Clustering and Integration in the
Organic Agriculture Sector in
The Netherlands
An exploratory research for CAB Groningen
Master thesis
Author: Kelly Leferink Student nr: 1460943
Master specialization: Small Business & Entrepreneurship, University of Groningen Supervisor 1: Dr. C.H.M. Lutz
2
Preface
In the past half year, I performed a research project for CAB in Groningen. The report resulting from this research now lies before you and is the final product of my study Business Administration at the State University of Groningen.
In this study, I focused on cluster- and integration developments in the organic agriculture sector in The Netherlands. I would like to thank dr. Hein Vrolijk for pointing me on this interesting research topic and his assistance during the research project. Also, I greatly benefited from the comments and expertise of dr. Clemens Lutz. The data used in the empirical part of this work was kindly provided by Stichting Skal. Last, I would like to thank my family and friends for their interest, advice and encouragements.
Kelly Leferink
3
Summary
Regional clustering and horizontal and vertical integration are both ways for companies to overcome problems in their conduct of business. In this study the relationship between horizontal and vertical integration on the one hand (in other words: internal integration) and regional clustering on the other hand is investigated with regard to the Dutch organic agriculture sector. In this study I focused on companies active in organic livestock agriculture production since investigating the entire sector lies beyond the reach of this project. According to the literature, companies which are located in environments that can be characterized by a high degree of regional clustering are expected to be less horizontally and vertically integrated than their counterparts. Furthermore De Jong (1989) states that the degree of internal integration for companies within a specific industry is subject to change during the industry life cycle. Considering the proposed relationship between internal integration and regional clustering, I expect that the degree of regional clustering is subject to change during the industry life cycle as well.
The research question of the study is:
To what extent are regional clustering and vertical and horizontal integration (internal integration) reflected in the organic livestock agro sector and are these two aspects related to each other?
4 economies of scale. Furthermore problems with respect to managing the high-growth companies in this stage encourage internal specialization activities as well.
In order to investigate changes in regional clustering and internal integration, a difference has been made between companies which have been certified for organic agriculture production during the early ‘90s and companies which have been certified recently. Accordingly these groups of companies have been compared on the degree and types of horizontal and vertical integration and on the degree of regional clustering. A difference has been made between companies in the primary and secondary sector. The primary sector refers to organic farmers. The secondary sector includes companies processing, trading and/or storing organic agriculture products. In addition, the companies have been categorized according to their type of livestock production as well: dairy production, meat production and egg production.
The analyses resulted in several interesting findings. With respect to the primary organic livestock sector, companies which have been certified in the introduction stage turn out to be horizontally and vertically integrated to a higher extent and regionally clustered to a lower extent compared to the companies which have been certified in the growth stage. These findings support the statement about the relationship between internal integration and regional clustering that has been made in literature. On the other hand, the findings resulting from the analyses about the companies in the secondary sector are less transparent. As a conclusion, the statement cannot be confirmed in the secondary sector.
The relationship between internal integration and regional clustering has also been investigated on the level of a product group. This analysis has been executed for the primary egg sector given the outstanding findings resulting from the analyses about regional clustering in this sector. On the basis of the analyses with respect to the primary egg sector, we confirm the existence of a relationship between internal integration and regional clustering as well.
6
Table of Content
Chapter 1 Introduction and Problem Statement ... 8
Chapter 2 Theoretical Background ... 12
2.1 The Diamond of Porter ... 12
2.2 Definitions of clustering ... 16
2.3 Dimensions of a cluster ... 19
2.4 Motives for clustering ... 20
2.5 Alternatives to regional clustering ... 22
2.6 Regional clustering and internal integration ... 26
2.7 Conceptual model ... 26
Chapter 3 Methodology ... 30
3.1 Propositions ... 30
3.2 Research phases ... 32
3.2.1 Phase 1: Learning about the research area ... 32
3.2.2 Phase 2: Literature background ... 32
3.2.3 Phase 3: Case studies of regional clustering in the agro sector ... 33
3.2.4 Phase 4: Processing and analyzing the data files ... 33
3.3 The Skal databases ... 34
3.4 The degree of internal integration ... 39
3.5 The degree of regional clustering ... 41
3.6 The relationship between the two issues ... 45
Chapter 4 The Dutch Organic Agriculture Sector ... 46
4.1 The agriculture sector ... 46
4.2 Principles of organic agriculture ... 47
4.3 Statistics about the organic agriculture sector ... 48
4.4 Organic agriculture value chain ... 52
4.5 Governmental support ... 54
4.6 Factors stimulating clustering and internal integration in the agriculture sector ... 55
4.7 Regional clustering in the Dutch agriculture sector ... 56
Chapter 5 Internal Integration in the Dutch Organic Agriculture Sector ... 61
5.1 Results for the period 1990-1996 ... 61
5.2 Results for the period 2007-2008 ... 68
5.3 Conclusions with respect to internal integration ... 73
Chapter 6 Regional Clustering in the Dutch Organic Agriculture Sector ... 79
6.1 Geographical maps ... 80
6.2 Calculations regional concentration ... 90
6.2.1 Geographical dispersion of companies in provinces ... 90
6.2.2 Geographical dispersion of companies in Corop areas ... 93
6.3 Conclusions with respect to regional clustering ... 94
7
Chapter 8 Conclusions and Recommendations ... 99
8.1 Conclusion ... 99
8.2 Limitations of the study and further research ... 104
8
Chapter 1 Introduction and Problem Statement
Agriculture has been playing an important role in The Netherlands for a long time. In the late 1960s, the organic agriculture sector attracted attention. People were becoming more and more concerned about the environment. In the 1980s, organic farming had been accepted as a sound production method in the agriculture sector. In 2006, the total sown area of the organic agriculture sector counted for about 2,5% of the total sown area in The Netherlands (agriholland.nl). The government has introduced initiatives to increase the organic sown area as well as consumer spending on organic food products in the upcoming years (LNV, 2007). At the moment two out of three Dutch consumers buy organic food products once in a while (Biologica, 2007).
