This document proposes a methodology to evaluate the impact of innovation platforms (IPs) using quantitative econometric tools and qualitative data. The methodology involves collecting data on IP structure through interviews, identifying performance elements based on objectives, and conducting focus groups to identify statements characterizing IP conduct and performance and thresholds for wealth. Individual surveys would then collect structure data and rank agreement with conduct/performance statements. Data analysis would include regression analysis to identify relationships between framework elements and principal component analysis to identify best conduct/performance statements. Qualitative data would also be analyzed to triangulate results. The methodology aims to provide more robust evaluation of IPs using mixed quantitative and qualitative methods.
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Field testing an econometric conceptual framework for innovation platform impact assessment
1. Collect data on IP ‘structure’ elements
through structured interviews of IP
facilitators or secretariat
Refer to the IP’s objec<ves as determined
by its members to iden<fy ‘performance’
elements
Conduct focus groups of IP members to
iden<fy:
• Field‐relevant statements to
characterize elements of IP ‘conduct’
and ‘performance’
• Locally relevant thresholds for a five‐
point indicator of wealth
• Qualita<ve narra<ves to illustrate the
conceptual framework
Individual survey of IP members to collect
individual ‘structure’ elements and rank
their agreement with statements
characterizing ‘conduct’ and ‘performance’
on 5‐rank Likert scale
Unlocking livestock development potential through science, influence and capacity development
ILRI APM, Addis Ababa, 15-17 May 2013
Developing capacity Influencing decisions
Field tes<ng an econometric conceptual framework for
innova<on plaHorm impact assessment
This document is licensed for use under a Crea3ve Commons A6ribu3on‐Noncommercial‐Share Alike 3.0 Unported Lisence May 2013
3 strategic lessons on:
1. ILRI research fellows will obtain their
MSc degree
2. Local field partners will get more
familiar with IP evalua<on methods
3. IP members will become aware of the
importance of evalua<ng their ac<vi<es
1. IP facilitators can invest their scarce
resources on facilita<ng elements that
most affect IP performance
2. Evidence to beneficiaries that IPs work
3. Evidence to donors that IPs are a good
investment to reach outcomes
Jean‐Joseph CADILHON, Agricultural Economist, Policy Trade and Value Chains Program, ILRI – j.cadilhon@cgiar.org
Delivering science
ILRI has been establishing IPs as equitable,
dynamic spaces designed to bring
heterogeneous actors together to
exchange knowledge and take ac<on to
solve a common problem
Methods to assess the impact of IPs have
mainly used qualita<ve methods or cost–
benefit analysis
There are no previous examples of using
quan<ta<ve econometric tools to evaluate
the impact of innova<on plaHorms
1. More robust results expected from
informa<on triangula<on
2. First a^empt to evaluate IPs with
quan<ta<ve method
3. Scien<fic research with high impact &
publica<on poten<al
Elements of a conceptual framework to monitor and evaluate
the impact of innovation platforms on value chains development
Context
• Mulple regression analyses to idenfy
stascally significant relaonships
between elements of the conceptual
framework
• Principal component factor analysis to
find the best statements that encompass
‘conduct’ and ‘performance’ elements
• Content analysis of qualitave data to
triangulate results from econometric
analysis
1. Overall elegant logic from the structure–conduct–performance model of markets
2. Concepts of new instuonal economics to make sense of real‐life markets
3. Elements of markeng research to characterize the relaonships between IP members
4. Markeng and development literature to idenfy statements that characterize the
different elements of IP ‘conduct’ and ‘performance’
Building blocks for the conceptual framework
Field research methodology
• Volta2 project (SNV, CSIR‐ARI)
• CRP Policies instuons and markets
• CRP HumidTropics
Data analysis methodology Current partners
Call for further collaboration
More partners welcome to field‐test the
conceptual framework in their local
secng