Sustainable Networks?
Corporate Influence on Private Food Regulation,
a Social Network Analysis
University of Amsterdam, Faculty of Social and Behavioural Sciences Research Project: Citizens in Europe
Supervisors: Dr. Julien Jeandesboz & Dr. Rosa Sanchez Salgado Second reader: Judith Huigens, MSc
Student Name: Jordy Willems Bachelor Thesis Political Science
Sustainable Networks?
Corporate Influence on Private Food Regulation,
a Social Network Analysis
Preface
As a bachelor student, this was my first real experience in doing research and writing a thesis. Although there were setbacks, it has been an instructive period. As the field of transnational private regulation slowly opens up for me, I continue to be confronted with new theoretical puzzles and complex cases. While conducting this research, I acquired much new insights in how certification associations make their decisions and the way they relate to other organizations in the field. However, more new questions arose than I was answering. It thus continues to attract my attention. First and foremost I want to thank Luc Fransen for introducing me to the field of private governance and always being open to questions. I also want to thank my supervisors, Julien Jeandesboz and Rosa Sanchez Salgado, for providing me with important instructions, besides setting me free to choose my own path. Finally, I want to thank my girlfriend Anne for her intelligent remarks and for coping with me during the process of writing.
Abstract
This thesis examines corporate influence on private food regulation with social network analysis. It focuses on decision-makers of certification associations that work for other organizations at the same time. The MSI (Multi-stakeholder Initiative)-structure that dominates the field of private food regulation requires close cooperation between organizations from different sectors, such as firms, NGO’s and governmental actors. Recent literature has pointed out potentially negative effects of predominant corporate influence on these certification associations’ standards and dictates an equal presence of for-profit and non-profit actors in order to address social and environmental issues successfully. The findings show that corporate influence on private food regulation is present, but that firms do not dominate the field; influential positions are being shared with non-profit organizations. Besides, the degree of corporate influence on certification associations did not change over the past decade.
Keywords
private regulation, certification association, cross-sector partnership, social network analysis, professional networks.
Table of Contents
List of Abbreviations ... 3
Introduction ... 4
Certification Associations as Cross-Sector Partnerships ... 5
Professional Networks and Influence ... 8
Research Design ... 9
Data and Methods ... 10
Network Analysis of Certification Associations ... 13
Conclusion ... 20
References ... 22
List of Abbreviations
4C Common Code for the Coffee Community Cert. Ass. Certification Association
CSR Corporate Social Responsibility
FLO Fairtrade International (before 2004: Fairtrade Labeling Organization) IFOAM International Federation for Organic Agricultural Movements
ILO International Labour Organization
ISCC International Sustainability & Carbon Certification
ISEAL International Social and Environmental Accreditation and Labeling MSI Multi-Stakeholder Initiative
NGO Non-Governmental Organization RA Rainforest Alliance
RSB Roundtable on Sustainable Biomaterials (before 2013: Biofuels) RSPO Roundtable on Sustainable Palm Oil
RTRS RoundTable on Responsible Soy SAI Social Accountability International SMBC Smithsonian Migratory Bird Center WTO World Trade Organization
Introduction
In recent decades, small-scale certification of sustainable agricultural products has developed into an extensive realm of transnational private food regulation. Non-governmental organizations (NGO’s) increasingly succeed in convincing companies to meet standards that aim to improve both social and environmental conditions in the production chain. On the other hand, business-driven initiatives have been set up by the industry to mitigate these societal pressures. The recent literature notes that in the competition for consumer’s legitimacy societal- and business-driven certification associations have become similar in their institutional organization of decision-making and have converged into multi-stakeholder initiatives (MSI’s) (Fransen, 2012a: 164). As a result, corporate and societal actors merged within these private regulators. The distinct and potentially conflicting views and norms of corporate and societal actors make such cross-sector partnerships challenging and prone to contestation and power asymmetry (Nicholls & Huybrechts, 2014: 1-2). However, because of the institutional structure of MSI’s, these power asymmetries formally do not exist. Still, several scholars signal a ‘race to the bottom’, in which social and environmental standards are downgraded because of increasing corporate prevalence in private regulation (Auld, 2010: 216; Bacon et al., 2008: 359; Egels-Zandén & Wahlqvist, 2006: 176). The claim of this thesis is that the institutional organization of certification associations cannot clarify the influence of corporate organizations sufficiently. In order to understand corporate influence on private regulation, it is necessary to examine structural influence of firms in the regulatory field.
The complex relationship between NGO’s and businesses involved in transnational voluntary regulation is coupled with ‘professionals that compete and cooperate within and across different types of organizations in the field’ (Henriksen & Seabrooke, 2013: 2). The multi-stakeholder model of most prominent certification associations in the food sector brings together many individuals with varying professional backgrounds. This results in a professional network of decision-makers, working for certification associations and NGO’s, firms or the government at the same time. Through this network they may seek likeminded views, form alliances and have possibilities to influence each other. Together, individuals in the network may encounter a common logic that shapes their collective action. Therefore, the shape, structure and properties of this network are important to explore in order to understand the relationships between the different organizations operating in the organizational field for sustainability.
Despite considerable attention to professional networks in the corporate realm (see Carroll et al., 2010; Heemskerk & Snyder, 2008; Maclean et al., 2006), there is little research on professional networks in the area of transnational private regulation. Using social network analysis, Bartley & Smith (2010: 348) were among the first to uncover the underlying relations of emerging ‘transnational communities of practice’. In particular, they focused on the relationship between different certification associations
in a connected network. A similar approach was recently used by several scholars in order to detect to what extent certification associations in the same sector are interconnected (Bitzer et al., 2012; Helmerich & Kaan, 2013; Henriksen, 2014b; Henriksen & Seabrooke, 2013). This thesis however, will focus on the presence and influence of the industry in this network of food-related certification associations, by revealing and analyzing the professional networks of individuals who play a key role in certification association’s decision-making processes. Drawing on data that holds the professional careers of all prominent decision-making individuals of ten relevant transnational sustainability certification associations in the food industry, this thesis uses social network analysis to visualize how and to what extent for-profit organizations are related to these certification associations. Overall, it will be examined to what extent
firms have influence in the professional network of transnational private regulatory organizations in the food sector. The research shows that several firms occupy important
influential positions in the network, but overall corporate organizations do not dominate the field. However, some certification associations experience a higher degree of corporate influence than others.
