Scholarly article on topic 'Applying Social Network Analysis on Rural Manufacturing of the Savannah of Bogota'

Applying Social Network Analysis on Rural Manufacturing of the Savannah of Bogota Academic research paper on "Agriculture, forestry, and fisheries"

CC BY-NC-ND
0
0
Share paper
Academic journal
Procedia Technology
OECD Field of science
Keywords
{"social networks" / "network structure" / "rural manufacturing" / "structural analysis" / "manufacturing systems."}

Abstract of research paper on Agriculture, forestry, and fisheries, author of scientific article — Sandra Molano, Andrés Polo, César López

Abstract In today's global volatile business environment, manufacturing organizations strive to streamline their flexibility towards delivering on time high quality products at lower costs and prices. Along this line, rural manufacturing networks constitute loosely coupled cooperation schemes among diverse partners, whose operation and interaction may be configured and synchronized in a rapid way. In order to the often unpredictable market needs to be addressed, the advantages network come from the greater scope for expanding the inter-relationships in ways that increase the scope for generating innovation. The SNA can contribute to the improvement process by focusing on the roles and the importance of key persons within process. The reason is that an improvement should focus on both, procedures and people. Therefore, the SNA, given its flexible applications, can emerge as an important management tool in the process of collection, transportation, and processing of milk in the savannah of Bogotá. The findings help to visualize the current practices at all levels when dealing with a rural manufacturing system and identify the areas in which more attentions have to be made for a more effective process.

Academic research paper on topic "Applying Social Network Analysis on Rural Manufacturing of the Savannah of Bogota"

Available online at www.sciencedirect.com

ScienceDirect

Procedía Technology 19 (2015) 1059 - 1066

8th International Conference Interdisciplinarity in Engineering, INTER-ENG 2014,9-10 October

2014, Tirgu-Mures, Romania

Applying social network analysis on rural manufacturing ofthe

Savannah of Bogota

Sandra Molano ' *, Andrés Polo , César López

aFundación Universitaria Agraria de Colombia, Calle 170 54 A 10, Bogotá, 110821, Colombia bUniversidad de La Sabana, Campus del Puente del Común, Km. 7, Autopista Norte, Chía, 250001, Colombia

Abstract

In today's global volatile business environment, manufacturing organizations strive to streamline their flexibility towards delivering on time high quality products at lower costs and prices. Along this line, rural manufacturing networks constitute loosely coupled cooperation schemes among diverse partners, whose operation and interaction may be configured and synchronized in a rapid way. In order to the often unpredictable market needs to be addressed, the advantages network come from the greater scope for expanding the inter-relationships in ways that increase the scope for generating innovation. The SNA can contribute to the improvement process by focusing on the roles and the importance of key persons within process. The reason is that an improvement should focus on both, procedures and people. Therefore, the SNA, given its flexible applications, can emerge as an important management tool in the process of collection, transportation, and processing of milk in the savannah of Bogotá. The findings help to visualize the current practices at all levels when dealing with a rural manufacturing system and identify the areas in which more attentions have to be made for a more effective process.

© 2015 PublishedbyElsevierLtd.Thisis anopen access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-reviewunderresponsibilityof"PetruMaior"University ofTirguMures,FacultyofEngineering

Keywords: social networks; network structure; rural manufacturing; structural analysis; manufacturing systems.

1. Introduction

According to the National Development Plan 2011-2014 "Prosperity for All" [7] Colombia should maintain an annual growth rate of 6% in a socially and environmentally sustainable manner. Initiatives taken by Trade Colombia

* Corresponding author. Tel.: +57 1 6671515; fax: +0-000-000-0000 . E-mail address: molano.sandra@uniagraria.edu.co

