How does the structure of social networks affect the

Resources, Conservation and Recycling 78 (2013) 36–46

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Resources, Conservation and Recycling journal homepage: www.elsevier.com/locate/resconrec

How does the structure of social networks affect the performance of its actors? – A case study of recyclable materials collectors in the Brazilian context June Alisson Westarb Cruz, Carlos Olavo Quandt, Heitor Takashi Kato, Roberta da Rocha Rosa Martins, Tomas Sparano Martins ∗ Pontifícia Universidade Católica do Paraná, Brazil

a r t i c l e

i n f o

Article history: Received 20 January 2013 Received in revised form 26 May 2013 Accepted 6 June 2013 Keywords: Social networks Recyclables materials Brazil Performance

a b s t r a c t The creation of partnership networks between the private sector, the government, and organized civil society has called the attention of researchers in the field of strategy, mainly the association between the creation of partnerships and the organizational performance. In this sense, organizational networks studies emerge through a series of questionings, among which is the understanding of how the structure of networks affects the performance of its actors. Thus, the objective of this paper is to identify the relation between a network structure and its actors’ performance. The chosen context is a recyclable material network in the city of Curitiba, in the Brazilian state of Parana, between 2007 and 2011. Through the study, it was possible to identify the actors in the network during a period of time (from 65 actors in 2007 to 102 in 2011), as well as its structural dynamics, and the association between the network motivational variables and performance (adjusted income), along with its persistence over time. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Brazilian society has recently gone through major changes, such as political democratization, the development and use of new technologies, a more conscious consumer choosing better products and services, economic stability, the opening of international markets and several privatizations in the public sector. Under such circumstances, strengthening relations between organizations within cooperative systems is a management tendency not only to face a new competitive environment, but also to promote social advantages. The creation of partnerships between the private sector, the government, and organized civil society has called strategic management researchers’ attention, especially relationships between partnership creation and organizational performance (Cruz, 2012). Becker (2007) underlines the importance of the organizational performance perception from the stakeholder perspective. He points out the emergence of management models characterized by informal social systems that provide cooperative interaction among its participants, stimulating repeated interactions over a course of time.

∗ Corresponding author. Tel.: +55 4132711859. E-mail addresses: [email protected], [email protected] (T.S. Martins). 0921-3449/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.resconrec.2013.06.002

In this context, this article describes the development of a social and organizational network structure between 2007 and 2011, identifying its association with income generation. The network is formed by the collectors of recyclable materials in the city of Curitiba, in the Brazilian state of Parana. This performance measure is directly linked to the main objective of the Rede de Organizações de Materiais Recicláveis da Grande Curitiba,1 going along with the argument that network structures favor improvement in performance for network actors with specific motivations. Under such framework, it is worth mentioning that the network analyses research and its impacts on society is moving toward a theoretical and an empirical maturity. There are several discussions, from different perspectives, on the advantages that arise from cooperation among the organizations in various economic sectors (Corten and Buskens, 2010, p. 5). In order to consolidate this maturity, network analysis through longitudinal series, which is hard due to data collection and measurement complexity, is essential to comprehend an event from a dynamic perspective. The main purpose of the article is to identify the relation between a network

1 Rede de Organizações de Materiais Recicláveis da Grande Curitiba is the recyclable material network in Curitiba (the capital city of the southern state of Paraná, Brazil). This network is formed by all actors that deal with recyclable materials in the city and the nearby cities. For the article we used the following translation: The Organizational Network of Recyclable Materials in the Greater Curitiba Area.

J.A.W. Cruz et al. / Resources, Conservation and Recycling 78 (2013) 36–46

structure, measured by several network indicators, and the generation of the recyclable materials collectors’ per capita income. The present article is organized into the following sections: Introduction; Literature review; Methodology; Data analysis; and Final considerations. 2. Literature review The aim of this section is to establish a theoretical relation among the main topics of the research, that is, social networks, their management peculiarities and its association to performance. The present review is based on two main views explored by researchers in recent years. The first one is an interdisciplinary approach, it sees networks as a form to manage relationships among economic actors. The second one presents the network as a tool for analyzing and understanding social relations within a cluster of players with distinct objectives (Martes et al., 2008). 2.1. The network concept From an interdisciplinary perspective, Van Aken and Weggeman (2000) emphasize that every organization is involved in some form of network. According to them, some structural and managerial aspects determine the creation of networks within an environment that has actors that involve themselves in horizontal and vertical alliances searching for congruent objectives. Such reflections are influenced by Powell and Smith-Doerr (1994), who describe networks as a set of relations among actors, whose content represent its typology and forms its intensity, being typically included by or overlapped in multiple networks. From a sociological perspective, Granovetter and Swedberg (2001) describe a network as a regular group of contacts among individuals or organizations. Cruz (2012) has with strong conceptual evidence when identifying partnerships, cooperation, association between organizations and individuals, in the present social environment: no organization, large or small, is independent and self-sufficient, that is, every organization is immersed in a network context. The involvement of actors in a network is called by Uzzi (1996) embeddedness. He separates the concept into three components: joint solutions to problems, trust, and information transfer. Even though the elements are considered separate, they are related in a single social structure. He highlights that bonds among actors, from different areas, in various sectors, are established through social relations. According Granovetter (1985) embeddedness is the incorporation of an actor into a network structure. Understanding this concept leads one to understand why the institutions and networks are formed, maintained, and transformed (Martes et al., 2008, p. 27). Simsek et al. (2003) point out the existence of three types of embeddedness: structural, relational e cognitive. Structural embeddedness represents the number of network connections, the higher the number of bonds among the actors, the higher the structural incorporation of a network. Relational embeddedness is the content of the relationships (trust and cooperation), and cognitive embeddedness corresponds to similarity of goals and social norms among the actors. 2.1.1. Network structure motivations One of the main points in the study of network structures is the social impact that this type of structure has in comparison to isolated organizational action. Various researchers point out the ability to generate social advantages as one of the main characteristics of this form of cooperation, among them Porter (1998), Schimitz (1992), Scott (1994) and Cointer and Roth (2010). In this context, the main question to be answered is why the organizations

