Social media networks in business-to-business selling: A dyadic customer and salesperson model

Juliana White et al.

Journal of Digital & Social Media Marketing2026https://doi.org/10.69554/oeyw3832article
ABDC C
Weight
0.50

What the paper says

Buyer–seller relationships are increasingly impacted by competitive intelligence (CI) captured and cultivated via social media networks. For sales organisations, understanding the nuanced processes of acquiring CI via these platforms — and how such intelligence can strengthen or strain the buyer–seller dyad — is essential. This study investigates the role of social capital in shaping both customer and salesperson use of social media to gather CI and the resulting impact on customer purchase intentions. A dyadic model of social media networks is developed and tested using data from both salespeople CI and customers CI at a mid-size business-to-business firm. The results indicate that customer-derived CI exerts a significant effect on salesperson CI, while the density and heterogeneity of a salesperson’s customer networks carry important implications for purchase behaviour. These findings suggest that salespeople building dense and heterogeneous customer networks on social media platforms may have tangible benefits for salespeople, customers and firms more widely. This article is also included in The Business & Management Collection which can be accessed at http://hstalks/business/.

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https://doi.org/https://doi.org/10.69554/oeyw3832

Or copy a formatted citation

@article{juliana2026,
  title        = {{Social media networks in business-to-business selling: A dyadic customer and salesperson model}},
  author       = {Juliana White et al.},
  journal      = {Journal of Digital & Social Media Marketing},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.69554/oeyw3832},
}

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Social media networks in business-to-business selling: A dyadic customer and salesperson model

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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.