German farmer viewpoints on field robots–an application of q methodology

Abstract Context Field robots are promoted to address labour shortages and improve the sustainability and productivity of arable farming. Existing research largely frames farmer attitudes along a continuum of acceptance using predefined constructs, leaving the rationalities shaping evaluations unexplored. Aims This exploratory study identifies distinct subjective viewpoints on field robots within a purposive sample of German arable farmers and reconstructs the evaluation logics shaping their attitudes. Methods Q methodology was applied with twenty German conventional farmers who sorted 30 statements covering economic, environmental, and social dimensions in January 2026. By-person factor analysis was used to identify shared viewpoints, complemented by post-sort qualitative explanations. Key Results Three distinct viewpoints emerged: a pragmatic, integration-oriented perspective centred on economic viability and operational integration; a technology-affirmative but cost-sensitive modernization perspective emphasising demonstrable agronomic benefits and practical validation; and an ecologically selective, control-oriented perspective stressing technological understanding, operational autonomy, and conditional support for specific applications. Only two of thirty statements qualified as consensus. Conclusion Within this sample, identical evaluative dimensions (economic viability, environmental benefits, or labour effects) did not carry the same meaning across farmer groups but were embedded in different evaluation logics. These preliminary findings suggest that farmer heterogeneity cannot be reduced to differing acceptance levels alone but reflects qualitatively distinct evaluative frameworks. Implications and Impacts Policies, advisory, and innovation strategies fostering field robot adoption should reflect these distinct decision logics rather than assume a uniform user group. Given the small purposive sample, these implications are preliminary and warrant verification in larger, representative studies.