Social capital and farmers’ leadership in Iranian rural communities: application of social network analysis

Abstract

This study aimed to analyze the role of social capital and leadership in improving the adaptive capacity of Iranian pistachio farmers by using Social Network Analysis (SNA). The results indicate that the studied network is not a dense network, and there are few reciprocal and face-to-face relations among farmers. The findings also illustrate that in all cooperative links, there were no noticeable bridging links among the farmers and their tendency toward bonding links, indicating less bridging social capital at the three studied villages. The nature of relationships in social networks will improve if the quality of communication between individuals in a network and actors from other networks and villages is enhanced. This can increase the productivity of social networks and lead to higher quality resources, better support, development of useful information between networks and improvement in farmers’ adaptive capacity.

Full text

Social capital and farmers’leadership in Iranian rural
communities: application of social network analysis
Zohreh Moghfeli
a
, Mehdi Ghorbani
b
, Mohammad Reza Rezvani
a
,
Mohammad Amin Khorasani
a
, Hossein Azadi
c
and J€
urgen Scheffran
c
a
Faculty of Geography, University of Tehran, Tehran, Iran;
b
Faculty of Natural Resources,
University of Tehran, Karaj, Iran;
c
Research Group Climate Change and Security, Institute of
Geography, University of Hamburg, Hamburg, Germany
(Received 30 November 2020; revised 21 October 2021; final version received 22 October 2021)
This study aimed to analyze the role of social capital and leadership in improving
the adaptive capacity of Iranian pistachio farmers by using Social Network
Analysis (SNA). The results indicate that the studied network is not a dense
network, and there are few reciprocal and face-to-face relations among farmers.
The findings also illustrate that in all cooperative links, there were no noticeable
bridging links among the farmers and their tendency toward bonding links,
indicating less bridging social capital at the three studied villages. The nature of
relationships in social networks will improve if the quality of communication
between individuals in a network and actors from other networks and villages is
enhanced. This can increase the productivity of social networks and lead to higher
quality resources, better support, development of useful information between
networks and improvement in farmers’adaptive capacity.
Keywords: bridging links; farmers’network; quantitative and qualitative methods;
adaptive capacity; rural areas
1. Introduction
Social capital, in general, refers to the pathways by which individuals and institu-
tions engage in social action, exchange resources, and form (more or less) stable
links within the society’s structural fabric. According to Strobe et al. (2020),
Hanifan (1916) was the first person who used the term social capital and described
it as “goodwill, participation, compassion and social interaction between individu-
als forming a social unit”and then, Mair and Duffy (2018, 130) used social capital
to describe how individuals and social groups have access to cultural, human,
social and physical assets.
Agriculture is known as one of the main sources of employment and income for
rural communities (Groth et al. 2017;M

endez-L
opez et al. 2019), especially in devel-
oping countries. In the agricultural context, social capital is of crucial importance,
because it increases collective actions, reduces transaction costs, enhances transaction
abilities, promotes the dissemination of information, improves mutual trust among
local people (Zarafshani et al. 2012), and more importantly, helps farmers to deal with
risks. In fact, investing in social capital is one of the most effective strategies that can
Corresponding author. Email: mehghorbani@ut.ac.ir
ß2022 Newcastle University
Journal of Environmental Planning and Management, 2022
https://doi.org/10.1080/09640568.2021.2008329

be adopted by households to cope with and respond to shocks (Ng’ang’aet al. 2016;
Simatele, Binns, and Simatele 2012).
During the past decade, farming in Iran has experienced problems such as a reduc-
tion in rainfall, drought, water shortage, and land and soil instability, which make this
economic sector more vulnerable. These problems are more severe in the arid and
semi-arid regions, including central and eastern areas of Iran (Mesgararn et al. 2016).
These central regions, on the other hand, are among the most important areas to culti-
vate pistachio in Iran, which is one of the significant agricultural products exported to
many other countries each year (Tajabadipour, Afshari, and Hokmabadi 2011). Being
located in this area, along with suitable soil conditions, a long history of pistachio cul-
tivation, and acquaintance of local people with the ways of cultivation, Damghan is
considered as one of the most important pistachio production sites in Iran. Therefore,
due to the importance of pistachio cultivation for the livelihood of the villagers in cen-
tral Iran, improving the farmers’adaptive capacity, knowledge transfer, and social cap-
ital in their network is of crucial importance.
Adaptive capacity (defined by IPCC [2014]is“the ability of systems, institutions,
humans, and other organisms to adjust to potential damage, to take advantage of
opportunities, or to respond to consequences”, 118), has crucial importance in agricul-
ture. Adaptability to climate change is an emergent quality of social systems that is
constantly altered by social relationships (Dapilah, Nielsen, and Friis 2020). However,
achieving adaptive capacity is not easy. It requires the combination of various capitals,
especially social capital since it utilizes social interactions to ease the transfer of
resources between actors. When shocks and tensions increase vulnerability, these social
interactions can boost cooperative behavior and sharing of resources (Adger 2009). In
fact, network structure is known as a base for social capital which enhances a com-
munity’s adaptive capacity by reducing its vulnerability (Ingold 2017). In the agricul-
tural process, these social networks facilitate the spread of essential information on
new technologies, and more sustained management practices (Dapilah, Nielsen, and
Friis 2020).
According to Newman and Dale (2007), different types of social capital are created
by two different kinds of network ties: bonding and bridging ties. Bonding ties refer to
the strong links among people such as family members, neighbors, and friends who
share certain characteristics. Bridging ties, on the other hand, are known as those
through which rural actors engage with extension services and other local stakeholders
that aid community members to gain access to external information and resources
(Diehl 2020). A mix of bonding and bridging networks will result in the increased
resilience and capability to adapt (Newman and Dale 2007). Consequently, the exist-
ence of social networks among farmers, the enhancement of bridging social capital,
and the presence of those who make a link between inner and outer farmers provide
producers with access to information and innovation, which in turn, boosts their resili-
ence (Bodin and Prell 2011).
Farmers’efficiency is influenced by social capital in a variety of ways. Reduced
exchange costs, a lower rate of individuals’relocation, information sharing and innov-
ation, risk-taking, and enhancing products’quality are some of these methods.
Farmers’learning has improved as a result of leadership’s support for group decision-
making (McDonough 2000). It can also boost self-confidence through stimulating
imagination, creativity, and inventiveness. As a result, the importance of leadership in
a social network cannot be overstated.
2Z. Moghfeli et al.