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in a network structure can bring more social advantages than if they were isolated? Some authors, including Inojosa (1998) emphasize the value creation leveraging in organizations found in a given network structure, relating the partnership among stakeholders as a positive relation of development. Further within this current, Powell et al. (1996) argue that some organizations have to cooperate in order to acquire resources and competences they do not have. Among the reasons observed to justify the relation of cooperation among participants of a network structure, is “the knowledge network”. When the goal is to learn and acquire different knowledge and competence, we can observe the intention to maximize the use of complementary resources and new technologies (Lei and Slocum, 1992). Another relevant reason is explained by the resource dependency theory: organizations cooperate to find valuable resources that they do not possess (Abok et al., 2013). Given these motivations, Koza and Lewin (1998) observe that the exploration of knowledge is associated with the discovery of new strategic opportunities for the creation of social effectiveness, new capabilities and investments, and such association motivates organizations and people to act cooperatively under a network structure. 2.2. Social network analysis Another way of seeing a network is from a methodological perspective. According to Mizruchi (2006), this approach goes back to the 1934 J.L. Moreno’s study, whose sociometric approach was based in a graphic relationship representation, just as in Barnes (1954), Bott (1957) and Mitchell (1969). The concept of networks is constructed around the idea that it is a kind of structural sociology, based upon a clear notion of the social relations effects over the behavior and results of its actors (Mizruchi, 2006). The analysis of social networks can be considered a methodology applied to the study of relations among actors with objects of any kind (Borgatti et al., 2002). Below are some of the main measurements typically used in social network analysis as Snijders et al. (2010) recommend: • Centrality: shows the number of connections an actor has with other actors in a network (Freeman, 1979a,b). Such measure is gauged by the division of a node by the maximum degree any other node can have. • Closeness: demonstrates the distance of a player in relation to other network players (Wasserman and Faust, 1994). To calculate the degree of closeness, the geodetic distance of a node in relation to all the other nodes in the network should be added up, the result is then inverted, thus obtaining the distance, and consequently the closeness, where the larger the distance, the smaller the closeness and vice versa. • Betweenness: demonstrates the interaction among non-adjacent actors. An actor is considered an intermediate if he connects several other actors that do not connect directly (Degenne and Forsé, 1999), measuring the sum of probabilities of the same node being in the way of all the other nodes of the network. • Density: calculation of the proportion of existing lines in a graph, relative to the maximum possible number of lines (Scott, 2000). • Geodesic distance: the shortest distance between two nodes (Wasserman and Faust, 1994). 2.3. Networks, management and performance Among some of the main authors that suggest the theoretical relationship between networks, management, and performance, Becker (2007) and Conti and Dorein (2010) point out that if

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development of network structures is participative and negotiated, it generates organizational maturity, mainly because it establishes a dynamic and evolutionary approach to environment. It provides a reflection about the implementation and control of strategies with focus on performance. The congruent objectives of a network structure can be reached more easily from a growing density of articulation by the State, corporations and organized civil society, where the options are not of one or another, but of a group of actors established within the network over the course of time and governed by a participative management system (Cruz, 2012). From the author’s point of view, such diversity of actors enables articulating actions on a local scale more easily, facilitating direct citizen participation and articulation of partners. Hence, the fact that the actions can be adapted to most diverse conditions faced by people is one of the most significant benefits of a locally developed network, focusing on specific performances for all actors in a network structure (Kneteman and Green, 2009). A diversity of actor types also spawns a differentiated perspective for the forms of performance. For Cruz et al. (2011) and Maciel et al. (2012), performance can be described as the result obtained in a determined action against a pre-established expectation. For the author, it is also necessary to emphasize the interdependence of economic, technical, cultural, political, institutional, and environmental factors in network performance. Along with the debate over the form of performance and its relevance in the specific context of network actors, particular emphasis is given to the complexity of measurement of positive association between the network structure and fulfillment of aims of network members. Such concern highlights the need to identify methods of network performance, allowing the verification if objectives are reached relative to expected objectives in order to validate strategies adopted and reassess the goals under a longitudinal and dynamic perspective. Finally, facing the theoretical evidence presented in this review, the following research questions are proposed: a. Is there a positive association between the degrees of centrality, closeness and betweenness and income generation by carrinheiros2 connected to organizations that participate in the Rede de Organizações de Materiais Recicláveis (The Organizational Network of Recyclable Materials)? b. Has the association between the degrees of centrality, closeness and betweenness with the carrinheiros per capita income generation been lasting over time (2007 and 2011)? 3. Methodology The following section presents the methodology of the study, its classification and design, along with the methodological procedures which deal with conceptual aspects of data collection and analysis, as well as the detailed description of the research stages. The study is exploratory and descriptive, between 2007 and 2011, composed by bibliographical, documental, field research, and a survey. Data collection was through questionnaires, semistructured interviews, analyses in documents and reports, together with the researchers’ participation in forums, meetings and congresses of the Rede de Associações de Carrinheiros da Grande Curitiba – Paraná – Brasil.3 The main characteristics of each form

