Managing collaborative research: insights from a multi-consortium programme on climate adaptation across Africa and South Asia

Abstract

Collaborative research requires synergy among diverse partners, overall direction, and flexibility at multiple levels. There is a need to learn from practical experience in fostering cooperation towards research outcomes, coordinating geographically dispersed teams, and bridging distinct incentives and ways of working. This article reflects on the experience of the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA), a multi-consortium programme which sought to build resilience to regional climate change. Participants valued the consortium as a network that provided connections with distinct sources of expertise, as a means to gain experience and skills beyond the remit of their home organisation. Consortia were seen as an avenue for reaching scale both in terms of working across regions, as well as in terms of moving research into practice. CARIAA began with programme-level guidance on climate hotspots and collaboration, alongside consortium-level visions on research agenda and design. Consortia created and implemented work plans defining each organisation’s role and responsibilities and coordinated activities across numerous partners, dispersed locations, and diverse cultural settings. Nested committees provided coherence and autonomy at the programme, consortium, and activity-level. Each level had some discretion in how to deploy funding, creating multiple collaborative spaces that served to further interconnect participants. The experience of CARIAA affirms documented strategies for collaborative research, including project vision, partner compatibility, skilled managers, and multi-level planning. Collaborative research also needs an ability to revise membership and structures as needed in response to changing involvement of partners over time.

Research collaboration and knowledge development in Africa: the case of neonatal conditions

“…In university-industry collaborations (UICs), scientists working in an academic environment often cite access to funding for students and additional research money as a benefit (Ankrah & Al-Tabbaa, 2015;Arza, 2010;D'Este & Perkmann, 2011;Lee, 2000;Meyer-Krahmer & Meyer-Krahmer, 1998;Perkmann et al, 2013;Tartari & Breschi, 2012;Welsh et al, 2008). Also, the intellectual resources arising from these relationships can provide new insights into the research agenda and lead to new projects (Arza, 2010;Garcia et al, 2019;Welsh et al, 2008).…”

“…Also, the trust created can spread through the networks of individual scientists involved in RC, increasing the chances of meeting other scientists and in this way expanding professional ties (Newman, 2001). Scientists have cited increased networking as a benefit of RC (Currie-Alder et al, 2020;Munung, Mayosi, & de Vries, 2017;Schmink et al, 2020;Tierney et al, 2013;Welsh et al, 2008).…”

Functioning strategies of the research groups' leaders in the context of funding and policy instabilities☆

“…Its effects on local Science, Technology, and Innovation (STI) systems have become a growing issue of analysis (Kuhlmann & Ordóñez‐Matamoros, 2017). However, most studies have focused on cases in the Global South, in locations such as: Venezuela (Diaz et al, 1983; Laya & Vessuri, 2019), Burkina Faso (Hermann et al, 2012), India (Priyadarshinia & Abhilash, 2020), Brasil (Fraundorfer & Rabitz, 2020), and Arabic‐speaking countries (Currie‐Alder et al, 2018, 2020), among others.…”

Beyond Indicators and Success Stories: An Emerging Method to Assess Social Learning in Large-Scale Transdisciplinary Research Programs

“…Addressing them requires collective coordination and action to deal with the interrelated social, environmental, and economic dimensions of the challenge and their associated nonlinear feedback systems. This recognition has led to a push for new modes of collaboration, coordination, and learning within international research programs, with a view to enhancing collaboration across disciplines, regions, and scales (Leemans, 2016;Currie-Alder et al, 2020). Social learning (SL) is one such approach to addressing the need for enhanced collaboration and learning that has been taken up in numerous major research programs on climate change in recent years (Kristjanson et al, 2014;Harvey et al, 2017;Cundill et al, 2018).…”