The thesis is structured as follows: First, a theoretical framework will be presented, which contains an overview of research on certification associations and explains cross-sector partnerships. The second part elaborates on the concepts of professional networks, influence and common ground and presents the research design. Third, the use of social network analysis will be justified and explained, the used data will be introduced and specified and concepts will be operationalized. Fourth, the professional network of the selected certification associations will be shown and analyzed. Finally, it will be discussed to what extent corporate influence is present and what the implications for private regulation in the food industry may be.
Certification Associations as Cross-Sector Partnerships
The combination of both a neoliberal notion of free and unlimited trade that characterized 1970’s and 1980’s Western policies, and export oriented strategies in developing countries moved social and environmental legislation in transnational production chains outside governmental reach (Bernstein & Cashore, 2007: 1; Fransen, 2011: 6). Due to trade agreements – mainly WTO-based – importing countries are unable to demand certain standards in production, while exporting countries either deliberately implement weak regulations in the sustainability field, or lack possibilities to effectively maintain these (Fransen, 2011: 6). The intensified globalization of production of mass consumer goods and food has resulted in a situation where ‘the organization of production has been geographically dispersed and functionally disintegrated’ (Fransen, 2011: 4-5). From the 1990’s onwards, private regulatory initiatives have risen, building on the voluntary adoption of their privately set standards by corporations and consumer’s demand for ethical products, in order to improve sustainable food production (Reinecke et al., 2012: 2). Following a strategy of naming
and shaming (Hafner-Burton, 2008), activist NGO’s generated bad publicity when a firm
infringes certain standards, which in turn forces the firm to take action. Nowadays, firms increasingly are being judged on their Corporate Social Responsibility (CSR). Certification associations thus act as watchdogs, certifying products that are produced in accordance with the set standards. They are bodies, ‘designed to embed social and environmental norms in the global marketplace, that derive authority directly from interested audiences, including those they seek to regulate’ (Bernstein & Cashore, 2007: 1).
Although the idea of this regulatory system is still functioning today, most certification associations no longer operate as single, independent bodies. They have become organizations that function through a cooperation between several sectors, including NGO’s, firms and (to a lesser extent) governmental actors (Fransen & Kolk, 2007: 667). As in other industries, certification associations in the food industry have largely transformed into multi-stakeholder initiatives (MSI’s), which assemble both corporate and societal actors in key positions in the decision-making process (Fransen, 2012a: 166). ‘The term MSI describes a universe of initiatives in which the expertise, skills and finance of non-profit and for-profit organizations are pooled’ (Fransen, 2012a: 166). Hence, multi-stakeholder certification associations are also known as cross-sector partnerships (Le Ber & Branzei, 2010a; 2010b; Manning & Roessler, 2013), which are set up ‘because of their potential for effective consensus-building, knowledge-sharing and interest representation’ (Fransen & Kolk, 2007: 667). An MSI-structure thus institutionally signifies a mixed occupation of seats in the board of directors by people from different sectors, including firms.
Several scholars point out that MSI’s face strong competition by business-driven initiatives that tend to exclude societal actors in their decision-making processes (Fransen, 2012a: 164). This has made some doubt the potential of private regulation, as they witness a regulatory ‘race to the bottom’ (Auld, 2010: 216; Raynolds et al., 2007: 160). As certification associations aspire to gather as many members as possible in order to cope with fierce rivalry from other private regulators, their ability to encourage challenging standards diminishes. In this way, Bacon et al. (2008: 359) question the extent to which certification associations ‘can avoid being co-opted by the corporate centered market system [they were] set up to challenge and transform’. Nicholls & Huybrechts (2014: 1) emphasize the striking differences between non-profit organizations and large companies in their organizational goals or logics. Therefore, cross-sector partnerships can be problematic and tend to induce power asymmetries, in which the stronger actor imposes its logics upon the weaker one (Nicholls & Huybrechts, 2014: 1). Although nowadays many firms acknowledge a certain degree of responsibility for social and environmental conditions in their production process (Merk, 2007: 9), they cannot be expected to guide sustainable production alone (Egels-Zandén & Wahlqvist, 2006: 176). Egels-Zandén & Wahlqvist (2006: 183) state that firms’ main reason to extend their corporate responsibility is not ‘to do the “right” thing […], but rather to gain and repair their legitimacy in the eye of the consumer’. Now that they took
a more central position in actively acquiring this legitimacy by joining the private regulators, ‘the important question becomes whether or not the firms […] seem to be able to enrol NGO’s, unions and governmental organizations […] to confer the necessary legitimacy’ (Egels-Zandén & Wahlqvist, 2006: 183).
The cooperation between non-profit and for-profit organizations, which is inherent to the structure of MSI, has made some scholars doubt the term private regulation (Abbot & Snidal, 2009; Andanova et al, 2009; Ansell, 2011). To some extent, especially with regard to business-driven initiatives, standard setting appears to be more like a process of self-regulation (Haufler, 2013). Andanova et al. (2009: 55) note that the intense cooperation between societal and corporate actors is supplemented with governmental involvement as well, as social standards are largely based on conventions of the ILO (International Labour Organization), an inter-governmental organization. Hence, the term hybrid governance (Andanova et al., 2009: 55) is suggested to be more appropriate in some cases. However, all large certification associations in the food industry are institutionally independent from governments, which means that there are no governmental actors or institutions among their key decision-makers. Nevertheless, these organizations might receive financial resources from and cooperate with governments. Acknowledging possible shortcomings, this non-governmental form of regulation will be designated as private regulation in this thesis.
