Do translocal networks matter for agricultural innovation? A case study on advice sharing in small-scale farming communities in Northeast Thailand
Recent research on agricultural innovation has outlined social networks’ role in diffusing agricultural knowledge; however, so far, it has broadly neglected the socio-spatial dimensions of innovation processes. Against this backdrop, we apply a spatially explicit translocal network perspective in order to investigate the role of migration-related translocal networks for adaptive change in a small-scale farming community in Northeast Thailand. By means of formal social network analysis we map the socio-spatial patterns of advice sharing regarding changes in sugarcane and rice farming over a period of five years. We find that, in translocally connected and mobile rural communities, a substantial share of advice originates from translocal levels. Translocal advice is dominantly provided through weak and formal ties with extension agencies and shared by few highly central larger-scale farmers within sparse local networks. This draws the picture of top-down translocal innovation flows driven by extension agencies and brokered through elite farmers. A closer look on institutional context and key actors of particular changes, however, suggests the potential of migration-related translocal networks and migration experience in fostering bottom-up innovations. Migration-related innovations transfers can promote adaptive capacity also among less favorably connected actors, especially if changes are geared towards limited household resources and are compatible with social practices of small-scale farming. We conclude that a translocal network perspective is instructive for research and extension interested in leveraging more inclusive agricultural innovation.
KeywordsAgricultural innovation Farmer advice sharing Migration Northeast Thailand Social network analysis (SNA) Translocal knowledge transfers
Bank of agriculture and agricultural cooperatives
Department of agricultural extension
Social network analysis
This article is based on research funded by the German Federal Ministry of Education and Research, Grant Number 01LN1309A. The responsibility for the contents of this publication lies with the authors. We thank the numerous interviewees for providing insights in their agricultural activities and their sources of advice. In particular we thank our excellent research assistants, Pichapon Robru and Nootchanok Jitpakdee, for facilitating and translating interviews, and Raks Thai Foundation for organizational support.
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