Social Network Dynamics among Farmers Vis-à-Vis Knowledge Transfer about Rythu Bharosa Kendras (RBKs) Services

Social structures among farmers play a critical role in shaping agricultural practices and the dissemination of information within rural communities. These structures, which encompass various forms of social networks, significantly impact how knowledge and resources are shared among farmers (Mashavave et al., 2013; Thuo et al., 2013). In many rural areas, farmers rely on their social connections including fellow farmers, local leaders and extension workers as primary sources of information (Nyambo and Ligate, 2013; Sukhna et al., 2022; Rana et al., 2023) about farming techniques, market opportunities and support services (Effiong et al., 2023). The dynamics of these social networks can greatly influence the effectiveness of information transfer (Fritsch and Kauffeld-Monz, 2008) and, consequently, the adoption of agricultural innovations and practices (Yamini et al., 2024; Weyori et al., 2017; Matuschke and Qaim, 2009). In India, the Rythu Bharosa Kendras (RBKs) represent a key initiative by the Government of Andhra Pradesh aimed at enhancing the agricultural support system. Established as part of a comprehensive strategy to improve farmer welfare and productivity, RBKs are designed to provide a range of essential services at village level itself (Saifuddin et al., 2024). In fact, the RBK concept, recognized by the Centre for the UN Award, has been praised for its transformative impact on agriculture, effectively meeting farmers’ needs from seed to sale (Anuhya et al., 2022). Services include access to subsidized inputs, e-crop booking, technical advice services, knowledge centre, interactions with scientists via video conferencing, training programs on latest agricultural technologies, weather-related infor-mation and market linkage through procurement (Saifuddin et al., 2024). Despite the availability of these services, there is a notable variation in how well farmers are informed and how effectively they utilize the resources provided by RBKs. This variation often reflects differences in the reach and impact of information dissemination channels. The role of social networks in this context is pivotal. Farmers’ knowledge about RBK services and their ability to make use of these services are heavily influenced by their social interactions. Social network theory suggests that information flows through connections between individuals, with some nodes (or individuals) serving as critical points for information dissemination (Spielman et al., 2011). For instance, farmers who are well-connected within their community or who have strong relationships with extension workers are likely to receive and spread information about RBK services more effectively than those who are less connected. Despite an extensive review of the literature, no studies were found specifically addressing the social network dynamics and their influence on knowledge transfer regarding RBK services. Thus, under-standing the structure and dynamics of these social net-works can provide valuable insights into how knowledge about RBK services is transferred among farmers.
       
The rationale for this study emerges from the need to understand the interaction between social network dynamics and the dissemination of information about RBK services. By investigating how different types of social connections influence farmers’ knowledge and utilization of RBK services, the study aims to uncover key factors that contribute to the effectiveness or limitations of these support centers. Identifying these dynamics is essential for developing targeted strategies to improve the outreach and impact of RBKs, ensuring that their benefits are more widely and equitably distributed. The objectives of this study are threefold: (1) to identify and classify the sources of knowledge transfer regarding RBK services among farmers in the study area, (2) to map the social networks of farmers in relation to their knowledge of RBK services and (3) to compare the network structures of farmers with varying levels of knowledge and identify the influential actors/factors within these networks that affect knowledge transfer. By achieving these objectives, the study seeks to provide a comprehensive understanding of how social networks impact the dissemination and utilization of RBK services. The insights gained from this research are expec-ted to inform the design of more effective communication and outreach strategies, ultimately enhancing the overall impact of RBKs and supporting the broader goals of agricultural development and farmer welfare.

The study was conducted during the 2020–2023 period at Acharya N.G. Ranga Agricultural University, Agricultural college, Bapatla, Andhra Pradesh, utilizing an exploratory research approach. Andhra Pradesh was purposively selected for this study due to the implementation of the Rythu Bharosa Kendras (RBKs), an innovative initiative by the state government aimed at providing agricultural support directly at farmers’ doorsteps. The RBKs were established on May 30, 2020, with a total of 10,641 centers set up across all village secretariats in the state (Saifuddin et al., 2023). A multi-stage sampling method was employed to gather data. In the first stage, East Godavari district was purposively selected from thirteen districts due to its high number of RBKs relative to other districts. In the second stage, four mandals within East Godavari were selected purposively based on the coverage of RBKs. In the third stage, three villages were chosen from each selected mandal using a simple random sampling procedure. Finally, in the fourth stage, ten farmers from each village were selected using random sampling. This resulted in a total sample of 120 farmers. Prior to data collection, it was verified that RBKs were operational in all selected locations.
       
Prior to gather data, interviews and focus group discussions were conducted with farmers. A compre-hensive list of sources of knowledge transfer regarding RBK services among farmers were compiled and classified. A structured interview schedule was then developed and administered to the respondents. The schedule included questions aimed at identifying the most important knowledge sources for acquiring RBK services, as well as the frequency of discussions with these sources and the utilization of sources. Respondents were required to choose from a prepared list of knowledge sources. It was ensured that all respondents had utilized at least two RBK services at the time of data collection to confirm their frequent engagement with RBK services and receipt of updated information.
       
