Drivers for differences in dairy farmers’ perceptions of farm development strategies in an area with nature and landscape as protected public goods

Abstract

Nature and landscape are increasingly appreciated as public goods and community assets in need of protection. Policy schemes aiming to protect vulnerable nature and landscape assets affect options for farm development and thus the opportunities for farm income strategies. Farmers as small business owners need to counter an ongoing income squeeze in their strategic decision. Farmers’ perception of the options affects strategic decision making. In a case study with dairy farmers operating in a highly comparable biophysical and socio-economic context, farmers differed in the perception leading to three main income strategies: ‘maximising’ or ‘ending’ of milk production and ‘diversification of farm business’ with the most dominant strategy being ‘maximising’. Multiple regression analysis was used to explore the significance of seven drivers for the differences between farmers’ perception of farm development options. The ‘personal views and preference’ is the most significant explanatory driver for all three income strategies. ‘View on markets’ is of less significance and ‘view on urban-rural relation’ is not significant in explaining differences between farmers. ‘Maximising’ and ‘diversifying’ are opposites in their drivers. To increase the effectiveness of policy schemes and support programmes, personal views and preferences of farmers need to be taken into account.

Keywords

dairy farm entrepreneurship income strategy public goods strategic decision making

Introduction

This paper studies the drivers for differences between dairy farmers’ perception of the viability of options for farm development to support a substantial part of farm income. Economically healthy farms are important for the local economy yet not all farm development options are positive for the development of vulnerable public goods which are seen as local community assets. Options for farm development like scale enlargement and specialisation negatively affect landscape and biodiversity values (Marsden, 2003; Wiskerke and Roep, 2007). Developments in the sector and the market may oppose the interest of the local surroundings creating a challenge for the farmer in the selection of a strategy.

Farm development has always affected and has always been affected by the context in which it operates, both in the past and in modern times (Bieleman, 1987; Feola et al., 2015). As a result of agricultural modernisation that stimulated specialisation, intensification and scale enlargement, production increased dramatically in the second half of the 20th century (Ploeg and Roep, 2003). The process of agricultural modernisation was actively stimulated by the government (Grin, 2012; Lowe et al., 1993; Ploeg, 2003; Wals et al., 2012). Modernisation allowed farm production to bypass the limitations of locally available resources and the presence of local markets. Modernisation of agriculture has been highly successful in increasing production; however, there were negative effects as well. Scale enlargement and intensification of agricultural production had a negative impact on environmental quality and landscape and biodiversity values (Knickel, 1990; Marsden, 2003; Primdahl and Kristensen, 2011; RIVM, 2002; Wästfelt et al., 2012; Wiskerke and Roep, 2007) and also resulted in a growing tension in sociocultural sustainability, especially for animal production systems (Boogaard et al., 2011). The location of the farm became an address for production, loosening the connection between product, production and location. These processes have been described as dis-connecting, dis-embedding and dis-entwining of food production (Wiskerke, 2009). In many regions the farmer is expected to take into account the quality of the landscape in making decisions on farm development which easily creates tensions with the dynamics in farm practices (Wästfelt et al., 2012). Especially in regions with high natural or cultural-historical value, or areas close to urban areas, the traditional growth path of farms is confronted by changing societal demand. Alongside scale enlargement and intensification farmers have developed new services and functions of rural areas for urban dwellers (Horlings, 2010; Organisation for Economic Co-operation and Development (OECD), 2006; Roep, 2000). New value chains have been developed based on regional products and on the characteristics of the farm and the rural context such as farmers’ markets, care and recreation (Oostindie, 2015; Potter and Tilzey, 2005). These new value chains are also a response to the ‘cost price squeeze’: an increase in the cost of the resources and a decrease in the price of the products delivered by the farm (Ploeg, 2000).

For a farmer, the development of new value chains and new products and services (diversification of farming) increases the number of possibilities for farm development. This further means that the process of strategic decision making (SDM) is of increased importance to balance the various interests and needs. For this paper we draw on literature on SDM in small businesses to study its application in farm development. ‘Strategy’ is defined in this study as “a choice out of available routes and means in order to realise a goal” (Encyclo, 2012). Family-owned farms share important characteristics with small businesses, as the farm is an independent business, managed by its owner or part owners and has a small market share (Culkin and Smith, 2000). Farmers operate like small business owners in a complex combination of tasks and responsibilities because they need to combine the entrepreneurial, managerial and technical role as a craftsman (Chandler and Jansen, 1992). Farmers personally learn from the experience of running the farm, as do small business owners (Atherton, 2003). This paper answers the call made in the literature to pay more attention to the contextualisation of entrepreneurship by studying entrepreneurship in connection with the context of the everyday and real life situations of business owners (Bjerke, 2007: 31; Johannisson, 2011; Watson, 2013).