2

Carrinheiros are independent garbage collects. Rede de Associação de Carrinheiros da Grande Curitiba – Paraná – Brasil is the network that gathers all the independent garbage pickers associations in the city of Curitiba, the capital state of Paraná, Brazil. We translated in the study: The Carrinheiros Network Associations in the Greater Curitiba Area. 3

of data collection are presented below, along with its objective, operational context, form of analysis and the results obtained. We conducted semi-structured interviews to identify the main motivations of actors to participate in the network. The individual interviews were conducted in 2007 with 19 representatives of the participating organizations – carrinheiros organizations, the government, private sector, and non-profit organizations. The interviews lasted approximately 40 min and followed a 12 question script based on the paper’s objectives. The questions were about network history, network objective, network motivation, type of network participation, means of participation, and actors’ relationships among others. The interviews were recorded and a script was written. Then, we used content analysis on the script. The method was operationalized through ATLAS.ti, version 6.0. Based on the results, we were able to identify four primary motivations for network participation: Exchanging relations and donation of materials correspond to any event of exchanging or donating of materials for recycling and renewing. Generally, these events take place between public organizations and those of carrinheiros, including an occasional exchanging of materials among the latter. Commercial relations refer to any event of recyclable materials trading. Here, trading is configured through barter between goods and money taking place among the network actors. The relations of financing and financial incentives correspond to any event of financing and financial incentive without goods exchanging. Generally, such events occur in the form of projects and programs of financial support that organization of carrinheiros and its associations receive. Finally, the regulation and development relations that are related to events associated with the promotion and defense of the carrinheiros rights and their associations. These are usually bound to actions focusing on child labor and welfare system, among others. Questionnaires were used to identify the main actors (organizations), their typologies and motivations to integrate a network. Between 2007 and 2011, the questionnaires were sent to each actor, through their managers. The questions in the instrument identify the actor, his typology and motivation, means of participation, actor relationship frequency, management characteristics in the network, network participation objective, benefits from network participation and to whom and why the actor relates to. New actors were revealed within a network as they were indicated by others, thus each new actor cited in the questionnaire was included in the network, and consequently in the sample. The outline of main actors in the network occurred as indications were repeated, and the established cutting off criteria was three sequentially and uninterruptedly surveyed actors that revealed no new actors (organizations). The data was submitted for social network analysis through a UCINET system, network analysis software, developed in the laboratories of Analytic Technologies, at the University of Greenwich – the United Kingdom. This system enables identification of network structures in general terms and by the type of relation (exchanging and donation of material, commercial relations, financing and financial incentives relations; and, regulations and development relations). The Documental research was motivated by two main objectives, the first comprising the identification of values referring to an average annual per capita remuneration of carrinheiros. The second refers to circularization, by sample, of relations among the actors in a network, the documental analysis was based on reports, contracts, arrangements, meeting minutes and internal controls, that were made available by the organizations integrating the network, after having been analyzed descriptively. Direct Observation verified if the motivations identified in the 2007 interviews remained relevant over the time (2007–2011), the observations made by the researchers occurred at the meetings between the organizations involved in a network and carrinheiros

Table 1 Integrated methodological representation. Data collection method

Sample

Form of data analysis

Result

Identify the main motivations of players in the network

Semi-structured interview

19 managers

Content analysis

Identify the actors participating in forums, meetings, and congresses

Document research

Descriptive analysis

Identify the key actors, their typologies and motives for integrating a network

Questionnaire

2007 – 002 2008 – 002 2009 – 002 2010 – 002 2011 – 002 2007 – 065

Identification of four motivations for relationships among actors in a network Initial identification of actors in a network

Confirmation of actors’ motivations along a historical series (2007–2011)

Direct observation

Circularize the relationships among network actors

Document research

Identify the amounts relative to average annual per capita remuneration paid to carrinheiros

Documental research

Identify the key motivations of network actors

Quantitative analysis

Identify the existence of persistence of associations among network indicators and income generation.

Qualitative analysis

2008 – 085 2009 – 091 2010 – 096 2011 – 102 2007 – 012 2008 – 008 2009 – 006 2010 – 006 2011 – 005 2007 – 013 2008 – 015 2009 – 018 2010 – 019 2011 – 020 2007–001 2008 – 001 2009 – 001 2010 – 001 2011 – 001 2007 – 065 2008 – 085 2009 – 091 2010 – 096 2011 – 102 –

Network analysis

Identification of a network structure in its general form and by type of motivations.


Confirmation of four motivations of relationship among network actors in a time series


Confirmation of relationship among actors.


Identification of average annual per capita remuneration paid to carrinheiros by their respective organizations

Correlation coefficient

Identification of positive and negative associations between network indicators and income generation by carrinheiros


Identification of a time series of persistence


Objective

Source: the authors, 2012.