Taking prior research about the regular agriculture food sector into account, regional concentrations are a well-known phenomenon in the agriculture sector. For example, all relevant suppliers and other specialized companies with respect to the mussels sector are located in Zeeland while many companies performing processing and/or trading activities with respect to cacao can be found in the Zaanstreek/ Amsterdam (Snijders et al., 2007). These regional cluster developments can result in a lot of advantages for the different companies joining the concentration process.
The hypothesis that firms located in regional clusters are expected to be more specialized than firms located elsewhere has been suggested by different authors (e.g. Marshall, 1938; Storper, 1997). According to the literature, companies in regional clusters tend to outsource various stages of production to specialized, local suppliers. This implies that companies not located in regional clusters tend to undertake these stages of production by themselves as vertically-integrated firms (Holmes, 1999). A similar relationship between regional clustering and horizontal integration, the breadth of the product line of a company, has been confirmed as well (Brookfield, 2007). Companies have several motives for becoming more internally integrated or more specialized, which will be explored in the next chapter.
This research addresses the following key questions:
9 Does this geographic pattern correspond to the presumed extent of vertical and horizontal (dis)integration as has been mentioned above?
This study contributes to the clarification of the structure of the organic agriculture sector in The Netherlands by analyzing the presence of regional concentration and the extent of horizontal and vertical integration for different product groups in the organic agriculture sector.
Research and consultancy company CAB in Groningen has decided to start a study to this subject, since they would like to specialize in the area of cluster studies and the agriculture sector is one of their main fields of research (cabgroningen.nl). CAB is active in the fields of policy research and policy advice. They have chosen for the organic agriculture sector since little research has been carried out in this sector with respect to clustering developments. They have asked me to accomplish an exploratory study. This study is relevant for CAB because it will give them more profound insight in the main cluster developments in the different subsectors of the organic agriculture sector, referring to two of their focus areas. CAB is especially interested in the changes in regional concentrations in this sector, in other words the dynamics of the sector, because these changes reflect the developments in the organic agriculture sector over time. CAB will be able to use the results of this study as a foundation for further research about this sector.
In order to accomplish this research, CAB has given me access to two Skal databases which contain information about all the registered organic companies in The Netherlands. The first database includes information about the primary agriculture sector, the farmers. The other database contains information about the secondary sector, which includes the companies processing, trading and/or storing organic agro products. The research will focus on both sectors because especially the relationship between companies in different stages of the value chain is interesting. These are the companies which supply or purchase the products of each other and therefore might want to operate in close geographic proximity in order to reduce costs or obtain other benefits.
10 companies, the organic livestock agro sector. This sector consists of clear product categories (such as dairy production, meat production and layers) and clear company activities (such as
processor, storage and butcher). In contrast, the organic crop production includes many
different product categories (like preserves, flavoring products, beverages and ornamental
horticulture) and is therefore more difficult to analyze.
This results in the following problem statement for this study:
To what extent are regional clustering and vertical and horizontal integration (internal integration) reflected in the organic livestock agro sector and are these two aspects related to each other?
The next subquestions cover the main points of interest of this study:
1. What are the main characteristics of the Dutch organic agriculture sector?
2. To what extent have (changes in) vertical and horizontal integration occurred in the organic livestock agro sector in The Netherlands during the data collection period (1990-2008)?
3. To what extent have (changes in) regional clustering occurred in the organic livestock agro sector in The Netherlands during the data collection period (1990-2008)?
4. Are the developments during the data collection period (1990-2008) with respect to internal integration and regional clustering in the organic livestock agro sector in The Netherlands connected to each other?
11 subquestion 2 and subquestion 3: Are companies located in environments that can be characterized by a high degree of regional clustering indeed less horizontally and vertically integrated than their counterparts?
The structure of this study will now be discussed.
12
Chapter 2 Theoretical Background
The phenomenon of clustering plays an important role in the current business environment. Joining a (regional) cluster can result in a lot of advantages for the participants. Therefore cluster developments take place in various business industries. This chapter deals with various issues related to clustering. The first paragraph outlines the role of The Diamond of Porter in explaining clustering. Subsequently, the background of clustering and different definitions assigned to clustering will be discussed. The dimensions of a cluster and the advantages of clustering will be presented in the succeeding paragraphs. Paragraph 2.5 explores alternatives to regional clustering and at the end of the chapter the relationship between regional clustering and internal integration will be discovered.
2.1 The Diamond of Porter
Porter’s book (1990) The Competitive Advantage of Nations contributed significantly to the cluster theory. Many recent studies with respect to clustering have been built upon his model, The Diamond (figure 2.1). The Diamond explains national competitive advantage as a function of four determinants; factor conditions, demand conditions, related and supporting
industries and firm strategy, structure and rivalry. Other factors that influence the national
system are chance and the government.
13 The determinants of The Diamond will now be discussed:
· Factor conditions
Factors of production are the inputs a country needs in order to compete in any industry. Porter (1990) distinguishes two types of factor conditions, the basic factors and the advanced factors. The basic factors are the natural resources, climate, location, unskilled and semiskilled labor and debt capital. Advanced factor include highly educated personnel, university research institutes and modern digital data communication infrastructure. The last category, the advanced factors, is the most important one for creating competitive advantage, according to Porter (1990).
Specificity is a second significant distinction among factors of production.
Generalized factors of production include for example the system of highways, highly
motivated employees with college education or supply of debt capital. These factors can be deployed in many different industries. The second category, specialized factors involve specifically skilled personnel, knowledge bases in specific fields and other factors of production relevant to a limited range of industries.
The competitive advantages for a nation will be most significant and sustainable in the case that the factors needed for competing in a specific industry are advanced as well as specialized. An example is the success of Germany in the optic sector (Porter, 1990). The presence of a pool of highly skilled people trained in specialized programs and graduates specialized in optical physics supported the product performance and quality of optic products.
