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Effects of Multi-stakeholder Platforms (MSP) on Innovation Networks
and Implications for Research for Development (R4D) in Agriculture
Introduction
ØMulti-stakeholder (MS) platforms, such as innovation platforms (IP), public-private partnerships (PPP)
are becoming more common but what they can achieve in innovation and scaling is limited and depends
on different factors.
ØThis poster and the broader research paper provide evidence what MS platforms can and cannot
achieve in their early phases and give insights about effectiveness and efficiency of Agricultural
Research for Development (AR4D) interventions such as CGIAR research programs (CRPs) in low and
middle income countries.
Table 1: Change in Multi-Stakeholder Innovation Networks Following AR4D with Multi-stakeholder Platforms
Materials and Methods
How MSPs embed in Livelihood Systems?
Results and Discussion
Conclusions and Recommendations
References
1.Schut, M., van Asten, P., Okafor, C., Hicintuka, C., Mapatano, S., Nabahungu, N. L., Kagabo D., Muchunguzi P., Njukwe E., Donstop-Nguezet P. M., Sartas M., Vanlauwe, B. (2016). Sustainable intensification of agricultural systems in the Central
African Highlands: The need for institutional innovation. Agricultural Systems, 145, 165-176. doi:http://dx.doi.org/10.1016/j.agsy.2016.03.005
2.Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. ICWSM, 8, 361-362.
3.Sokal Robert, R., & James, R. F. (1969). Biometry. The principles and practice of statistics in biological research
Murat Sartas1,2,3
Marc Schut1,2
Piet van Asten4
Frans Hermans5
Cees Leeuwis2
1International Institute for
Tropical Agriculture (IITA) -
Kacyiru, P.O. Box 1269. Kigali,
Rwanda
2Wageningen University and
Research Center (WUR) - KTI,
Box 8130, Wageningen, the
Netherlands
3Swedish University of
Agricultural Sciences (SLU) -
SOL, Box 7012, Uppsala,
Sweden
4Leibniz Institute
for Agr. Dev. in Transition
Economies (IAMO), Theoder-
Lieser-Strasse 2, 06120 Halle,
Germany
5International Institute of
Tropical Agriculture (IITA), East
Naguru Road 15, Kampala,
Uganda
Contact:
m.sartas@cgiar.org
www.iita.org
Figure 1: Organizations in Livelihood Systems and AR4D
interventions.This study focused on the changes in target innovation
networks surrounding multi-stakeholder platform
Figure caption here
Collaborators
AR4D interventions have different
relations with organizations in the
livelihood systems with different roles
in achieving innovations and scaling.
These stakeholders (S) are;
Platform S (a) : Participates in AR4D
events and have a direct influence in
AR4D innovation activities
Innovation Network S (b) : Directly
connected to Platform - S and have
an indirect influence in AR4D
Innovation System S (c): Not
connected to Platform S directly but
have an influence on the success of
innovations
Livelihood System S (d) :
“Consumers” or end-users of
innovations with no influence on
innovation processes in AR4D
Where did we study?
The study covered three different country
MSPs with field activities in different
provinces (Figure 2).
Figure 2: Areas Covered by Our Study1
Which methods?
The study used two different methods:
Ø(Social) Network Analysis2:
To investigate changes in innovation
networks by focusing on three different
functions:
§Collaboration
§Knowledge exchange
§Influence spread
ØLogistical Models
To statistically inquire significant factors
playing a role in the changes in
innovation networks functions. We
utilized a combination of “enter” and
“stepwise” logistics models.3
What happens to collaboration in innovation
networks following AR4D with Platforms?
ØInitial collaboration networks was organized around locally central actors (a, Figure 3) and included
different sub-clusters with a combination of national and international stakeholders (b, Figure 3).
ØPlatforms do not necessarily increase collaboration in innovation networks. In all our cases number of
collaborating actors decreased. In addition, with the exception of Rwanda, the number of collaboration
connections decreased (Table – 1).
ØFollowing AR4D, some sub-clusters (c, Figure 3) dropped from the network. The decrease in the
connectivity was much higher between the organizations which are connected with only one channel
(Table -1).
Figure 3: Maps of Collaboration in Multi-stakeholder networks in Burundi, DRC and Rwanda in the early and (a year)
later phases of AR4D. Each node represent an organization. Node sizes represent the size of collaboration connections of
the organizations. Dark green nodes represent Burundi, blue DRC and light green Rwanda organizations. Number of
organizations in the collaboration decreased following AR4D with multi-stakeholder Platform.Majority of organizations in the
platform stayed in the collaboration (a), some clusters continued (b) and some others left the networks (c).
What happens to knowledge exchange and influence
spread in innovation networks following AR4D?
ØDespite the decreases in collaboration, number of organizations exchanging knowledge and the number
of connections among them increased in Burundi and Rwanda (Table 1).
ØNumber of influential organizations and their connections in innovation networks depended on the
country case (Table 1).
ØSimilar to the collaboration, number of knowledge exchange and influence connections with multiple
channels increased following AR4D with platforms (Table 1).
What are the significant factors contributing to changes
in innovation networks following AR4D with Platforms?
ØFunding provided to platform and initial characteristics of the innovation networks were significant in explaining
the changes in innovation networks for all functions, in terms of both decision to drop from and join to
innovation networks (Table -2).
ØFarmers, community level stakeholders were less likely to stay in innovation collaboration networks (Table -2).
ØNGOs and research stakeholders were less likely to join knowledge networks (Table -2).
Table 2: Results of Logistic Regression on Factors Affecting the Changes in Multi-stakeholder Innovation Networks
Ødo not necessarily create larger and denser collaboration in innovation
networks. They might lead to centralization of collaboration, decrease the
chances of farmers and stakeholders in local levels to continue
collaboration
Øcan create larger and denser knowledge networks if the initial knowledge
network do not include competing innovations. Knowledge exchange in
innovation networks might decrease when there is a group of
stakeholders supporting other innovations.
1. investigation of initial network configurations in innovation networks
2. prioritizing key functional gaps hindering innovation and scaling
3. using organization and event based financial incentives
Our study shows that AR4Ds with MS Platforms
We suggest that AR4D interventions with platforms can
improve their effectiveness and efficiency through
Acknowledgements
This work was carried out under the
framework for Improving Agricultural
Livelihoods in Central Africa (CIALCA).
CIALCA formed apart of the CGIAR
Research Program on Integrated Systems for
Humid Tropics. We would like to
acknowledge Belgian Development
Cooperation and CGIAR Fund Donors for
their provision of funding and CIALCA and
HUMIDTROPICS teams for supporting our
study processes.