In rural areas large parts of the land are in use by farmers (Berkhout and van Bruchem, 2006), making farmers important stakeholders in regional development (de Lauwere, Verstegen et al., 2006). Policy schemes and development programmes of local governments influence business development, e.g. by supporting the diversification of small business (Liberman-Yaconi et al., 2010) or in the adaptation to changes in the environment (Feola et al., 2015). Policies and support programmes are important for rural economic development which aims for a sustainable land use, a key challenge for rural areas (Woods, 2012). However, the final strategic decision for the development of a farm is made by the farmer in the role of owner–manager who has an autonomous position in decision making (Culkin and Smith, 2000; Hang and Wang, 2012; Jocumsen, 2004; Pietola and Lansink, 2001). This means that in order to be effective, policies and programmes need to connect to the world of the decision maker (Pietola and Lansink, 2001). Therefore it is important to understand how farmers’ SDM is related to the biophysical and socio-economic context in which the farm operates (Korsgaard et al., 2015). SDM by the farmer takes place in a complex system and needs to be studied in an integrated way, it is not a purely economic driven decision (Hansson and Ferguson, 2011; McKeever et al., 2015; Welter, 2011). SDM in small businesses is complex and heterogeneous which makes it less predictable than, and different from, SDM in large business (Jocumsen, 2004; Liberman-Yaconi et al., 2010). SDM in small business does not necessarily follow economic logic (Farmar-Bowers and Lane, 2009; Gustafsson, 2009) and is influenced by the personal characteristics of the owner–manager (Begley and Boyd, 1986; Curseu et al., 2008: 42; Jocumsen, 2004; Liberman-Yaconi et al., 2010). However, studying the personal characteristics in relation to business strategies is complex as the same strategy can be followed by owner–managers with different characteristics (Bjerke and Hultman, 2002: 66). Looking more closely at SDM in small business it is known to be an iterative process of informing, option generating and deliberating that starts at the moment decision making is triggered (Hang and Wang, 2012; Jocumsen, 2004; Liberman-Yaconi et al., 2010). The small business owner’s perception of the situation has been found to be more decisive for the outcome of SDM than formal analyses (García-Pérez et al., 2014; Parnell et al., 2000). The perception of entrepreneurial opportunities is affected by the environment in which small business operates (Sutcliffe and Zaheer, 1998; Yanes-Estévez et al., 2010). This means that at the start of a SDM process, the owner–manager already has a perception of the options for business development, the ‘room for manoeuvre’.

To study the differences between owner–managers’ perceptions of the options for business development, we designed the construct perceived Room for Manoeuvre (pRfM). We defined the pRfM as ‘the options perceived as viable in order to obtain a (substantial part of) business income’ (Methorst et al., submitted for publication). The label ‘perceived Room for Manoeuvre’ was chosen as it connects closely to the real life world of the farmer as entrepreneur deliberating about the question: ‘what are my options, what is my room for manoeuvre’. Based on the pRfM, the farmer assesses the options deemed viable as an input for SDM. The pRfM may include options that might be viable, yet are not preferred by the farmer. Continuation of current activities is seen as an opportunity as well, as it can be perceived as a way to realize the goal. In the context of a farm as a running business, opportunities may include the adaptation of ideas and opportunities already in practice on other farms. The construct pRfM was tested in the context of family-owned dairy farming operating in a highly similar biophysical and socio-economic context. Significant differences between farmers were found (Methorst et al., submitted for publication). The farmers differed in three dimensions (or income strategies) of the pRfM: (1) ‘diversifying’; (2) ‘ending’; and (3) ‘maximising’ production. Using two-stage cluster analysis for the scores on the three dimensions, four clusters (or patterns of farm development) of farmers were found. These patterns of farm development proved to be coherent in their characteristics, consistent over a longer period of time and they were meaningful to stakeholders in dairy farming. This means the pRfM appears to act as a pre-filter for farmers in their selection of options for further assessment in the SDM process. The construct pRfM thus allows farmers to be distinguished in their perceptions of options for farm development. This opens the question on the drivers behind these differences in pRfM. Understanding these drivers is of practical relevance for the design and implementation of policies and support programmes for small business development. In this paper we use an empirical study in the context of family owned dairy farmers. Dairy farming faces structural changes that increase the importance of SDM due to liberalisation and globalisation of the markets (Clark, 2009; Hansson et al., 2010).

In the theoretical background, we describe the analytical framework for this study followed by the methodology section which presents the characteristics of the case study, the operationalisation of the framework and the statistical methods used for data analysis. The results and the discussion section will show that the driver ‘personal view and preference’ plays an important role which has important implications for future policy making.

Theoretical background of pRfM and the drivers

The heterogeneity in farm development in relation to the context in which the farmers operate is described in literature on farming styles (Long and Ploeg, 1994; Ploeg, 2003; Ploeg and Ventura, 2014). Farming styles research has shown that the explanation for the existing heterogeneity in farm development cannot be reduced to ‘external’ structural forces such as ‘markets’ or ‘nature’ impacting on farming, even when these are mediated by capable farmers into all their farming practices and decision making. The socio-cultural embeddedness of farmers, their shared values and norms and how they see themselves as ‘a farmer’ or like to be seen do matter significantly in explaining different farm development strategies and result in different patterns of farm development. The farmer has agency, a room for manoeuvre, to act within the structures that confine the choices. Or, as described in an article on the resilience of family farms (Darnhofer et al., 2016: 116): ‘the structures – both on – and off-farm, both material and social – constrain choices. But their influence is mediated by farmer's beliefs, and the potentials farmers perceive in a dynamically changing context’. The agency of the farmer, the room for manoeuvre, is the centre of the construct pRfM. The analysis of the pRfM by the business owner, the viability of the opportunities for business development, is influenced by the business owner’s perception. This perception is influenced by dominant paradigms, lock-in effects and path dependencies (Cowan and Gunby, 1996; Lamine et al., 2012; Vanloqueren and Baret, 2009). pRfM is an operationalisation of the concept ‘evoked set of opportunities’ which is defined as ‘the full set of possibilities perceived as (entrepreneurial) opportunities by a decision maker’ (Krueger et al., 2009: 122). We use as the definition of entrepreneurial opportunities: ‘feasible means to obtain benefits for the firm’ (Hansen et al., 2009: 14). The construct pRfM is related to the strategic awareness capability which is defined as ‘the process of continuously improving how one identifies and conceptualises one’s own world, recognises events in this world, interprets these events and makes decisions for appropriate action to achieve positive business outcome’ (Hannon and Atherton, 1998: 112). To construct our analytical framework we used a combination of a literature study and an exploratory study in the context of the case study. The latter is relevant to connect entrepreneurship research to the real life context (Bjerke, 2007: 31; Johannisson, 2011; Watson, 2013). The resulting analytical framework has seven drivers which reflect the subjective perception of the farmer.