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40


Table 2 Types of organizations involved in Rede de Associação de Carrinheiros 2007–2011. Organization type

2007

2008

2009

2010

2011

Private organizations Public organizations Third sector Organizations of Carrinheiros Total organizations

4 14 11 36 65

10 21 13 41 85

10 21 13 47 91

10 21 13 52 96

10 21 13 58 102

Source: The author (2012).

within associations, having them been analyzed descriptively, we could conclude that the four main motivations to participate in the network remained the same, thus allowing us to establish longitudinal series. In order to facilitate the comprehension of the operational flow of the research, we present a chart with the objective, data collection method, sample, form of analysis and the results of each stage. To verify the association between the variables proposed, we opted to carry out a preliminary correlation, defined as a measure of association between variables, that is, to what degree the behavior of one – another is associated to. According to Siegel (1975), in a non-parametric case, the usual measure of correlation is the coefficient (r) of correlation of Spearman. In this survey, the Spearman correlation was used to check the possible relations between the variable Income * Salary and the other variables of motivation. 4. Data analysis The Rede de Associação de Carrinheiros (The Carrinheiros Network Associations), headquartered in the city of Curitiba (in state of Paraná – Brazil) has its origins in a group of people understanding about the necessity of organization and promotion of carrinheiros work dignity, whose main activity is the selective collection of recyclable materials from Brazilian households. It was formally established at a Forum, in April 2001. It initially had the participation of public and private companies with a strong support from the community, that promoted a dialog between carrinheiros and forum participants. Based on the fact that collected materials were sold at very low prices and, usually through intermediaries, and parents carried their children along to pick garbage on the street, the Forum created a non-governmental organization, whose initial goal was to promote, execute activities and deliberate about actions related to this practice. So, this organization was an association for carrinheiros to gather efforts and act as a group in a cooperative system like. Over time and through the mobilization and organization of carrinheiros, several other associations and cooperatives were created, thus multiplying and building the structure of the Rede de Associação de Carrinheiros (The Carrinheiros Network Associations), which started receiving more actors (Table 1). The network has actors from the private, public, and the third sector, whose aims are not always congruent. However, they almost always envision a common goal, that is, the promotion of carrinheiros’s work in a dignified and profitable manner, stimulating the concepts of citizenship and environment, through the economic leverage of its members. Table 2 shows quantitatively the types of organizations actively involved in the Network, between 2007 and 2011. According to the quantities and typologies presented in Table 2, the sociograms presented in this paper (Fig. 1) illustrate the general structure of network interactions between 2007 and 2011. It can be observed that from the second period on, not all organizations are directly connected. There are actors who are isolated or with

little interaction, which proves the characteristic of symmetry in a network, since its borders are not very clear and the actors have the same capacity to influence each other, which shows the variation of structural and relational embeddedness starting from the network indicators presented. The sociograms (Fig. 1) clearly show the increase in bonds among the actors during the period observed. They also show a growing number of actors and its complexity, which in 2007 demonstrate Third Sector Organizations (in red) having higher centrality, and being slowly substituted by the organizations of carrinheiros and the private sector, thus displaying the very first evidence of carrinheiros’ organizations autonomous development. Regarding the network’s structural configuration in 2007, it is clear that, despite its relatively small size (Dens = 0.0591), there is a large number of interconnected organizations, with 247 links, with a small distance (Av. Dist. = 1.93), that is, for an organization to contact another one, only two intermediaries are needed. In 2008, we can observe an increased density (Des = 0.0611), number of actors (85) and links (436). In 2009, however, even though the number of actors increased, the network structure became weaker. Such conclusion is based on a significant fall in density (Dens = 0.049), the number of links (401) and an increase in an average distance (Av. Dist. = 2.595). Followed by a strong recovery of network indicators, the year of 2010 brings a substantial growth in the number of actors, (96), links (632) and density (Dens = 0.0693), along with a fall in distance between actors (Av. Dist. = 2.388) in comparison to the previous year, which demonstrates a strengthening in the network structure during this period. Finally, following the previous year’s tendency, in 2011 there was a limited growth in the number of actors (102) and links (640). On the other hand, its density suffered a small decrease (Dens = 0.0621), contrary to the distance between the actors that increased (Av. Dist. = 2.436), which is considered normal due to the fact that the density is calculated by the proportion of existing lines in a graph, relative to a maximum number of possible connections. 4.1. Metrics of network centralities Even though a graphic presentation of a network enables the identification of nodes and links, it is clear that some actors take on a central role in relationship established. This way, we used some indicators of centrality to highlight the participation of certain types of actors in the network structure. In this respect, there are three types of centrality indicators used in this paper: the degree; closeness; and betweenness. Degree of centrality: the degree of centrality shows the number of links an actor has with other actors in a network. In the presented context, special attention is given to Third Sector Organizations (Cod. 55; 53; 58) in the networks’ initial stages, which are characterized by high degrees of centrality (Cod. 55 – 92,188; Cod. 53 – 79,688; Cod. 58 – 20,313). Such fact can be explained by the networks’ origin, that is, an initial dependence on Third Sector Organizations in terms of executive actions, articulation among actors and attraction of new members into the network structure. Regarding the participation of public organizations, a higher degree of centrality can be observed from 2008 on. Their actors (Cod. 39; 40; 47) have above than average degree centrality (2008 – 8852; 2009 – 8303; 2010 – 11,140; 2011 – 9765). The same happens with private organizations, which showed a significant increase in degree centrality, especially from 2009 on. Their actors (Cod. 57; 80; 77; 51; 38; 67) are characterized by an above average indicators for the period observed (8303). Analyzing the collectors’ organizations degree centrality, we can see a higher concentration of actors with above average concentration can be observed in the initial years (2007 and 2008). From 2009