2212-0173 © 2015 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of "Petru Maior" University of Tirgu Mures, Faculty of Engineering doi: 10. 1016/j. protcy.2015.02.151

such as free trade agreements, Pacific Alliance and Andean Community are intended to promote exporting by small-to medium-sized firms encouraging collaboration through of association. The agricultural sector shows the government commitment to harness the wealth and the potential of the Colombian countryside, consolidate growth and improve competitiveness in order to diversify production, expand markets and improve the income of farmers. The Colombian Government to improve the conditions of the farmers has implemented trade policies to stimulate the domestic market and provide allocation of useful public goods and services, but the rural sector is still not being used fully, as planned. In 2012, Colombian farmers expressed dissatisfaction with the current situation of the agricultural sector through the protests. Although, the agricultural sector is a priority for the Government in the global development agenda due to the persistence of the international challenges, farmers placed mainly the blame for the recession on the performance of the sector in the negative effects of the free trade agreement United States-Colombia.

In this scenario, Colombian milk sub-sector is facing a series of challenges to articulate with success in international markets and consolidate the internal market. The National Council for Economic and Social Policy (Conpes) has generated policies to achieve the improvement of competitiveness in the dairy sector of Colombia. The objective of the document CONPES 3675 [4] is to improve the competitiveness of the Colombian dairy sector through the development of strategies capable of reducing production costs and increase productivity, promote partnership schemes, strengthen the institutional management of the dairy sector. The policy also seeks to improve sanitary and safety aspects in order to strengthen the competitiveness of the sector, improving public health safety as well as access to national and international markets. This has motivated the analysis of problems for each level of the productive chain, with the involvement of the different relevant trade associations for production, storage, transport, processing and commercialization, as well as entities responsible for inspection, surveillance and control of the production and commercialization of milk and milk-based products.

In Colombia most of the milk is produced by specialized enterprises, leaving very relegated economically to small and medium businesses. These enterprises are mainly located in cold areas of the country and close to the consumption centers. The present government policies to reach target groups indicate the need to undertake a comprehensive analysis of the production and first handler of milk, in the areas of Boyaca and Cundinamarca, especially in the savannah of Bogota and Ubate.

This paper applies the theory and techniques of social network analysis (SNA) to examine existing information and materials flows formally and informally within dairy rural organizations in the savannah of Bogota as are material suppliers, farms, conveyors, dairy producers; financial institutions, technology centers and universities, to analyze the network structure of value activity in manufacturing clusters, and to identify possible improvement areas to strengthen the effectiveness of this process to potentiate government policies.

2. Literature review

The rural sector is recognized to play a significant role in the reduction of rural poverty. Social, economic and institutional actors play a key strategic role in the dynamics of rural sector by prompting and articulating development processes [8]. It is argued that rural development strategies must take heed of network forms and that rural policy should be recast in network terms [15]. Those networks also play a key role in mobilizing resources (local or external) for the development and implementation of different types of innovation in the productive system of rural areas [8]. Innovation is a social process involving different social actors and their formal and informal relationships, in which the role played by each of them depends on social, institutional and even personal variables; they are very active elements in the governance of rural innovation systems [9]. The competitiveness of a rural region could be directly influenced by the farmers' ability to generate, access and understand knowledge and information based on collective and interactive learning [9]. This involves internal as well as external social networks.

Vanclay [16] outlines key social principles influencing farmers' resilience strategies, elucidating how their decision-making is part of a socio-cultural process whereby strategic reasoning is informed holistically by economic, social and cultural factors. According to Ward and Brown [17] innovative projects in rural areas are part of the wider global processes involved in economic and social development and depend on the combination of a number of factors. In dairy manufacturing, are identified factors as policy or legislation, market developments and natural

conditions dictating production [15]. MacDonald et al. [12] also has identified the uptake of contemporary farm management technologies as critical aspect of such adaptation and factors elucidating farmers' uptake of technologies relate to the information that is available to farmers, the extension processes determining farmers' use of information, and the drive, motivation and capabilities of farmers to implement new information. It is learning processes in relation to rural development, learning processes depend on several factors, such as the individual perspective, set of values and attitude of each agent involved [5], especially farmers. The network concept has become widely utilized in socioeconomic studies, networks may also have particular utility in understanding diverse forms of rural development [14], he firm's capabilities and competitive forces are the main factors forcing firms to collaborate. Firms with advanced collaborative capabilities tend to acquire trust and reputation by collaborating with other firms continuously [7], as expressed by the Colombian government in the document COMPES 3575 [4]. Successful firms are moving away from strategic positions in the value chain to a value creating system [12]. These firms add value by collaborating with suppliers, business partners, allies and customers. From a manufacturing network perspective, the relative position of individual firms with respect to one another influences both strategy and behavior [3].