The first driver is the personal view and preference: how owner–managers view themselves and their preferences (Farmar-Bowers and Lane, 2009), their personal motivations (Alsos et al., 2003; Vik and McElwee, 2011) and self-conceptualisation (Burton and Wilson, 2006). The second driver is personal development, consisting of education level (Carter, 1998; Jongeneel et al., 2008), experience (Hansson and Ferguson, 2011) and networks of the owner-manager (Clark, 2009; Granovetter, 1973; Ferguson and Hansson, 2015; Thornton et al., 2011). The third driver is view on entrepreneurial competences relating to the business strategy (Bergevoet, 2005; Bergevoet et al., 2004; Lans et al., 2011). The fourth driver is the view on continuation of the firm. In family-owned business the influence of the family is important for the owner’s view on continuation (Gasson et al., 1988). The fifth driver is view on current business situation, based on material resources (Shucksmith and Herrmann, 2002) and path dependency as a result of choices made earlier (Clark, 2009). The sixth driver is the view on market development, that is whether and how the market is expected to change (Hansson and Ferguson, 2011; Shucksmith and Herrmann, 2002). The seventh (and last) driver is the view on urban-rural relation. The change in societal views over the last few decades on the urban–rural relation and the role of agriculture have created a market for diversification strategies (Atterton and Ward, 2007), especially in peri-urban situations (Zasada, 2011).

The seven drivers of pRfM span a wide range of influencing factors as it is based on the real life context. The farmer’s perceptions of these seven drivers influence his subjective view on the situation of his farm, this in turn influences his SDM process. The pRfM is not static, pRfM evolves with changes in the situation of the business and the owner–manager. The three income strategies which were found in the pRfM reflect possible development and not necessarily actual farm development. In other words, it is a measure of attitudes and options perceived as viable. Options perceived as viable are not necessarily put into practice (Zwan et al., 2011).

Methodology

This section describes the characteristics of the case study, the operationalisation of the seven drivers of pRfM and the methods used for data analysis.

The case study

The unique value of Kampereiland as case study is the highly comparable situation in which all dairy farmers operate. Differences between farms are therefore more likely to be the result of differences between the farmers. The context of a farm does affect farm development, for this reason the context of farming in the case study area needs to be described.

Kampereiland (‘the island of Kampen’) is a river delta where the river IJssel meets the lake IJsselmeer, which was created when the former sea was closed by a dam in 1932. The town of Kampen owns the islands in the river delta since 1363. Using land reclamation techniques, the amount of land was expanded to around 4,000 ha of agricultural land and 800 ha water, roads and nature areas. The main activity is dairy farming (102 of the total 108 farms). The isolation aspect of being an island is no longer a physical reality due to bridges and two new polders in the former sea. The history as an island has, however, influenced the culture and identity of Kampereiland, even though the town of Kampen was less than 10 km away. The 600 people have good social connections with an active community centre, a church, a primary school, a quarterly journal and various social and leisure groups. A yearly harvest festival is organised around the museum farm and attracts thousands of visitors. The former coastal areas were designated as Natura 2000 nature reserves (2011) and Kampereiland became part of a National Landscape (2005) due to its characteristic Dutch river delta landscape influenced by centuries of farming.

All farms are tenant farms with the town of Kampen as the lessor. The lessor’s policy is to take care of the ‘heritage of our fathers’ using four guiding principles: (1) retain property of Kampereiland, (2) obtain a reasonable financial return, (3) take care of nature and landscape values, and (4) conduct a loyal tenancy policy. After an increase to 170 in the 1950s when around 60 new farms were built, the number of active farms decreased to 108 in the year 2012 (of which 102 dairy farms). A farm has on average around 45 ha in use including land owned or rented outside of Kampereiland. The tenancy situation affects the land market in Kampereiland as there is no free land market. To buy land the farmer needs to go to neighbouring areas (5+ km). The economy of the farms in Kampereiland strongly relies on dairy farming, though farm income is often supplemented by an off-farm job by the farmer or a family member. Dairy farms in Kampereiland were until the 1980s known for their larger than average size and high economic return; however, the development of farm income in Kampereiland became worrisome in the last decades (Duitman, 2005; Methorst, 2013). There are no organic dairy farms at the time of the survey and fewer than 10 farmers are engaged in diversification of their farm. The milk is delivered to (inter)nationally operating dairy organisations, mostly cooperatives.

The policies and legislation concerning the two Natura 2000 areas and the National Landscape affect the development potential of dairy farming in Kampereiland. To support the sustainable development of Kampereiland, the lessor developed a programme aiming to support long-term economic viability of the farmers while strengthening the nature and landscape values. Dairy farming in Kampereiland is affected as well by national and supranational legislation on environment, animal health and animal welfare. The end of the European milk quota system in 2015 is expected to lead to scale enlargement and specialisation of production in Dutch dairy farming (Meulen et al., 2012). The change in EU dairy market policies has increased price volatility while accessibility of capital for investment decreased due to the financial crisis. These developments combined increase the economic challenge for dairy farmers in the development of their farm.

The uniqueness of the case study is the highly comparable context, which allows the study of differences between individual farmers. An important question is to what extent will the specific context of this case study affect the results in such a way that it limits their general validity. The Kampereiland case study is in many aspects a ‘normal’ area with specialised dairy farmers. For people who are not aware of this specific context, it will look like an ‘ordinary’ Dutch dairy farm region. Two aspects are specific for the case study: (1) all farmers are tenant farmers, and (2) there is no free land market in the direct surroundings of the farms as the lessor owns all the land. This situation does affect farm development options for the farmers in the case study, yet it does not necessarily limit the general validity of the findings. Firstly, this study does not aim to compare the effects of a specific condition in context on the perception of development options. The aim is to understand the differences between farmers operating in a comparable context. Secondly, the clusters of farmers that were identified were acknowledged by the stakeholders as being valid for dairy farming in general. There is therefore no reason why the results would not represent general (Dutch dairy) farming.