· Demand conditions
The second determinant of the international competitive advantage of industries is the home demand in a nation. Three properties of home demand are important in achieving national competitive advantage:
o Home demand composition: the mix of segments and the nature of home buyers. An example is the relatively large home demand in Japan for microwaves. This has resulted in a lot of attention to the technology and subsequently to a stronger international position (Porter, 1990).
14 o Internationalization of domestic demand: mechanisms that internationalizes the domestic demand of a nation. For example the sales of US medical equipment companies have been stimulated by offering training opportunities in the US to foreign doctors. These companies find many potential customers when they try to sell abroad (Porter, 1990).
· Related and supporting industries
The presence of supplier industries or related industries in a nation that are internationally competitive. They create advantages for example due to easier access to the most cost-effective inputs, ongoing coordination between suppliers and the process of innovation and upgrading. A network of these competitive industries in a nation (or region) can be defined as a cluster. A well-known example of a cluster is the presence of internationally successful supplier industries to footwear in Italy, such as the design services and leather processing industries (Porter, 1990).
· Firm strategy, structure and rivalry
The way in which companies are created and managed and the nature of domestic rivalry is another determinant in The Diamond of Porter (1990). Nations are most likely to succeed in industries where the national environment’s most favored organization types and management practices are well fitted to the sources of competitive advantage of the industry. In Italy, for example, companies often compete by using a focus strategy and producing customized products. This strategy corresponds well to the characteristics of the fragmented industries (such as footwear, furniture and lightning) Italy is successful in. Economies of scale are modest in these industries or can be overcome through collaboration among related industries.
Two additional factors that can influence the national system:
· Chance
15 · Government
The government of a country can improve or detract from the national advantage, according to Porter (1990). For example, the government is often a major buyer of products in a nation and can thereby influence the nation’s industry.
The determinants are mutually connected to each other. The unit level for analyzing the national competitive advantage of a country or region is the industry. In most of the cases, the success of a country or region isn’t based on a separate industry, but on the intertwinement of several supplying and/or related industries, that is, in clusters of industries. The systematic nature of The Diamond promotes the clustering of a nation’s competitive industries. The successful industries of a nation are usually connected with each other through horizontal (common customers, channels, technologies etc.) or vertical (buyer/supplier) relations (Porter, 1990). Furthermore, Porter (1990) discovered that internationally successful industries are generally located in one or a few small geographic areas. This phenomenon can be explained by the fact that the influence of the determinants of The Diamond and their mutual reinforcement are increased by close geographic proximity in a nation.
Jacobs et al. (1996) underline another important contribution of Porter’s cluster theory. Porter recognizes the strong relationships between the primary (agriculture), secondary (industry) and tertiary (services) sectors in an economy. The different sectors are strongly connected to and dependent on each other. This corresponds to the focus of this study about regional concentrations in the organic agriculture sector since the companies active in this sector are operating in the different sectors as well. In order to perform a sound cluster analysis, the relationships between companies in the different sectors have to be taken into account.
Alongside these positive contributions of The Diamond criticisms point out that the cluster concept of Porter is more a composition of accepted agglomeration phenomena instead of new groundbreaking insights into the reasons for firms to participate in a regional cluster process (Vom Hofe et al., 2006). Therefore we will discuss contributions of other authors with respect to motives for regional clustering in paragraph 2.4 in order to get a better understanding about the relevance of clustering.
16 relevance of the different elements of The Diamond in describing cluster developments will be discussed in the conceptual model of paragraph 2.7. Before that we will first explore the definitions assigned to the phenomenon of clustering by different authors in the next paragraph.
2.2 Definitions of clustering
Since the 19th century clustering is a phenomenon that has been widely investigated and analyzed. Marshall (1890) is usually acknowledged as the founder of the phenomenon that the economic productivity of firms results from the location and proximity of economic agents to another (Hofe et al., 2006). In fact, he started the ‘industrial districts’ literature. Those companies that operate close to others obtain benefits compared to companies that operate far from each other, according to Marshall (1890). He identified three factors that explain the development of an ‘industrial district’: labor market pooling, knowledge spillovers among firms and cost advantages produced by specialized intermediate inputs. First of all, companies will be attracted to a specific region if the specialized labor supply in that region is excellent. The second factor addresses the exchange of knowledge between companies. In the case that companies are closely located to each other, knowledge exchange between companies is easier to accomplish compared to companies that operate far from each other. Finally, companies closely located to a chain of specialized intermediate suppliers have the advantage of favored access to the knowledge and services of these specialized intermediate suppliers.
About one hundred years after the contribution of Marshall, the phenomenon of clustering attracted the attention of Porter (1990) and Krugman (1991). Porter (1990) has introduced The Diamond model as described in paragraph 2.1. Krugman (1991) supports Marshall’s arguments, putting forward the three factors fostering the development of industrial districts. Furthermore he introduces two facts which contribute to the concentration of industries. Because of the increasing costs of transactions across distance he puts forward that the preferred locations for manufacturers are those where demand is larger or supply of inputs is convenient. These locations are generally the locations chosen by other producers. The second fact contributing to concentration are economies of scale. Producers have an incentive to concentrate production in a limited number of locations because of economies of scale.
17 in many different ways to define a cluster. Some of these definitions will be discussed in this paragraph.
Porter (1998, p. 197) defines a cluster as a geographic concentration of interconnected
companies, specialized suppliers, service providers, firms in related industries, and associated institutions in particular fields that compete but also cooperate.
In the study Industry Clusters and SMEs, Muizer et al. (1998) come up with a new working definition of modern industry clusters. They emphasize that the formulation of a clear and widely accepted definition of industry clusters is hampered by different approaches and theories in the literature of clustering. Their definition is a cooperation arrangement with the
strategic objective of maintaining or enhancing the competitiveness of its participants which includes at least 4 partners one or more of which being a small or medium sized enterprise (SME). According to Muizer et al. (1998), this definition can be used to assess the role and
position of SMEs in industry clusters. They have set a condition for the number of parties in order to exclude bilateral cooperation agreements. Furthermore the definition puts emphasis on the strategic objective of clustering because a long term strategic cooperation arrangement is the main point of interest according to them.