In recent years, institutional adoption of the MSI-structure is certainly a trend in private food regulation (Fransen & Kolk, 2007: 668). For instance, Utz Certified, that originated as a business-driven initiative created by international retailer Ahold, used to be controlled by production and retail firms only. Nowadays, it has a Supervisory Board that consists of members drawn not only from producers and retailers, but civil society organizations and trade unions as well (Utz Certified, 2013). The MSI-structure not only pools expertise, skills and finance from different sectors, it also increases the certification association’s legitimacy in the eye of the consumer (Fransen, 2012a: 164, 166) and is therefore attractive to both NGO-based and business-driven initiatives. It serves as a ‘collaborative way of aligning the interests of lead firms in the global economy with the activist watchdogs who want to raise the standards of what is considered appropriate corporate behavior’ (Henriksen, 2014a: 3). Because the MSI-structure in this way incorporates the regulated in the regulator, it is difficult to measure the influence firms have on private regulation when looking only at the key decision-makers. It is likely that in all MSI’s boards of directors there are individuals with a function in the corporate sector at the same time. Thus, as Bitzer et al. (2012: 355) argue, these ‘[cross-sector] partnerships should be studied not only as autonomous entities but also as networks of partnerships’. It is necessary to uncover the certification associations’ professional networks, in order to find out which relations they have with other organizations and if these are mainly NGO’s, governmental organizations or firms.
The recent literature has elaborated on the growing interconnectedness of certification associations (Bartley & Smith, 2010; Bitzer et al., 2012; Dingwerth & Pattberg, 2009). Dingwerth & Pattberg (2009: 708-9) argue that the narrow field of
individuals that operated within the upcoming branch of private regulatory standards from the 90’s on, was the basis for a high level of social interaction that remained or even increased. They illustrate ‘how social interaction and the development of norms that result from such interaction can account for important facets of transnational rule-making organizations’ (Dingwerth & Pattberg, 2009: 731). Additionally, intensified cooperation between such organizations within meta-standard organizations, such as overarching standards association ISEAL, strengthened the network (Fransen, 2012b; Loconto & Fouilleux, 2013). What the literature has mainly neglected, though, is the way corporate actors are active in this process of growing interconnectedness. Since their institutional presence in the field has strengthened due to large-scale adoption of the MSI-structure, it is important to examine their positions in the network and the influence they possess.
Professional Networks and Influence
When individual decision-makers with different experiential backgrounds and professional duties assemble to make decisions, as is the case in MSI-structured certification associations, they ‘face the challenge of finding common ground in the absence of any particular shared abstract body of knowledge’ (Henriksen, 2014a: 2). The uncertainty that this challenge causes, makes these individual’s dependency of likeminded colleagues more presumable. As Galaskiewicz (1985: 640) notes, ‘especially under conditions of uncertainty, professionals will seek out those with whom they can communicate easily’, and thus rely on their professional network. A network can be broadly defined as a set of actors, connected by a given type of relation (Diani, 2002: 175). Professional networks thus are a group of professionals, connected by their occupational career (Galaskiewicz, 1985: 639). Network theory assumes that collective action is being influenced or shaped by preliminary present social networks (Diani, 2002: 174). However, networks not only facilitate collective action (Glasbergen, 2010), they are also an expression and product of collective action (Della Porta & Diani, 1999).
Examining professional networks in the corporate sector, Mizruchi (1996: 271-2) notes the importance of interlocking directorates, which occur ‘when a person affiliated with one organization sits on the board of directors of another organization’, as they are ‘powerful indicators of network ties between firms’. Decision-makers encounter each other during board meetings, where they share thoughts that can advance behavioral norms or produce shared norms (Heemskerk & Fennema, 2009: 810). Domhoff (1975: 6) states that the more people interact, the more affection they obtain for each other; they form an inner circle, a cohesive group of interlocking directors. An important aspect of such cohesive groups is that their members are relatively open to views and opinions of other group members, compared to those of non-members, and that it is more likely that they form shared views with them (Heemskerk & Fennema, 2009: 810; Laumann, 1966). In other words, these inner circles are subject to social closure. In network terminology, social closure exists when the actors one is connected to, are
connected to each other as well (Heemskerk & Fennema, 2009: 811). The idea of social closure is a closed group of individuals without many relations outside of it. Social closure is usually regarded as a negative attribute, because it tends to lead to groupthink (Hart, 1990; Janis, 1972). On the other hand, these strong relations are fundamental for the creation of trust. Following this logic, it is likely that when an individual works for different corporate companies, and regularly meets other corporate group members, he shares more business-oriented views and norms than an individual that works for both non-profit and for-profit organizations or for non-profit organizations only. Since these views and norms shape behavior, the collective action that originates in a board of directors will be more influenced by a business’ logic when the board includes more members of the corporate network. Thus, the more corporate organizations are tied to a certain certification association, the more potential influence they possess.
