Adaptive practices of researchers involved in low-tech co-innovation processes: Feedbacks from a multi-site experience with ICTs for irrigation systems

Despite their theoretical potential to increase yields and reduce water use, Information and Communication Technologies (ICTs) remain poorly used in irrigation systems, particularly at the farm scale and in smallholder farms. ICTs innovations still need to be adapted to each local context to be more accessible to farmers. Co-innovation through a “low-tech” approach can increase the fit of technologies to end users’ needs and help farmers to make, maintain and reproduce technological objects. Nevertheless, for researchers, being involved in such co-innovation approaches can be challenging as they have to continually adapt technological interventions to the social and environmental conditions. With the aim of supporting researchers’ adaptive practices, this paper proposes an original approach to bring a reflexive stance about how co-innovation unfolds within and across case studies. A methodology to assess the interplay between local contexts, technologies, and facilitation processes from a researcher’ perspective was implemented on a multi-country action-research project. Several on-farm experimentations, under a given overarching “low-tech” approach, were documented through qualitative interviews with the researchers involved in their implementation. As in any co-innovation processes, the development of ICTs makerspaces in agricultural settings proposes an alternative way to put ICTs back in the service of farmers. While the process of adapting technology to micro-desires and microenvironments can help restore economic and social accessibility, it also involves a great deal of information and facilitation work. Hence, low-tech approaches are promising solutions to address irrigation efficiency challenges, but their implementation in real world contexts forces researchers to adjust, relocate efforts, develop new facilitating skills, which in turn produces shifts in their position. This research finally raises questions about how to drive change in complex contexts while respecting strictly limited timelines, and opens up perspectives for clustering initiatives and capitalize on researchers’ feedbacks.