Partnerships as a Key to Enhancing the Digital Transformation of Agriculture: Analyzing Farmers’ Propensity to Collaborate and Finance
The article focuses on discussing the design and assessing the prospects for implementing the proposed cooperation and funding mechanism for activities supporting the digital transformation of agriculture in Poland and identifying factors influencing farmers’ willingness to participate. The research is based on a face-to-face survey method using a structured survey questionnaire conducted in 2022 using the CATI ( Computer-Assisted Telephone Interview ) survey technique and a logistic regression model. The survey was conducted among farmers in Poland in the region of Western Pomerania ( n=388 ). The results of the survey demonstrate that the implementation of a cooperation and funding mechanism based on private contributions from farmers has potential, but that it requires overcoming several important barriers, including financial, psychological (lack of trust, sense of government responsibility) and perceptual barriers. Farmers’ willingness to participate in this mechanism varies according to the socio-economic characteristics of their farms. This willingness significantly increases with high perceptions of climate change risk and agricultural area, and significantly decreases when conventional/intensive or traditional/extensive production is practised. The interaction effect between education and risk attitudes was also significant. The results of our study are key to understanding which farmers are most open to participating in the proposed mechanism and what factors motivate or discourage them from this type of cooperation and co-financing. Furthermore, they bring new data providing new insights into complex decision-making mechanisms in agriculture.
Authors
- Michał Soliwoda (ORCID: https://orcid.org/0000-0003-4207-4641)
- Agnieszka Kurdyś-Kujawska (ORCID: https://orcid.org/0000-0002-6024-2947)
Institutions
- Koszalin University of Technology (PL)
- University of Łódź (PL)
Publication Details
- Journal
- Procedia Computer Science
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.procs.2025.10.007
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00