Although the degree of presence of corporate organizations in the network offers several insights, not every organization is equally important. Haas (1992: 2-3) argues that ‘control over knowledge and information is an important dimension of power and […] the diffusion of new ideas and information can lead to new patterns of behaviour’. The structural position specific organizations hold within the network is thus crucial for their degree of influence (Hafner et al, 2009: 570). Manning & Roessler (2013: 3) note the critical presence of bridging agents in MSI’s, because of the boundary-crossing challenges that such a cross-sector cooperation entails. Bridging agents are defined as ‘individuals who operate […] across organizational […], sector and project-boundaries, and in doing so translate complex and ambiguous conditions into collaborative opportunities and constraints’ (Manning & Roessler, 2013: 3). From a structural viewpoint, these bridging agents are key actors in the network, connecting different parts that without them would not be connected, thus enlarging their influence (Hafner et al., 2009: 571). Another important structural attribute of an actor in the network is the amount of connections it has to other relevant actors. When decision-makers of several certification associations meet and interact within another organization, this organization takes a central position in the network. Such a central position provides access to both material and informational resources and offers the ability to influence these (Hafner et al., 2009: 570).
Research Design
In order to examine the influence of firms on private food regulation, analyzing the network of interlocking decision-makers thus appears to be promising. Before the analysis is started, a comparison is made of professional networks of 2002 and 2012, as an effort of triangulation. According to the literature, the 2012 network is denser than the 2002 network: certification associations have become more interconnected (Bartley & Smith, 2010; Dingwerth & Pattberg, 2009). When the results support this preliminary research, the used method can be considered successful.
The first small part of the research is based on a comparison between the professional certification associations’ network of 2002 and 2012. The presence of firms will be measured in both 2002 and 2012 by determining how many firms are directly connected to separate certification associations by interlocking decision-makers. Based on the broad institutional adoption of the MSI-structure (Fransen & Kolk, 2007) and the growth of private food regulation as a whole (Reinecke et al., 2012), it is expected that
the amount of firms connected to certification associations is larger in the 2012-network than in the 2002-network, both absolute and relative (H1).
The second part draws on a thorough analysis of structural aspects of the professional certification associations’ network of 2012. It will be examined which organizations serve as bridging agents between different certification associations and which organizations serve as central actors. Also, it will be looked at if social closure is present in the network. Overall, the extent to which firms are present in these structural positions serves as the main focus. On this matter, the literature is divided and hence two contradicting hypotheses are prepared. Based on scholars that witness increasing corporate power on private regulation (Bacon et al., 2008; Egels-Zandén & Wahlqvist, 2006; Haufler, 2001) it is expected that most of the important structural positions in the
network are occupied by firms (H2). On the contrary, based on scholars that emphasize
successful cross-sector cooperation in private regulation (Bitzer et al., 2012; Manning & Roessler, 2013) it is expected that the important structural positions in the network are
equally occupied by firms, NGO’s and governmental organizations (H3). The next chapter
provides a description of the used data and clarifies how the mentioned concepts are measured.
Data and Methods
Social network analysis aims to identify relations between actors (Hafner et al., 2009: 561). In order to examine the relations between certification associations and other organizations in the field – specifically firms – the Professional Networks in Transnational
Sustainability Governance Project Database, established by Fransen & Schalk (2013) has
been used. This database contains information of all employees from 22 certification associations. Although the database also contains certification associations from different sectors, only those operating in the food industry are relevant in this research. Table 1 lists the ten certification associations that are used in the analysis, which are either mainly dedicated to social or environmental sustainability in the food sector. All of these certification associations are currently MSI’s, except for RA and SMBC1 (Dentoni & Peterson, 2011; WWF, 2010). ISCC (International Sustainability & Carbon Certification) and RSB (Roundtable on Sustainable Biomaterials), currently considerable certification associations, are deliberately not included in this database, because ISCC
1 Although RA is founded by environmental experts and NGO’s and SMBC by environmental experts and
academics (IISD, 2014: 33), they do not signify a partnership between non-profit and profit and thus are not considered to be MSI’s.
only has a food branch since 2012 – ISCC PLUS (ISCC, 2013) – and RSB since 2013 (http://rsb.org/about/what-is-rsb).
Table 1 Selected Certification Associations in the Food Sector2
Name Year founded Year MSI Product
4C: Common Code for the Coffee Community 2004* 2006 Coffee Bonsucro: Better Sugar Cane Initiative 2008 2008 Sugarcane
FLO: Fairtrade International 1997# 2002 Multiple
IFOAM (Organic): International Federation for 1972# 1997 Multiple Organic Agricultural Movements
RA: Rainforest Alliance 1987# - Multiple
RSPO: Roundtable on Sustainable Palm Oil 2004 2004 Palm Oil
RTRS: Roundtable on Responsible Soy 2006 2006 Soybean
SAI: Social Accountability International 1997 1997 Multiple SMBC (Bird Friendly): Smithsonian Migratory 1998 - Coffee
Bird Centre
Utz Certified (Utz Kapeh, until 2007) 2002* 2007 Multiple
*Founded as business-driven initiative
#Founded as NGO-based initiative
Besides basis characteristics of all certification associations’ employees like gender, nationality, age and education, the database contains all organizations that every employee works or has worked for over the 11-year period from 2002 to 2012. These organizations can either be other certification associations, corporate companies, universities, governmental organizations or NGO’s. The data has been constructed with online available information, both on certifications association’s websites as in personal profiles on LinkedIn (Fransen & Schalk, 2013). This data provides the basis for an analysis of the professional network of decision-makers. In order to analyze the data, it was transferred to Ucinet 6 (Borgatti et al, 2002) and then imported into NetDraw (Borgatti, 2002) to visualize the network.