There are some studies (e.g. Azhar, Malik, and Muzaffar 2019; Zaw and Lim
2017; Wilkin, Biggs, and Tatem 2019) in the context of society’s response to climate
disasters using SNA. Some other studies have also analyzed the role of social networks
in accepting agricultural innovations, such as those by Simon et al. (2021), Hermans
et al. (2017), Cadger et al. (2016), and Madureira et al. (2019). However, so far, no
study has investigated social capital and leadership among rural agricultural commun-
ities using SNA in Iran and/or other parts of the world. Given the importance of the
role of local leaders among Iran’s rural agricultural communities, the analysis of social
capital and leadership using the SNA has great importance toward providing important
knowledge, insights, and perspectives on the governance of agricultural systems and
local, national, regional, and international planning in Iran and other similar countries.
Thus, we used the results of many studies that applied network measures to assess
social capital. These findings are incorporated into our evaluation of the community’s
social capital, combining the network approach with the idea of social capital as a col-
lection of norms that support cooperation, collaboration, and leadership. This study
evaluates whether the social capital of society along with important leadership charac-
teristics, individually or in combination, can lead to success in collective action. It is
one of the few studies that helps understand the relationship between social capital and
leadership through the application of SNA. In addition, the findings of this study can
help researchers developing social capital concepts in the SNA to gain a better insight
into social capital and the factors that affect it. Therefore, this study has three objec-
tives to pursue: (1) to study different kinds of social capital in the pistachio producers’
network, (2) to explain leadership and identify key actors in this network, and (3) to
explain the interaction of social capital and adaptive capacity of the studied farmers.
2. Conceptual framework
2.1. Concepts and applications
Social network approaches posit that an individual’s behavior is influenced by rela-
tions, technical ties, and networks more than by the norms and attributes that an indi-
vidual possesses (Jyothi and Devarani 2019). Given the importance of networks for
farmers seeking knowledge, Marquez, Resinas, and Ruiz-Cort
es (2017) and Felician
(2020) emphasize that “not all social networks are created equally.”They stress the
need for distinguishing between ‘bonding’ties (interactions between family members,
friends, and neighbors) and ‘bridging’ties (reaching outside the community and offer-
ing access to various information and resources).
The frequency, complexity, and intensity of challenges in rural communities are
increasing, necessitating the need for effective rural leadership that is practical and
capable of managing diverse issues (Preston and Barnes 2017). The search for effect-
ive leadership in rural settings is undoubtedly the most difficult task confronting rural
communities. The majority of the literature focuses on improving the lives of urban
residents, neighborhoods, and communities (Ihrig et al. 2018). For rural communities,
there is a scarcity of studies on leadership and social capital. Leadership, people’s
commitment, and how they feel about their communities are all mentioned in the lit-
erature as important factors in a community’s ability to achieve its goals and outcomes
(World Health Organization [WHO]), 2020). Leadership, on the other hand, has been
considered as being critical in moving communities in the proper direction. The litera-
ture also implies that leadership and people’s attitudes about their communities are
Journal of Environmental Planning and Management 3

linked to rural towns’overall prosperity (Hewitt and Rumley 2020). Furthermore,
social capital is frequently cited as having a positive impact on people’s capacity to
identify themselves efficiently, and it is frequently cited, along with leadership, as
being critical for the initiation and maintenance of environmental conservation and
management at the rural community level (Hailey and Fazio-Brunson 2020).
2.2. Literature review
In this regard, some studies have been carried out on how different dimensions of
social capital help adaptive capacity. Dressel et al. (2020) stated that social capital
linking and bridging in the social network had a major impact on adaptive capacity.
When actors recognized the benefits of cooperating with lower levels and demon-
strated social trust in authorities and management levels higher up, they felt better pre-
pared to face future challenges in adaptive capability. According to Simes et al.
(2020), generalized trust, or trust in the majority of individuals, equals bridging social
capital, whereas particularized trust equals bonding social capital. The process of
diversification, according to Dapilah, Nielsen, and Friis (2020), is dependent on house-
hold engagement in diverse group activities and formal and informal social networks.
Their research also revealed that group activities and social networks can have nega-
tive consequences by promoting conflict, exclusion and marginalization among specific
community groups (Kamta and Scheffran 2021). Furthermore, few diversification
measures are incompatible with others, thus jeopardizing the community’s future adap-
tive capacity and resilience. According to Barnes et al. (2020), using the power of
social networks to reduce climate vulnerability and boost adaptive capacity, as well as
encouraging individual and group learning and carefully examining power dynamics,
could add significant value to existing approaches.
The social relationship between rangeland stakeholders was studied by Ghorbani
et al. (2015) using SNA and emphasizing trust and cooperation between them (as prin-
cipal dimensions of social capital). Their results showed that cohesion and social cap-
ital are poor. Relation stability and network balance are also poor, and trust and
cooperation ties are not suitably arranged. Therefore, enhancing trust and cooperation
among people increases social capital. In addition, examining the common dimensions
of social capital such as ‘informal insurance’(friends helping friends) and ‘social
learning’is important. Wuepper, Ayenew, and Sauer (2018) show that the entire social
network is hit by impacts such as droughts or floods and social learning is clearly very
important for adaptive capacity. Social learning is critical for facilitating and growing
community capacity, as demonstrated by Christmann et al. (2015). Since collective
action challenges necessitate the participation of various stakeholders with a range of
values and perceptions across scales (Biesbroek and Wals 2017), the focus is fre-
quently on collective learning rather than individual learning (Phuong et al. 2018).
According to van Valkengoed and Steg (2019), knowledge and experience, which are
commonly thought to be major hurdles to adaptation, were found to have just a minor
impact on adaptation. Experience and risk perception, flooding and hurricanes, and
preparatory behaviors have gained disproportionately more attention in research,
whereas other motivating factors, dangers, and adaptive behaviors have received less
attention. Some of the previous studies have also found positive and negative relation-
ships between social capital, knowledge flow, and agricultural creativity in smallholder
agricultural systems (Speranza 2013; Wossen et al. 2013; Chen, Wang, and Huang
4Z. Moghfeli et al.