Kerste et al. (2001) have investigated the role of small and medium-sized businesses in regional clusters in The Netherlands. The concept cluster is defined in this study as a strategic
cooperation agreement in which at least one small or medium sized company participates in the cluster. Kerste et al. (2001) do not illustrate the significance of the condition of a strategic
objective. Nonetheless this is not in line with the perception of Porter (1998) and Marshall (1890). They do not stress the importance of the condition of a strategic objective in the concept of clustering. Furthermore, they distinguish two types of cooperation between companies in a cluster, regional cooperation and other (non-regional) cooperation types. The first one is about companies that cooperate with other companies and/or organizations located in the same region. The second one refers to companies that cooperate on a national or international level with companies and/or organizations outside the home region. The first type of cooperation characterizes the regional cluster which is the focus of this study.
18
type of cooperation between (or: a network of) two or more companies, their suppliers, clients and/or knowledge organizations, which should result in some kind of innovation. Cooperation
between companies results in possibilities to help each other within the innovation process according to Baarsma et al. (2003). Therefore they define clustering as the type of cooperation which results in innovation.
Many of these definitions include some kind of limitation to the applicability of the concept ‘cluster’. For example, Muizer et al. (1998) and Kerste et al. (2001) require a minimal number of SMEs to be included in the cluster and they have added a condition about strategic objectives. Furthermore, Baarsma et al. (2003) emphasize the importance of innovation as a result of clustering.
Porter’s definition (1998) is the exception that doesn’t set specific requirements about the type or number of participants in the cluster (for example SMEs) or the ultimate goal of clustering (for example innovation or another strategic objective). Therefore, I will use the definition of Porter (1998, p. 197) in this study:
A geographic concentration of interconnected companies, specialized suppliers, service providers, firms in related industries, and associated institutions in particular fields that compete but also cooperate
By using this definition, the risk of excluding some parties and/or certain linkages between companies which can be relevant for this study decreases. Furthermore, this definition emphasizes the geographical component as a characteristic of a cluster, which corresponds to the regional focus of this study.
An example of a cluster in The Netherlands is the mussels industry in the province of Zeeland (Snijders et al., 2007). All relevant suppliers and other specialized companies with respect to the mussels industry are located in this province. This and another example of clusters in the agriculture sector in The Netherlands will be discussed extensively in chapter 4.
19 concentrations of related companies that might, but not necessarily have to, cooperate. A network on the other hand requires some kind of cooperation between the companies in the network. Furthermore, companies in a network can operate close or far from each other. Close geographical proximity is not a requisite.
Another difference between the concepts of cluster and network is the relevance of a strategic goal. Companies within a network have explicitly chosen to participate in a network in order to cooperate. However close geographical proximity of companies within a cluster can be a coincidence for some of the cluster parties and cooperation between these companies is not necessarily a requirement.
2.3 Dimensions of a cluster
As formulated in paragraph 2.2, a cluster can be defined as a geographical region of mutually connected companies. The origin of a cluster varies, depending on the activities of the cluster, the sector or branch of the cluster and the region of the cluster (Kerste et al., 2001). Jacobs et al. (1996) defined different dimensions to analyze a cluster. Subsequently, Kerste et al. (2001) came up with a new categorization based on the study of Jacobs et al. (1996):
· The geographical dimension
The clustering of economic activities within a specific geographical area. · The horizontal dimension
The clustering of competitive firms which perform similar activities. They operate in similar stages of the value chain of related industries and they are direct competitors on the product market.
· The vertical dimension
The clustering of complementing firms which operate in different stages of the value chain of a specific product or service.
· The institutional dimension
Clustering of companies and knowledge institutions as an interactive learning process. The goal is producing and utilizing new technologies. For instance, cooperation between a large company, several small companies and a research institute in order to develop a new production technology.
· Diagonal dimension
20 Moreover, Muizer et al. (1998) found out that a cluster is usually composed of several players (large players, SMEs, public institutes) and is often structured as a combination of several dimensions. Their study resulted in some statements:
The vertical dimension is predominant in the case that a large outsourcing company in the cluster forces its suppliers (often SMEs) to cooperate
The horizontal dimension is predominant in a situation where supplying SMEs start a cluster in one branch of industry in order to compensate for their material
disadvantages
The geographical dimension is predominant in a cluster in which a regional government institution is the initiator and tries to enhance the competiveness of a region
The institutional dimension is predominant in the case that a knowledge institution is the initiator of the cluster and strives for commercial exploitation of a specific R&D invention
The dimensions of a cluster should be taken into account in this study about the organic agriculture sector, because they clarify the structure of a specific cluster and the relations between the parties of the cluster. Furthermore the geographical dimension is a requisite for a cluster in this case, given the regional focus of the study.
2.4 Motives for clustering
Companies participating in a cluster obtain several advantages over companies operating on their own. Kerste et al. (2001) distinguish three categories of motives that companies have in order to participate in a cluster: strategic, technological and economic motives.
Strategic motives
21 to a large, well-known company in order to take advantage of the relations and reputation of this company.
Technological motives
A company might want to participate in a cluster for technological motives. Companies joining a cluster will be able to share knowledge, skills and experience of other cluster parties in order to stimulate innovation. Clustering will increase the quickness of executing innovation processes. Furthermore clustering results in synergy effects with respect to innovation, which will lead to a higher quality of the innovation processes. Finally, the risks associated with innovation will be reduced caused by the participation in a cluster.
Economic motives
The main economic reason for joining a cluster is overcoming the disadvantages associated with the limited scale of individual firms. Scale- and scope effects are possible outcomes of sharing capacities. Companies might obtain efficiency advantages by executing joined R&D projects or other activities. Another economic motive is enhancing the quality of products and services and thereby enlarging the value added. For instance, two companies may want to offer a joint service point for their products.
