Social Networks as Drivers for Technology Adoption: A Study from a Rural Mountain Area in Italy

Abstract

Innovation processes includes social and communicative elements. The role of innovative technology for the development of farming systems is investigated in literature, but only a few studies deal with the influence of networks on the adoption of technologies by farmers. The aim of this paper is to verify if the adoption of smartphones for professional reasons by farmers is influenced by the networks to which farmers belong, the socio-demographic characteristics of the farmers, and their farm’s size. The case study is in the Valtellina valley, a rural mountain area in the north of Italy, where 53 livestock farmers were interviewed. The methodology is based on two steps. First, social network analysis is applied to diagnose the relationships of farmers in terms of connectivity and closeness and to detect the centrality measures of farmers in three different social relationships: production networks, market networks, and information exchange networks. A multiple linear regression model is then applied to test whether centrality measures of the three networks, the farmers’ socio-demographic characters, and the farm’s features drive the adoption of smartphones for professional reasons. Results suggest that the centrality measures in production networks positively drive the adoption of smartphones, while the centrality measures of market and information exchange networks do not have the same effect. At the same time, the farmers’ age negatively affects the use of smartphones for professional reasons, while the size of the herd, and the education and gender of farmers have no significant influence. The study contributes to the debate around the Agricultural Knowledge Innovation System and supports local policies based on the inclusion of farmers in the technological development in rural areas.

The contribution of a catchment-scale advice network to successful agricultural drought adaptation in Northern Thailand

“…local, translocal) and multiple time points to monitor changing dynamics. Where previous authors have documented a need to strengthen the connectivity of social networks for agricultural governance [27,28], our research adds to the understanding of the network qualities in terms of transmitting efficacious advice to stimulate adaptive capacity through facilitating more successful adaptations. These observations lead to policy implications summarized in the next section and add to proposed indicators for conceptual resilience frameworks (e.g.…”

“…severity, duration, timing of onset) could not be uncovered. As other evidence suggests, farmers that have diversified production [4] and younger farmers [27], can be more inclined to take on adaptive management or innovative technology. Generally, farmers who received information on what they should do in response to drought made changes on their farms and were more likely to do so if they had higher levels of education.…”

“…Within contemporary research and policy, there are calls to strengthen the connectivity of social networks for agricultural governance [27,28] and for increased farmer inclusion in the development of local adaptation strategies [27,29,30]. These concepts can be viewed through an institutional analysis lens and continuing attempts to understand the interplay between governments and the self-governing aspects of natural resource management [15,31] and the role social networks play in fortifying resilience to drought [32].…”

Reducing Antimicrobial Use and Dependence in Livestock Production Systems: A Social and Economic Sciences Perspective on an Interdisciplinary Approach

“…In addition, there is no guarantee that alternatives will be immediately adopted by farmers, as it was the case for the live oral Lawsonia vaccine in pigs, that was not widely used despite positive results ( 18 ). Studies cut across many disciplines have shown that the adoption of new technologies by farmers can be influenced by numerous factors, e.g., environmental factors such as land use ( 21 ) and land characteristics ( 22 ); personal features such as age, human capital or risk preferences ( 23 ); economic attributes such as market intervention by regulators ( 24 ) and costs of acquiring the technology ( 25 ); extension services ( 22 ) as well as cultural and social factors including social identity ( 26 ), social networks ( 27 , 28 ) and peer group influence ( 29 ). It is therefore clear that farmers' behavior is embedded in both biophysical and social landscapes ( 30 ) and that decision-making processes are complex and context dependent.…”

The Effect of Verbal and Iconic Messages in the Promotion of High-Quality Mountain Cheese: A Non-Hypothetical BDM Approach

“…These aspects make alpine livestock farming suffer a lack of profitability due to a lower land and labor productivity when compared to lowland agriculture [ 7 , 11 , 12 ]. In this context, the ecosystem services of extensive livestock farming must be mentioned: such as the conservation of biodiversity, balance between native and invasive species, prevention of fires, maintenance of landscapes, conservation of the soil by reducing the risk of erosion, conservation of the organic wealth of the soil, less pollution, and better management of water resources.…”