The importance of proximity dimensions in agricultural knowledge and innovation systems: The case of banana disease management in Rwanda

Highlights

• Different forms of proximity are important to be incorporated into AKIS research.

• Geographical proximity plays a role in the informal networks of larger villages.

• Cognitive and social forms of proximity take over where distance is not important.

• Geographical distance doesn't affect the official government extension system.

• Farmers are socially close in a smaller community where distance does not matter.

Abstract

CONTEXT

Social networks play an important role in the diffusion of knowledge, and farmers draw on their personal networks to enhance their adaptive capacity to shocks. Different forms of proximity have been long recognized as important factors in knowledge and information exchanges. However, the specific roles and their interactions in agricultural knowledge and innovation systems (AKISs) are still far from clear. In this study, we investigate the underlying forces that drive tie formation within the knowledge-sharing networks of banana farmers in four different villages in Rwanda.

OBJECTIVE

Our study has three objectives: First, we discuss the importance of various types of proximities in AKIS research. Second, we empirically contribute to how different forms of proximity influence the way knowledge diffuses in formal and informal networks by studying a plant disease's management. Finally, we discuss our findings' relevance for targeted interventions to help rural communities transition to greater resilience.

METHODS

We review different proximity concepts and adapt them for use within an AKIS context. We then apply this framework to assess the proximity effects on the advice-seeking networks of banana farmers in four purposefully chosen villages in Rwanda. We used a structured questionnaire to collect social network information about the management of banana Xanthomonas wilt (BXW), from all banana growers (N = 491) in these four villages. We distinguished the informal advice networks among farmers from the official government extension system—the formal advice network. We employed exponential random-graph models to assess the determinants of the networks we observed, especially geographical, cognitive and social proximity indices.

RESULTS AND CONCLUSIONS

We found that geographical proximity significantly affects knowledge exchange within larger villages' informal advice networks; but not in smaller villages, where both cognitive and social proximities play substantial roles. We argue that farmers are socially closer in smaller communities where geographical distance does not matter, and that geographical distance only starts to matter after a certain community size threshold is reached.

SIGNIFICANCE

We provide solid empirical evidence to help plan targeted interventions toward greater resilience for rural communities. We argue that properly integrating informal social networks can result in more effective knowledge exchange within AKISs, enhancing their resilience.

Introduction

The agricultural knowledge and innovation system (AKIS) framework has become a popular analytical framework to study how agricultural knowledge is co-produced and disseminated. AKIS describes which actors, networks, and institutional environments play a significant role in these processes (Abebe et al., 2013; Rivera et al., 2005; Spielman et al., 2008). This approach has broadened the previously linear view of agricultural innovation processes to a distributed process in which different actors can play roles to solve the so-called “wicked” (complex) problems associated with unsustainable technologies and practices (Hebinck et al., 2021; Hermans et al., 2015; Leeuwis and Aarts, 2011). With the rising interest in collaborative processes, collaborative networks have become a popular object of study. Within the last decade, the AKIS literature has adopted a network perspective that highlights the role of knowledge/advice networks to explain and predict information flows and their role in enhancing smallholders' capacity to innovate (Compagnone and Hellec, 2015; Danielsen et al., 2020; Hermans et al., 2017b; Rudnick et al., 2019; Spielman et al., 2011).

In addition, the literature has shown a positive association between knowledge networks and agricultural systems' resilience (Darnhofer et al., 2016; Šūmane et al., 2018; Tittonell, 2020). The need for resilient agricultural systems increases constantly insofar as agriculture is exposed to multiple shocks, stresses, and growing uncertainty (Meuwissen et al., 2019). Such networks facilitate knowledge exchange including information relevant to coping with the multiple shocks, stresses, and growing uncertainty farmers are exposed to (Meuwissen et al., 2019). Dense social networks are therefore both the expression of and prerequisite for developing different types of social capital and trust (Aguilar-Gallegos et al., 2015; Cofré-Bravo et al., 2019).

Although this network perspective has been successfully applied to studying the effects of different network characteristics at the macro level, not a lot of attention has been paid to the underlying forces that drive tie formation within such networks. We aimed to address this gap by investigating what types of proximity influence the formation of knowledge-sharing ties in a formal and an informal advice network. Proximity refers to the individual's tendency to form interpersonal relationships with those who are close by. However, closeness is viewed in the literature as a multidimensional concept that is not limited only to geographic distance (Boschma, 2005; Geldes et al., 2015; Mattes, 2012).

This paper is structured as follows: The subsequent Theoretical Background section digs deeper into the proximity literature and how these insights can be applied to agricultural advice networks in AKIS. We then apply these theoretical insights to a specific case to see how these different forms of proximity influence the diffusion of knowledge, specifically knowledge about a banana disease in Rwanda. This banana disease, banana Xanthomas wilt (BXW) is a fast-spreading crop disease that threatens the livelihood of banana growers (McCampbell et al., 2018).

We describe our case study in Rwanda and formulate several hypotheses on how different forms of proximity may play out in formal (extension-driven) and informal (farmer-to-farmer) advice networks. In the Methodology section, we describe data and how we collected them, as well as the model used to study our social networks' structural characteristics. The Results section statistically describes the social networks of four villages and presents the effects of cohesion, multiple connections, preferential attachment, and geographical proximity on tie formation. The Discussion section presents the possible underlying reasons for the effects we observed by comparing them to previous studies. The Conclusion states our scientific contribution and how this study supports policy-making vis-à-vis the diffusion of agricultural innovation.