2014). Relatively little research has been done on social capital analysis and leadership
in rural agricultural cooperatives. This is important because the improved infrastructure
and dynamics of social capital in small farming systems are recognized as a way to
have the potential to become aware of sustainable natural resource management poli-
cies and to improve performance and assistance in different parts of the world. In fact,
a comparative study of social networks illustrates how various sources of social capital
can influence agricultural knowledge networks and farmers’leadership in different
contexts. Therefore, in this study, an attempt has been made to identify a range of
openings for initiatives to improve funding, coordination, strengthening leadership
opportunities among smallholder farmers, increasing social capital, and improving the
leadership of pistachio fields using SNA. The findings of this study will provide evi-
dence, insights, and important perspectives on agricultural processes at home and
abroad and federal food security programs to improve leadership and increase pistachio
production among pistachio growers in Iran and other pistachio-producing countries.
Despite the fact that some research on the study of social capital and leadership among
rural agricultural communities has been conducted using SNA in various parts of the
world, no such research has been conducted in Iran. This is the first research that looks
at the role of social capital and leadership in enhancing the adaptive potential of
Iranian rural communities at the same time. In this way, to address this gap, this study
aimed to investigate social capital and leadership in three villages (Mehmandoost,
Zarrinabad, and Hossein Abad-Doolab) using the SNA method. Therefore, linked to
the main objective, this study attempts to answer the following questions:
1. What is the role of social networks and social capital of farmers in
adaptive capacity?
2. What is the leadership role in the farmers’social networks and adaptive capacity?
3. Material and methods
3.1. Study area
The study area includes three agricultural villages of Damankouh district, located in
the east of Damghan, Iran, with an area of 4,550 square kilometers and an approximate
population of 4,030. The total amount of area which is under cultivation in this district
is 2,800 hectares, and the approximate number of pistachio producers is 1,900. In this
study, three villages, including Mehmandoost, Zarrinabad, and Hossein Abade-Doolab,
located in the west of this district (Figure 1), were selected. There were several reasons
for choosing this region (Damghan city). Firstly, Damghan city is a significant region
in pistachio cultivation in Iran. Secondly, farmers in this area are dealing with various
problems such as pest control, water shortages, and drought. Moreover, villages
(Hossein Abade-Doolab, Zarrinabad, and Mehmandoost), which were selected ran-
domly, are all close in terms of geographical proximity and have relatively similar cli-
matic conditions. Finally, they have similar social, cultural, and traditional
characteristics. Pistachio cultivating areas and the total number of producers in the
studied villages are presented in Appendix 1 [online supplementary material]. It is also
necessary to mention that a large proportion of pistachio producers from the selected vil-
lages live in nearby cities (such as Damghan), and only their gardens are located in
those villages. Nonetheless, only producers who were permanent residents of the studied
villages were selected and assumed as the complete network (Appendix 1 [online
Journal of Environmental Planning and Management 5

supplementary material]. It is worth mentioning that in the current study, we did not
undertake sampling and used a full or complete network method. The complete network
of stakeholders included all pistachio producers in the study area. In other words, in this
research, all pistachio producers who are permanent residents in the villages of the study
area have been selected.
3.2. Social network analysis
We used SNA in this study to investigate farmers’social capital and cooperation and
to identify key actors in their network. Several studies have used this method to inves-
tigate social capital at the local community level (Bodin and Crona 2009; Cadger et al.
2016; Ghorbani and Azadi 2021). This method demonstrates various interactions
among various actors and is capable of virtualizing means of connection and informa-
tion flow (Sabot et al. 2017). This method not only quantifies network criteria at the
group and individual levels but also employs graphs to depict links between different
nodes. As a result, macro-level indices (Density and Reciprocity), subgroup level indi-
ces (E-I), and micro-level indices (Centrality Degree and Betweenness Centrality) from
social network analysis were used in this study (Appendix 2 [online supplementary
material]). Density was used to examine the cohesiveness and also to measure social
capital in the network. It is defined as the figure of existing ties divided by the number
of possible ties (Bodin and Crona 2009). Values of the network density vary between
0 and 1 (or 0–100%). Value 1 displays a very dense network whereby all of the nodes
Figure 1. Location of case study regions. (1) Location of the study area in Iran. (2) Location
of the study area in Semnan Province. (3) Location of study areas in Damghan cityz. (4)
Location of the studied sites in Damankouh area of Damghan city.
6Z. Moghfeli et al.

are connected, and 0 shows a scattered network (Hanneman and Riddle 2005). The
level of cohesion and network connectivity can be measured by using this index
(Ribeiro and Rodriguez 2017). Structural cohesion is a sociological notion for a suit-
able formal definition and assessment of social group cohesion. It is defined as the
smallest number of actors in a social network who must be eliminated in order to dis-
connect the group (Kalolo et al. 2019). Network connection, on the other hand, refers
to the complex process of linking various portions of a network to one another
(Espinosa et al. 2020).
Furthermore, the reciprocity index was used to indicate the fraction of reciprocated
ties and demonstrate mutuality and reciprocity of relations among actors (Fujiyama
2019). This index, which is known as a key element of social networks that encour-
ages actors to make contributions for equal and responsible input, is one of the mecha-
nisms that leads to social capital (Br
anyi and J
ozsa 2015). In other words, social
capital is measurable by social network analysis via the use of this index in small
groups of networks which also motivates and facilitates knowledge exchange between
people in the social network (Cherni 2016).
Bridging ties are defined as the ties that connect various subgroups in which acces-
sibility to outside resources of numerous kinds is provided and are beneficial not only
in initiating or supporting collective actions but also in providing opportunities to gain
access to information and knowledge (Fisher 2013). In order to discover whether there
are external relationships between producers, in addition to internal relationships,
and measure bridging ties in their network, the External-Internal (E-I) index, which
calculates the scale of internal (bonding) and external (bridging) links (Sylvere and
Emmanuel 2016) and measures the variety of an individual’s network based on a
chosen category (Mittelmeier et al. 2016), was used. This index ranges from 1, illus-
trating that the stakeholders interact only with members of their own group, to 1, signi-
fying the stakeholders interact with others outside of their own group, and zero means
that links are divided equitably (Kharanagh, Banihabib, and Javadi 2020).
In social network analysis, centrality reflects the importance of an actor’s ideas,
credibility, power, and acceptance. If some specific actors in a network have a signifi-
cantly larger number of relationships than others, it means that those specific actors
have more centrality in the network (Bodin and Crona 2008). It is a suitable index to
identify key individuals. Therefore, based on the findings by Bodin and Crona (2008),
in this study, Degree Centrality and Betweenness index were utilized. Betweenness is
the metric that ranks actors on the number of times they act as a bridge along the
shortest path between the two actors (Chaudhury et al. 2017). Degree Centrality evalu-
ates node involvement in a network and is defined by the number of nodes that a focal
node is connected to (Ahajjam, Haddad, and Badir 2018). Consequently, how to com-
municate directly with others can be considered as power (King 2000). In-degree and
Out-degree are two factors of Degree Centrality (Lilly, Tah, and Kurul 2017). The dis-
tinction between In-degree and Out-degree usually reflects the social dynamism of the
network (Bodin and Crona 2008). Each actor or node in a social network is assigned a
numerical value that indicates their social value via a social capital measurement.
When such a value is purely determined by network structure, the social capital value
function is a sort of network centrality measure (Ghaffar and Hurley 2020). Such cen-
trality measurements assign values to nodes in a network based on their ‘importance’,
with different definitions of importance used. Closeness centrality, which measures an
individual’s average distance from all other nodes in the network, and Betweenness
Journal of Environmental Planning and Management 7

