Julius Nyangaga about using SNA to understand innovation systems

Dr Eva Schiffer recently took us (a group of researchers from the International Livestock Research Institute, ILRI) through an introductory session to Social Network Analysis – the concept, the methodologies, its application.  Most of us were from the innovation side of the research world where qualitative constructs and processes in systems are easily appreciated. But deep inside (at least for me, and I am sure for most participants) we were anxiously looking for what promised to deliver quantitative bridges through which we could explaining meanings to number-minded die-hards.

The course (and the tools) did not disappoint.  All participants were ecstatic about the course, because through SNA we could now analyse systems from a ‘connections’  point of view, especially when considering actors (individuals, groups, organizations, or institutions) and their possible relationships (e.g. information flow, product or service delivery, income payments, influence, etc.).  The use of the software programs (VisuaLyzer and UCINet) to graphically display these actor-relationships was invaluable, but even more powerful was quantification of the patterns of relationships. Properties such as size, density and degrees of connectivity, centres of network or actor power and influence, subgroup types and clique or cluster analysis, etc. could be presented in numbers, charts and models

However, when considering how we want to communicate with our professional colleagues we are challenged by definite facts stated clearly about SNA. For one the concept works on very distinct actors rather than populations. A link should come from a clearly defined actor to another. Most published examples seem to only use such systems – Jane is a friend to James, who is friends to John and Mary. But we want to use representative samples for statistical inference about populations? Should SNA only be limited in application to systems like organizations where the actor is an easily observable Mr or Ms So and So? How do we present large numbers of certain actors (farmers, traders, pastoralist communities, or even a population of vectors in disease transmission studies)? How do we present mass media (newspapers, radio)? We wanted to use SNA to analyse innovation systems, e.g.  farmers get market information from extension officers; the regulation offices sends out policy messages to its field agents, who share these with traders, etc. Am I missing something here about the potential use of SNA?

The second challenge lies in the fact that actor ties (or links) are indicated in binary measures, i.e. the relationship is only either present (=1) or absent (=0). This may be inadequate if one was to assign scales to the ties for certain types of analysis, e.g. level of ‘influence power’, or percentage of returns earned by one actor from another. For example, farmers can share production information among themselves (how do you present this?!!) but they find links to extension agents for the same more valuable. Or market actors in a value chain are linked by product flow and revenue earnings but returns at each link vary and we want to use SNA to analyse for bottle necks and efficiencies. How can we develop questions that elicit binary responses be framed to show weights of link? How do we use graphical displays and quantified analysis to show such products – after all value chains are in many cases graphical constructs that should tell certain tales?

This is my first post on this log and the challenges I have stated and questions I have posed may be old hat to many out there. If you have already figured that out, please help those of us who are new the wood.

Julius Nyangaga,

Innovation Works, ILRI

2 Responses

  1. Hello,

    With respect to your question about mapping the relationships among actors (farmers, extension agents, etc), the tool that you want to look at is Value Network Analysis (VNA). I use VNA very often in conjunction with an SNA. Whereas SNA can show you the interpersonal relationships, the VNA shows how tangible and intangible value flows between the actors.

    See: http://valuenetworks.com/, a paper describing the method is available at: http://www.openvna.com/howToGuides/A_ValueNetwork_Approach.pdf (I also describe the method myself in my book, Net Work.)

    Verna Allee and the VNA consortium have just released a toolkit for drawing and analyzing maps.

    I use both SNA and VNA in my practice, they are very complementary.

    best regards,

    /patti anklam

  2. Hi Julius,

    Your first question raises a methodological point that I have grappled with since starting to use SNA to understand information flows in both value chains and innovation systems. When asking farmers about their information sources I generally get a mixture of specific (individual) names, organisational names and also vague references to groups such as neighbours, NGOs or extension agents. From a communication perspective I find this interesting as it represents the relationships between formal and informal information sources and also shows that sometimes farmers associate more with individual extension agents than with the institution providing the service – in one study in which I asked farmers to name both the extension agent and their organisation one particular actor was named in association with 4or5 organisations and was clearly the key broker in the network. Feedback interviews confirmed that he had changed organisational affiliation regularly but this had not reduced his influence on the innovation system. My own solution to this formal-informal dilemma is to ask respondents for both individual and organisational names and to include vague references but to give them all the same attribute code so it is possible to see their influence in the network but they are also easy to remove from the network to conduct metric calculations.

    With regard to the use of binary coding – it is possible to use valued coding and increase the value of ties to represent an increasing scale. I also use value coding to give qualitatitive values in the context of agricultural information 1= soil management, 2= seed varieties, 3 = planting etc. Again this is obvioulsy unsuitable for calculating metrics but Ucinet will allow you to calculate binary metrics in valued networks.

    Thanks for the link about VNA Patti, am very excited to check that out.

    Hope this is useful
    Louise

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