Operationalisation of pRfM and the drivers

The main construct pRfM was defined as: ‘the options perceived as viable in order to obtain a (substantial part of) farm income’. The construct was operationalised by listing 15 options of farm development that are known as routes for farm development in Dutch dairy farming in general and in the case study area in particular. The options for farm development are grouped as follows (options may be combined on the same farm):

Dairy production system – intensive, extensive, certified organic

Diversification – people oriented care, recreation, farm shop, dairy processing

Diversification – not people oriented energy, nature, other company, off-farm job

End to dairy production – income from other source

Other – Joint farming, relocating the farm, other option

A 16th, blank, option was included to allow farmers to introduce options not yet named; however, this still did not lead to new options outside of the 15 listed. Respondents were asked to indicate on a Likert scale from 1 to 5 for each option their perception on the viability of the option in their situation, the so-called ‘first-person opportunity’ (McMullen and Shepherd, 2006). The seven drivers influencing the pRfM were operationalised in the context of the case study using a set of questions for each driver in the questionnaire with a 5-point Likert scale (‘certainly not agree’ to ‘certainly agree’). The questions were carefully phrased to make the question and answer independent from the specific situation of the farm(er) and to make sure the respondents would not be faced with inconsistencies in the questions. The questions were designed in such a way that a farmer should be able to respond without needing extra information from sources apart from his own operational knowledge. In the creation of the questionnaire expertise was used from experienced sociologists, an expert in questionnaire development and from an independent advisor active in Kampereiland. The questionnaire was tested by two dairy farmers situated close to Kampereiland. The total questionnaire consists of 95 questions and would take between 40 to 60 minutes to complete. The questionnaire was designed as a booklet in order to give it an attractive appeal. The questionnaire was both printed and available on the internet leaving the choice to the farmer which one to use. Each farmer received a personalised printed version of the questionnaire including an individual code and password to be used for the internet version of the questionnaire. Next to the printed version by mail, all farmers also received a personalised e-mail with a direct link to the internet version of the questionnaire.

The results were analysed using Principal Component Analysis (PCA); this allows sets of questions to be determined which are related and can be combined in one measure.¹ The resulting set of measures alongside individual questions are presented in Appendix C (including the number of questions, the variance accounted for, and the reliability of the measure using Cronbach Alpha value (Field, 2009)). The reliability of the two measures for networks (driver 2, personal development) was low, likely due to the similar socio-cultural situation leading to small differences between farmers. This means it is not possible to differentiate for networks between respondents in a highly reliable manner (Cronbach Alpha values of .48 and .33). However, as these measures are the best estimate available and the analytical framework aims to represent the real life context, they were included in the analysis. The PCA on the questions on competences showed goal-orientedness as the primary measure and analysing, networking and pursuing as secondary, meaning these three will be correlated. This correlation means it is hard to determine the individual effect of each of the three measures. However, as the measures are based on literature (Lans et al., 2011) and the statistics are good (Cronbach Alpha values of .83, .71, .82), the measures for the three competences were used in the analysis.

Data analysis

The questionnaire was sent to all 102 dairy farmers resulting in 78 completed questionnaires. The 24 non-respondents were deemed to be similar to the respondents by local experts. Using multiple regression analysis, we studied the contribution of each driver as part of the total model. The dependent variables are the three dimensions of pRfM: ‘diversifying’, ‘ending’ and ‘maximising’ of production (Methorst et al., submitted for publication). As independent variables we used the 22 variables which represent the seven drivers for the pRfM (Appendix C). Stepwise regression (F-change analysis) was used to determine the explanatory value of each of the seven drivers in the total model. In this analysis the explanatory variables of a specific driver are both included and excluded in the regression model to establish the change in F-value as a result of adding this set of explanatory variables. F-change analysis is used to determine the contribution of each of the seven drivers to the explanatory value of the model. To determine the influence of each of the 22 individual independent variables, the Beta value of each variable resulting from the regression analysis is used (see Appendix C). The analytical framework spans a large range of variables as it reflects the complexity of real life for an entrepreneur. This results in seven drivers which are described by 22 independent variables which are used in the regression analysis. To test whether multiple regression analysis is an appropriate tool in this setting (22 independent variables and 78 cases), we performed extensive testing on the assumptions for the use of multiple regression analysis.² The results showed a positive result for the assumptions. The regression analysis for the three dimensions resulted in a relative large standard error as part of the regression model, and this can be interpreted as a confirmation of considerable variance between the respondents. This is important as the farmers are operating in a highly comparable context. A small standard error would indicate a high degree of predictability of farm development due to small differences between the farmers in their answers. This in turn would indicate that farmers share their rationale which points towards a strong external influence on the farmers’ views, indicating that all farms react in a similar way to the environment in which they operate. In reverse reasoning, the combination of a relative small sample size with the relative high standard error in the regression models combined with the high coherency in the quantitative and qualitative results indicates that the farmers operate in the same, highly comparable context, yet operate as independent individuals.

Results

The three models proved highly significant (at 0.001 or less) in explaining the differences between farmers in all three dimensions of pRfM with significant effects for diversifying (with an F-change of 2.98), for ending (3.81) and for maximising production (3.18). The statistics to test for the assumptions are all within the acceptable range (see Appendix A for results).