Centrality, which measures the extent to which a node lies on the shortest paths
between other pairs of nodes in the network, are the most notable measures in the con-
text of social capital (Oldham et al. 2019).
3.3. Data collection and analysis
In this study, a total of 210 farmers (66 farmers in Mehmandoost, 70 farmers in
Zarrinabad, and 74 farmers in Hossein Abad-Doolab) were investigated as a complete
network in 2016. To begin with, the names of these farmers were compiled by polling
local knowledgeable people in each village. Indeed, during this phase, we defined the
social network boundaries and bounded our network (Cadger et al. 2016), which con-
stitutes the first phase in social network analysis.
Based on our observations in the study area and the opinions of local knowledge-
able people, we recognized that there are generally four types of relationships among
pistachio producers in the villages studied. In fact, producers collaborate with others
for irrigation, agricultural equipment exchange, product marketing and sales, and pest
control. In the irrigation section, the presence of people who manage the irrigation sys-
tem and determine specific times for garden irrigation can shape the irrigation relation-
ships in every village. Furthermore, in the villages studied, some of the producers do
not have expensive agricultural equipment. Thus, they can rent from producers who
have that equipment. These actions result in the formation of relationships in the
exchange of agricultural equipment. Producers have contacts with others to identify the
price of products in markets (especially in Damghan city) and decide whether it is
more advantageous to sell fresh pistachios during the selling season (in summer) or
dry, store, and sell them as dried pistachios at other times. Regarding the presence of
some insects and pests in gardens in the study area, one of the most important relation-
ships that exist between producers is to control and eradicate pests. For instance, pro-
ducers consult with their peers to determine which pesticide is more effective or when
is the best time to use it to eliminate pests. Thus, we attempted to investigate these
relationships in every village. Furthermore, it should be noted that the collaborative
links in garden irrigation among villages were not explored between villages, owing to
the fact that producers’relationships in this regard are within the villages and they
have no ties with producers from other villages.
In the following phase, two questionnaires were designed to investigate the men-
tioned groups’cooperation. The first one focused on every single village, and each
farmer was asked to number each of the four presented linkages (irrigation, agricultural
equipment exchange, marketing and sales, and pest control) that they have with other
producers in their village from 0 to 3. 0 represents no connection, while 3 represents
the strongest connection they have with others. The second questionnaire was designed
to investigate the relationship between all producers, and it included the list of farmers
from other villages as well as a list of producers from each village. Thus, farmers
were asked to specify farmers who lived outside of their village and had relationships
with them, and then assign the numbers (0 to 3) for each of the three presented links
(agricultural equipment exchange, marketing and selling, and pest control). Other
information, such as farmers’age and size of their farms, was also obtained during the
interviews (Appendices 6–8 [online supplementary material]).
Finally, survey data were collected and inserted into Excel as two-dimensional
matrices for each link and village. These matrices were then imported into UCINET
8Z. Moghfeli et al.

software for analysis. This software is a useful app to visualize and perform statistical
analysis on network structure. It is mostly used in the social sciences to analyze socio-
metric survey data. The program features a large number of matrices for characterizing
social networks, centrality measures, role analysis, and positions of nodes within net-
works, finding cohesive subgroups (clustering), elementary graph theory, and permuta-
tion-based statistical analysis. We were able to calculate all social network analysis
indices, including Density, Reciprocity, E-I, and Degree Centrality, using this software,
which also draws network data as a graph.
4. Results
The density index is provided in Table 1 in which the amounts of this index, among
farmers in Mehmandoost, Zarrinabad, and Hosseinabad in the trade of farming instru-
ments, irrigation, marketing, and pest control, have been very different (between 2.6%
and 13.3%). These findings suggest that bond ties in these three villages are found to
be low. Based on the result of the density index in the network studied, the decline in
the social bonding capital of the pistachio producers’network in the villages studied
resulted in a low level of participation among pistachio producers.
Farmers in the villages studied have more relationships with one another, and as a
result, more of those indexes are in pest control rather than other links, implying that
farmers in the study area are dealing with a variety of pest-related problems (e.g.
Agonoscena pistaciae).
In Table 1, the results of analyzing the reciprocity index are presented.
Accordingly, the result of the reciprocity index (marketing, farming instruments, irriga-
tion, and pest control) in the villages studied is at a low level (between 2.83% and
11.6%). This index could be threatening farmers’knowledge transfer.
After combining the matrices of all the studied links by the Boolean Combination
index in the UCINET software, the density index was analyzed (Table 2). The result
indicates that in these three areas, the amount of density index was between 19% and
Table 1. Density and reciprocity index in pistachio producers’network.
Village
Number
of producers Cooperative links Density (%) Reciprocity (%)
Mehmandoost 66 Exchanging
farming tools
6.3 0
Irrigation 2.8 0
Marketing and sales 5.9 2.8
Pest control 6.3 7.5
Zarrinabad 70 Exchanging
farming tools
7.3 7.3
Irrigation 7.8 4.1
Marketing and selling 12.2 8.8
Pest control 13.3 11.6
Hossein
Abade-Doolab
74 Exchanging
farming tools
7.6 7
Irrigation 6.3 9.6
Marketing and sales 7.1 11.3
Pest control 9.1 11
Journal of Environmental Planning and Management 9

27%. These values display low density rates in the network of pistachio farmers when
engaging in agricultural actions. In these villages, social capital in agricultural acts is
not included in a favorable condition concerning the direct relationships between the
level of network density and social capital.
In this paper, the degree of the E-I index in producers’bridging social capital was
explored in relation to the importance of bridging ties. In addition, the three villages
were explored for the need to employ information resources, innovation in agricultural
tool sharing, marketing, and pest management with the goal of enhancing pistachio
output, bridging linkages, and the E-I index. Table 3 indicates bonding and bridging
links of proficiencies in the four studied cooperative links. Accordingly, in the
exchange of agricultural tools, inner links (bonding links) were about 91%, while
bridging links were around 8%. Therefore, both bridging social capital and adaptive
capacity are under threat.
Table 3 also shows that 82% of the linkages in the cooperative marketing among
the percipiency were bonding and 17% were bridging. This finding signifies that the
producers established less cooperation in marketing and product sales with producers
outside their villages. Accordingly, both bridging social capital and their access to
information resources in product sales and their prices are restricted. The negative
level of the E-I index (64%) confirms that there were a larger number of bonding
links among gardeners in comparison with bridging links, which shows that proficien-
cies tend to keep inner-group cohesion. It can be said that fewer bridging links were
created among gardeners from these three villages to take part in pest control (85% in
the villages and 14% among the villages). The negative level of the E-I index, in add-
ition, depicted that bonding links were more than bridging links. To put it another
way, this shows gardeners’tendency toward consistency maintenance within groups
and the low level of bridging social capital in the three villages studied. Due to the
lack of gardeners’participation with other villages, their access to information resour-
ces in pest control will be limited, so the result is the decline of adaptive capacity to
cope with pistachio tree diseases.
Table 4 indicates the results of bonding and bridging links and the E-I index
among producers in each village studied, who have cooperative connections for the
trade of agricultural equipment, drainage, marketing, and pest management. It can be
said that among most of the investigated cooperative links in Mehmandoost, Hossein
Abad-Doolab, and Zarrinabad, farmers tend to establish a link with their local people
and try to maintain bonding links. The negative level of the E-I index in cooperative
links further supports this idea. They have a tendency to keep bonding consistency
in all cooperative links generally, and regarding the negative level of the E-I index
in all studied villages, a low level of bridging social capital and proficiency links
is observable.
Table 2. Index of density in the combined matrix of participatory connections in the network
of producers.
Village Number of producers Density (%)
Mehmandoost 66 19
Zarrinabad 70 27
Hossein Abade-Doolab 74 25
10 Z. Moghfeli et al.