Social Network Analysis (SNA) was employed to map and analyze the networks of knowledge sources regarding the knowledge transfer of RBK services. Network maps were created to visualize the relationships between various information actors. To better understand the operational information network, bimodal networks representing diverse information sources were constructed. UCINET, an open-source software, was used for network mapping and calculating network measures such as Degree, Between-ness, Closeness Centrality and Density. Binary relations between network members were entered into UCINET and visualized with Netdraw. In this study, binary relationships between entities were represented as affiliation networks, with data entered as a rectangular matrix where rows and columns represented different sets of entities, including people, events, groups, or organizations. This methodology follows the approach outlined by Vishnu et al., (2019), where affili-ation networks correspond to individual farmers’ varied sources of information.

Classification of farmers’ knowledge sources on RBK services
 
Based on focus group discussions and interviews with farmers in the study area, knowledge sources related to RBK (Rythu Bharosa Kendras) services were identified and categorized into three distinct types, this categorization aligned with the findings of Adolwa et al., (2012).  These are summarized in Table 1. Local interpersonal sources refer to information channels that involve direct, personal interactions within the farmers’ immediate social environment. These included friends or neighbouring farmers, relatives engaged in farming, progressive farmers recognized for their advanced practices, the village secretary who may facilitate information dissemination and agro-input dealers who provide both products and advice. Cosmopolite interpersonal sources encompass knowledge obtained through personal interactions with individuals from different or more distant geographic locations. This category included technical staff of RBK (Village Agricultural Assistants/ Village Animal Husbandry Assistant), Agricultural Extension Officers (AEOs), Mandal Agricultural Officers (MAOs), Assistant Directors of Agriculture (ADAs), Joint Directors of Agriculture (JDAs), scientists from institutions such as ANGRAU (Acharya N.G. Ranga Agricultural University), DAATTC (District Agricultural Advisory and Transfer of Technology Centres) and KVK (Krishi Vigyan Kendras) and field technicians from private agro-companies. Cosmopolite impersonal sources involved indirect forms of communication that are not based on personal interaction. These sources included publications such as magazines and journals, newspapers, radio broadcasts, television programs, online platforms like WhatsApp and social media and Short Message Service (SMS) for disseminating concise information and updates.


       
Analysis of the data presented in Table 2 indicated that local interpersonal sources, including relatives, progressive farmers and village secretaries, are critical for farmers with low levels of RBK knowledge, A similar trend was also observed by another researcher in a different context (Vishnu et al., 2019). These sources exhibited high degree centrality, suggesting their significant role in the immediate social networks of low-knowledge farmers. For high-knowledge farmers, cosmopolite interpersonal sources, such as technical staff of RBKs and agricultural extension officers, play a more prominent role, these findings were consistent with the findings of Saifuddin et al., (2022); Saifuddin et al., (2024) and Saifuddin et al., (2024). This shift indicated that as farmers’ knowledge increases, they rely more on formal, external sources of information. The study also highlighted that online platforms and newspapers are crucial for disseminating information about RBK services. Online platforms, with their high degree and closeness centrality for high-knowledge respondents, demonstrate their effectiveness in reaching and engaging well-informed farmers. In contrast, news-papers hold a central role for low-knowledge farmers, reflecting their ongoing importance in rural information dissemination despite the rise of digital media. In contrast, the Assistant Director of Agriculture (ADA) and the Joint Director of Agriculture (JDA) were identified as the least utilized sources of information regarding RBK services among the farmers in the study area. This suggested a preference for more immediate and locally accessible sources of knowledge over higher-level administrative and technical contacts.


 
Mapping of social networks of farmers in relation to their knowledge of RBK services
 
Farmers’ knowledge of RBK (Rythu Bharosa Kendras) services was classified into two levels: low and high. The study mapped the social networks of farmers in relation to their knowledge of RBK services across all three categories of knowledge sources. This mapping examined how farmers’ interactions with various types of information sources influence their level of knowledge of RBK services.
       
A comparison of Fig 1 and Fig 2 revealed that the network density and the number of connections among high-knowledge farmers regarding RBK services are greater than those among low-knowledge respondents within the locale interpersonal sources. Network density is the proportion of actual connections between nodes compared to the total number of possible connections among all pairs of nodes (Grunspan et al., 2014). This suggested that high-knowledge farmers have more extensive and densely connected networks of local interpersonal sources compared to their low-knowledge counterparts.