The only driver that is significant and so the most important for all three dimensions is personal views and preferences (F-change values are the highest for all three dimensions (resp. 2.62, 4.91, 3.71, see Appendix B for results). For ‘diversifying’, the only other significant driver is personal development (2.08), this shows that the perception of ‘diversifying’ as an option is mainly related to the personal views and development of the farmer. For ‘maximising’ the other significant drivers are: view on own competences, view on current farm situation and view on markets (resp. 2.70, 1.89, 2.48). This shows that the drivers for ‘maximising’ clearly differ from ‘diversifying’. Looking at ‘ending’, the other drivers we see besides personal views and preferences are view on continuation/family in combination with personal development and view on current farm situation (resp. 4.41, 2.23, and 2.47). The perception of ending the farm as an option is most influenced by the current farm situation and the view on the continuation of the farm. Looking specifically at the driver view on continuation/family, we see (higher F-change value for ‘diversifying’ as for ‘maximising’) that the view on continuation and the connection with the farmer’s family is more of importance for ‘diversifying’. However, neither value is significant. Notable as well is that the driver view on urban–rural relation is the least important in the total set of drivers, being the only one that is not significant for any of the three dimensions.

The correlations between the 22 independent variables and each of the three dimensions offer a closer look at the differences between the dimensions (the Beta values, see Appendix C). As the cause and effect relation can be both ways, we use ‘correlation between’ and not ‘the effect of’. The variable I want to be part of the top 10% dairy farmers is significant and positive for ‘maximising’ (.23) and not significant for ‘diversifying’ (.03) indicating a difference in the personal preference. Education level is significantly negative correlated with ‘diversifying’ (−.28) and is not significantly correlated with ‘maximising’ (.05) which will be further discussed in the light of literature. Will the farm continue when you stop is significant for ‘diversifying’ (.28) and ‘ending’ (−.25), but not significant for ‘maximising’ (−.12). This indicates a stronger relation between the view on farm continuation and diversification as an option than to maximising. The view on sufficiency of income is highly significant for ‘ending’ (−.39), but not significant for either ‘diversifying’ or ‘maximising’ (−.16 and −.12). The variable farm location is not relevant for me is only significant for ‘maximising’ (.27) indicating a different relation to the location of the farm. The view on the general viability of diversification differs between ‘diversifying’ and ‘maximising’ (.13 and −.22) but is for both not significant. The differences between the three dimensions for growth of the farm is a necessity and view on involvement of citizens with rural areas are small and not significant.

Overall, the results show different sets of drivers that are of importance for the three dimensions. Two drivers which are often labelled as ‘farm-external’ (markets and urban–rural developments) are least important and the personal views and preferences of the farmer are of most importance.

Discussion, conclusions and outlook

This empirical study explored the influence of seven drivers in relation to the farmer’s pRfM for farm development. The pRfM acts as a pre-filter in a SDM process. Farmers differ in three dimensions (or income strategies): ‘diversifying’ (e.g. care, education, farmers’ markets), ‘ending’ (i.e. leaving the dairy farming sector), or ‘maximising’ (using farm external inputs to maximise yields per ha) of production. The most influential driver is the personal views and preference on either maximising or diversifying of production. Further qualitative research is needed on the rationale of the farmers behind these perceptions. However, the data do suggest a connection between the perception on the viability of options and the view on one’s identity as a farmer (see also Burton and Wilson, 2006; Hansson et al., 2012). Identifying as a farmer is revealed in the literature to be of influence in the perception of diversification of farm activities. Diversification refers to the diversion of resources from conventional agricultural production to alternative enterprises on the farm, excluding off-farm work (Vik and McElwee, 2011), or the development of non-traditional (alternative) enterprises on the farm (McElwee and Bosworth, 2010). Several researchers have pointed to the primary focus of agricultural firms on improving current conditions rather than exploring new ideas (Haugen and Vik, 2008; McElwee, 2006; Morgan et al., 2010; Vesala and Vesala, 2010). The situation with price stability and economic support programmes may have induced a loss of the ability to critically assess the situation of the farm (McElwee and Bosworth, 2010). The findings of this paper confirm other studies on the driving factor to change the farm development strategy, revealing that personal motivation to look outside the dairy sector is not the most important factor (Vik and McElwee, 2011). So when farmers do consider opportunities that lie outside of their personal preference, this is driven by a need to change the strategy (push) rather than a desire to change the strategy (pull). In agriculture, the shift towards diversification is seen as a shift towards more entrepreneurial behaviour (Grande et al., 2011) though, for small businesses in general, diversification of production is found to indicate a survival strategy (Robson et al., 1993). The context of dairy farming is likely to have affected this finding due to: (1) path dependency (Wilson, 2008); (2) the lack of urgency for a critical assessment due to protected markets (McElwee and Bosworth, 2010); and (3) the primary focus on improving current conditions rather than exploring new ideas (Haugen and Vik, 2008; McElwee, 2006; Morgan et al., 2010; Vesala and Vesala, 2010).

Higher education level was not positively correlated with ‘diversifying’ which opposes the findings of Carter (1998). In our study most farmers with higher education studied agriculture which is likely linked to a preference for modernisation and maximisation of production. Higher education as such is not a clear variable, it has to be viewed in combination with the type of education followed, which in turn connects to personal preference. The differences in perception on farm development are likely to affect programmes related to the conservation of nature and landscape values as community assets. Farmers who perceive maximising production as the best option are less connected to the location of the farm. This separation between production strategy and farm location is expected to create a more stressful relation with policy schemes aiming to protect nature and landscape values for the strategy of maximising production. The diversifying production strategy is more connected to the location of the farm and to the family farm context. Diversifying production benefits from nature and landscape values, as it contributes to the rural setting on which their image is based on urban oriented markets. Therefore, local shareholders in favour of nature and landscape values are more likely to find a partner in farmers with a diversifying production strategy. For farms moving towards ending dairy production, the relation with policies on nature and landscape protection is less tense as there is no expansion of activities foreseen. However, there will be a transfer of production factors to other farmers or stakeholders when the farm closes. For local stakeholders this transfer presents a momentum to represent the interest of nature and landscape as vulnerable community assets.