According to the results in cooperative links of farming tools exchange, some
actors in Mehmandoost and Hossein Abade-Doolab (with 1 in E-I) had the highest
level of this index among all pistachio proficiencies in all the villages studied. They
established links with outer gardeners to exchange farming tools (Appendices 9–11
[online supplementary material]) (it is worth mentioning that the abbreviated names in
each figure, are the names that the current study assigned to the individual partici-
pants). On the contrary, there were some producers (Appendices 3–5 [online supple-
mentary material]) who had the lowest E-I index (1). The lowest level of this index
signifies that they tend to have inner cooperative links in the exchange of farming
tools. In fact, they shared their links and trust with those who were in the same group
with them in their own village. Table 3 indicates bonding and bridging links for profi-
ciencies in four studied cooperative links. Accordingly, in farming tool exchange, 91%
are within groups, and 8% are outside groups. The negative level of the E-I index con-
firms the fact that inner links (bonding links) are more than bridging links. Therefore,
both bridging social capital and adaptive capacity are under threat.
Some actors take the opportunity to have more contact, while some of them may
be in a position to control information transfer among groups. These central actors,
referred to as leader farmers, are provided with access to information and opportunities
to spread innovations, thanks to their position. The leading farmers have essential roles
in agriculture. Some of these roles are accelerating the spread of or blocking innov-
ation and impressing other people. Not only is the identification of key farmers or
leading farmers in the network important, but also their role in the information transfer
between the producers and resources is indispensable. The identification of central
actors who have more power in controlling the network is possible by using an
Table 3. Internal and external links and E-I index in all producers’network.
Cooperative links Index Number (%)
Farming tool exchange Internal links 1,958 91
External links 172 8
E-I index 1,786 83
Marketing and selling Internal links 2,266 82
External links 488 17
E-I index 1,776 64
Pest control Internal links 2,534 85
External links 420 14
E-I index 2,114 71
Table 4. Internal and external links and E-I index in producers’network for every village.
Village Cooperative links Internal links External links Total E-I index
Mehmandoost Farming tool exchange 540 40 580 0.86
Marketing and sales 494 117 611 61
Pest control 504 115 619 0.62
Zarrinabad Farming tool exchange 654 74 728 0.79
Marketing and sales 1,082 234 1,316 0.64
Pest control 1,146 191 1,337 0.71
Hossein Abade-Doolab Farming tool exchange 764 58 822 0.85
Marketing and sales 690 137 827 0.66
Pest control 884 114 998 0.77
Journal of Environmental Planning and Management 11

analysis of social networks. In this study, to identify these key actors in the pistachio
farmers’network, we used Centrality Degree indices, including In-degree, Out-degree,
and Betweenness Centrality. The matrices of the four links studied were combined on
the basis of the UCINET program Boolean Combination index in matrix algebra.
According to the results, in Mehmandoost, there were some actors who had a high
level of those centrality degree indices. By obtaining a high level of Out-degree
Centrality, for example, they have the highest amount of social influence on the
studied network and have a high level of Betweenness. They will be recognized as a
contributing factor in the development of pistachio production and cooperation through
establishing novel relationships. Considering Appendices 12–14 [online supplementary
material], based on which mixed matrix model of cooperative links is presented, and
the size of each node adjusted according to In-degree, Out-degree, and Betweenness
Centrality of each actor, it can be stated that No-Am, Mo-Ami, Ma-Ja, and At-Mo
actors are determined as key actors that have the most social influence, and Ho-Ag
actor is known as an isolated actor. Thus, it is essential to draw attention to develop
cooperation among farmers to increase their adaptive capacity and productivity.
In Zarrinabad, the results of In-degree, Out-degree, and Betweenness Centrality
show that three actors scored between 55.07 and 75.36 in In-degree Centrality and
between 48.37 and 69.56 in Out-degree Centrality. This demonstrates that they have
the highest level of authority, social popularity, and influence in this village. These
actors with the pivotal role and social power in the network of pistachio proficiencies
have a contributing role in managing gardeners’cooperation with the aim of pistachio
production. With regard to the combined matrix of participatory links, it can be said
that the four actors have the highest intermediation and control power, respectively
(scoring between 3.03 and 8.56 (Appendices 15–17 [online supplementary material]).
The results of the above indices in Hossein Abade-Doolab show that in a combined
matrix of four actors, In-degree Centrality ranged between 45.20 and 61.64. This
means that they play a key role in the production and have a social influence upon all
cooperative links. Furthermore, the combined matrix of the four actors shows that for
Out-degree Centrality (between 41.09 and 68.49), these people have a significant
impact on the distribution of participatory links among pistachio proficiencies. In add-
ition to authority, popularity, and social influence, they were able to control participa-
tory links in the network and affect the flow of information resources. The role of
these actors in the producers’network is shown in Appendices 18–20 [online supple-
mentary material]. The size of each node represents the In-degree, Out-degree, and
Betweenness Centrality of proficiencies of this village.
5. Discussion
5.1. Social network and social capital of farmers
According to the results, the social capital among the studied farmers is not high. This
may be due to insufficient production of products, lack of timely and adequate social
learning, farmers’distrust of other farmers and even government authorities, reduced
self-sufficiency, and lack of adequate legal support and assistance, such as agricultural
insurance. In addition, the high costs of agricultural machinery and inputs, among
other factors, affect the social capital of farmers. Furthermore, social capital in Iran’s
agricultural sector is not high due to limited physical resources, talent, manpower, and
limited development opportunities. Other reasons for the lack of sufficient social
12 Z. Moghfeli et al.