Other classifications
Marshall (1890) mentioned three factors that explain regional cluster developments as discussed in paragraph 2.2. These factors are labor market pooling, knowledge spillovers
among firms and cost advantages produced by specialized intermediate inputs.
Another classification for advantages resulting from the participation in a cluster has been introduced by Bell (2005). He explores two categories of benefits deserved to cluster parties. The first category includes benefits from agglomeration economies, like direct observation of competitors and the presence of nearby suppliers. The other category contains advantages
caused by network-based effects, such as enhanced social interaction.
Motives for clustering in the agriculture sector
22 operate in the same stage of a specific value chain, different stages of the value chain or even in different value chains.
Several motives for regional clustering have been discussed in this paragraph. The relevance of regional clustering for companies in a specific industry is elucidated by means of this discussion.
2.5 Alternatives to regional clustering
Regional clustering is one way to realize scale and scope advantages for small companies, as discussed in paragraph 2.4. In this case the benefits are collected by some kind of cooperation
between companies in a specific region. Another way to realize scale and scope advantages is within a company by means of internal integration. There are two types of internal integration:
horizontal and vertical integration.
Horizontal integration
Horizontal integration, or in other words diversification, refers to a situation in which a firm produces a wider variety of products (Besanko et al., 2007). An example of this kind of integration is the situation in which a farmer formerly specialized in cows decides to keep pigs as well. Companies realize economies of scope if the expansion of the variety of goods and services its produces results in savings. De Jong (1989) explores the two most common motives for horizontal integration. The first motive for horizontal integration that has been mentioned frequently is risk elimination by operating in different industries. The second refers to financial opportunities for the company. A company operating in a stagnating industry might want to invest her resources in a growing industry in order to continue and expand the business.
Vertical integration
23 chain in the activities of the company. This is the case if a farmer producing milk wants to produce and sell cheese as well.
Limited resources of small companies can but do not have to be a restriction for horizontal and/or vertical integration. For example, the farmer who decides to produce and sell cheese in-home as well does not necessarily needs many more resources in order to expand the scope of his activities.
Concluding, a firm has to take a make-or-buy decision with respect to the production of goods and services (Besanko, 2007). Vertical integration refers to ‘make’, implying that the company performs the activity itself, while market transactions refer to ‘buy’, which means that the company purchases the activity or input from an independent firm. The advantages and disadvantages of each decision, which are opposites of each other, have been summarized in table 2.1 and 2.2.
Table 2.1: Advantages of market transactions, costs of integrating (Besanko, 2007, p. 109)
Table 2.2: Costs of market transactions, advantages of integrating (Besanko, 2007, p. 109)
Regional clustering can be perceived as an in-between alternative to these two opposites. Besanko (2007) mentions that close-knit semiformal relationships among suppliers and buyers, which are often based on long-term implicit contracts, are another way to organize exchange. This can be defined as a cluster.
Benefits of integrating / Costs of the market
Costs of poor coordination between steps in the vertical chain when activities are performed by different companies
Private information may be leaked when an activity is performed by an independent firm Transaction costs
Benefits of the market / Costs of integrating
Market firms can achieve economies of scale that in-house departments producing only for their own needs cannot
24
Internal integration and the industry life cycle
De Jong (1989) has introduced a theory in which he states that the degree of internal integration for companies within a specific industry is subject to change during the industry life cycle. He has distinguished four different stages in the life cycle for products, technologies or industries: introduction, growth, maturity and decline. An S-shaped growth curve (figure 2.2) is the result of the combination of these four stages.
Figure 2.2: The industry life cycle (De Jong, 1989)
Stage 1 Introduction
25 Stage 2 Growth
In the case that the product succeeds during the introduction phase, it faces the growth stage. The product sales and revenues increase fast. The growth stage can among others be characterized by an increased scale of production, product and process innovations and increased sales effort of the suppliers. New players enter the market with similar products which causes the total number of suppliers to increase. They are able to introduce product processes which totally take in the economies of scale given the sufficient size of the market, which results in more vertically specialized firms, or in other words disintegration. Another reason for a tendency toward vertical (and horizontal) specialization in this stage are problems with respect to managing the high-growth companies.
Stage 3 Maturity
The market starts to mature in the end of the growth phase. All new techniques have already been introduced and the number of companies that can produce on an optimal scale decreases. This results in an increase in the degree of vertical forward and/or backward integration in order to decrease costs and acquire dominant positions within the market. This development continues during the maturity phase. Overcapacity depicts the market and the output is stabilizing or even declining in this stage. Changes in sales are predominantly caused by changes in the size of the market. Companies react with product differentiation, market segmentation and cooperation. Horizontal integration is a common phenomenon in the maturity phase. Companies in this phase are threatened by stagnation. In order to protect the existence and expansion of their business, companies start to look out for alternative products in growing industries. In general the companies which undertake horizontal integration are the large and financially strong companies in the market.
In the end of the maturity stage, the companies which have been vertically integrated often turn out to be in the best position. They are able to incorporate other companies which result in an oligopolistic or even monopolistic market structure.
Stage 4 Decline
26
2.6 Regional clustering and internal integration
The relationship between regional clustering and the degree of internal integration of a company is a topic often discussed in the literature about clustering. For example Marshall (1938) states that geographical proximity makes it possible for specialized input producers to emerge in areas with localized industries. Furthermore Stigler (1951) puts forward that as an industry increases in size, companies may start to specialize in activities, especially those subject to increasing returns to scale. He suggests that localization increases the effective economic size of an industry, allows for gains from specialization and results in lower levels of vertical integration compared to geographically dispersed companies (Enright, 1995, p.107).
Enright (1995) states that regional concentration improves the effectiveness of market transactions by reducing the cost of transactions and reducing the changes that companies engage in opportunistic behavior. This will stimulate firm interdependence and therefore tend to encourage vertical disintegration, e.g. the tendency to obtain inputs from specialized suppliers rather than making them within an integrated company, as well.