This study shows that SDM in farm development is not so much a rational process in which economic parameters are of primary importance. Presenting diversification opportunities for farm development to farmers experiencing limitations on income strategies is less likely to be successful. An opportunity will only be perceived as a viable opportunity by a farmer when it is in line with their personal view and preference. This means the discussion about the future of farming needs to address the personal views and preferences in relation to farm development and its effect on public goods. For an individual farm the number of options perceived as viable is important, a farm business is more likely to be able to absorb changes in the market or in the business situation when it has more than one opportunity for business development (Darnhofer et al., 2010).

An important question for further research is the rationale of farmers for their perceptions on the viability of options for farm development. An interesting option is to study how the perception of the options for farm development relates to possible differences in the embeddedness of the farm in the context in which the farm operates. The implication of our findings is that policy schemes and support programmes which do not address the personal preference of farmers are less likely to be successful. Differences in the embeddedness may offer a route to study the personal preferences of the farmer. And personal preferences can and do change, which opens routes for policy schemes which focus on the attitudes and intentions of farmers in the light of changes in the context that lead to changing opportunities for farm development. Addressing personal views and preferences can be linked to supporting the development of networks in which business owners operate, an issue raised by Moyes et al. (2012). A programme focusing on merely informing about the opportunities which are favoured by policy makers is less likely to be effective.

Footnotes

Acknowledgements

The authors wish to thank the anonymous reviewers for the valuable comments. This research was possible thanks to the co-operation of De Stadserven (the lessor) and the Tenants Union.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Appendix A: Multiple regression models and test statistics

Appendix B: F -change values for seven drivers on the three dimensions of perceived options for dairy farm development

Appendix C: Beta values of the multiple regression models on the three dimensions of perceived options for dairy farm development

References

Alsos

Ljunggren

Pettersen

(2003) Farm-based entrepreneurs: What triggers the start-up of new business activities? Journal of Small Business and Enterprise Development 10: 435–443.

Atherton

(2003) The uncertainty of knowing: An analysis of the nature of knowledge in a small business context. Human Relations 56: 1379–1398.

Atterton J and Ward N (2007) Diversification and Innovation in Traditional Land-based Industries. London: Rural Innovation, National Endowment for Science Technology and the Arts (NESTA).

Begley

Boyd

(1986) Executive and corporate correlates of financial performance in smaller firms. Journal of Small Business Management 24: 8.

Bergevoet

RHM

(2005) Entrepreneurship of Dutch Dairy Farmers, Wageningen: Wageningen University.

Bergevoet

RHM

Ondersteijn

CJM

Saatkamp

(2004) Entrepreneurial behaviour of Dutch dairy farmers under a milk quota system: Goals, objectives and attitudes. Agricultural Systems 80: 1–21.

Berkhout

van Bruchem

(2006) Landbouw Economisch Bericht 2006, Den Haag: Wageningen UR-LEI, pp. 228.

Bieleman

(1987) Boeren op het Drentse zand 1600–1910. Een nieuwe visie op de ‘oude' landbouw, Wageningen: Wageningen University.

Bjerke

(2007) Understanding Entrepreneurship, Cheltenham, UK: Edward Elgar Publishing.

10.

Bjerke

Hultman

(2002) Entrepreneurial Marketing: The Growth of Small Firms in the New Economic Era, Cheltenham, UK: Edward Elgar Publishing.

11.

Boogaard

Oosting

Bock

(2011) The sociocultural sustainability of livestock farming: An inquiry into social perceptions of dairy farming. Animal 5: 1458–1466.

12.

Burton

RJF

Wilson

(2006) Injecting social psychology theory into conceptualisations of agricultural agency: Towards a post-productivist farmer self-identity? Journal of Rural Studies 22: 95–115.

13.

Carter

(1998) Portfolio entrepreneurship in the farm sector: Indigenous growth in rural areas? Entrepreneurship & Regional Development 10: 17–32.

14.

Chandler

Jansen

(1992) The founder's self-assessed competence and venture performance. Journal of Business Venturing 7: 223–236.

15.

Clark

(2009) Entrepreneurship and diversification on English farms: Identifying business enterprise characteristics and change processes. Entrepreneurship & Regional Development 21: 213–236.

16.

Cowan

Gunby

(1996) Sprayed to death: Path dependence, lock-in and pest control strategies. The Economic Journal 106: 521–542.

17.

Culkin

Smith

(2000) An emotional business: A guide to understanding the motivations of small business decision takers. Qualitative Market Research: An International Journal 3: 145–157.

18.

Curseu P, Vermeulen P and Bakker R (2008) The psychology of entrepreneurial strategic decisions. In: Vermeulen PAM and Curseu PL Entrepreneurial Strategic Decision-making: A Cognitive Perspective chapter 3, pp. 41–67.

19.

Darnhofer

Bellon

Dedieu

(2010) Adaptiveness to enhance the sustainability of farming systems. A review. Agronomy for Sustainable Development 30: 545–555.

20.

Darnhofer

Lamine

Strauss

(2016) The resilience of family farms: Towards a relational approach. Journal of Rural Studies 44: 111–122.

21.

Duitman

(2005) Analyse melkveebedrijven op Kampereiland, Kampen: Alfa-Berk-Countus, pp. 57.

22.

Encyclo (2012) Encyclo Online Encyclopedie. Available at: www.encyclo.nl/begrip/strategie (accessed 15 August 2012).

23.

Farmar-Bowers

Lane

(2009) Understanding farmers' strategic decision-making processes and the implications for biodiversity conservation policy. Journal of Environmental Management 90: 1135–1144.

24.

Feola

Lerner

Jain

(2015) Researching farmer behaviour in climate change adaptation and sustainable agriculture: Lessons learned from five case studies. Journal of Rural Studies 39: 74–84.

25.

Ferguson

Hansson

(2015) Measuring embeddedness and its effect on new venture creation – A study of farm diversification. Managerial and Decision Economics 36: 314–325.

26.

Field

(2009) Discovering Statistics using SPSS, London: Sage publications.

27.