capital include the high risk of agricultural production, the high cost of product main-
tenance, lack of value of Iranian currency in comparison to foreign currency credits,
lack of an development of conversion industries, and lack of incentive system and
profitability in other sectors, especially services. To enhance social capital in farmer
communities, special attention must be paid to trust, cooperation, sense of community,
culture, and tradition. All five dimensions are important in agricultural and rural devel-
opment because they influence how people relate to one another, organize themselves,
and interact for development. An effective agricultural information flow is also essen-
tial for improving social capital. Sharing, exchanging, transmitting, and disseminating
agrarian information among agricultural stakeholders enhance this flow. Therefore,
effective and appropriate information networks should be made open in order to
increase the flow of awareness. To that end, it is preferable to provide appropriate con-
tact networks, such as increased communication between domestic international
research organizations and international agents, in order to enhance the transfer of
information and achieve high levels of sustainability.
For this purpose, it is better to have appropriate communication channels for more
communication between researchers, leading farmers or local leaders, and others (in
other pistachio-growing regions of Iran and even the world), so as to improve the flow
of knowledge and achieve high levels of adaptive capacity. The most significant
vehicle for information and knowledge is a social network (Fong 2003) because it
facilitates learning through the transfer of knowledge among network members
(Inkpen and Tsang 2005) and reduces conflict, which is important to increase farmers’
production (Balogun, Yusuf, and Oloniniyi 2017). Furthermore, it is known as an
important factor that develops an understanding of relationships within the community.
The occurrence of stakeholder participation in creating and sharing knowledge among
farmers’social networks is determined by the existence of social capital in farmers’
social networks.
Based on the results, the level of density and reciprocity in the studied network was
low, which revealed the existence of low mutual, reciprocal, and face-to-face interac-
tions among farmers. In fact, a small number of farmers rely on others for the exchange
of farming tools, irrigation, marketing, and receipt of information about the price of
products, and where problems exist, they rely on their own experience. These major
factors result in low contribution, cooperation, and bonding social capital among farm-
ers. On the contrary, dense and reciprocal ties help farmers to expand their network. By
making these relationships and mutual cooperation, social capital among farmers will
increase which, in turn, is essential to avoid economic damage. As Michelini (2013)
states, lack of local contribution has an adverse impact on the regional economy, as it
increases social rejection and boosts the vulnerability of people who suffer from a lack
of capital and skill. This will lead to a reduction in social capital.
As the results showed, the network studied is not a dense network, and there are
no face-to-face relationships among farmers. However, interactions, especially daily
interactions, can lead to the connection of social wealth and the development of social
learning at the group level. Therefore, to increase social capital and adaptive capacity,
national, local, and international cooperation between producers, planners, politicians,
and even different governments must be improved. Therefore, transferring new find-
ings to local leaders and leading farmers in a region through training courses, various
webinars, and exhibitions at the national, regional, and international levels with the
help of various organizations, in order to increase knowledge and transfer much
Journal of Environmental Planning and Management 13

information, are of high importance. Our findings could be useful to improve leader-
ship and increase pistachio production in Iran and other similar countries by increasing
evidence, insights, and important perspectives on the leadership of modern farming
methods, and food security at state, regional, and international levels. The findings
from this study are in line with the results of some other similar research (e.g. Udom
et al. 2017; Ambrose and Mohammed 2020). According to a study by Udom et al.
(2017), climate crises affect local agricultural security and sustainable lifestyles.
Following the increase in vulnerability due to climate change in a community, the sen-
sitivity of social networks, agricultural sectors, and social capital increases. As a result,
the social capital of that community (for example, local cultural values and ideology)
combined with local knowledge and skills can increase the capacity for adaptation and
reduce the vulnerability of the agricultural sector. All the communities were found by
Ambrose and Mohammed (2020) to possess a moderate capacity to cope with climate
change effects. This is owing to their wealth accumulation, access to farm inputs, irri-
gation potential, literacy level, and infrastructural and institutional availability. Salam
et al. (2021) found that while households’susceptibility differs depending on their
livelihood assets (human, social, financial, physical, and natural), their capacity follows
a similar pattern. Vulnerability and adaptive capacity were found to have a substantial
negative relationship, whereas this study discovered high relationships between social
and human capital, human and financial capital, social and financial capital, and phys-
ical and natural capital.
The outcome illustrates that in all cooperative links and all the villages studied,
there were no noticeable bridging links among the farmers and their tendency toward
bonding links, indicating less bridging social capital. Less cooperation with farmers
who are in other villages leads to low availability of innovative and informational
resources and new technologies in pistachio production, which in turn leads to a
decrease in adaptive capacity while farmers face challenges of pistachio cultivation.
This result is consistent with the study by Seitova and Stamkulova (2017), which con-
firms that weak ties are important to access new knowledge among farmers and shows
that the role of social networks in this process is noticeable. In this regard, Micheels
and Nolan (2016) state that being able to obtain and assimilate knowledge about new
technologies and having the ability to apply these technologies so as to resolve differ-
ent problems on farms occur when farmers have a higher level of bridging social cap-
ital. Furthermore, as Cofr
e-Bravo, Klerkx, and Engler (2019) indicated, frost damage,
drought, and fires are some calamitous events about which farmers are likely to
receive information on the way they should be dealt with by linking and bridging
social capital via open networks.
Separated parts of the network can be connected by network ties and bridging ties.
Actors who can connect the non-redundant sources of knowledge and information
together are people with broker roles. Those actors have the opportunity to access the
external sources of information that are provided by bridging structural holes (Fritsch
and Kauffeld-Monz 2010). Intellectual leaders or organizational entrepreneurs are not
necessarily people who are at the top or in the top positions of the organizational hier-
archy, but these people are often those who act around the social groups and within
the social boundaries. Through their brokering position, they are able to gather infor-
mation and communicate with different groups and, by virtue of their peripheral pos-
ition, they can introduce actors to new social groups. This advantage is due to their
structural position in the social network and is often regarded as a social capital
14 Z. Moghfeli et al.

(Bodin and Prell 2011). Knowing people with a high number of bridging links in the
farmers’network would help us to identify people who can play a key role in access-
ing new knowledge and recourses from outside. Accordingly, in farming tools
exchange, only Ab-Ak in Mehmandoost and Ho-Ka in Hossein Abade-Doolab have
the highest level of E-I index among all the pistachio proficiencies. Mo-Va in
Mehmandoost and Ham-EF and Ho-Kaz actors in Hossein Abade-Doolab obtained the
highest score for E-I in marketing and selling pistachio. No particular person with the
role of bridging is seen in pest control. However, the presence of people who can
make a lot of links with actors from other networks and villages will increase relation-
ships, enhance productivity, and develop the ability to gain support, resources, and
information from networks. These results are in line with the findings obtained by
Pratiwi and Suzuki (2017) who have confirmed that these broker actors in the farmers’
network have a key role in bringing information into the farmers’network.
5.2. Leadership in farmers’network
Leaders or influential actors are required to generate social capital in order to achieve
economic development and a harmonious society, as well as to generate a flow of ben-
efits (Bodin and Crona 2009). These actors have a higher number of social ties com-
pared to others, and since they are located well within the network, primarily in a
central position, they can promote collective actions and facilitate the distribution of
novel ideas and practices. These actors can link various boundaries by occupying this
central position and utilizing a large number of social ties (Bodin 2017). Social net-
works are known as a tool that enables leaders to succeed in spreading ideas, support-
ing flows, and ultimately moving the system toward a positive change, and therefore,
the position of leaders in social networks becomes important. Thus, the position of
people in the network, as well as the status of being in the center of the network and
being surrounded by others, reflects the concept of social influence and social power
(Bodin and Prell 2011). Therefore, if a key member of the community who is well-
positioned in the social network can be persuaded to accept a new belief or experience,
then the social influence resulting from that person’s strong links with others can lead
to the dissemination of new ideas and also to the process of accepting new terms
(Bodin and Prell 2011). Measuring the number of relationships that an actor has
received to collaborate with other people is one of the useful methods for calculating
influence in the social network. These types of connections are known as Degree
Centrality (Bodin and Prell 2011). Based on Hauck, Schmidt, and Werner (2016),
these indices are used to not only identify key stakeholders but also to recognize their
relationships with regard to information, regulation, and social pressure.
According to the findings, we found that in each village there are actors with a
high level of In-degree Centrality in the pistachio producers’network. This means that
these people are more popular than others in the studied network. Furthermore, they
are farmers who are regarded as sources of advice, help, or information about irriga-
tion of the pistachio gardens, market conditions, exchange of farming equipment, and
most importantly, pest control. Furthermore, these farmers have the highest level of
Out-degree Centrality, which demonstrates that they are a source of help and advice
for others. Based on the highest score in Betweenness Centrality, which measures the
potential of an actor to control the flow of information, it can be proved that the iden-
tified farmers have an essential role in the transmission and flow of information in the
Journal of Environmental Planning and Management 15

