Factors influencing the adoption of digital sales support tools in short food supply chains by agricultural producers

Sylvie Michel et al.

European Business Review2025https://doi.org/10.1108/ebr-03-2025-0093article
AJG 2ABDC B
Weight
0.41

Abstract

Purpose This study aims to develop a framework for the adoption of digital sales support tools in short food supply chains within the agricultural sector, based on the Technology Acceptance Model-Technology-Organization-Environment framework. Design/methodology/approach The research used a mixed-methods approach. First, a qualitative phase, involving 15 semi-structured interviews, informed the development of a conceptual model. Second, a quantitative phase tested the model using structural equation modeling. Findings The validated model confirms the hypothesized relationships between the intention to adopt and various technological, organizational and environmental factors. These factors include perceived ease of use, perceived usefulness, financial resources, human factors and market pressure. Interestingly, greater financial resources were found to have a negative relationship with adoption intentions. Furthermore, mimetic behaviors emerged as a significant driver of adoption. Originality/value This research suggests that public authorities aiming to promote digitization within farmers’ value chains can leverage these findings to foster adoption.

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https://doi.org/https://doi.org/10.1108/ebr-03-2025-0093

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@article{sylvie2025,
  title        = {{Factors influencing the adoption of digital sales support tools in short food supply chains by agricultural producers}},
  author       = {Sylvie Michel et al.},
  journal      = {European Business Review},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1108/ebr-03-2025-0093},
}

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Evidence weight

0.41

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

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
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.