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Fig. 1. Interactions of generic nature in the network between 2007 and 2011. Source: the authors, 2012.

on, there is a significant decrease of centrality for this type of actor, who in general terms, ceased to appear as central actor in the network, as opposed to an increased number of actors from private and public sectors who go on interacting more effectively within the network. The degree of centrality indicators for the ten most relevant actors in each period can be observed in Table 3, in which types of organization are presented separately by color: yellow represents carrinheiros’ organizations, green is for public organizations and blue for private sector organizations. The degree of closeness indicates how close the actors are one to another. Regarding this measure, we can observe an increase during the studied period, with only 22 actors above the average in 2007 (50.686), going to 28 in 2008 and more than 30 actors in the remaining years. Special attention is given to actors Code 55 and 53 (2007), whose closeness is high, as well as the centrality degree as presented before and the betweenness presented later on, thus showing the effectiveness of these actors in the network’s initial stage, as can we can see in Table 4.

In general, we can observe an evolution in the distribution of the closeness degree among the actors in the network, resulting in a growing number of actors above average, and a decrease relative to the average, even though several actors appear to be disconnected from the network’s structure in 2008, a phenomenon that would gradually decrease in other periods. Another indication confirmed by the closeness degree is a substantial increase in closeness of actors coming from public and third sector organizations in the network structure, the two types being the closest over the time, at the expense of carrinheiros organizations, which show more closeness in 2007, whereas they are gradually replaced by public and third sector organizations in subsequent years. The degree of betweenness demonstrates the importance of an organization within a network is also visible from the number of contacts intermediated by it. In this context, when it comes to the actor’s power of betweenness, as well as degree centrality, the actors coming from organizations of carrinheiros tend to show more relevance at the initial stages (2007 e 2008), being

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Table 3 Degree centrality indicators by network actor between 2007 and 2011.

N. 1 2 3 4 5 6 7 8 9 10

Cod. 55 53 17 58 3 16 21 26 45 9

2007 92,188 79,688 28,125 20,313 17,188 14,063 14,063 14,063 14,063 12,500

Cod. 1 55 2 39 3 40 57 20 66 26

2008 52,391 52,381 35,714 35,714 26,190 25,000 23,810 22,619 21,429 20,238

GENERAL Cod. 2009 1 41,111 57 35,556 40 30,000 55 30,000 39 28,889 2 21,111 3 21,111 80 21,111 66 18,889 14 17,778

Cod. 68 1 39 2 55 47 80 57 40 77

2010 58,947 54,737 30,526 28,421 28,421 27,368 26,316 25,263 24,211 23,158

Cod. 68 1 39 57 47 80 55 40 51 77

2011 64,356 32,673 32,673 28,713 25,743 25,743 24,752 22,772 22,772 22,772

2010 Cod. 13.494 39 13.085 1 13.014 47 13.014 55 12.960 40 12.960 80 12.943 72 12.873 53 12.873 48 12.855 77

2011 17.750 17.657 17.474 17.354 17.295 17.295 17.235 17.206 17.177 17.177


Table 4 Closeness indicators by actor between 2007 and 2011.

N. 1 2 3 4 5 6 7 8 9 10

Cod. 55 53 17 3 45 26 21 16 9 23

2007 92.754 83.117 57.658 53.782 52.893 52.893 52.893 52.893 52.893 52.459

Cod. 1 55 2 39 3 40 57 20 66 26

2008 3.115 3.115 3.098 3.098 3.089 3.088 3.087 3.086 3.085 3.084

GENERAL Cod. 2009 Cod. 1 8.662 1 57 8.596 39 40 8.523 47 2 8.515 55 55 8.515 2 3 8.499 40 14 8.483 80 39 8.483 3 66 8.483 77 80 8.483 14


substituted in terms of importance by private enterprises, which become actors with higher betweenness. As for the third sector actors, they assume higher relevance starting in 2008, this fact being initially explained by the attributions of betweenness allotted to actors 53 and 55. As for an increased representativeness of betweenness by private organizations, it occurs due to the closer direct contacts between carrinheiros’ organizations and them, dealing and selling materials. So, this significant increase in the degree of betweenness refers to private actors that trade. Finally, the actors representing government organizations appear to be of particular importance in betweenness due to the programs, projects and actions within a network, as well as those of the third sector, which is considered as an important group in promoting new relations among all actors. Their actions mainly refer to regulation practices toward carrinheiros organizations and the monitoring of organized collections. Table 5 shows the relevant database, as well as other analyses of centrality. 4.2. Network structure motivations When it comes to the main motivations for actors to participate in carrinheiros organizations, four reasons stand out along the entire historical series. We now present the motivations. Material donation and exchanging relationship network: The relationships originated by this motivation obtained significant density during 2007 (0.03) and 2008 (0.0105), and from this point on, it became a secondary type of relationship relative to other motivational categories mapped. There is a relevant existence of