For many traditional manufacturing associations in Colombian rural areas, the dairy industry in municipalities north Savannah of Bogota, as Lenguazaque, is typical and representative in the development context and network formation process. By the analysis the degree of association of dairy farmers belonging to a dairy cooperative (COPALAC) to improve the competitiveness of its association challenges facing the global economy, employing social network analysis (SNA) to track the formation process. In this context, it becomes imperative to study each actor's role. Thus in this paper we propose to analyze the structural characteristics of rural manufacturing networks using a formal, quantitative modeling approach social network [1]. We will show how social network analysis can both supplement and compliment more traditional, in a supply chain for dairy products in the savannah of Bogotá, including associated farmers and not associated to a dairy cooperative, suppliers, transporters of raw milk, dairy processors and customers; also, studying external actors such as universities and financial centers. This paper studied the relationship characteristics and spatial evolution of the networks in this manufacturing in less developed rural areas in savannah of Bogota.

3. Data Collection

This study was conducted through a questionnaire and interviews with various stakeholders in the Savannah of Bogota, specifically in the town of Lenguazaque and surrounding areas. The object of study was the relationships developed between the members of the cooperative organization COPALAC and other actors in the supply chain. COPALAC is an organization with a few years in the dairy market, and now has ninety-five partners from small, medium and large producers, and its main customer is Parmalat. Currently, it has been identified two hundred (200) potential vendors that can contribute to the goals in the medium and long term to produce 12,000 liters of milk daily; Similarly the cooperative wishes to extend its productive field beyond the marketing of milk, transforming and distributing products to become self-sustainable without relying on pasteurization companies. Because of this, it is a clear need to generate a new configuration of its logistics system, oriented toward the mission and vision of the organization, relying on processes, operations and best practices that drive improvements in performance, functionality and growth of the organization, among others.

Were identified as relevant actors in the study, organizations and companies that possibly by forming a cluster can influence farmers' productivity and competitiveness of the region. These participants were classified as: COPALAC partners who are the producers of milk, their customers (including Parmalat who is their biggest client), other families who are small producers, milk collection and transportation companies, financial institutions, universities and suppliers of inputs to the production process of milk. To carry out the research study a sample was determined. The selection of the sample enterprises was based on two criteria: 1) the number of the samples exceeding 10% of total producers, and 2) the sample representing different size scales (large, medium and small) and all the participants in the supply chain.

By the interview with the producers, suppliers, clients, universities, and several government authorities of the department, some data including census data in this industry were obtained.

4. Methods

Social Network Analysis (SNA) and UCINET software, developed by Borgatti et al [2], were selected to analyze the structure, nature and characteristics of two types of networks. According to the study objective, which seeks to determine the nature of the relations of the producers in the area with other agencies, both in terms of formal business exchanges and informal social linkages, they were obtained a cooperative network and a friendship network. Within the formal business exchanges it can be named the delivery of goods and services and linkages as production linkages, service linkages, supply chain linkages, financial linkages and knowledge linkages. The friendship network exposes the proximity between two producers and the presence of information interchange. In order to collect the information a questionnaire was designed, and we ask the producers if they share some kind of formal business exchanges with the other organizations in the sample. For the second network we ask for a different kind of relationship, one relationship more focused in the interchange of informal information.

4.1. Social Network Analysis inLenguazaque

Fig. 1. Cooperative Network

Fig. 2. Friendship Network

Two 23x23 networks were obtained (Fig. 1-2). For the analysis, four indicators were employed: Density, Degree Centrality, Betweenness Centrality and Geodesic Distance. The actors were named: Associate Producers (AP), Non Associate Producers (NAP), Parmalat (PAR), Customers (C), Transportation Brigade (T), Financial Institution (F), University (U), and Suppliers (S).