García-Pérez

Yanes-Estévez

Oreja-Rodríguez

(2014) Strategic positioning and strategic types of small firms. Journal of Small Business and Enterprise Development 21: 431–449.

28.

Gasson

Crow

Errington

(1988) The farm as family business: A review. Journal of Agricultural Economics 39: 1–41.

29.

Grande

Madsen

Borch

(2011) The relationship between resources, entrepreneurial orientation and performance in farm-based ventures. Entrepreneurship & Regional Development 23: 89–111.

30.

Granovetter

(1973) The strenght of weak ties. The American Journal of Sociology 78: 1360–1380.

31.

Grin

(2012) The politics of transition governance in Dutch agriculture. Conceptual understanding and implications for transition management. International Journal of Sustainable Development 15: 72–89.

32.

Gustafsson

(2009) Entrepreneurial decision-making: Thinking under uncertainty. In: Carsrud

Brännback

(eds) Understanding the Entrepreneurial Mind: Opening the Black Box, New York, NY: Springer-Verlag, pp. 285–304.

33.

Hang

Wang

(2012) Strategic decision-making in small and medium-sized enterprises: Evidence from Australia. International Journal of Business Studies: A Publication of the Faculty of Business Administration, Edith Cowan University 20: 91.

34.

Hannon

Atherton

(1998) Small firm success and the art of orienteering: The value of plans, planning, and strategic awareness in the competitive small firm. Journal of Small Business and Enterprise Development 5: 102–119.

35.

Hansen DJ, Shrader R and Monllor J (2009) Composite definitions of entrepreneurial opportunity and their operationalizations: Toward a typology. Frontiers of Entrepreneurship Research 29(17): Article 1. Available at: digitalknowledge.babson.edu/fer/vol29/iss17/1 (accessed 18 August 2015).

36.

Hansson

Ferguson

(2011) Factors influencing the strategic decision to further develop dairy production – A study of farmers in central Sweden. Livestock Science 135: 110–123.

37.

Hansson

Ferguson

Olofsson

(2010) Understanding the diversification and specialization of farm businesses. Agricultural and Food Science 19: 269–283.

38.

Hansson

Ferguson

Olofsson

(2012) Psychological constructs underlying farmers’ decisions to diversify or specialise their businesses – An application of theory of planned behaviour. Journal of Agricultural Economics 63: 465–482.

39.

Haugen

Vik

(2008) Farmers as entrepreneurs: The case of farm-based tourism. International Journal of Entrepreneurship & Small Business 6: 321–336.

40.

Horlings

(2010) Vital Coalitions, Vital Regions Partnerships for Regional Development, Wageningen: Wageningen Academic Publishers, pp. 175.

41.

Jocumsen

(2004) How do small business managers make strategic marketing decisions? European Journal of Marketing 38: 659–674.

42.

Johannisson

(2011) Towards a practice theory of entrepreneuring. Small Business Economics 36: 135–150.

43.

Jongeneel

Polman

NBP

Slangen

LHG

(2008) Why are Dutch farmers going multifunctional? Land Use Policy 25: 81–94.

44.

Knickel

(1990) Agricultural structural change: Impact on the rural environment. Journal of Rural Studies 6: 383–393.

45.

Korsgaard S, Ferguson R and Gaddefors J (2015) The best of both worlds: How rural entrepreneurs use placial embeddedness and strategic networks to create opportunities. Entrepreneurship & Regional Development 27: 574–598.

46.

Krueger

Kickul

Gundry

(2009) Discrete choices, trade-offs, and advantages: Modeling social venture opportunities and intentions. In: Robinson

Mair

Hockerts

(eds) International Perspectives on Social Entrepreneurship, Basingstoke, UK: Palgrave Macmillan, pp. 117–143.

47.

Lamine

Renting

Rossi

(2012) Agri-food systems and territorial development: Innovations, new dynamics and changing governance mechanisms. In: Darnhofer

Gibbon

Dedieu

(eds) Farming Systems Research into the 21st Century: The New Dynamic, The Netherlands: Springer, pp. 229–256.

48.

Lans

Verstegen

Mulder

(2011) Analysing, pursuing and networking: Towards a validated three-factor framework for entrepreneurial competence from a small firm perspective. International Small Business Journal 29: 695–713.

49.

de Lauwere CC, Verstegen JAAM, Buurma JS, et al. (2006) Ondernemers en de actoren in hun omgeving in beweging : zoektocht naar de rode draden in agrarische transitieprocessen. Den Haag: LEI.

50.

Liberman-Yaconi

Hooper

Hutchings

(2010) Toward a model of understanding strategic decision-making in micro-firms: Exploring the Australian Information Technology Sector. Journal of Small Business Management 48: 70–95.

51.

Long

Ploeg

JDvd

(1994) Heterogeneity, actor and structure: Towards a reconstitution of the concept of structure. In: Booth

(ed.) Rethinking Social Development: Theory, Research & Practice, Essex: Longman, pp. 62–89.

52.

Lowe

Murdoch

Marsden

(1993) Regulating the new rural spaces: The uneven development of land. Journal of Rural Studies 9: 205–222.

53.

Marsden

(2003) The Condition of Rural Sustainability, Assen: Royal Van Gorcum.

54.

McElwee G (2006) The enterprising farmer: A review of entrepreneurship in agriculture. Journal of the Royal Agricultural Society of England 167(1): 66–75.

55.

McElwee

Bosworth

(2010) Exploring the strategic skills of farmers across a typology of farm diversification approaches. Journal of Farm Management 13: 819–838.

56.

McKeever

Jack

Anderson

(2015) Embedded entrepreneurship in the creative re-construction of place. Journal of Business Venturing 30: 50–65.

57.

McMullen

Shepherd

(2006) Entrepreneurial action and the role of uncertainty in the theory of the entrepreneur. Academy of Management Review 31: 132–152.

58.