‘A network is a set of actors (nodes) connected by a specific type of relation (tie)’ (Diani, 1999: 175). In this research, organizations form the nodes of the network. They are related to each other by decision-makers working for two or more organizations; these persons thus act as ties. Originally, the database was shaped as a two-mode network matrix with the rows being employees and the columns being organizations. In order to extract the decision-makers from the total of employees, the functions of employees are clustered in six categories: 1) Executive, Board of Directors, Council; 2). Advisory, Supervisory, Committee; 3) Policymaking, Standard Governance; 4) Market Development, Business Member Service; 5) Communication; 6) Administrative, Organizational Support (Fransen & Schalk, 2013). In order to take a comprehensive grip
2 Source: Raynolds et al., 2007: 157; Bartley & Smith, 2010: 349; Fransen & Kolk, 2007: 683; IISD, 2014:
of all potential ties between standards and other organizations, the persons of function level 1, 2 and 3 are regarded as decision-makers and are thus included in the analysis. This results in a selection of 246 decision-makers. The organizations are divided into four categories: 1) certification associations3; 2) for-profit organizations; 3) non-profit organizations; 4) governmental organizations. All for-profit organizations are regarded as firms, even though this category also includes organizations such as banking houses.
In the network, an interlocking decision-maker is regarded as a connection between two or more organizations. According to network theory, interaction only exists between two interlockers of different organizations when they meet each other (Heemskerk & Fennema, 2009: 815). Thus, organizations are considered to be connected to each other when they are either directly tied, or tied through a separate organization (indirectly tied). For instance, when a decision-maker of Utz also works for RSPO, Utz and RSPO are considered as directly connected; when decision-makers of Utz and SMBC both work for WWF, Utz and SMBC are considered as indirectly connected. In order to find if social closure is appearing in the network, attention is given to the presence of so-called strong ties (Granovetter, 1973). These are present when the organizations a certification association is directly connected to, are also directly connected to each other, while ties to other organizations are limited. In this case, social closure is present and the origination of common norms and views is likely (Janis, 1972; Hart, 1990).
Network theory suggests that structural positions in a network are crucial for an actor’s influential capacities (Hafner et al., 2009: 570). Over time, several attributes have been developed that reflect an actor’s structural position, related to other actors in the network. One of the most important and frequently used structural attributes of networks is centrality (Freeman, 1979: 217). Therefore, it is also one of the most debated measures in social network analysis and a great variety of similar measures have been developed over the years (Bonacich, 1987). In this research, three commonly accepted and most used centrality measures (Borgatti, 1995) are wielded to define different aspects of organizations’ structural capacities to influence the network. These measures will be normalized in order to correctly compare the individual actors by using the standard Freeman normalization (Everett & Borgatti, 2005: 10). This assures that double interlocking directors between the same organizations are not included twice in the score.
Degree centrality measures the ability of an actor to influence its direct
environment (Freeman, 1979: 219) and is defined as the number of ties directly connected to a node. Degree centrality is an appropriate measure to find the most influential actors in the network, because ‘the probability of receiving […] something that is randomly distributed in the network, will be entirely a function of the number of ties that a given node has’ (Borgatti, 2005: 62). High-scoring nodes on degree centrality
3 For the sake of clarity, only the ten selected certification associations are designated as such in the
have been called big linkers (Heemskerk & Fennema, 2009: 810), as they are those that connect most other nodes of the network. Another well-known measure in social network analysis is closeness centrality, which measures an actor’s independence. It is determined by an actor’s closeness to all other nodes in the network and thus indicates the ability of an actor to communicate or distribute knowledge or information, without relying on other actors (Freeman, 1979: 224-5). An actor’s closeness centrality is defined as the sum of the shortest distances from all other nodes in the network (Freeman, 1979: 225). Thus, the higher the score the more independent an actor is.
Betweenness centrality focuses on the non-local network dynamics of an actor and
measures its ability to facilitate or block distribution of knowledge or information through the entire network. It is defined as the sum of the shortest paths that pass through a node and thus indicates its connecting position of relatively remote parts of the network (Freeman, 1979: 222-4). Actors with the highest betweenness centrality can thus be regarded as organizations that harbor bridging agents (Manning & Roessler, 2013: 3), connecting parts of the network that without them would not be connected (Hafner et al, 2009: 571).
Together, these centrality measures provide comprehensive knowledge of the influential capacities of organizations in the network. However, in calculating these scores no attention is given to the type of organizations they are connected to. This means that an organization in the network may score relatively high on certain centrality measures, although it is not connected to any certification association at all and thus has no influence on them. Therefore, these scores must be carefully interpreted, acknowledging the theoretical attributes of the network. An organization’s centrality measures are only relevant when it is connected to a certification association.
Network Analysis of Certification Associations
In this section, the results of the network analysis will be presented. As stated above, before analyzing the network the correctness of the used method will be tested on account of triangulation. Figures 1 and 2 show the networks of respectively 2002 and 20124. Conform to the findings of preliminary research (Bartley & Smith, 2010; Dingwerth & Pattberg, 2009) the network of 2012 shows more interconnectedness between certification associations than in 2002, which validates the data. In the 2002-network three of the selected certification associations are unconnected to others; in the 2012-network only two are. Moreover, both direct and indirect connections between certification associations have increased. Table 2 contains all connections between certification associations in 2002 and 2012.
