2. Lens for exploring the generation, spread, and use of new
agricultural knowledge, along with the social, economic, and
political forces that shape the process1,2,3
Politics
Culture Environment
Research Extension Farmers
Economics Values
2,3
• Innovation is putting something new into use
1
• Technological or institutional (way of organizing or process)
3
• Not necessarily brand new, just new to the user
2
• Often many innovations in a ‘package’ and often spur more innovations
3
• Blurred roles…all actors can generate, spread, and use knowledge
3. • Multi-year project to improve beekeeping training and
participatory extension in Vietnam
• Involved two universities, a national ministry, and a bee research center
• Introduced new basic hive design which required project team
to adapt instruction methods
• Both have spread rapidly in the wider region
• People are modifying hive design….these are spreading too!
• Multi-layered value chains have established themselves
• People are better off! Minimal added
‘Spaces’ for labor
Docile native learning and Insatiable
bees Honey acts as sharing demand for
History of
store of social honey
beekeeping
capital
4. • Classic methods fall short
• Innovation systems are unique and constantly changing5
5
• comparisons or generalizations impractical
• Need to adopt a learning approach to evaluating AIS
performance and interventions
• Delve into how and why to understand trends6
• Qualitative techniques are useful for understanding complex
situations
• Paint a focused, rich picture
• Key Questions7:
• Who are the players and how do they interact? What drives them? What
influences the system? What is/not working?
5. Experience
Mapping [For
data collection]
Observations
/ Visits Mind Causal Process Training
Mapping
Theory of
Journaling Change Crowd Source
Stakeholder Maps
Social Media Consultations
Dialogues
Experimentation
Visualizing
Innovation Histories
Most
Reflect
Acting/Implementing Exploring Significant
Change
Deciding Analyzing Net-Map
Scenario
Social
Planning
Network
Action
SWOT Analysis
Planning Stakeholder
Priority
Outcome Setting Analysis
Mapping
Foresighting Venn Diagrams
Nominal
Group Matrix
Flow (adapted from
Diagrams presentation by
Hambly Odame,
2013)
Conceptualize
• Many tools and methods for various needs and stages
• Mix, match, and adapt for the specific situation!
6. • Social Network Analysis
• Understand who is involved & how
they are connected
• Explore motivations, power,
structure of network
• Participatory
• Diverse actors & vantage points
requires everyone to get involved Boru Douthwaite
and have a stake in running the
show
• Story/Experience
• More useful than numbers for
understanding how and why things
are the way they are, especially at
Micro & Meso scales/timeframes
idrc.ca
7. • Ex-ante approach where stakeholders reflect on experiences
• Build innovation timeline , network maps, and learning histories
• Similar to case studies
• Used in situ: improving performance, ex situ: general strategies
• Beekeeping Extension in Vietnam:
• Chronicle the spread of hive designs, instruction methods, and subsequent
innovations
• Map extension, project, community, and value-chain networks at various
stages
• Gather stories of stakeholders
• Strengths: detailed profile, builds shared understanding
• Weaknesses: hindsight bias, lessons not immediately apparent
8. • Participatory tool for understanding social networks
• Easily adaptable to a wide array of situations and needs
• Key stakeholders map out connections between system actors
• Depending on purpose, aspects like motivation, influence, and strength of
connections can be examined and plotted
• Used for planning, reflection, monitoring, evaluation
• Beekeeping Extension in Vietnam
• Map extension system (before, during, after, ideal)-who is talking to who?
• Map community networks-who is excluded from ‘learning space’?
• Strengths: wide application, easily used with other tools
• Weaknesses: requires strong facilitation skills, possible
reluctance to share sensitive information
9. • Flexible alternative to traditional logic model
• Contribution to an outcome rather than claim attribution
• Guides intervention by focusing on actors, behavior, groups, and
relationships
• Begins with participatory visioning exercise, then the paths to
achieving the vision are plotted out
• Monitoring is built in to each step along the path
• What do we expect to ‘see’ at Stage X?
• Beekeeping Extension in Vietnam
• At beginning of project, subsequent projects by Vietnamese extension staff
• Strengths: adaptable, works with classic approaches
• Weaknesses: data collected by project team, unexpected outcomes
10. • Method for cooperatively managing change with diverse group of
actors…think ‘coalition management’
• Four steps:
1. Engage for shared understanding of context and perspectives in group
2. Formalize group: agree on goals & roles, establish operational structure
3. Implement and evaluate: plan (outcome mapping), define success
4. Build further: learn from stage 3, adapt operational structure, solidify
institutions
• Beekeeping Extension in Vietnam
• Layered dialogues with program team, ministry, universities, bee research
center tied in with regional and local stakeholder dialogue groups
• Strengths: pool resources & expertise, address complex issues
• Weaknesses: time commitments, requires openness & understanding
11. • How can quantitative methods contribute to understanding
Agricultural Innovation Systems?
• Will it be easier to incorporate them at certain scales and timeframes?
• How can other fields use the ideas and principles of AIS?
• What can they take away? What are some areas AIS can learn from?
• What are some ethical concerns here?
fao.org fao.org
12. 1. Hall, A., Dorai, K., & Kammili, T. (2012). Monitoring agricultural innovation system interventions. In: Agricultural innovation
systems: an investment sourcebook. Washington, D.C.: World Bank.
2. Hall, A., Mytelka, L., & Oyeyinka, B. (2006). Concepts and guidelines for diagnostic assessments of agricultural innovation
capacity UNU-MERIT, Maastricht Economic and Social Research and Training Centre on Innovation and Technology.
3. Assefa, A., Waters-Bayer, A., Fincham, R., & Mudahara, M. (2009). Comparison of frameworks for tudying grassroots
innovation: Agricultural innovation systems (AIS) and agricultural knowledge and innovation systems (AKIS). Innovation
Africa: Enriching Farmers Livelihoods, , 35-56.
4. Otis, G. (2013). Beekeeping extension in vietnam. Video: <http://www.youtube.com/watch?v=44vn_jonGVg>
5. Hambly Odame, H. (2012). Assessing innovation for prioritizing investment. In: Agricultural innovation systems: an investment
sourcebook. Washington, D.C.: World Bank.
6. Hambly Odame, H., Hall, A., & Dorai, K. (2012). Assessing, prioritizing, monitoring, and evaluating agricultural innovation
systems. In: Agricultural innovation systems: an investment sourcebook. Washington, D.C.: World Bank.
7. Schiffer, E. (2012). Using net-map to assess and improve agricultural innovation systems. In: Agricultural innovation
systems: an investment sourcebook. Washington, D.C.: World Bank.
8. Douthwaite, B., & J. Ashby. (2005). Innovation histories: a method for learning from experience. ILAC Brief 7, CGIAR.
9. Kammili, T. (2011). A briefing paper on monitoring and evaluation practice for rural/agricultural innovation: how do you
measure the impact of innovation initiatives? LINK Policy Resources on Rural Innovation, Hyderabad: Learning, Innovation, and
Knowledge (LINK).
10. Kunkel, P., Gerlach, S., & Frieg, V. (2011). Stakeholder dialogues manuel. Deutsche Gesellschaft für Internationale
Zusammenarbeit (GIZ) GmbH www.collectiveleadership.com
Qualitative Techniques for Assessing Agricultural Innovation Systems by Steve LeGrand is licensed under aCreative Commons Attribution-
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