Development of an entrepreneur scan as a driving force for sustainable Farming

To respond to the challenges of sustainable farm development it is no longer sufficient for farmers to be a craftsman. Entrepreneurial and management skills are becoming an important requisite. Farmers are thus forced to learn and further professionalize in the field of entrepreneurship.
The research aims to operationalize the complex multidimensional concept of entrepreneurship in a context of sustainable farming, and to develop and validate an entrepreneur scan for supporting and guiding entrepreneurship of farmers. After validation, the ultimate goal is to make the scan available to extension workers and discussion groups in agriculture and horticulture, where it can be used as stand-alone instrument, or integrated in ISA (Integrated Sustainability Assessment) tools to stimulate entrepreneurship as a driving force for sustainable farming.
In order to develop and validate the entrepreneur scan, a mixed methods design was set up, consisting of an initial stage of qualitative data collection and analysis, followed by a stage of quantitative data collection, analysis and interpretation. The scientific value was guaranteed by relying on expert knowledge and scientific literature, while the practical and local relevance of the scan was attained by relying on stakeholder participation throughout the development process.
The entrepreneur scan is hierarchically structured according to eight themes, which are further 2. Planning-Organization-Control, 3. Networking-Collaboration, 4. Risk Management, 5. Opportunity Recognition and Exploitation, 6. Searching and Learning Behavior, 7. Innovation and 8. Craftsmanship. The option was taken to integrate the themes and indicators into a multi-level radar graph, which is a communicative representation for complex indicator sets. At each level, the farmer can observe his strengths and weaknesses, and compare his scores with average scores of a reference group.
After an initial test and validation phase at about fifty dairy farms, use of the scan as an instrument for setting up a learning trajectory was evaluated in a pilot study with two discussion groups of eleven dairy farms each. Further testing and validation of the scan in different agricultural and horticultural sectors is recommended. Also its potential for integration in ISA tools should be further explored.