pistachio producers’network. As intermediary actors, they connect different parts of
this network and facilitate an agreement that is based on public consent among the
various farmers. These farmers who can also build bridging links between others play
an important role in bringing information and innovation to the network (Bodin and
Prell 2011). They are well-known as popular advisers who share knowledge with farm-
ers and enhance social learning within the network of pistachio producers (Nyantakyi-
Frimpong, Matous, and Isaac 2019; Mittal, Padmaja, and Ajay 2018). Moreover, as
gatekeepers for the flow of information which is received from extension agencies,
they can translate the knowledge into a more understandable form for the community
(Taylor and Bhasme 2018). Accordingly, in the studied farmers’network, the identi-
fied farmers are regarded as local powers and key people in pistachio production, and
they play a central role in the transfer of pistachio production knowledge, participating
in management, and adaptive capacity expansion. In fact, these actors are people to
whom other farmers turn when they need a solution to a problem or information. As a
result, they play an important role in cooperative actions such as informing other farm-
ers about various climatic shocks and their impact on production by receiving and
transmitting relevant information from agencies and other possible outside networks.
5.3. Framers’social capital and adaptive capacity
Adger (2009) illustrates that adaptive capacity is important in communities whose live-
lihood depends on natural resources. He also argues that the adaptive capacity of soci-
eties is connected to the ability of society to act collectively. For a social and
geographic demonstration of vulnerability and dealing with risks, the social capital of
individuals and groups is essential (Adger 2009).
Basically, adaptability requires (1) an inflow of ecological knowledge, which
shows bridging social capital, (2) an active decision-making process based on prevail-
ing ecological knowledge, which shows bonding social capital, and (3) a high level of
rule compliance among users, which refers to the bonding of social capital (Bodin and
Prell 2011).
In the villages studied, based on the low density index, it can be declared that net-
work closure and as a result, farmers’bonding social capital are at a low level, which
limits collective action in the pistachio producers’network. In this regard, based on
the low level of the E-I index, it can be proven that bridging the social capital of the
studied network is low, which threatens the flow of external information into the pista-
chio producers’network and will reduce farmers’adaptive capacity because, based on
Bodin and Prell (2011), in order to increase adaptation and achieve adaptive manage-
ment in the farmers’network, negotiated knowledge should be achieved. For this pur-
pose, social capital bonding and bridging could improve.
The increase in social capital (especially bridging social capital) not only enhances
the efficiency of the farmers’promotion but also facilitates the transfer of information
and cooperation among them. It also prevents the community from fragmentation and
vulnerability. Moreover, it enables access to information, financial, and supporting
resources beyond social limitations. This factor itself increases the efficiency of farm-
ers and facilitates the transfer of information and collaboration. It also provides access
to outer information on production and increases acceptance of agricultural innovation
and technology, which enhances production.
16 Z. Moghfeli et al.

Agricultural knowledge is transmitted through social contacts; therefore farmers’
ability to gather information is determined by their relationships with agricultural
informants and network structures within their local areas. Peer advice networks are
vital for supporting knowledge-gathering and relationship networks. The purpose of
this work is to contribute to a better understanding of the function of social capital in
agricultural and rural development, as well as to boost adaptive capacity. Its goal is to
understand what social capital means in more practical terms for rural people and
farmers, and how it functions to promote adaptability in agricultural and rural contexts.
Individuals in communities with positive social relationships are more inclined to pool
their resources and work together to achieve a common objective. As a result, high
levels of social capital boost the size and quality of social networks, as well as views,
attitudes, and the amount and quality of information available. Strong social ties, for
example, can lead to improved access to knowledge and information, as well as finan-
cial resources. It could have a positive effect on improving their adaptive capacity by
changing the attitude of farmers. In fact, linking and bridging social capital in the sys-
tem have significant impacts on farmers’attitudes. By cooperating with the following
levels and expressing social trust in each other at the network level and even outside a
network, actors can be effective in changing each other’s attitudes by transferring their
knowledge and experiences. This study concludes that self-efficacy and social net-
works play important roles in farmers’intention and attitude for adaptive capacity.
Farmers with higher non-cognitive skills, including perceived self-efficacy, are more
likely to improve adaptive capacity. In fact, programs and policies designed to elevate
farmers’self-efficacy may be helpful for increasing conservation behavior and improv-
ing adaptive capacity.
These findings are in line with those of Balogun, Yusuf, and Oloniniyi (2017),
Ayanlere, Omotesho, and Muhammad-Lawal (2018), and Gayatri, Sumarjono, and
Satmoko (2018). Less social capital among the producers can lead to a challenge for
pistachio production, may damage farmers’income, and may reduce their access to an
external source of information. It will also have a negative effect on other capitals in
the region, increase the volatility of the network of pistachio growers, and increase
social rejection and insecurity of gardeners while confronting some problems such as
water scarcity, drought, fluctuation in product prices, and disease in pistachio trees,
which in turn reduce their ability to adapt.
6. Conclusion
As evident from our analysis, the studied network is not a dense network, and there
are few reciprocal and face-to-face relations among farmers while it is proven that
reciprocal relations and everyday interactions can lead to bonding social capital,
social learning, and increased production. Furthermore, the result shows that bridg-
ing social capital among the villages studied is low, which in turn limits the extent
of information and innovations that come into the network. Moreover, there were
some farmers with a key mediation role who are able to monitor the flow of infor-
mation in the network of pistachio producers and have the ability to gain public
satisfaction in utilizing resources. Those actors have a key role in improving adap-
tive capacity so that they can gain new agricultural knowledge and innovation from
outside and spread this among farmers. It is also essential to mention that the
studied network is a fragmented network that does not have enough bridging links,
Journal of Environmental Planning and Management 17

