Bibliometric Analysis of Digital Entrepreneurial Education and Student Intention; Reviewed and Analyzed by VOSViewer from Google Scholar

Abstract

The backdated research dedicated to digital entrepreneurship education is immense, which makes it difficult to create an overview. Conversely, forward-thinking bibliometric visualization mapping and clustering can assist in visualizing and structuring difficult research literature. Hence, the goal of this mapping visualization study is to thoroughly discover and create clusters of EE to convey a taxonomic structure that can oblige as a basis for upcoming research. The analyzed data, which is drawn from Google Scholar through Publish or Perish tool, contain 1000 documents published between 2007 and 2022. This taxonomy should generate stronger bonds with digital entrepreneurial education research; on the other, it should stand in international research association to boost both interdisciplinary digital entrepreneurial education and its influence on a universal basis. This work strengthens student’s understanding of current digital entrepreneurial education research by classifying and decontaminating the most powerful knowledgeable relationship among its contributions and contributors. The bibliographic analysis includes ‘citation network’, ‘author’s research area’ and ‘paper content’ regarding the desired topic. In this paper, the above three mentioned terms are integrated which produces a bibliographic model of authors, titles of their papers, keywords and abstract by using Harzing’s Publish or Perish tool for extracting data from Google Scholar and further using VOSViewer to visualize networking map of co-authorship and term co-occurrence to administer the data for an instinctive and appropriate understanding of university students concerning ‘digital entrepreneurial intention’ research. This paper uses bibliometric analysis to analyze the keyword co-occurrence and co-authorship and VOSViewer is used for visualization.

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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 24 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.