relationships among actors, motivated by circulation of material coming from donations and exchanges, which are generally limited to a maximum of 125 (2007) and a minimum of 75 links (2008), apart from a decadent density and metrics of centrality (degree, closeness, and betweenness) initially relevant (2007 and 2008) and afterwards with minor impact, involving fewer and fewer actors, thus generating distinct clusters. Analyzing groups of actors via their centrality metrics in all periods observed, one can perceive an objective mutation of the network’s status, An initial centralization and great involvement of the third sector in articulating exchanges and donations, whereas from 2008 on, they assumed a minor role in these relationships since many organizations of carrinheiros assumed control of exchanges among themselves and those with private institutions, while the donations remained among few public institutions and collectors organizations. (2008 and 2009). As of 2010, we can observe a fall in relationships among carrinheiros’ organizations, where they became more directly involved with private and public organizations, with a significant decrease in betweenness by the third sector, which led to decreased closeness and consequently, centrality, which remained constant in 2011. Trading relationship network: These relationships include those with their origins in the practice of trading, and they correspond to the second most important category in all of the historical series of the network, relative to the indicators. This fact is justified by the clear relationship between the commerce, and the income generation of collectors, which is the main objective of the network. With an increasing density (0.0163; 0.0195; 0.0201; 0.0230; and 0.0237), growth in number of actors engaged, rise in the number of connections (68; 139; 165; 188; and 244) and a decrease in the


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Table 5 Indicators of betweenness centrality by network actor between 2007 and 2011.

N. 1 2 3 4 5 6 7 8 9 10

Cod. 55 53 17 9 13 16 3 21 26 6

2007 0,252 0,138 0,011 0,01 0,009 0,009 0,004 0,003 0,002 0,001

Cod. 1 55 39 2 3 4 57 80 20 75

2008 0,136 0,092 0,031 0,024 0,014 0,012 0,011 0,011 0,009 0,008

GENERAL Cod. 2009 1 0,158 57 0,091 55 0,069 39 0,067 40 0,067 3 0,038 80 0,033 72 0,029 66 0,026 20 0,025

Cod. 68 1 39 55 47 79 57 80 77 40

2010 0,256 0,213 0,052 0,05 0,042 0,036 0,034 0,032 0,028 0,027

Cod. 68 1 39 57 47 55 80 77 48 72

2011 0,34 0,131 0,07 0,067 0,041 0,04 0,04 0,035 0,032 0,029


average distance between actors (3057; 2343; 2474; 2696; and 2663), the commerce-motivated relationships count on an almost exclusive participation of carrinheiros’ organizations and the private sector, with a discreet Third Sector participation, setting up commerce of some relatively few materials donated by private and public institutions. Analyzing groups of actors via their metrics of centrality in all periods observed, one can notice a discreet involvement of the third sector’s representatives, which in the first year (2007) was represented by actor 55, having important degrees of centrality, betweenness and closeness, due to its attributions of articulation between collectors and private companies and the large amount of trading materials that came from donations. These characteristics changed in 2008, its metrics of centrality (degree of centrality, closeness and betweeness) decreased. In 2009 the articulation by non-governmental organizations became essential to promote a recovery in the recyclable market, highly affected by the 2008 world financial crisis and by the scarcity of public projects to finance third sector initiatives. The actors within private sector demonstrated a growing degree of betweenness over the time, with large relevant groupings starting in 2010. This fact proves a relational autonomy between private organizations selling recyclable materials and their suppliers, represented by organizations of collectors, without the need for the third sector’s involvement. Financing and financial incentives relationship network: Motivations originating from financing and financial incentives in the Rede de Associação de Carrinheiros (The Carrinheiros Network Associations) correspond to relations directly connected to the development of the network, whose objective is to generate income and autonomy for the collectors. These motivations had initial significant density (2007 – 0.0344), which decreased by 2009 (0.0079), and went back up in 2010 (0.0113) and in 2011 (0.0119). Despite a significant drop in the number of links between 2007 (143) and 2011 (123), it is worth pointing out that this type of relationship was strengthened from 2010 on, with a decrease in its distance, as well as in other indicators of structural equivalence. Upon analyzing the relational structure though the historic series, there is a clear decrease in relationships of financing and financial incentives between 2007 and 2009, whereas starting in 2010, there is a strengthening of this relationship. This phenomenon is explained by a shrinking number of partnerships established during the 2008–2009 period, which are, according to documental descriptions, directly related to a lack of resources for this means, while they returned in 2010, and intensified in2011, primarily through Third Sector Organizations.

Regulation and development relationship network: The number of connections has a growing perspective, equivalent to the number of participating actors. As for the average distance, it varies between 1926 (2007) and 2508 (2011), with growing distancing until 2009, that became constant ever since. The third sector and public organizations focused on promoting and defending collectors’ rights by directly following the network deliberations and interventions in each organization that represents the main network actors. Among the main topics addressed, special emphasis is given to the monitoring of child labor, promotion of welfare, work accident prevention, formalization of legal entities, constitution of formal groups, and promotion of new ones. Relationships motivated by regulation and development count on effective involvement of many network actors, and on the binding of actors in collectors’ organizations, third and public sector, whose objective is to promote activity development, as well as observe the legal framework. 4.3. Association and persistance of network with development To verify the association between the network structure and performance, and answer the guiding questions proposed at the end of theoretical approach, we initially researched in historical series the average amount generated to the members of each collectors’ organization in a year. The data was registered from the moment an organization of carrinheiros (an actor) was considered a network member, therefore, the historical series is not constant over the period analyzed (from 2007 to 2011) for some actors. After the identification of the amounts, the next step consisted in the income verification compared to Brazilian minimum wage in the year established by the historical series. Such relation is needed to identify income generation compared to a time measure, which enables us to identify the real growth, by applying the following equation: adjusted income =

average per capita annualincome . minimum wage of the period

From the results obtained, the so called Adjusted Income becomes a variable of performance to analyze the association, the motivation variables data were obtained from conjoint analysis of the structural and relational embeddedness. From the definition of performance variables and motivation analysis, we have opted to examine the non-parametrical correlations of the performance variable (adjusted income), and motivational variables studied, through Spearman correlation in accordance with specificities described in methodological

