Petr Matous

Roles of extension and ethno-religious networks in acceptance of resource-conserving agriculture among Ethiopian farmers

This article analyses roles of social and extension networks in adoption of resource-conserving practices among Ethiopian farmers. We gathered data from 297 randomly sampled households on their agricultural practices, social networks, access to the extension, and geographical location. After examining general determinants of practising resource-conserving agriculture, we employ a two-stage regression with full-maximum likelihood correction for selection bias to establish the roles of general social networks and external professionals in acceptance of conservation techniques. In accordance with previous research, probit regression in the first stage shows that the access to extension increases with farmers’ wealth and the size of their personal networks, and decreases with the distance of their households from village centres. However, after accounting for this unequal access to extension, the second-stage linear regression shows that regardless of education, wealth or geographical location, those whose religion and ethnicity match with their agent, report learning more about conservation from extension sources. Furthermore, farmers who are socially well connected within the community tend to be less receptive to agents’ recommendations regarding resource conservation. Dissemination policy of conservation agriculture should consider the ethnic and religious affinity between farmers and their extension agents. It also needs to pay more attention to socially and geographically isolated individuals.

Exploring dynamic mechanisms of learning networks for resource conservation

The importance of networks for social-ecological processes has been recognized in the literature; however, existing studies have not sufficiently addressed the dynamic nature of networks. Using data on the social learning networks of 265 farmers in Ethiopia for 2011 and 2012 and stochastic actor-oriented modeling, we explain the mechanisms of network evolution and soil conservation. The farmers’ preferences for information exchange within the same social groups support the creation of interactive, clustered, nonhierarchical structures within the evolving learning networks, which contributed to the diffusion of the practice of composting. The introduced methods can be applied to determine whether and how social networks can be used to facilitate environmental interventions in various contexts.

Multilevel Network Analysis Using ERGM and Its Extension

Exponentials random graph models (ERGMs) model network structure as endogenous based on the assumption that network ties are conditionally dependent, i.e. the existence of a network tie depends on the existence of other network ties conditioning on the rest of the network. In multilevel network contexts, ERGMs offer a statistical framework that captures complicated multilevel structure through some simple structural signatures or network configurations based on these tie dependence assumptions, i.e. network ties are interdependent not only within levels but also across levels. The interpretations of ERGM parameters make hypothesis testing about multilevel network structure possible. In this chapter, we first review the multilevel network data structure and multilevel ERGM specifications. Then we will apply these models to a dataset collected among 265 farmers and their communication network in a rural community in Ethiopia, thus providing an interesting description of this farming community. The modelling example highlights the features of these models and their theoretical importance, i.e. within-level network structures are interdependent with network structures of other levels; and within level nodal attributes can affect multilevel network structures. For example, we extend the model specifications with two new configurations, the “Alternating” forms of cross-level three-paths and Four-cycles, and discus their possible interpretations.

Social networks and environmental management at multiple levels: soil conservation in Sumatra

Many agrarian communities in developing countries suffer from insufficient productivity and use farming practices that deteriorate the environment both locally and globally. Research suggests that social networks play a role in environmental management, different studies emphasize different aspects of network structures, and the implications of the scales at which networks operate are not explicitly discussed. Here, I ask what types of social structures in farmer networks are conducive to environmental protection and agricultural productivity enhancement, and I show that the answer depends on the scale of the investigation. Using original data representing 16 farmer groups comprising 315 households and 1575 information-sharing links, I analyzed the structure of farmers’ social connections in relation to their soil conservation and productivity-enhancing practices, assessed through their usage of organic and chemical fertilizers. Furthermore, I conducted qualitative interviews with 25 stakeholders from different levels of the agricultural system to gain additional insights into the drivers of farmers’ behaviors. The quantitative analysis distinguishes the effects of intraand extra-group links and reciprocity at the household and group levels. Fixed-effects logistic regression was applied at the household level to examine farmers’ soil management practices. At the collective level, I used linear regression to estimate the proportion of adopters for each soil management practice. A lack of education and a lack of extra-group links are associated with unproductive practices, and a lack of reciprocity is associated with a lack of conservation efforts at both the household and collective levels. Dense intra-group links have opposite effects at the two levels. Whereas links within the farmer groups are associated with unproductive soil management by households, these links are associated with productivity maximization at the collective level. Qualitative interviews showed that farmers who opt for organic fertilizers do so partially because of pressure from global traders, mediated through external links and amplified by dense and reciprocal relations within their groups. The results highlight the need for environmental management policies to be based on research at multiple scales and demonstrate that, counter-intuitively, increasing global economic interconnectivity may, in some cases, stimulate the adoption of conservation practices via local social networks.

Effects of Social Network Structure on the Diffusion and Adoption of Agricultural Technology: Evidence from Rural Ethiopia

This paper investigates the effects of social network structure on the diffusion of agricultural technologies using household-level panel data from Ethiopia. We correct for possible biases due to the endogeneity of social networks using a social experiment in which we provide mobile phones to randomly selected households. We find that the effect of social networks varies depending on the network structure and characteristics of the technologies considered. The diffusion of information on a simple technology is determined by whether farmers know an agricultural extension agent. However, the diffusion of information on a more complex technology is not promoted by simply knowing an extension agent but by knowing an agent that a particular household can rely on and by clustered networks in which most friends of the household are friends of each other. This finding suggests that knowing and understanding more complex technologies require strong external ties and flows of the same information from multiple sources.