4 Four of the selected certification associations were founded after 2002, therefore the 2002-network only
Figure 1 Certification associations’ professional network of 2002
Table 2 Interconnectedness of Certification Associations, 2002 & 2012
2002 Cert. ass.* Direct connection Indirect connection
RA - Utz
SMBC - Utz
Utz - RA, SMBC
2012
4C RA -
FLO - RSPO, RTRS, Utz
RA 4C RSPO, Utz
RSPO RTRS FLO, RA, RTRS, SMBC, Utz
RTRS RSPO FLO, RSPO, SAI, SMBC, Utz
SAI - RTRS, Utz
SMBC - RTRS, RSPO, Utz
Utz - FLO, RA, RSPO, RTRS, SAI, SMBC
*Cert. Ass. = Certification Association
Table 3 Direct Connections Between Organizations and Certification Associations, 2002 & 2012
Cert. Ass.* Total 2012 (2002) Firms 2012 (2002) % of Firms 2012 (2002)
4C 5 (-) 2 (-) 40% (-) Bonsucro 2 (-) 1 (-) 50% (-) FLO 17 (5) 10 (3) 59% (60%) IFOAM 8 (3) 4 (2) 50% (67%) RA 2 (1) 1 (1) 50% (100%) RSPO 15 (-) 9 (-) 60% (-) RTRS 16 (-) 8 (-) 50% (-) SAI 8 (1) 1 (0) 13% (0%) SMBC 7 (7) 2 (2) 29% (29%) Utz 18 (10) 9 (5) 50% (50%) Total 98 (27) 47 (13) 48% (48%)
*Cert. Ass. = Certification Association
The first small part of the research focuses on comparison between 2002 and 2012 on absolute and relative presence of firms in the network. Table 3 lists the number of directly connected organizations to each certification association in both the 2002- and 2012-network, as the number and percentage of firms directly connected to certification associations. The absolute presence of firms in the 2012-network is larger than in 2002: in 2002, 13 firms were directly connected to certification associations; in 2012, 47 are. However, in relative terms the presence of firms stayed exactly the same: in 2002, 48% of all organizations directly connected to certification associations were firms; in 2012, still 48% are. On the individual level, three certification associations experienced a decline of directly connected firms; one experienced an increase; two
experienced no difference. These results are only partly consistent with the first hypothesis (H1): in absolute terms, the amount of firms connected to certification associations has increased; in relative terms it stayed roughly the same. The findings show that direct influence of firms through the board of directors of certification associations as a whole did not increase, despite MSI’s joining the field between 2002 and 2012. These results are understandable, as most certification associations already transformed into MSI’s before 2002, except for Utz Certified. The four new private regulators that got involved in the market after 2002 (4C, Bonsucro, RSPO and RTRS) already existed as MSI’s from the moment of their foundation (see Table 1). Therefore, they introduced both for-profit and non-profit organizations to the network and the overall percentage of firms did not change much.
In 2012, in absolute terms, most firms are present in the direct network of FLO (10), least in the direct network of Bonsucro (1), RA (1) and SAI (1). In relative terms, most firms are present in the direct network of RSPO (60%), least in the direct network of SAI (13%). Direct corporate influence through the board of directors thus is most present at FLO and RSPO; it is least present at SAI.
The second part of the research is focused on structural positions in the 2012-network and the extent to which these are occupied by firms. To start with, social closure can be located at several parts of the network (see Figure 2). When searching for organizations directly connected to certification associations, which are also directly connected to each other while ties to other organizations are limited, the direct network of SMBC stands out. Of all seven directly connected organizations, six are connected to each other as well (excluding SMBC). Only WWF has multiple connections to other organizations, the others are only directly connected to each other. This indicates that social closure is present in the direct network of SMBC, thus the origination of common norms and views is likely here. Of these six organizations surrounding SMBC, only two are firms. Therefore, it is not likely that these common norms and views are predominantly influenced by corporate actors.
In two other parts of the network social closure can be determined. In the direct network of RTRS, a group of seven organizations are directly connected to each other, besides being directly connected to RTRS. Contrary to SMBS’s direct network, this group only accounts for less than half of RTRS’ direct network (7/16). However, within this group common norms and views are likely to be formed, although they are mitigated by connections to other organizations. Of the seven present organizations, four are firms, thus predominant corporate influence on possible groupthink is likely. In FLO’s direct network social closure is present as well. A group of seven organizations are directly connected to each other, besides being directly connected to FLO. Likewise, connections to other organizations are weak. Of these seven organizations, six are firms, so corporate influence on possible groupthink is predominant. This group thus may have a significant influence on FLO’s decision-making process. Other groups of interconnected
organizations in the network are too small to be influential and thus are not worth mentioning.
Table 4 Big Linkers, Scores on Degree Centrality
Organization Normalized score Raw score Direct connections with cert. ass.*
WWF 0.117 10 RSPO, RTRS, SMBC, Utz
Rabobank # 0.106 11 FLO (2), RSPO, RTRS
Garion University 0.096 9 FLO, RTRS
CLAC # 0.096 9 FLO (2)
Panel A. Int. Market # 0.096 8 RTRS, Utz
*Cert. Ass. = Certification Association # = For-profit Organization
In order to determine which individual organizations are most influential in the network, three centrality measures have been calculated (see Appendix). Although these give an indication of the degree of influence of a certain organization, they must be carefully interpreted. In order to be able to actually influence private regulation, an organization must be connected to a certification association in the first place. Naturally, because they are the object of research, certification associations score high on most measures. These scores are irrelevant, because the focus of this part of the research is on the organizations the certification associations are influenced by, not the certification associations themselves. Therefore, certification associations have been excluded from the analysis and the tables presented below. Table 4 lists the big linkers, the five organizations with the highest normalized score on degree centrality; it only includes those directly connected to at least one certification association. It is clear that the normalized score on degree centrality does not necessarily equal the raw score. For instance, the World Wildlife Fund (WWF) scores higher on the normalized measure than Rabobank, but lower on the raw measure. This is because the normalized score does not account for multiple connections between the same organizations. Rabobank has two direct connections with FLO, which are expressed by the raw score, but not by the normalized score. Therefore, WWF is directly connected to most different organizations, while Rabobank has most interlocking directors, of which some are connected to the same company. These results indicate that WWF is the most influential organization in the network in terms of having the ability to receive the most information being distributed. Rabobank follows closely with only a slightly lower score but has more individual directors in boards that are able to influence decisions. Firms are definitely present among the best scoring organizations on degree centrality, but they are not largely dominant. WWF, the most influential organization in degree terms, is an NGO. Such is Garion University, the third best scoring organization. Rabobank (2nd), CLAC (4th) and Panel A. International Market (5th) are firms, thus corporate presence is considerable.