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Table 6 Correlation of Spearman among variables examined. Motivational variables

Period 2007

1 – Degree General 2 – Degree Com 3 – Degree Fin 4 – Degree Mat 5 – Degree Reg and Des 6 – Clos General 7 – Clos Com 8 – Clos Fin 9 – Clos Mat 10 – Clos Reg and Des 11 – Btw General 12 – Btw Com 13 – Btw Fin 14 – Btw Mat 15 – Btw Reg e Des

.946** .793** .343* .836** .368* .912** .655** .345* .820** .389* .748** .749** .366* .742** .418*

2008 .339* .373* .243 .219 .306 .336* .353* .298 .281 .312* .105 .381* .049 .235 .225

2009

2010

2011

.414** .444** .479** .418** .395** .451** .374** .461** .440** .331* .427** .394** .435** .363* .472**

.315* .395** .326* .091 .203 .395** .431** .352* .223 .246 .408** .332* .320* .038 .349*

.513** .475** .223 .395** .439** .440** .479** .121 .373** .199 .456** .412** .151 .318* .226

Source: The author (2012). Gray shading denotes the non-significant correlation at 95% level of confidence. * Correlation significant to 95% level of confidence. ** Correlation significant to 99% level of confidence.

approach, where the correlations were calculated per year as follows in Table 6. Analyzing the results of associations referring to period of 2007, we could verify that the variable adjusted income is positively correlated with all motivational variables and with the positive associations between the indicators of network centrality and income generation by collectors. In 2008, the positive association of centrality with adjusted income remains only through trading relations in all measures (centrality degree, closeness and betweeness), which leads to an understanding of a direct relationship between trading among actors and the effective income generation by carrinheiros. Regarding the association of general characteristics of network and income generation, this is confirmed in centrality and closeness, with no evidence of association in betweenness. Regarding the variables of betweeness, closeness and centrality, these do not demonstrate positive association in the motivations of materials donation and exchanging, financing and financial incentives, and regulation and development. In 2009, as well as in 2007, the association between variables appeared as perfectly contemplated, confirming the positive association between all four motivations and centrality indicators. In 2010, the association is again significant, even though the motivations bound to donations and exchange of materials show no association in any indicators of centrality and the motivations arising from regulation and development demonstrate association only in their betweeness centrality. Meanwhile, other motivations, including the general relationships, show positive association between variables of financing and financial incentives and trading in general. Finally, in 2011, the association between the variables resembles 2010, with the general structure fully associated (degree of centrality, closeness and betweenness). In the case of commercial motivation, as well as in the entire historical series, it remains positively associated, showing the strong correlation between intra-network trading and collectors’ income generation. As for the activities of financing and financial incentives and regulation and development, these appear partially associated, with positive association only with the centrality degree of regulation and development, and with no further evidence of association during the period examined. The persistence of positive and negative associations is demonstrated through a descriptive analysis of results relative to the

historical series. By observing the opportunities for correlation between variables of motivation and the one of performance (Adjusted Income), we can notice that only the relationships originating in trading remain positively associated to Adjusted Income. Such persistence tends to be directly linked to the characteristics of degree of centrality, closeness, and betweenness, thus confirming the hypothesis of positive association between the practice of network trading and income generation. Another important persistency observed was the link between the general network relationship and the Adjusted Income, which does not represent a positive persistency of betweenness, but in all the other indicator. Upon analyzing the association persistence of the category Financing and Financial Incentives, we can observe a recurring negative association in 2008 and 2011, while all other periods and groups of indicators (degree of centrality, closeness and betweenness) were positively related. Similarly to Financing and Financial Incentives, the category of Donation and Exchange of Materials demonstrated positive association of centrality degree, closeness and betweenness during the whole period, but in years 2008 and 2010, its positive association was not confirmed, not persisting in the time series. The associations established by the regulation and development indicators (degree of centrality, betweenness and closeness) were irregular because no type of indicator (centrality degree, betweenness and closeness) had its positive or negative associations along the analyzed historical series which refers to sporadic linking between the variables of motivation and performance. In general, when answering the guiding questions of this study, it can be stated that trading relations demonstrate the main association with income generation (Adjusted Income), having its persistence proven over the period analyzed. As opposed to other relationship motivations (exchange and donation of materials; financing and financial incentives; regulation and development) that do not demonstrate behavior of either positive or negative association over time. Under such evidence, correlation between the trading relationships of the network can be affirmed, in its characteristics of centrality, betweenness, and closeness with performance. Such statement can be neither confirmed nor refuted by other types of motivation, due to its non-regularity in the time series. The inconsistency of persistence of positive and negative associations is observed between 2007 and 2011. Here, the period of 2007 demonstrates positive association in all income-related motivations (this flow was interrupted in 2008) which represents many non-confirmed associations. This was not repeated in 2009, when all associations again turned to be persistent, taking on an irregular flow in 2010 and 2011. 5. Theorectical and empirical discussion This research supports the argument that the immersion of an actor in a network structure is a factor directly related to performance, generating the need of analyzing the positioning relative to embeddedness, which is a directly associated, persistent factor. According to this paper’s theoretical approach, this concept is discussed in Becker (2007), Mizruchi (2006) and Cruz (2012). The proposed point of view demands that future investigations about networks and performance give special attention to actors’ specific motivations relative to the network, to establish direct and indirect circumstances of association between variables. As a result, it provokes a contributive relation in network structural analysis, as presented in Wasserman and Faust (1994), Scott (2000), Degenne and Forsé (1999), Freeman (1979a,b) and Borgatti et al. (2002), and its association or no association to organizational or individual performance. In the historical series observed, it was possible to


