We address this research gap in our study. Accordingly, to achieve organic farming targets, it is important to understand the reasons for the regional differences and the factors that lead to higher shares of organic agricultural land. The aim of this study is to identify the conditions or combinations of factors that have led to the regional differences in the share of organic cultivated land in Finland. Finland serves as an interesting case study because of its clear regional differences, both in terms of organic farming and other characteristics. We test the empirical validity of the categorisation developed by Ilbery et al. , with the addition of one economic factor. Ilbery et al. suggested that three groups of factors – physical, structural, and socio-cultural – affect the regional concentration of organic farming. Therefore, we consider a variety of potential factors that affect the regional distribution of organic farming, such as a long organic heritage, agricultural sectors, and market diversity. The importance of subsidies is also included as one of the studied factors, as economic incentives may impact conversion decisions and food systems in general . Qualitative comparative analysis is utilised as the research method because it allows to consider the unique features of each reviewed case and enables the assessment of multiple complex causalities as well as different combinations of factors that affect an outcome . Furthermore, Cairns et al. and Verweij and Trell have shown the potential of QCA for spatial research, which supports its use as a method to examine regional differences in organic farming. The organic farming conversion aid scheme began in Finland in 1990, and after 1995 when Finland joined the EU, the share of organic farming began to grow significantly . In 1990, only about 0.5% of Finnish farms were organic; however, within 10 years that share had grown to around 6%. According to Lampkin et al. , the conversion rates in the 1990s can be partially linked to the subsidy levels in Europe. Countries with high payment levels, such as Austria and Finland, plant benches experienced notable growth in organic farming. Lehtim¨ aki and Virtanen stated that the institutionalisation of organic agriculture in Finland was mainly due to economisation.
The Finnish Government set a goal in 2013 to increase the share of organic farming to 20% of the total area under cultivation by 2020 . However, this target was not achieved despite the share of organic agricultural land increasing rather steadily over the past 12 years . In 2019, organic agricultural land accounted for 13.5% of the total cultivated land in Finland . Globally, Finland was ranked 13th in terms of its share of organic agricultural land in 2018 . The number of organic farms has increased at a slower pace than the share of organic cultivated land, with the number of organic farms even decreasing in some years . The expansion of farms explains this development: the average size of an organic farm was approximately 34 ha in 2005 and approximately 61 ha in 2019. However, average farm sizes vary by region . In the Eurostat regional breakdown, these regions correspond to the NUTS3 regions . Although the target for organic farming in Finland was set as a nationwide goal, there are clear regional differences in organic land area as a proportion of the total agricultural area . In 2019, regional shares of organic land varied between 7.2% and 28.8% . Hence, some regions have already exceeded the government’s target, while others remain far behind. The largest average organic farm size is in North Ostrobothnia in Northern Finland. However, the highest organic shares are in Eastern Finland, where population density is rather low and grain yields are smaller than the average for Finnish farms. The population density also indicates if the region is rural or urban, although almost all Finnish regions are predominantly rural.For this analysis, the prime sector designates the production sector that covers the largest share of the utilised agricultural area. In this study, we also focus on mainland Finland. The Åland Islands, a small group of islands between Finland and Sweden, have unique characteristics that are distinct from the mainland, and thus the region is excluded from the analysis.
Overall, about half of the organic agricultural land in Finland is grasslands, about one-fifth is in crops production and the majority of the organic animal farms are beef or dairy farms . Approximately 3% of beef and milk is produced organically, while the corresponding share of organic eggs is almost 7% . Oats are the most common organically cultivated cereal in Finland, representing about 6.5% of the total oats production . Organic farms also produce, for example, potatoes, carrots, and berries . In Finland, the retail sales of organic products more than doubled between 2011 and 2019, increasing from 163 to 368 million euros and accounting for about 2.6% of the Finnish grocery trade . In addition to the regional differences shown in Table 1, regional variation is also evident in the history of organic farming. Development and educational work related to organic farming started most notably in Finland before 1990, but only in a few regions. Prior to 1990, there were several key milestones that occurred primarily in South Savo, Kainuu, and North Karelia, but also in Uusimaa and South Ostrobothnia . In South Savo in the 1980s, the key factors in the development of organic farming were the establishment of active organic advisors, the Mikkeli eco-county, and the Partala Centre for Rural Development for research on organic farming . In Kainuu, an organic farming advisor and the eco-municipality experiment in Suomussalmi created a network of organic farmers who developed organic agriculture in the region . The first university-level organic farming programme began at the University of Joensuu in North Karelia in the mid-1980s . In addition, organic farming was promoted by industry-related associations and education programmes in Uusimaa during the 1970s and 1980s . Before 1990, South Ostrobothnia had established one organic farming association and employed an active advisor . Studies of organic farming should acknowledge the differences between organic and conventional farming, as they may have a clear influence on conversion decisions. In Finland, the notable economic differences between organic and conventional farming include cost structure, crop yields, profitability, and subsidy levels . Statistics demonstrate the differences in grain crop levels between organic and conventional farming: conventional cereal production is more efficient in terms of land use. This is also the case in many other countries .