In order to determine the connectivity of the networks, it was decided to calculate the density. This shows the relationship between the number of existing connections and the maximum number of possible connections. The average density of the Cooperative network is 54,15%, and the average density of the Friendship network is 48,42%. According to information gathered in the producers, they are located in a region of the Department of Cundinamarca in Colombia, called Savannah of Bogotá, which is a very productive region in milk and dairy products. These producers are located in the area since their families arrived in the region many years ago. This makes many of them are known informally, in many cases maintaining a strong friendship, which is shown with the density of the Friendship Network. Moreover, the farmers in the past have worked individually, focusing only on the production of your herd.

A few years ago, COPALAC cooperative was created, which seeks to unite these small producers, relate them to other organizations in the region, and form a cluster that means for them advantages in buying to the providers, collection facilities for production, options for financial loan application, and technology transfer agreements with universities. It is observed the higher density of the Cooperative Network, which means that beyond the informal ties, COPALAC has succeeded to power them together to work cooperatively.

4.3. Degree centrality.

This indicator shows how central is a person or node with respect to those around him and across the network. For the interpretation of this indicator is necessary to focus on the actors taking into account the degrees of input and output. These nodes are divided into source nodes, receiver nodes, and powerful nodes.

4.2. Density

Table 1. Cooperative and Friendship Network Degree Centrality

Cooperative Network

Friendship Network

Degree NrmDegree Share

Degree NrmDegree Share

1 API 17.000 77.273 0.062

2 AP2 17.000 77.273 0.062

4 AP4 17.000 77.273 0.062

6 AP6 17.000 77.273 0.062

8 AP8 16.000 72.727 0.058

5 AP5 16.000 72.727 0.058

7 AP7 15.000 68.182 0.055

3 AP3 15.000 68.182 0.055

9 AP9 15.000 68.182 0.055

10 AP10 15.000 68.182 0.055

22 PI 15.000 68.182 0.055

23 P2 15.000 68.182 0.055

15 PAR 15.000 68.182 0.055 21 U 13.000 59.091 0.047

18 T1 12.000 54.545 0.044

19 T2 11.000 50.000 0.040

20 F 6.000 27.273 0.022 17 C2 5.000 22.727 0.018

16 CI 5.000 22.727 0.018

13 NAP3 5.000 22.727 0.018

14 NAP4 4.000 18.182 0.015

11 NAP1 4.000 18.182 0.015

4 AP4 16.000 72.727 0.064 23 P2 15.000 68.182 0.060 22 PI 15.000 68.182 0.060

2 AP2 14.000 63.636 0.056

3 AP3 13.000 59.091 0.052 21 U 13.000 59.091 0.052

I API 13.000 59.091 0.052

9 AP9 13.000 59.091 0.052

6 AP6 13.000 59.091 0.052 15 PAR 12.000 54.545 0.048

18 T1 12.000 54.545 0.048

10 AP10 12.000 54.545 0.048

5 AP5 11.000 50.000 0.044 8 AP8 11.000 50.000 0.044

19 T2 11.000 50.000 0.044

II NAP1 10.000 45.455 0.040

13 NAP3 9.000 40.909 0.036 12 NAP2 9.000 40.909 0.036

7 AP7 8.000 36.364 0.032

20 F 6.000 27.273 0.024 17 C2 6.000 27.273 0.024

14 NAP4 4.000 18.182 0.016

12 NAP2 4.000 18.182 0.015 16 C1 4.000 18.182 0.016

In the above table we can see the Degree Centrality for each one in the Cooperative Network and in the Friendship Network. In the Cooperative Network we can see the important role the associates play, becoming in fundamental part of cooperative work, while the non associate producers are relegated in aspects related with the interchange of goods or the formal working relationships. However, the Friendship Network is observed to be much more homogeneous and distributed among all players, even if no are in COOPALAC. Nevertheless, in total there are more than two hundred producers not associated yet, and, it is expected that these friendship networks observed in the sample can be a tool or medium for the flow of communication and awareness of the benefits of working together.