Brookfield (2007) has investigated the degree of vertical and horizontal integration for Taiwanese machine tool companies in the industrial district Taichung and machine tool firms located elsewhere on the island. Brookfield (2007) introduced two hypotheses which both have been confirmed in his study. The first one refers to vertical integration: ‘Vertical
integration should be less for companies located in a multi-centered, locally owned industrial district’. The second one is about lateral (horizontal) integration, as measured by the breadth
of the product line of a company: ‘Lateral (horizontal) integration, as measured by the
breadth of a company’s product line, should be less for companies located in a multi-centered, locally owned industrial district’. This assumption can partly be explained by the
fact that economies of scope are less important in environments where inputs are widely available and therefore enable multi-product areas without multi-product firms (Goldstein and Gronberg, 1984). Furthermore Enright (1998) states that competitive feelings resulting from close geographical proximity of competitors may also be a reason for some companies to narrow the product scope.
2.7 Conceptual model
27 relations between the concepts. The different elements of the conceptual model will be clarified successively.
negative relation
Figure 2.3: Conceptual model
Regional clustering versus internal integration
The relationship between regional clustering and horizontal and vertical integration has been discussed in paragraph 2.6. The conclusion of the paragraph is that regional clustering and internal integration are negatively related to each other, where internal integration can be distinguished in horizontal and vertical integration.
The dimensions
The geographical dimension is a requisite in order to use the definition ‘cluster’ in this study, as assumed at the end of paragraph 2.3. Therefore this dimension is incorporated in the research concept of this study which is cluster developments in the organic agriculture sector.
The other dimensions of a cluster have been connected to the factors of Porter’s Diamond in the conceptual model.
28 operating in similar stages of different value chains can be characterized by competition, although they might want to cooperate as well.
The vertical dimension of a cluster, clustering of complementing firms that operate in different stages of the value chain of a specific product or service, has been connected to the ‘Factor conditions’ of Porter. The inputs necessary to compete in the industry are partly produced in earlier phases of the value chain of a specific product. For example, a butcher needs high quality meat in order to deliver steaks to his customers.
The diagonal dimension, clustering of different companies in related industries that share specific competencies, has been related to the ‘Related and supporting industries’. Companies that are located in different stages of different value chains can benefit from each other as well.
The institutional dimension has been absorbed by the other dimensions in the conceptual model. For example, a cluster in which agriculture companies and specific knowledge institutes participate can be characterized by the diagonal dimension as well. The agriculture companies on the one hand and the knowledge institutes on the other hand operate in different stages of different value chains.
As a consequence, one element of The Diamond of Porter has not been included in the conceptual model: Demand conditions. In this study I will not pay attention to the demand side of the market in investigating cluster developments. The study focuses on the companies in a cluster and the relationships between them.
The industry life cycle
The industry life cycle influences the model as a whole. The degree of internal integration and the degree of regional clustering for companies differ for each stage of the industry life cycle. Correspondingly, the relevant dimensions are subject to change as well.
29 perform certain activities, produce certain products or why those companies are situated in a specific region. A way to find out about these motives is taking interviews with the relevant company owners or experts in the industry, but the restricted time period won’t allow for this. Individual motives of companies for regional clustering and internal integration are points of interest for further research with respect to clustering in the organic agro sector in The Netherlands.
30
Chapter 3 Methodology
This chapter defines the methodology and structure of this study. Several propositions with respect to the conceptual model will be introduced in this chapter as well.
3.1 Propositions
Several propositions can be drawn from the conceptual model (figure 2.3) and the theory described in chapter 2. I will first discuss the industry life cycle for the organic agro sector in The Netherlands before I will introduce accompanying propositions.
This study focuses on the developments in the organic agro sector in the period 1990-2008 since the Skal databases contain information about companies registered in this period. This is a long period in which two stages of the industry life cycle as mentioned in paragraph 2.5 can be distinguished.
The organic agro sector in The Netherlands attracted more and more attention during the ‘90s and the sector professionalized to a higher degree (Melita, 2000). Supermarkets started to introduce some organic products into their assortments in the early ‘90s (Van den Ham, 2007). The graph ‘Aantal biologische landbouwbedrijven aangesloten bij Skal’ in Van den Ham (2007) shows that the number of Skal registered agro companies has increased slightly during the early nineties. Given the limited growth rate, we may assume that the sector faced the introduction phase of the industry life cycle during the early ‘90s. According to De Jong (1989), vertical integration is expected to be common among companies in this stage. It is a way to overcome problems with the supply of inputs and with the sales and distribution of the processed products. Given the theory of De Jong (1989), I assume that the degree of vertical integration is relatively high for companies which have been registered at Skal during this period. Furthermore, the degree of horizontal integration is expected to be relatively high for these companies as well, compared to companies which have been registered recently. This will be explained in the introduction of proposition 2.
31 The current organic agro market can be characterized by growth. Customer spending has increased with 12,4% in 2008 and the number of Skal registrations has increased as well (Biologica, 2008). The Dutch government has introduced new growth objectives in 2007, the market share of organic products should grow over the next period every year with 10% (LNV, 2007). Besides this, the organic cultivated area should increase with 5% each year. Given the developments we may assume that the organic agro sector in The Netherlands currently faces the growth phase of the industry life cycle as described by De Jong (1989) in paragraph 2.5 and, consequently, companies tend to become more vertically and horizontally disintegrated (in other words, specialized). This can be explained by the fact that the companies are able to introduce new processes which take in the economies of scale. Furthermore problems with respect to managing the high-growth companies in this stage encourage internal specialization activities as well. Therefore, I assume that the degree of vertical and horizontal specialization is relatively high for companies which have been registered at Skal during the last few years.
P2: The degree of vertical and horizontal specialization is relatively high for companies which have been first registered by Skal during the last few years.
Proposition 3 and 4 are related to the relationship between regional clustering and internal integration. I expect that the organic livestock companies in the database act up to the statements made in the literature as described in paragraph 2.6. This results in the following propositions:
P3: Companies located in environments that can be characterized by a high (low) degree of regional clustering, are expected to be less (more) horizontally integrated than their counterparts.