suffers from a low level of social capital bonding and bridging, and has issues with
adaptation. Hence, some actions should be taken to improve farmers’social capital
bonding and bridging in order to increase their adaptive capacity. It is pertinently
suggestible that building local cooperation will increase the cooperation of garden-
ers (especially those who have less access to external information, awareness, and
decision-making in the process of pistachio production).
Furthermore, preparing a situation in which farmers can negotiate their problems
and demands about the pistachio cultivation process with more knowledgeable farmers
who play a key role in their network, with agricultural researchers, and engineers, will
help them improve their bonding links and make their network more coherent. It will
further improve their bridging links with farmers who are outside their villages, hence
boosting farmers’social capital. In this way, farmers will be able to receive more use-
ful information about market status, ways of controlling dangerous pests, and new
ways of watering gardens, which are useful when facing water shortages. These
actions will improve the knowledge flow in the pistachio producers’network and con-
sequently, their adaptive capacity against problems such as water scarcity, drought,
pests, and unstable market status. In this regard, governmental or non-governmental
institutions are known as significant external services that can boost pistachio farmers’
awareness and improve their information by means of workshops and classes about the
ways of coping with environmental, climatic, and economic shocks. In addition, it is
suggested that through such classes and further training, pistachio farmers become
more informed about the benefits of boosting cooperative actions and increasing social
capital in their network, especially in dealing with various present and potential prob-
lems that they encounter. It is also important to mention that this study faced some
limitations including difficulty in finding all the farmers who were resident in the vil-
lages studied, lack of study of permanent residents in the village, spending a lot of
time interviewing all of them, and analyzing the vast amount of data gathered, which
should be considered in future studies. According to the absence of similar studies on
the relationships of pistachio producers in the study area with formal institutions and
organizations such as banks, agricultural institutions, and agricultural engineers, it is
recommended that future studies consider these relationships. This form of study, in
addition to investigating bridging and linking social capital of pistachio producers,
would lead to some suggestions to solve some problems of farmers that are caused by
the lack of interrelationships with formal institutions.
In order to enhance the sharing of knowledge for efficient and sustainable agricul-
tural management activities, understanding the function of the farm network is essen-
tial for effective agricultural production interventions. The presence of influential
farmers and local leaders is also important to help transmit new findings to the local
community in order to achieve goals and strategies and disseminate information.
However, networks with few leaders with a high focus on information can have
adverse effects on learning. As a result, knowledge and information will be reduced,
and other actors will not have access to multiple sources of information. The main
implication of this study’s findings highlights the importance of correct ties. In order
to help promote learning and mitigate the possibility of transmitting obsolete know-
ledge, agricultural informants acting as ‘bridging links’should ideally be more seas-
oned and knowledgeable than the advisor. The consequences of these developments
are significant in terms of agricultural adaptation and management in a context where
agricultural development is influenced by environmental and other socio-political
18 Z. Moghfeli et al.

challenges. Understanding how expertise is transferred within a society and how activ-
ities are applied will have a significant influence on the success of development agen-
cies that are centered on agricultural development.
If extension services approach locally networked farmers who are the link between
these organizations and the rest of the population, they serve as ’hubs’of information.
In funding decisions, politicians and program administrators should be willing to sup-
port international cooperation. Our findings provide evidence, insights, and important
perspectives on the domestic and international agricultural systems, governance, and
federal food security programs to improve leadership and increase pistachio production
among pistachio growers in Iran and other pistachio producing countries.
Indeed, decades earlier, the importance of studying social interactions and social
systems to explain the diffusion of cultural knowledge was illustrated in the anthropo-
logical literature, but without directly utilizing SNA. SNA has recently begun to be
used by researchers involved in the transmission and dissemination of local informa-
tion to map the pathways of transmission of intra-cultural and intercultural knowledge.
Our exploration has brought some big observations. Second, information transmission
patterns have been discovered to be much more nuanced than previously predicted,
and to extend beyond the definitions or social classes commonly used in studies of
knowledge transmission, such as kin-based groups. A second core result of applying
SNA to the local knowledge transfer analysis relates to our knowledge of how people
choose sources of knowledge and pursue foreign intelligence. To transfer new know-
ledge, the social international organizations such as FAO, enable access to information,
financial, and supporting resources beyond social limitations. This factor itself
increases the efficiency of farmers and facilitates the transfer of information and col-
laboration at the international level.
Despite the importance of social networks in disaster resilience and recovery, gov-
ernment programs do not place enough focus on them. Policies emphasize linking
social networks (i.e. governments’relationships with foreign states, donors, and
others), but household bonding networks (relationships with immediate family mem-
bers and relatives), bridging networks (relationships with neighbors and friends), and
local linking relationships (particularly with NGOs and local governments) are large.
This study argues that the government should review existing policies for disaster
management, assistance to local communities, better use of local social capital, and
leadership potential.
Overall, the findings presented in this paper show that social networks provide a
broad view of current SNA applications in a selection of studies, case reports, and ana-
lytical and global methods through the development of leadership features.
Furthermore, social capital has its limitations, and the social capital innovation rela-
tionship may have a decreasing return structure. The primary takeaway from these data
is that forming new relationships is expensive, and maintaining old ones takes time,
energy, and expense. As the strength of the ties grows, there is less time to look for
fresh resources that could lead to innovative ideas. Other goals may be overlooked if
social capital is the first objective. The findings show that social capital among local
players is critical for network leadership development. Our research begins to shed
light on how the organization of these networks varies, as well as which agricultural
actors play key leadership roles. This study adds to the body of knowledge on policy
networks and network governance in emerging economies in the study area and else-
where in the world, highlighting the proclivity of local and regional organizations to
Journal of Environmental Planning and Management 19

occupy central network leadership roles. Furthermore, the findings of this research will
contribute to the advancement of realistic information about how resources are shared
in the agricultural environment, as well as the function of various actors in network
leadership positions. It will also be useful in providing insight into how to harness
these networks for actual agricultural advancements. Information on how farmers par-
ticipate in collaborative relationships is useful for coordinating and implementing
development programs. This increased data collection will enable the examination of
complete partnership network architectures as well as comparisons between full and
core network structures. More study is needed to broaden the sample of agricultural
development policy networks, evaluate contextual social-ecological variables, and link
network-level characteristics to data on diverse organizational activities’outcomes.
This provides an opportunity to improve our understanding of the importance of net-
works in achieving development goals and to propose concrete steps for organizations
to work effectively with communities around the world to address pressing agricultural
challenges in an era of rapid environmental and societal change. They prove that the
SNA is a versatile instrument that gives a distinct and valuable viewpoint on compli-
cated social processes at different levels in relation to agricultural management, i.e.
micro (farmers), intermediate (government, domestic planners, and policymakers), and
macro (international) levels. We believe that the results of this research will contribute
to new applications and scientific advances and a special look at the inter-
national level.
Disclosure statement
No potential conflict of interest was reported by the authors.
Supplemental data
Supplemental data for this article can be accessed here.
ORCID
Mehdi Ghorbani http://orcid.org/0000-0002-0439-3513
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