Capitalising on the Social Interactional Nature of Digital Entrepreneurship: An Agenda for Digital Entrepreneurs

Llandis Barratt‐Pugh et al.

Journal of Entrepreneurship2026https://doi.org/10.1177/09713557261420058article
AJG 1ABDC C
Weight
0.50

What the paper says

Digital entrepreneurship (DE) is transforming traditional entrepreneurship (TE). This article investigates how social network interactions underpin DE development by harvesting knowledge for venture growth. A review of DE literature revealed few empirical social interaction studies exploring strategies for DE development. This study focused on that knowledge gap, using social network and social capital theories for the conceptual framework. Forty-one interviews with experienced DEs were analysed using a novel application of social network and social capital theory as an analytical framework with an iterative grounded theory approach. The findings validated a social interaction research approach. The evidence indicated that DE is primarily a product of the knowledge harvested from network relations with the digital technologies as critical, enabling tools. The nuanced findings also indicated how different DE networks generated different forms of social capital. Knowledge that flows from social interactions appears to fuel DE innovation. Finally, an eight-stage agenda was constructed for DEs to enable them to capitalise on their own future social networks.

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https://doi.org/https://doi.org/10.1177/09713557261420058

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@article{llandis2026,
  title        = {{Capitalising on the Social Interactional Nature of Digital Entrepreneurship: An Agenda for Digital Entrepreneurs}},
  author       = {Llandis Barratt‐Pugh et al.},
  journal      = {Journal of Entrepreneurship},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/09713557261420058},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.