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Table 7 Classification of Embeddedness by type of relation. Type of relation

Measure Degree of centrality

Betweenness

Closeness

General Donation and material exhange Financing and financial incentives Trade Regulation and development

Embeddedness of association Embeddedness of non-association Embeddedness of non-association Embeddedness of association Embeddedness of non-association

Embeddedness of non-association Embeddedness of non-association Embeddedness of non-association Embeddedness of association Embeddedness of non-association

Embeddedness of association Embeddedness of non-association Embeddedness of non-association Embeddedness of association Embeddedness of non-association


identify the direct and persistent relationship of structural embeddedness, as in Simsek et al. (2003), through network trading with income generation for carrinheiros, even though in the other types of embeddedness and motivations for association, it is inexistent or little persistent. In this context, it is recommended not to discard variables that are not associated, relative to an indirect association to income or directly related to other factors, which have influence on income sustainability. These variables enables us to propose concepts of associated and unassociated embeddedness, to be used exclusively in time series, due to the need of identifying persistence. Thus, suggesting an effective theoretical contribution to Uzzi (1996) and Granovetter (1985). Associated embeddedness is represented by positive association, persistent among variables of performance, featured in the present study through Adjusted Income, and the motivational variables, featured in the present study by types of embeddedness, (motivational categories). In this research, associated embeddedness is represented by trading relations between actors and adjusted income, because it features persistent associations in the historical series in all metrics of centrality (degree of centrality, closeness, and betweenness). On the other hand, unassociated embeddedness corresponds to persistent absence of positive associations between variables of performance and motivation. In present paper the relationships of regulation and development, donation and exchange of materials, and financing and financial incentives would be considered, embeddedness not associated to Adjusted Income, possibly being associated to other variables, emphasizing the mutual existence of associated embeddedness and non-associated one in network structure. In this context, it is worth tracing back to the scenario initially presented by Polanyi and re-discussed by Granovetter (1985), which presents a need of theorization over relations of immersion at macro and micro level, from a complementary perspective of association between network objectives and their relational motivations. Based on identifying associations between the variables, as in Mizruchi (2006), the historical series was evaluated from the perspective of persistence in time, whose data respond the second guiding question of the survey, since they demonstrate persistent association in an entire series of relationships originating from trade among actors, whereas the other motivations are not persistently associated over time. Such evidence confirms the relevance of the proposed concepts of embededness and non-association, whose applicability on research data lead to a constant classification in Table 7. 6. Final considerations For this paper’s final considerations, it is worth going back to one of the main questions of network study, which is to understand how organizational behavior is affected by social relationships and what impact it has on performance. Thus, our stating point is the principle that an actor is differently impacted by his positioning within the

network. In this context, given the objective of this survey, two guiding questions have been derived. The first question (if there is an association between centrality measures and income generation) is answered by a confirmation if the motivation is trading relations, and it was not confirmed by the other motivations (regulation and development; donation and exchange of materials; and financing and financial incentives). Based on identification of association between variables, the historical series was assessed from the perspective of persistence over time, and its data respond partially positively the second question (if the association between the degrees of centrality and income generation lasts over time). The results are characterized by persistent associations in the entire series of relationships, deriving from the practice of trading among actors. Other motivations were non-persistently associated over time. The study indicates the need to observe a phenomenon from different sides and at different times, because the possibility of finding many other sub-phenomena creates a particular reality that can establish new concepts. This possibility might absorb realities as different as concepts it encompasses, justifying the present research and motivating new approaches on the relational topic between network structures and performance. Finally, it is worth highlighting that the present research is limited to identifying association between the suggested variables, not making it possible to verify the cause and effect between them, nor identify their dependence and/or independence. Acknowledgement We would like to thank the CNPQ (Conselho Nacional de Desenvolvimento Tecnológico) for the support. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/ j.resconrec.2013.06.002. References Abok A, Waititu A, Ogutu M, Ragui M. A resource-dependency perspective on the implementation of strategic plans in Non-Governmental Organizations in Kenya. Prime Journal of Social Science 2013;2(4):296–302. Barnes J Class. Committees in a Norwegian Island Parish. Human Relations 1954;7:39–58. Becker DV. Redes de cooperação do estado do Rio Grande do Sul: Um estudo dos motivos da participação das empresas em redes. Dissertação de Mestrado. Santa Maria: UFSM; 2007. Bott E. Family and social network. London: Tavistock; 1957. Borgatti SP, Everett MG, Freeman LC. Ucinet for windows: software for social network analysis. Harvard, MA: Analytic Technologies; 2002. Corten R, Buskens V. Co-evolution of conventions and networks: an experimental study. Social Networks 2010;32:4–15. Cruz JAW. A Relação entre Estrutura de Redes Sociais e Desempenho: Um estudo de caso de associações de carrinheiros no Paraná – Brasil. Tese de Doutorado. Programa de Pós Graduação em Administração. Curitiba: Pontifícia Universidade Católica do Paraná; 2012.

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