Call the attention the role of the university, because in the friendship network appears in sixth place, which means, the close relationship that has developed between teachers and researchers of the University with the farmers, through projects that work together. It should be noted that the approach of the university, in this case The Agrarian University Foundation was achieved by Colombia COPALAC initiative.

4.4. Betweenness Centrality.

This indicator denotes people who are in the network in a privileged position where, because of its location, are bridges between other actors, that is to say, these are the people that other people must go through to achieve communication with the other members of the network.

Table 2. Cooperative and Friendship Network Betweenness Centrality

Cooperative Network Friendship Network

Betweenness nBetweenness Betweenness nBetweenness

23 P2 20.078 8.692 4 AP4 35.633 7.713

22 PI 20.078 8.692 2 AP2 32.514 7.038

15 PAR 17.272 7.477 23 P2 28.691 6.210

2 AP2 11.071 4.793 22 PI 28.691 6.210

4 AP4 9.180 3.974 6 AP6 20.962 4.537

1 API 9.165 3.967 11 NAP1 13.061 2.827

6 AP7 9.165 3.967 12 NAP2 12.450 2.695

8 AP8 5.359 2.320 1 AP10 12.226 2.646

5 AP5 4.276 1.851 5 AP5 10.800 2.338

20 F 3.199 1.385 10 APIO 10.675 2.311

13 NAP3 2.718 1.177 9 AP9 9.849 2.132

16 Cl 2.535 1.097 8 AP8 8.956 1.939

17 C2 1.927 0.834 3 AP3 8.606 1.863

11 NAP1 1.689 0.731 21 U 6.747 1.460

12 NAP2 1.323 0.573 15 PAR 6.282 1.360

14 NAP4 1.219 0.528 18 TI 6.282 1.360

10 APIO 1.084 0.469 19 T2 6.100 1.320

3 AP3 1.084 22.727 17 C2 4.245 0.919

9 AP9 1.084 22.727 13 NAP3 3.518 0.761

7 AP7 1.084 22.727 7 AP7 2.535 0.549

21 U 0.317 0.137 14 NAP4 2.021 0.437

18 T1 0.091 0.039 20 F 1.976 0.428

19 T2 0.000 0.000 16 Cl 1.178 0.255

In the Cooperative Network is observed that the two suppliers have the highest degree of intermediation with 20.078%, meaning that they have high power over the communication that flows through the network. Maybe, because there are few suppliers and they provide both producer members and non-members, have ties with most nodes in the network. In the Friendship Network, nodes AP2 and AP4 with 35,633% and 32,514% are who have the higher degree of Betweenness Centrality. This is understandable, because they belong to the board of the COPALAC, maintain close relationships with producers, transporters, and Universities.

It is worrying to see the poor paper of the financial institution, which is explained because most farmers do not have the necessary documentation to obtain a loan. It is recommended the creation of a coordinated cluster between the University, producers and financial institutions, among others in order to develop projects with high added value to find enough financial support to bring them up.

4.5. Geodesic distance.

This indicator shows how close are some actors to others, taking into account that there may be many connections between two actors in a network. In the event that an actor needs to send a communication with some urgency, it will choose to send the information via the shortest path to the target in order to arrive quickly and without distortion. The average geodesic distance between the accessible actors (length of any actor to any other actor) in the Cooperative Network is 1,494, and in the Friendship Network is 1,542.

That means that in both networks with 1,5 steps one each can communicate with another, or in another words there are 1,5 degrees of separation between the actors that are in the network. This number indicates that it is very easy than any actor within the network establishes a relationship with any other actor, get to know or have a reference for possible projects together.