Farmers' Access to Resources via Networks in Remote Rural Areas with Mobile Phone Reception: Creating a Resource Battery for a Mountain Tribe in South India

Abstract Inhabitants of the most remote areas tend to have low access to information and resources potentially contributing to well-being. Ongoing expansion of ICTs deeper into rural areas is expected to improve this situation by enabling them to contact geographically distant others. We interviewed 79 women and men in an indigenous tribe in the mountains of Tamil Nadu, India, where explosively expanding mobile phone signal entered prior to other types of infrastructure, and we inductively developed a scale for assessment of the inhabitants’ overall access to valued resources through their personal networks. It was found that the mobiles contributed primarily to the maintenance of existing networks and to speedier mobilization of already accessible resources. However, since the phone owners called only with people whom they already knew well, they did not expand their networks nor increased their overall access resources.

Energy and resilience: The effects of endogenous interdependencies on trade network formation across space among major Japanese firms

The dynamic drivers of interfirm interactions across space have rarely been explored in the context of disaster recovery; therefore, the mechanism through which shocks propagate is unclear. This paper uses stochastic actor-oriented modeling to examine how trade networks among the 500 largest Japanese companies evolved during 2010 and 2011, i.e. before and after the Great East Japan Earthquake to identify sources of vulnerability in the system. In contrast to previous reports on broken supply chains, the network displayed only modest change even in the directly affected areas. Controlling for distance and for firm size, we find that when firms changed their partners, they preferred firms that were popular among other firms, that had partners in common with them and that also bought some products or services from them. These findings concur with a criticism that Japanese firms avoid external actors and exhibit inflexibility in reorganizing their networks in times of need, which contrasts with the non-cliquish network structures observed in high-performing economic sectors. The results also highlight the role of energy firms in disaster resilience. Unlike other large Japanese companies that cluster in major urban centers, energy firms are distributed across Japan. However, despite their peripheral physical locations, energy firms are centrally located in trade networks. Thus, while a disaster in any region may affect some energy firms and lead to large-scale temporary shocks, the entire network is unlikely to be disconnected by any region-specific disaster because of the spatial distribution of the topological network core formed by energy companies.

Social network ties predict land use diversity and land use change: a case study in Ghana

While it is well documented that informal social ties play a role in information exchange on land management practices, the structural features of such networks that govern individual choice on land use change remain elusive. This study aims to correlate information network structures with localized or “micro-level” land use diversification and land use change. We ask the following: (i) what is the network structure of producers who manage diverse land use types? and (ii) are network topologies and the emergence of new network ties related to land use change? This work draws on a longitudinal study with producers in the transition zone of Ghana. We use social network analysis to assess the social relationships of 40 focal producers embedded in networks of 116 producers, combined with field observation to chart land use types and size. Land use ordered across eight types, from forest and agroforests to crops and grasslands. Converting land to crop production was correlated to the addition of ties in a focal producer’s network, while the diversity of land use types was correlated to the number of institutional ties as well as gender of the focal producer. We illustrate that local networks relate to land use change whereas external ties drive the introduction of new land use types. Given that the diversity of land use types may be a signature of livelihood resilience, the promotion of external, bridging ties can contribute to an increase in land use diversification. However, a strong local network is needed to implement this change.

An experiment in strengthening the networks of remote communities in the face of environmental change: leveraging spatially distributed environmental memory

Agrarian communities in different regions develop diverse coping strategies to address the environmental changes they face. In this work, we test how to stimulate farmers’ social learning across diverse regions to promote informed responses to soil degradation. We invited 117 randomly selected members of 16 randomly selected Sumatran communities to three 3-day networking and training events in regions with diverse socio-environmental histories. One event was held in the respondents’ remote rural district (Tanggamus), the second was held in a more densely populated region on Sumatra Island (Kalianda), and the third was held in a heavily populated region on Java Island (Garut and Ciamis). Eighteen months later, we surveyed the information-sharing networks and agricultural practices of 370 members of these communities. The participants had become popular sources of agricultural advice, but the strength of this impact depended on the region in which their networking intervention was conducted. The participants in the event on Java had become the most central members of their communities. Although all the participants received the same formal information, those who interacted with the farmers in a region with the longest history of population pressure and land degradation management were more likely to adopt the recommended practices. The participants in this intervention doubled their odds of adopting organic fertilizers compared with those who networked only with peers in their local environment. Environmental memory of coping with change can be shared between regions through social learning, which can be stimulated by simple interventions.

Analyzing the coevolution of interorganizational networks and organizational performance: Automakers’ production networks in Japan

Organizations create networks with one another, and these networks may in turn shape the organizations involved. Until recently, such complex dynamic processes could not be rigorously empirically analyzed because of a lack of suitable modeling and validation methods. Using stochastic actor-oriented models and unique longitudinal survey data on the changing structure of interfirm production networks in the automotive industry in Japan, this paper illustrates how to quantitatively assess and validate (1) the dynamic micro-mechanism by which organizations form their networks and (2) the role of the dynamic network structures in organizational performance. The applied model helps to explain the endogenous processes behind the recent diversification of Japanese automobile production networks. Specifically, testing the effects of network topology and network diffusion on organizational performance, the novel modeling framework enables us to discern that the restructuring of interorganizational networks led to the increase of Japanese automakers’ production per employee, and not the reverse. Traditional models that do not allow for interaction between interorganizational structure and organizational agency misrepresent this mechanism.