Perception Gaps in Precision Livestock Farming Adoption: Cross-National Evidence from Finland and Albania
Precision livestock farming (PLF) technologies can improve the socio-economic and environmental performance of livestock farms. However, the differences between the benefits perceived by current adopters and the expectations of farmers planning to adopt them, and how this gap varies across national contexts, remain underexamined. This study investigates the disparity between the experienced benefits of current adopters and the expectations of planned adopters, serving as a group-level proxy for disconfirmation. It further explores how this gap varies between Finland and Albania, two countries at different stages of PLF adoption maturity. Combining Expectation Confirmation Theory (ECT) with Diffusion of Innovations (DoI), the study used a structured survey of 73 cattle farms (32 current adopters and 41 planned adopters); differences were assessed using Mann–Whitney U tests, effect sizes, confidence intervals, and equivalence tests. Among current adopters, environmental perceptions were statistically equivalent across the two countries (p = 0.001), while the socio-economic comparison was inconclusive; overall, adopters showed no substantial cross-country divergence. In contrast, planned adopters’ expectations differed markedly, most strongly in the environmental benefits (r = 0.585). The gap was large in Albania but negligible in Finland, suggesting that the magnitude and direction of this group-level disconfirmation proxy may vary with PLF adoption maturity. These findings extend ECT beyond individual-level analysis and offer practical guidance for tailoring advisory services across PLF adoption stages.
Authors
- Dorjan Marku (ORCID: https://orcid.org/0000-0002-8680-4725)
- Oriola Theodhori
- Ardita Hoxha-Jahja (ORCID: https://orcid.org/0009-0000-1900-6873)
Institutions
- Savonia University of Applied Sciences (FI)
- Fan Noli University (AL)
Publication Details
- Journal
- Agriculture
- Published
- 2026-09-25
- DOI
- https://doi.org/10.3390/agriculture16192090
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00