In Finland, the yield of organic oats, for example, was about 2300 kg per hectare in 2020, and the corresponding number for conventional oats was about 3900 kg per hectare . However, the organic farms in Finland appear to perform better in terms of profitability , an observation that has also been made in other countries . QCA is designed for comparing a small or intermediate number of cases ; it also incorporates both qualitative and quantitative methods. QCA emphasises the unique characteristics and the full complexity of every case . It is also a comparative approach, which aids the identification of similarities and differences between cases. This process can be achieved using a truth table with a data matrix that expresses the possible combinations of causal conditions . Moreover, QCA is an explanatory model that can be used to test a theory with empirical evidence and, significantly, reveal contradictions . In addition, QCA enables the assessment of multiple complex causalities . In contrast to many statistical methods, QCA is not designed to specify a single causal model that best matches the data; instead, it can be used to define the number and character of the different causal models that exist among selected cases . According to Cairns et al. , the QCA method has the potential to examine the complex spatial factors that affect area-level issues. Furthermore, multiple types of data can be used in QCA to enable comprehensive coverage of the studied topic . These significant features support the decision to use QCA in our study. This study employs the fuzzy-set QCA method, and the analysis is performed with fsQCA 3.0 software . More specifically, we use a four-value fuzzy-set technique ; therefore, in line with several previous studies, the data are calibrated into four-value categories . The fuzzy-set technique was selected because of the nature of our data: both the outcome and the conditions are mostly quantifiable. Crisp-set QCA only allows dichotomous values for the factors, whereas fuzzy-set QCA allows scores at intervals between 0.0 and 1.0 . Therefore, the fuzzy-set approach enables us to categorise both the outcome and the conditions more precisely than other QCA techniques, as the conditions are often not clearly present or absent, but something in between. Defining the studied outcome and the selected conditions marks the starting point in QCA. Researchers then produce a raw data table, in which each case indicates a specific combination of conditions and an outcome . It is recommended that a necessity analysis is conducted separately before a sufficiency analysis to test if some conditions are necessary for the outcome to be present . For the sufficiency analysis, the software produces a truth table from the raw data and displays the data as a list of configurations . The Boolean minimization reduces the long Boolean expression to the shortest expression that will uncover the regularities in the data . More specifically, the Boolean minimization eliminates all the irrelevant conditions from the set relation .
The consistency measures of the results indicate the set-theoretical importance of the outcome, and the coverage measures reveal the empirical importance of the results . Overall, the results require some interpretation, potentially in terms of causality. Therefore, rolling bench the interpretation demands a case-oriented review. The studied outcome in this research is the regional organic shares of total agricultural land , which relates to the Finnish national target for organic farming. We selected the causation factors based on the previous literature and the number of variables that would be reasonable in proportion to the studied cases . According to Ilbery et al. , structural , physical , and socio-cultural factors lead to different concentrations of organic farming. In addition, Helenius et al. stated that food systems are affected by several factors, such as socioeconomic and biophysical aspects, and people as actors and decision-makers. Therefore, it is necessary to include several different factors in this analysis. The data on subsidies and market diversity were obtained by conducting a survey. The survey was sent to all Finnish organic producers who had given permission to use their contact information. The survey, which was conducted as an electronic survey in 2015, was complemented by postal surveys and telephone interviews. According to the Finnish Food Authority , there were 4247 organic farms in Finland in 2015. A total of 840 organic farmers answered the survey. By region, 16–23% of organic farms were covered. The organic farmers who answered the survey represented farms of different sizes and types. Approximately 600 farms produced field crops, 205 meat, 95 horticultural products, 41 milk, 24 eggs, and 23 other produce, such as honey. Some of the farms produced several products. Thus, the survey respondents represent comprehensively different type of organic farms in Finland, roughly in proportion to organic agricultural land. The average farm size in our survey was approximately 57 ha; according to the Finnish Food Authority , this was about 5 ha larger than the average for organic Finnish farms in 2015. The respondents had begun organic farming between 1966 and 2014; therefore, answers were obtained from farmers with a wide range of experience. Overall, the survey provided a representative sample of organic Finnish farms. The survey included several questions about the background information of the farm . The research questions, that were mostly structured, concerned the conversion, sales, economics, and estimates of the organic farming development. The most important questions for this study addressed the reasons why the farms were converted to organic and how the sales of their produce were distributed across the different market channels and regions.