Exploring farmers’ perspectives on collective action: a case study on co-operation in Dutch agri-environment schemes

Abstract

To improve the ecological effectiveness of agri-environment-climate measures (AECM), collective approaches to co-ordinate AECM beyond the farm level have emerged, which are characterised by different levels of co-operation between individual farmers. As participation is voluntary, understanding farmers’ perspectives on collective action in the context of these economic incentive instruments is crucial to improve existing or design novel approaches. We conducted a Q study on farmers’ viewpoints on collective AECM in the Netherlands, where all AECM have to be realised jointly since 2016. Our results reveal three dominant views on collective AECM: a collective-oriented, a business-oriented and an environment-oriented perspective. Clear preferences for the collective approach show that even in cultures with strong values of independence joint action is possible, as farmers’ autonomy can be strengthened through co-operation. Considering different perspectives on collective approaches within the institutional design can help to develop more targeted, and thus successful, incentives.

Keywords:

• economic incentive instruments
• landscape level approach
• co-operation
• farmer motivation
• Q methodology

Acknowledgements

We thank all our interview partners for participating in the study, Iris Flamand for translating and conducting the interviews, the representatives of the involved collectives for their support with finding interview partners, BoerenNatuur for providing the shapefiles of the Dutch collectives, Sigrid Ehlert for creating the overview of case studies and the anonymous reviewers for their constructive feedback on the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethics declaration

In accordance with ethical guidelines and good scientific practice, we obtained consent from each of our interviewee in the following way: We informed about confidential data usage and purpose of the interview in an information and consent form before the interview which was signed by all interviewees. Right before the interview started, we again asked for consent to record the interview. All collected data was anonymised to ensure privacy. The original data is stored on a secured server by Leibniz Centre for Agricultural Landscape Research (ZALF) until it will be deleted according to its’ data policy regulations.

Supplemental data

Supplemental data for this article can be accessed here.

Notes

1 See https://github.com/aproxima/htmlq

2 See https://github.com/aiorazabala/qmethod

3 In the following, the numbers in brackets refer to (Statement: factor array). When referring to several viewpoints, one number means that all viewpoints have ranked the statement the same way, while three numbers indicate three different rankings). When referring to one viewpoint only, the factor array relates to this viewpoint only.

4 If no further reference is mentioned, the quotation refers to the statement mentioned before. In case of ambiguity, a reference is provided in the form of ‘stat_number of item’. P refers to participant, each of whom received a number for anonymisation.

Additional information

Funding

This work was supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 818190 and by the ZALF Integrated Priority Project 2022.