/123456789/322951 | - |
dc.description.abstract | In the age of Green Development, the Internet has revolutionized the outdated economic model with its one-sided transactions and limited information flow. The Information Age introduces a new economic paradigm, where online platforms are vital for economic growth and innovation. However, challenges like market saturation and dominance by a few online giants hinder smaller businesses. To overcome these hurdles, a thorough examination of the economic landscape through big data is essential. This research utilizes big data to analyze and improve network platforms, focusing on factors such as economic growth, real-time resource allocation, customer acquisition, and pricing. Results show that platforms using big data achieve remarkable efficiency in resource allocation, outperforming traditional platforms by 93.8%. They also excel in customer mining and flexible pricing, leading to a growth economy 65.7 times faster than traditional models. A novel strategy emerges: proactive resource allocation and deep exploration of platform data to catalyze platform economy growth, ensuring its sustainability in Green Develop | ru |
dc.language.iso | en | ru |
dc.publisher | EDP Sciences | ru |
dc.rights | info:eu-repo/semantics/openAccess | ru |
dc.subject | ЭБ БГУ::ОБЩЕСТВЕННЫЕ НАУКИ::Экономика и экономические науки | ru |
dc.title | A Comprehensive Analysis of Big Data-driven Strategies for Enhancing Economic Sustainability in the Era of Green Development | ru |
dc.type | conference paper | ru |
dc.rights.license | CC BY 4.0 | ru |
dc.identifier.DOI | 10.1051/e3sconf/202453702022 | - |
dc.identifier.scopus | 85196917764 | - |
Располагается в коллекциях: | Статьи ИБМТ |
Полный текст документа:
Файл | Описание | Размер | Формат | |
---|---|---|---|---|
e3sconf_sdea2024_02022.pdf | 2,1 MB | Adobe PDF | Открыть |
Все документы в Электронной библиотеке защищены авторским правом, все права сохранены.