Table 5 Big Linkers of Certification Associations
Organization Raw degree score Direct connections with cert. ass.*
WWF 4 RSPO, RTRS, SMBC, Utz
Rabobank # 4 FLO (2), RSPO, RTRS
Kraft Foods # 4 RA (2), RSPO, Utz
Solidaridad 3 RTRS, SAI, Utz
Panel A. Int. Market # 2 RTRS, Utz
Max Havelaar 2 FLO, Utz
Garion University 2 FLO, RTRS
Unilever # 2 RSPO, RTRS
*Cert. Ass. = Certification Association # = For-profit Organization
The raw degree centrality scores in Table 4 are calculated for the whole network of organizations, but one can also calculate a raw degree score solely measuring direct connections with certification associations. This results in a different selection of high ranking organizations, which are listed in Table 5. Because several organizations score equal on this modified raw score, eight organizations are included in the table. Not only is WWF directly connected to most different organizations, it is also the only organization directly connected to four different certification associations. Both Rabobank and Kraft Foods directly connect to three certification associations, although they have a double connection that results in a raw degree of 4. Solidaridad shares interlocking directors with three certification associations; Panel A. International Market, Max Havelaar, Garion University and Unilever all have two directly connected certification associations. Corporate presence is slightly dominating among the most influential organizations between different certification associations, as four out of eight big linkers are firms, of which two are among the three highest ranked.
Table 6 Best Scoring Organizations on Closeness Centrality
Organization Normalized score Directly Connected to cert. ass.*
Group Lactalis # 47.000 Bonsucro
Renewable Fuels Agency 47.000 Bonsucro
ANPE 7.231 IFOAM
CONAPO 7.231 IFOAM
GALCI 7.231 IFOAM
*Cert. Ass. = Certification Association # = For-profit Organization
Table 7 Best Scoring Organizations on Closeness Centrality Without Isolates
Organization Normalized score Direct Connections with cert. ass.*
Solidaridad 0.470 RTRS, SAI, Utz
Rabobank # 0.454 FLO, RSPO, RTRS
WWF 0.439 RSPO, RTRS, SMBC, Utz
Max Havelaar 0.433 FLO, Utz
Panel A. Int. Market # 0.431 RTRS, Utz
*Cert. Ass. = Certification Association # = For-profit Organization
The second calculated centrality measure is closeness centrality. High-scoring organizations on this measure are most independent and thus their influence is less mitigated by other organizations. Table 6 lists the five best scoring organizations on closeness centrality. Unsurprisingly, those organizations connected to the most remote certification associations of the network score high on closeness. Both Bonsucro and IFOAM are situated isolated from the network of interconnected certification associations. The organizations directly connected to them thus have a relatively big influence in terms of independency. These results are highly distorted, because the high score is an effect of being independent of the network, not within the network. When the isolated parts of the network (the ego-networks of Bonsucro and IFOAM) are left out, the influential independent organizations within the network become the best scoring actors. These are listed in Table 7. Solidaridad is the most independent influential organization in the network. Of the five organizations best scoring on closeness centrality, two are for-profit organizations. NGO’s seem to account for most of the independent positions in the network.
Table 8 Best Scoring Organizations on Betweenness Centrality
Organization Normalized score Direct Connections with cert. ass.*
Solidaridad 0.191 RTRS, SAI, Utz
WWF 0.143 RSPO, RTRS, SMBC, Utz
Kraft Foods # 0.120 RA, RSPO, Utz
Max Havelaar 0.109 FLO, Utz
Rabobank # 0.091 FLO, RSPO, RTRS
*Cert. Ass. = Certification Association # = For-profit Organization
The third and last centrality measure that is calculated is betweenness. It indicates bridging agents are present in the organization, and the actor thus connects different parts of the network that without it would not have been connected. It is thus a measure that concerns the network as a whole. Table 8 lists the five best scoring organizations on betweenness centrality. Again, Solidaridad is the organization that has the most influential position in the network. Unsurprisingly, the organizations in Table 8 are all
present in Table 5 as well. As they connect several certification associations, these organizations are able to facilitate or block information or knowledge through the entire network. Without these key actors, the whole network would not be connected as it is now. Of these important organizations, only two are firms. As the two best scoring organizations are NGO’s, corporate influence through bridging agents is not dominating the network.
Overall, the scores on the different centrality measures reflect a variety of influential organizations. Best scoring on all different measures are WWF, Rabobank and Solidaridad. Rabobank is by far the most influential firm in the network; Kraft Foods and Panel A. International Market also occupy considerable structural positions. These results are not consistent with the second hypothesis (H2): most of the structural positions in the network are not occupied by firms. The results are only partly consistent with the third hypothesis (H3), since the important structural positions in the network are more or less equally occupied by both firms and NGO’s. However, governmental organizations do not occupy any of the highly influential positions, which is remarkable. All certification associations experience a different degree of corporate influence. IFOAM and Bonsucro do not experience corporate influence through the network, as they are not part of it. Of the certification associations within the network, 4C is least influenced directly by other organizations as it is not directly connected to any key influential actor in the network. SAI and SMBC do not experience any structural corporate influence as well; they are only directly connected to key influential NGO’s. FLO, RSPO and RTRS experience most corporate influence in structural terms.
Corporate influence on private food regulation through the professional networks of certification associations is considerable, but does not exceed societal influence. This research shows that cross-sector partnerships between non-profit and for-profit organizations manage to avoid power asymmetries over time. In terms of network connectedness, private food regulation is clearly separated from governmental organizations, as they occupy none of the influential positions. This balanced cooperation between business and society indicates that these forms of non-state governance are able to survive and jointly improve social and environmental conditions in global food production.