P4: Companies located in environments that can be characterized by a high (low) degree of regional clustering, are expected to be less (more) vertically integrated than their counterparts.
32 the companies which have been registered during the last few years. This expectation is graphically represented in figure 3.1.
Figure 3.1: The industry life cycle of the organic agro sector in The Netherlands
3.2 Research phases
This paragraph clarifies the methodology of the study. The different research phases will be defined and the steps that have to be taken in order to accomplish the phases will be clarified.
3.2.1 Phase 1: Learning about the research area
I have read different studies about the (organic) agro sector in The Netherlands in order to get a better understanding of the area of research. Most of the reports about the organic agro sector I have read were published by Biologica (biologica.nl), LEI (lei.wur.nl) and Skal (skal.nl). Studies about clustering in the agriculture sector in The Netherlands were reports of interest as well. Examples of these are De economische kracht van Agriculture food in
Nederland (Snijders et al., 2007) and Vergane Glorie of Nieuw Elan (Vrolijk, 2008). The
extensive information about the research objective has supported me in the process of writing a research proposal.
3.2.2 Phase 2: Literature background
33 regional clustering. The relevant theoretical background with respect to this project has been summarized in chapter 2.
3.2.3 Phase 3: Case studies of regional clustering in the agro sector
Examples of regional clustering in the agro sector in The Netherlands will be explored in paragraph 4.7. These examples will be used to verify the relevance of the concepts used in the conceptual model. The conceptual model serves as a guideline for the descriptions about clustering developments in different product groups. Obviously I preferred to describe the cluster developments in the organic agriculture sector given the subject of this study, but unfortunately written examples of clustering in this sector are hard to find. Therefore I decided to explore two sectors in the non-organic agriculture sector in The Netherlands in which regional clustering plays a significant role. The sectors which have been described are the mussel sector in Zeeland and the ornamental horticulture industry in and around Aalsmeer. Some facts with respect to internal integration will be discussed as well, although in general it is hard to find information about the degree of horizontal and vertical integration of companies in a specific sector.
3.2.4 Phase 4: Processing and analyzing the data files
The cluster developments in the organic agriculture sector over time in The Netherlands will be analyzed with the help of the Skal databases. The research area has been fenced off given the extensiveness of the databases and the limited time period of the research project. The focus of the study is the organic livestock agro sector because this subsector consists of clear product categories (such as dairy production, meat production and layers) and clear company activities (such as processor, storage and butcher) in the Skal databases. In contrast, the Skal databases include many different non-specific product categories with respect to organic crop production (like preserves, flavoring products, beverages and ornamental horticulture). Therefore this sector is more difficult to analyze. The research will focus on both the primary sector (farmers) and the secondary sector (companies which process, trade and/or store organic agriculture products) because especially the relation between companies in different stages of the value chain is interesting.
34 subparagraph 3.4 and 3.5. The methodology with respect to the relationship between the aspects is the topic of subparagraph 3.6. First, I will start with some commentary about the Skal databases and about classifications that have been applied in order to classify the companies in relevant groups.
3.3 The Skal databases
Skal is an organization assigned by the government which controls the organic agriculture production in The Netherlands (skal.nl). They inspect and certify companies which produce, process, trade or store organic agro products. The companies which have been certified have all been registered in two databases. The first database contains data about the primary agro sector. All organic agro companies (1383) which have been certified up till December 2008 are included in the database. The other database contains information about the secondary agro sector. This includes an overview of all certified companies in October 2008 (1169) which process, trade or store organic agriculture products. The information collected in the databases includes Skal nr, company name, address, postal code, city, company type/product and certification date.
I’ve decided to focus on the organic livestock agro sector, as discussed in the description of research phase 4. The distribution of the companies of the Skal databases in the primary and secondary organic livestock agro sector can be found in appendix 1. Companies can be active in more than one product category.
Categorization of the companies
In order to be able to analyze the cluster developments with respect to the topics of interest in the organic agro market, I first had to introduce ways to classify the companies in the databases. I have introduced 4 different classifications, each with respect to a specific topic of interest. The classifications will be applied to each company which is active in organic livestock production, processing, trade or storage. However, in some cases it will not possible to group a company according to each of the 4 classifications. These exceptional cases will be discussed later.
35 the companies should be determined in which industry or industries and product group(s) they are active. What should be noted with respect to this subject is that the agriculture sector consists of different levels: the level of industries and the level of product groups. The degree of horizontal integration for a specific company should be determined for both of these levels. The levels are displayed in figure 3.2.
Figure 3.2: Levels of the agriculture sector
The level of industries consists of four different groups. The first group includes companies specialized in livestock production. The second group includes companies that are active in organic livestock production and the production of cattle food. Companies which are active in livestock production and crop production as well belong to group three. Group four includes companies specialized in crop production. With respect to this categorization, I have decided to make a difference between cattle food and other crop production although cattle food is in fact a crop production activity. However since cattle food is an input for livestock production, and other crop products are not, I would like to make a difference between these two types of crop production. The division between crop production and cattle food production is not relevant for companies in the secondary sector since cattle food is not an input for these companies.
36 Based on the descriptions of company activities in the Skal databases, I decided to introduce three different livestock product groups: meat, dairy and eggs. This categorization corresponds best with the product categories mentioned in both Skal databases. All company activities recorded in the primary and the secondary database can be grouped according to this categorization. For example in the primary sector Skal distinguishes dairy production, meat production and layers as agriculture activities. With respect to processing and trade activities, dairy, eggs and egg products and meat and meat products are some of the options recorded in the Skal databases.
