scholarly journals Social Network Analysis of the Stakeholders Involved in the Dromedary Sector in the Mediterranean Region

2021 ◽  
Vol 13 (21) ◽  
pp. 12127
Author(s):  
Véronique Alary ◽  
Lina Amsidder ◽  
Abdelilah Araba ◽  
Cecilio Barba Capote ◽  
Sonia Bedhiaf-Romdhani ◽  
...  

Marginal arid zones in the south Mediterranean are faced with the dramatic departure of their labor forces through migration. Interest in the capacity of the dromedary species to enhance desert ecosystems and to be a potential lever of economic development of these marginal zones only started to grow in the last two decades. Based on an empirical survey of 179 stakeholders in four Mediterranean countries, we explored the links of the stakeholders in the dromedary sector in two dimensions: horizontal links with peers and vertical links along the value chain and in resource management. Both descriptive statistics and social network analysis highlight the original organization of the dromedary sector around herders and their social and cultural organization at the territorial level. Therefore, even if milk production and processing start to constitute an opportunity for the young generation who do not necessarily have the financial capacity to invest in a large dromedary herd, this change towards milk valorization can only happen if it is linked with the traditional system based on mobility. Using a systemic approach and working toward multiple valorizations of dromedary products instead of only targeting milk productivity should be explored.

2021 ◽  
Author(s):  
marco nunes ◽  
Antônio José de Abreu Pina

Projects can be seen as the crucial building blocks whereby organizations execute and implement their short, and long-term strategic vision. Projects are thought to solve problems, drive change, satisfy unique needs, add value, or exploit opportunities, just to name a few. In order to successful deliver projects, project management tools and techniques are applied throughout a project´s lifecycle, essentially to efficiently and in a timely manner, identify and manage project risks. However, according to latest reviewed literature, projects keep failing at an impressive rate. Although research in the project management field argues that such failure rate is due to a huge variety of reasons, it highlights particular importance to a still underexplored and not quite well understood (regarding how it emerges and evolves) risk type, that may lead projects to failure. This risk type, called as corporate behavioral risks, usually emerge, and evolve as organizations work together across a finite period of time (for example, across a project lifecycle) to deliver projects, and is characterized by the mix of countless formal and informal dynamic interactions between the different elements that constitute the different organizations. Understanding the extent to which such corporate behavior influences project´s outcomes, is a breakthrough of high importance that positively impacts two dimensions; first, enables organizations that deliver projects (but not only), to increase the chances of project success, which in turn is a driver of sustainable business, because it allows the development and implementation of effective, and timely corrective measures to project´s tasks and activities, and second, it contributes to the scientific community (on the organizations field), to generate valuable and actionable new knowledge regarding the emergence and evolution of such cooperative risks, which can lead to the development of new theories and approaches on how to manage them. In this work, we propose a heuristic model to efficiently identify and analyze how corporate behavioral risks may influence project´s outcomes. The proposed model in this work, lays its foundations on four fundamental fields ((1) project management, (2) risk management, (3) corporate behavior, and (4) social network analysis), and will quantitatively measure four critical project social networks ((1) communication, (2) problem-solving, (3) advice, and (4) trust) that usually emerge as projects are being delivered, by applying the theory of social network analysis (SNA), more concretely, SNA centrality metrics. The proposed model in this work is supported with a case study to illustrate its implementation across a project lifecycle, and how organizations can benefit from its application.


2021 ◽  
Author(s):  
marco nunes ◽  
Antônio José de Abreu Pina

Projects can be seen as the crucial building blocks whereby organizations execute and implement their short, and long-term strategic vision. Projects are thought to solve problems, drive change, satisfy unique needs, add value, or exploit opportunities, just to name a few. In order to successful deliver projects, project management tools and techniques are applied throughout a project´s lifecycle, essentially to efficiently and in a timely manner, identify and manage project risks. However, according to latest reviewed literature, projects keep failing at an impressive rate. Although research in the project management field argues that such failure rate is due to a huge variety of reasons, it highlights particular importance to a still underexplored and not quite well understood (regarding how it emerges and evolves) risk type, that may lead projects to failure. This risk type, called as corporate behavioral risks, usually emerge, and evolve as organizations work together across a finite period of time (for example, across a project lifecycle) to deliver projects, and is characterized by the mix of countless formal and informal dynamic interactions between the different elements that constitute the different organizations. Understanding the extent to which such corporate behavior influences project´s outcomes, is a breakthrough of high importance that positively impacts two dimensions; first, enables organizations that deliver projects (but not only), to increase the chances of project success, which in turn is a driver of sustainable business, because it allows the development and implementation of effective, and timely corrective measures to project´s tasks and activities, and second, it contributes to the scientific community (on the organizations field), to generate valuable and actionable new knowledge regarding the emergence and evolution of such cooperative risks, which can lead to the development of new theories and approaches on how to manage them. In this work, we propose a heuristic model to efficiently identify and analyze how corporate behavioral risks may influence project´s outcomes. The proposed model in this work, lays its foundations on four fundamental fields ((1) project management, (2) risk management, (3) corporate behavior, and (4) social network analysis), and will quantitatively measure four critical project social networks ((1) communication, (2) problem-solving, (3) advice, and (4) trust) that usually emerge as projects are being delivered, by applying the theory of social network analysis (SNA), more concretely, SNA centrality metrics. The proposed model in this work is supported with a case study to illustrate its implementation across a project lifecycle, and how organizations can benefit from its application.


2020 ◽  
Vol 36 (4) ◽  
pp. 439-452
Author(s):  
Riccardo Da Re ◽  
Sergio Pedini ◽  
Fabio Maria Santucci ◽  
Bianca Maria Torquati

This article illustrates the trust relationships among the members of the Brazilian Association of Fairtrade Farmers Organizations (BRFair), which is a second-level network of coffee-producing cooperatives. Representatives of 19 cooperatives were interviewed in 2018 to verify their opinions about the other associations regarding several aspects. Through software specific for social network analysis, the direction and level of trust among the various cooperatives were measured. One cooperative is recognized as the most active and trustworthy, while the other ones are followers and perform peripheric roles. Several improvements are possible, including improvement in the performance of this second-level network and strengthening of its bargaining role with the other actors of the value chain.


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