Conclusion
This thesis has drawn on social network analysis to examine the extent to which firms influence certification associations through their professional network. Based on network theory, influence has been defined as both direct connections to and structural positions of certification associations’ network of interlocking directors. Although firms are definitely influential actors in the connected field of private food regulators, the findings show that they are not dominant and no large power asymmetries seem to exist. When comparing the contemporary network with the network of 2002, it shows that overall corporate influence has remained the same over the past ten years.
However, private food regulation has grown remarkably, whereby more firms have entered the field. In 2012, influential positions in the network are occupied by several non-profit organizations as well, WWF and Solidaridad being the most influential organizations in structural terms. FLO and RSPO are subject to most corporate influence, both direct as in structural terms; SAI experiences the least corporate influence on both measures. It is remarkable that governmental organizations do not possess much ability to influence certification associations through interlocking directors. Thus, the term
private regulation seems to remain an adequate term for the governance carried out by
these cross-sector partnerships.
According to the findings of this research, the intensified cross-sector cooperation that originated in the past fifteen years has not led to an unequal power balance between corporate and societal actors. This supports the literature that points out the potential of private regulation, as it signifies a successful basis for jointly addressing and improving social and environmental practices across the food sector. However, these findings only show one small piece of the picture and thus have their limitations. As Diani (2002: 195) notes, social network analysis offers a significant contribution to the structural part of research on civil society, but it can and must be enriched by qualitative studies as well. Naturally, influence on collective action is not only wielded through interlocking directors; there are many other ways firms can express their power on certification associations. Furthermore, future research should connect the structural presence of firms and actual behavior of individual certification associations. In this way, the actual effect of corporate influence on private food regulation may be visible. Together, they may shed light on a relatively new field of governance that, although still under development, is about to keep playing a crucial role in future transnational regulation.
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Appendix
Normalized Centrality Measures for All Connected Organizations (n = 93)
Organization Degree Closeness Betweenness Type Org.*
IFOAM 0.096 11.750 0.005 Cert. Ass.
Utz 0.202 0.500 0.280 Cert. Ass.
RA 0.032 0.318 0.086 Cert. Ass.
SMBC 0.085 0.329 0.018 Cert. Ass.
4C 0.064 0.256 0.070 Cert. Ass.
FLO 0.191 0.410 0.227 Cert. Ass.
RTRS 0.181 0.480 0.173 Cert. Ass.
RSPO 0.160 0.463 0.200 Cert. Ass.
SAI 0.096 0.355 0.120 Cert. Ass.
Bonsucro 0.032 47.000 0.000 Cert. Ass.
betterc 0.043 0.342 0.036 NGO SustainableHarvestInternational 0.021 0.258 0.000 NGO WorldWildlifeFund (WWF) 0.117 0.439 0.143 NGO GlobalSustainabilityAssociates 0.053 0.337 0.000 Firm ApicoopLtd 0.043 0.307 0.000 Firm IFATLatinoamerica 0.043 0.307 0.000 NGO Paual 0.043 0.307 0.000 Firm GrupoPlan 0.074 0.328 0.000 Firm FundaciónHaciendasMundoMaya 0.074 0.328 0.000 NGO WorldHeritageAlliance 0.074 0.328 0.000 Gov. Banamex 0.074 0.328 0.000 Firm FICSAC 0.074 0.328 0.000 NGO Kraftfoods 0.053 0.414 0.120 Firm ANPE 0.043 7.231 0.000 NGO CONAPO 0.043 7.231 0.000 Gov. GALCI 0.043 7.231 0.000 Firm NYU 0.021 0.273 0.000 NGO GlobalAccessCorporation 0.043 0.275 0.000 Gov. SocialFingerprint 0.043 0.275 0.000 Firm CREATeorg 0.043 0.275 0.000 NGO
Organization Degree Closeness Betweenness Type Org.* UFCW 0.043 0.275 0.000 NGO UNICommerceGlobalUnion 0.043 0.275 0.000 NGO InternationalUnionofFoodWorkers 0.043 0.275 0.000 NGO ABNAmro 0.021 0.305 0.000 Firm Solidaridad 0.074 0.470 0.191 NGO MaxHavelaar 0.043 0.433 0.109 NGO PanelAInternationalMarket 0.096 0.431 0.027 Firm OneAccordPartners 0.043 0.355 0.000 Firm MelittaCoffee 0.043 0.355 0.000 Firm AuBonPain 0.043 0.355 0.000 Firm IBC 0.043 0.212 0.000 Firm Cooxupé 0.043 0.212 0.000 Firm InternationalCoffeeOrganization 0.043 0.212 0.000 Gov. UgandaCoffeeDevelopmentAuthority 0.021 0.211 0.000 Gov. GarionUniversity 0.096 0.420 0.027 NGO Rabobank 0.106 0.454 0.091 Firm Ecolog 0.085 0.392 0.000 Firm isealalliance 0.085 0.392 0.000 Firm monsanto 0.085 0.392 0.000 Firm PvdA 0.032 0.379 0.000 Gov. Nutreco 0.021 0.342 0.000 Firm LosCrobo 0.021 0.342 0.000 Firm CafeOrganicoJacaranda 0.032 0.372 0.000 Firm ASA 0.021 0.342 0.000 NGO UNEP 0.085 0.392 0.000 Firm Indonesianeconomistassociation 0.032 0.335 0.000 NGO Greenpeace 0.032 0.335 0.000 NGO FELDA 0.032 0.335 0.000 Firm FELKOP 0.032 0.335 0.000 Firm EcoFuture 0.032 0.306 0.000 Firm Eartwark 0.032 0.306 0.000 Gov. CLAC 0.096 0.312 0.001 Firm Barrelino 0.032 0.306 0.000 Firm