Each company in the primary and secondary Skal databases should be classified into one of the groups of the level of industries and in one or more groups of the level of product groups in order to determine the degree of horizontal integration on each level. However, this will not be possible for all of the companies. For some companies in the organic agro sector, such as an organic supermarket or a warehouse, it is not obvious which organic products they produce, process, trade or store. It is not even clear in which industry they do business: organic livestock production, organic crop production or both. These companies cannot be categorized in either the groups of the level of industries or in the groups of the level of product groups. As a result the degree of horizontal integration cannot be determined for these companies. Furthermore no difference has been made in the Skal databases between companies performing stock rearing activities (opfok) with respect to dairy cattle and stock rearing activities with respect to meat cattle. As a result, the companies performing exclusively stock rearing activities cannot be connected to the different product groups (dairy, meat and eggs) as well. As a consequence, those companies have not been included in the population for the analyses about the degree and types of horizontal integration. Unfortunately I am not able to search for a pattern in the characteristics of these companies given the limited data availability. On the other hand, I have no reason to assume that those companies have certain characteristics in common.
37
food production (veevoeder productie), stock rearing (opfok), also called base material
production, (primary) agriculture (landbouw), processing of agriculture products (bewerking) and trade & storage of these products (handel & opslag). Manure is a residual product of livestock production and is not an input for another stage of the livestock value chain. Therefore we will leave this product out of consideration in this study.
Companies can be active in more than one stage of the value chain. The company activities described in the Skal databases can all be grouped according this categorization. Several types of processing activities such as general processing and processing for another company will be grouped together in the activity ‘processing agriculture products’. Furthermore activities such as shop, import, trade and storage belong to the activity ‘trade and storage’.
The production of cattle food is the stranger in the group since this is an activity related to crop production (plantaardige landbouw). However, it is an input for the livestock production as well. Therefore the combination of cattle food production and livestock agriculture can be perceived as a special form of vertical integration, operating in succeeding stages in the value chain.
The degree and types of vertical integration can be determined for all companies in the Skal databases, also for companies with unknown industries or product categories. The analyses with respect to vertical integration will separately be executed for companies belonging to this group.
38 registered during this period will be included in the analysis about the introduction stage. Skal has given me access to databases reflecting the situation at the end of 1996. All companies in the primary and secondary sector which have already been registered by Skal at the end of 1996 are included in these databases. In total 404 companies are included in the primary database and 232 companies in the secondary database. In the meantime 66 of the 404 companies in the primary sector have left the organic agriculture market. Within the secondary sector 45 out of 232 companies have left the market.
Currently, the organic agro sector still faces growth as has been described in paragraph 3.1. The Skal databases include information about companies registered up to and including 2008. I decided to select the companies registered during the last two years, 2007 and 2008, in order to generate a group of a substantial size. In total 163 companies have been registered by Skal during 2007 and 2008 in the primary sector and 326 companies have been registered during this period in the secondary sector. From this moment on, I will use the name ‘early innovators’ to refer to the companies which have been registered by Skal during the period 1990-1996 and which are still active in the market. The companies which have been registered during that period as well but have left the market in the meantime will be named ‘dropouts’. Finally, the companies which have been registered during the last period 2007-2008 will be named
‘late adopters’.
4. The last classification criterion refers to the location of a specific company. The companies will be grouped in provinces and Corop areas according to their location. The Netherlands consist of 40 different Corop areas. The Corop areas have been formulated on the base of main cities and their service area. By introducing this criterion it will be possible to analyze the cluster developments for each province and Corop area and subsequently search for differences between the developments per province.
39 The next two paragraphs clarify the methodology of the analyses with respect the degree of internal and regional clustering.
3.4 The degree of internal integration
The methodology with respect to subquestion 2, changes in the degree of horizontal and vertical integration of companies, will be explained in this subparagraph.
Horizontal integration
For each of the companies should be determined if it is horizontally specialized (specialized in one industry or product category) or horizontally integrated (operating in more than one industry or product category) and if so, to what extent. I will use the number of diversification as mentioned by De Jong (1989) in order to make a difference between the degrees of horizontal integration. The number of diversification can be defined as the number of industries or product groups in which a company produces products or services. The number of diversification will be calculated for both the level of industries and for the level of product groups as has been mentioned in paragraph 3.3. As a consequence, two independent numbers of diversification will be determined for each company.
On the level of industries, four options for the number of diversification are possible. In the case that a company is specialized in livestock production, the company is active in one industry and therefore the number of diversification is 1. The same is true for a company specialized in crop production. On the other hand the number of diversification is 2 in the case that a company performs livestock production and crop production because those are two different industries. The combination of livestock production and cattle food production results in number 2 as well.
40
Vertical integration
Moreover the difference between vertical specialization and integration should be made. A company is vertically specialized in the case that a company operates in one single stage of the value chain. On the other hand, a company is vertically integrated if the company operates in more than one succeeding stage of the value chain. The degree of vertical integration will be defined with the help of the number of integration1. The number of integration can be defined as the number of integrated stages in the value chain. The possible successions of stages in the organic livestock value chain will now be discussed.
In the previous paragraph we have distinguished five main types of activities within livestock agriculture: cattle food production, stock rearing, primary agriculture, processing and trade & storage. Since vertical integration refers to performing activities in different succeeding stages of the value chain, it is important to take into consideration all possible successions of stages. The different options are displayed in figure 3.3.
Figure 3.3: Possible successions of stages within the organic livestock value chain (LEI., 2005b. Edited)
Cattle food is an input for primary agriculture as well as for stock rearing. Besides this, some products are traded or stored directly after primary production. With respect to the Skal databases, this is only the case with eggs. Even fresh milk has mostly been processed before it is sold to consumers. However, the Skal databases do not distinguish between eggs and egg products so it will not be possible to match the corresponding value chains to these different product groups.
1
De Jong (1989) introduced a formula for the number of integration as well. However, that formula cannot be applied in this study. As a result, I introduced an alternative formula for the degree of integration, which has been deduced from the number of diversification as mentioned by De Jong (1989).
Cattle food Primary agriculture Processing Trade & storage
Cattle food Primary agriculture Trade & storage
Stock rearing Primary agriculture Trade & storage
Stock rearing Primary agriculture Processing Trade & storage Cattle food
