five

Dataset for the Modeling and Bibliometric Analysis of E-business in Entrepreneurship (1997–2024)

收藏
Figshare2025-06-02 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Dataset_for_the_Modeling_and_Bibliometric_Analysis_of_E-business_in_Entrepreneurship_1997_2024_/29209520
下载链接
链接失效反馈
官方服务:
资源简介:
This comprehensive collection was designed to facilitate in-depth research into the scholarly landscape of e-business within the entrepreneurial context. The dataset was meticulously compiled from the Scopus database and encompasses 355 peer-reviewed documents published over a 27-year period, from 1997 to early 2024. The final selection adhered to strict inclusion criteria (IC), ensuring that each document (a) was directly relevant to E-business in Entrepreneurship, (b) represented a full publication year, (c) was a peer-reviewed article, and (d) was fully accessible for analysis. This curated corpus represents the contributions of 750 authors affiliated with 75 different countries, offering a rich, global perspective on the evolution of the field.The core of this repository is the E-business in Entrepreneurship Dataset (CSV), a single comma-separated values file containing extensive metadata for each publication. The metadata fields include author(s), document title, year, EID, source title, citation count, document type, affiliations, abstract, author and indexed keywords, and funding details, among other bibliographical information.In addition to the primary dataset, this collection provides a suite of analytical and visual outputs generated through our bibliometric and modeling research methodology. The research design is visually summarized in the Research Framework (PNG) file. For the bibliometric analysis, visualizations were created using Microsoft Excel and R Biblioshiny. These include a summary of Main Information (PNG), a graph of the Annual Scientific Production (PNG), a Thematic Map (PNG) illustrating core research themes, and an analysis of Trend Topics (PNG). For the modeling component, a predictive analysis was conducted using Python to forecast future publication volumes. The output of this analysis is provided as a projection of annual scientific output from 2025 to 2034, visualized in a PNG format using a piecewise model. This complete package is intended to serve as a foundational resource for scholars and practitioners seeking to understand, analyze, and project the trajectory of research at the intersection of e-business and entrepreneurship.
创建时间:
2025-06-02
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作