Methorst

(2013) Monitoring economische ontwikkeling melkveehouderij Kampereiland, Dronten: Department of Applied Science, CAH Vilentum, pp. 29.

59.

Methorst RG, Roep D, Verhees FJHM, et al. (submitted for publication) Differences in farmers' perception of opportunities for farm development.

60.

Meulen

HABvd

Everdingen

WHv

Smit

(2012) Actuele ontwikkeling van resultaten en inkomens in de land- en tuinbouw in 2012, Den Haag: LEI Wageningen UR, pp. 204.

61.

Morgan

Marsden

Miele

(2010) Agricultural multifunctionality and farmers' entrepreneurial skills: A study of Tuscan and Welsh farmers. Journal of Rural Studies 26: 116–129.

62.

Moyes

Whittam

Ferri

(2012) A conceptualisation of the relationship capital of rural small service firms. Local Economy 27: 136–151.

63.

Oostindie

(2015) Family Farming Futures: Agrarian Pathways to Multifunctionality: Flows of Resistance, Redesign and Resilience, Wageningen: Wageningen University.

64.

Organisation for Economic Co-operation and Development (OECD) (2006) The New Rural Paradigm, Paris: OECD Publishing.

65.

Parnell

Lester

Menefee

(2000) Strategy as a response to organizational uncertainty: An alternative perspective on the strategy-performance relationship. Management Decision 38: 520–530.

66.

Pietola

Lansink

(2001) Farmer response to policies promoting organic farming technologies in Finland. European Review of Agricultural Economics 28: 1–15.

67.

Ploeg

JDvd

(2000) Revitalizing agriculture: Farming economically as starting ground for rural development. Sociologia Ruralis 40: 497–511.

68.

Ploeg

JDvd

(2003) The Virtual Farmer. Past, Present, and Future of the Dutch Peasantry, Assen: Royal van Gorcum.

69.

Ploeg

JDvd

Roep

(2003) Multifunctionality and rural development: The actual situation in Europe. In: Huylenbroeck

Durand

(eds) Multifunctional Agriculture: A new paradigm for European Agriculture and Rural Development, Hampshire, UK: Ashgate, pp. 37–53.

70.

Ploeg

JDvd

Ventura

(2014) Heterogeneity reconsidered. Current Opinion in Environmental Sustainability 8: 23–28.

71.

Potter

Tilzey

(2005) Agricultural policy discourses in the European post-Fordist transition: neoliberalism, neomercantilism and multifunctionality. Progress in Human Geography 29: 581–600.

72.

Primdahl

Kristensen

(2011) The farmer as a landscape manager: Management roles and change patterns in a Danish region. Geografisk Tidsskrift-Danish Journal of Geography 111: 107–116.

73.

RIVM (2002) Natuurbalans. Alphen aan de Rijn.

74.

Robson

Gallagher

Daly

(1993) Diversification strategy and practice in small firms. International Small Business Journal 11: 37–53.

75.

Roep D (2000) Vernieuwend werken, sporen van vermogen en onvermogen. In: Rural Sociology. Wageningen: Wageningen Universiteit.

76.

Shucksmith

Herrmann

(2002) Future changes in British agriculture: Projecting divergent farm household behaviour. Journal of Agricultural Economics 53: 37–50.

77.

Sutcliffe

Zaheer

(1998) Uncertainty in the transaction environment: An empirical test. Strategic Management Journal 19: 1–23.

78.

Thornton PH, Ribeiro-Soriano D and Urbano D (2011) Socio-cultural factors and entrepreneurial activity: An overview. International Small Business Journal 29(2): 105–118.

79.

Vanloqueren

Baret

(2009) How agricultural research systems shape a technological regime that develops genetic engineering but locks out agroecological innovations. Research Policy 38: 971–983.

80.

Vesala

(2010) Entrepreneurs and producers: Identities of Finnish farmers in 2001 and 2006. Journal of Rural Studies 26: 21–30.

81.

Vik

McElwee

(2011) Diversification and the entrepreneurial motivations of farmers in Norway. Journal of Small Business Management 49: 390–410.

82.

Wals

AEJ

Lans

Kupper

(2012) Blurring the boundaries between vocational education, business and research in the agri-food domain. Journal of Vocational Education & Training 64: 3–23.

83.

Wästfelt

Saltzman

Gräslund Berg

(2012) Landscape care paradoxes: Swedish landscape care arrangements in a European context. Geoforum 43: 1171–1181.

84.

Watson

(2013) Entrepreneurship in action: Bringing together the individual, organizational and institutional dimensions of entrepreneurial action. Entrepreneurship & Regional Development 25: 404–422.

85.

Welter

(2011) Contextualizing entrepreneurship – Conceptual challenges and ways forward. Entrepreneurship Theory and Practice 35: 165–184.

86.

Wilson

(2008) From ‘weak’ to ‘strong’ multifunctionality: Conceptualising farm-level multifunctional transitional pathways. Journal of Rural Studies 24: 367–383.

87.

Wiskerke

JSC

(2009) On places lost and places regained: Reflections on the alternative food geography and sustainable regional development. International Planning Studies 14: 369–387.

88.

Wiskerke

JSC

Roep

(2007) Constructing a sustainable pork supply chain: A case of technoinstitutional innovation. Journal of Environmental Policy & Planning 9: 53–74.

89.

Woods

(2012) New directions in rural studies? Journal of Rural Studies 28: 1–4.

90.

Yanes-Estévez

Oreja-Rodríguez

García-Pérez

(2010) Perceived environmental uncertainty in the agrifood supply chain. British Food Journal 112: 688–709.

91.

Zasada

(2011) Multifunctional peri-urban agriculture – A review of societal demands and the provision of goods and services by farming. Land Use Policy 28: 639–648.

92.

Zwan Pvd, Verheul I and Thurik AR (2011) The entrepreneurial ladder, gender, and regional development. Small Business Economics 39: 627–643.