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Fig 3 illustrated the social network of cosmopolite interpersonal knowledge sources for respondents with low knowledge of RBK services, characterized by a density of 0.358 and a total of 172 ties. In contrast, Fig 4 depicted the social network of cosmopolite interpersonal knowledge sources for respondents with high knowledge of RBK services, with a density of 0.375 and 180 ties. These figures indicated that while both groups have relatively similar network structures, the network associated with high-knowledge respondents is slightly denser and includes a greater number of ties. This suggested that respondents with higher knowledge of RBK services had more interconnected and extensive cosmopolite interpersonal networks compared to those with lower knowledge.

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The analysis of Fig 5 and 6 highlighted that notable differences in the cosmopolite impersonal knowledge networks between respondents with low and high knowledge of RBK services. Fig 5 depicted the network for respondents with low knowledge, which has a density of 0.406 and includes 146 ties. In contrast, Fig 6 showed the network for respondents with high knowledge, featuring a higher density of 0.514 and 185 ties. These findings indi-cated that respondents with high knowledge of RBK services are associated with a more densely connected network of cosmopolite impersonal knowledge sources. The increased density and number of ties in the high-knowledge group suggest a greater engagement with and exposure to a diverse range of impersonal information sources. This enhanced connectivity likely facilitates a more comprehensive understanding of RBK services among individuals with higher levels of knowledge.

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Comparing network structures and key influencers in knowledge transfer among farmers with different RBK service knowledge levels
 
The analysis of Table 3 indicated that several notable patterns in the normalized centrality measures for local interpersonal sources used by respondents with varying levels of knowledge about RBK services. Degree centrality measures the number of direct information connections an actor has within a network (Matous and Todo, 2015). For respondents with low knowledge, relatives or family members have the highest degree centrality (0.667), indicating their prominent role in the network. In contrast, for those with high knowledge, the village secretary had  highest degree centrality (0.650), suggesting a key role in connecting high-knowledge individuals within the network.    

      

An actor with high closeness centrality will have close connections with many others, positioning them well to access information or resources from across the network (Spielman et al., 2011). In terms of closeness centrality, relatives or family members exhibited the highest measure for respondents with low knowledge (0.618), implied that they were more accessible in the network. For high-knowledge respondents, agro-input dealers show the highest closeness centrality (0.618), indicating their effective positioning to provide information. Regarding betweenness centrality, the village secretary has the highest score for respondents with high knowledge (0.307), highlighting their significant role in bridging connections between different parts of the network. For those with low knowledge, progressive farmers have the highest betweenness centrality (0.230), reflecting their intermediary role in linking various network members (Msaddak et al., 2017).
       
The findings from Table 4 provide insights into the centrality measures of cosmopolite interpersonal sources for respondents with different levels of RBK services knowledge. The Technical Staff of RBK (VAA/VAHA) emerged as the most central source, showing the highest degree centrality for both low (0.633) and high knowledge (0.678) respondents, underscored their pivotal role within the network. In contrast, the Joint Director of Agriculture (JDA) consistently ranks lowest in degree centrality (0.100 for low knowledge and 0.183 for high knowledge), indicating a less significant position. For closeness centrality, the Agricultural Extension Officer (AEO) ranked highest among low-knowledge respondents (0.500), suggesting greater accessibility within the network. Meanwhile, the Technical Staff of RBK (VAA/VAHA) had highest closeness centrality for high-knowledge respondents (0.627), reflecting their effectiveness in information dissemination. In terms of betweenness centrality, the Technical Staff of RBK (VAA/VAHA) also leads for both low (0.273) and high knowledge respondents (0.356), highlighting their essential role in connecting various network segments. On the other hand, the JDA and ADA had lowest betweenness centrality scores, indicating a more marginal role in bridging network connections.

This study illuminated the critical role of social networks in shaping farmers’ knowledge of Rythu Bharosa Kendras (RBK) services. Key findings revealed that local interpersonal sources, such as relatives and village secretaries, were vital for low-knowledge farmers, while cosmopolite interpersonal sources, notably technical staff of RBKs, were crucial for high-knowledge farmers. Online platforms and newspapers emerged as significant dissemination channels, with online platforms particularly effective for high-knowledge farmers. The higher network density among well-informed farmers underscored their extensive engagement with diverse information sources. These insights suggested that tailored communication strategies, enhancing both local and cosmopolite networks, could improve RBK service outreach. Future research should explore these dynamics in varied contexts to further validate these findings and refine strategies for agricultural support services.

The authors gratefully acknowledge the farmers who participated in this study and provided valuable insights. We also extend our sincere thanks to Acharya N.G. Ranga Agricultural University for its support and resources, which were instrumental in facilitating the research.

Disclaimers
 
The views and conclusions expressed in this article are solely those of the authors and do not necessarily represent the views of their affiliated institutions. The authors are responsible for the accuracy and completeness of the information provided, but do not accept any liability for any direct or indirect losses resulting from the use of this content.
 
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No animals are involved in this research study.

The authors declare that there are no conflicts of interest regarding the publication of this article. No funding or sponsorship influenced the design of the study, data collection, analysis, decision to publish, or preparation of the manuscript.