5. Conclusions

The associate relationships are the main channels in forming dairy enterprises, and the cooperative relationships formed with processors and financial institutions become comparatively stable. Besides, the associates become comparatively more active than those not associated, and the intermediary agencies and the service institutions act as bridges for the inter-small producers' cooperation. The core relationships of which respond to the enterprise sizes, status, capabilities, are still much affected by the cooperative position in a rural community environment. With further development of cooperatives, the level of trust among enterprises sometimes can begin to deteriorate due to breach of contracts, but actions taken by farmers to join in a cooperative COPALAC gives them a competitive advantage over those who have not yet been associated, can be seen on the networks as there is greater rapprochement between those associated with external aid agencies to appropriate supports provides national government to improve the conditions of rural manufacturing enterprises. To accomplish this, COPALAC must seek alternatives to develop a processing of its own milk products, this will help partners better prices with suppliers, transportation companies also own cause. At the same time, it can be expected that the competition will force network extension to take in contacts outside the region. So farmers is evident that states, can improve their living conditions and to really harness the wealth and the potential of the Colombian countryside. However, enterprises in those clusters located in less developed rural areas, are most likely to do this by following the "indirect globalization" way. The external agents as universities play a crucial role in integrating the farmers or rural enterprises into manufacturing networks. Finally, the SNA can complement processes focusing on the functions and the importance of key persons within a rural manufacturing process, the reason is that an improvement should focus on both a procedure and people. Therefore, the SNA, given your applications flexible, can emerge as a management tool important in the areas of rural manufacturing management.

References

[1] Borgatti SP, Everett MG. A graph-theoretic perspective on centrality. Social Networks 2006; 28 (4): 466-484.

[2] Borgatti SP, Everett MG, Freeman LC. Ucinet for Windows: Software for Social Network Analysis. Harvard. MA: Analytic Technologies;

[3] Borgatti SP, Li X. On social network analysis in a supply chain context. Journal of Supply Chain Management 2009; 45 (2): 5-21.

[4] Consejo Nacional de Política Económica y Social. Departamento Nacional de Planeación. CONPES 3675; 2010.

[5] Collier MJ, Scott M. Conflicting rationalities, knowledge and values in scarred landscapes. J. Rural Stud 2009; 25 (3): 267-277.

[6] Dargan L, Shucksmith M. LEADER and innovation. Sociología Ruralis 2008; 48 (3): 274-291.

[7] Departamento Nacional de Planeación. Plan nacional de desarrollo 2011- 2014 "Prosperidad para todos"; 2010

[8] Esparcía J. Innovation and networks in rural areas. An analysis from European innovative projects. Journal of Rural Studies 2014; 34: 1-14

[9] Guillaume R, Doloreux D. Production systems and innovation in satellite regions: lessons from a comparison between Mechanic Valley

(France) and Beauce (Quebec). Int. J. Urban Reg. Res 2011; 35 (6): 1133-1153.

[10] Hanneman R, Riddle M. Introduction to social network methods. Riverside: University of California; 2005.

[11] Huayou Z, Sibao D. Reconstruction of industrial location in view of industrial agglomeration. Chinese Geographical Science 2006; 16(4): 812.

[12] McDonald R, Macken-Walsh A, Pierce K, Horan B. Farmers in a deregulated dairy regime: Insights from Ireland's New Entrants Scheme. Land Use Policy 2014; 41: 21-30.

[13] Morrison A, Rabellotti R. Knowledge and information networks. An Italian wine cluster. European and Planning Studies 2009; 17 (7): 9831006.

[14] Murdoch J. Networks - anew paradigm of rural development? Journal of Rural Studies 2000; 16 (4): 407-419.

[15] Schoon, B, Grotenhuis R. Values of farmers, sustainability and agricultural policy. J. Agric. Environ. Ethics 2000; 12: 17-27.

[16] Vanclay, F. Social principles for agricultural extension to assist in the promotion of natural resource management. Aust. J. Exp. Agric 2004; 44:213-222.

[17] Ward N, Brown DL. Placing the rural in regional development. Reg. Stud 2009; 43 (10): 1237-1244.

[18] Wasserman S, Faust K. Social network analysis: methods and palliations. New York: Cambridge University Press; 1999.