innovative innovation research

It’s been fascinating to see the reaction to the announcement that Oliver Williamson and Elinor Ostrom will receive this year’s Nobel for economics (and if you want to argue about whether or not it’s a real Nobel, let me refer you to Felix Salmon’s take on the issue, which I endorse!). As I said yesterday, I’m particularly happy about Ostrom winning. I’m not sure I explained why very well yesterday, so I’m going to take another crack at it.

Ultimately, I would like to see business research start to look more like biology, or geology (or, really, any of the natural sciences). This is part of why I ended up thinking of myself as an evolutionary economist. One of the things that economists and management scholars don’t do very well is observe and classify – which is the first step in the natural sciences. Because the economy is a complex adaptive system, it is often very difficult to directly measure the things that we are most interested in – consequently, a lot of the data that is used consists of proxy measures (Michael Martin has some interesting things to say about these issues on his blog). A big part of the reason that I love Ostrom’s research is that she starts with observation and classification, then builds theory about how the complex system works based on these rigorous first steps. Mario Rizzo describes this process well:

The central problem on which her employment of the notion of “thick rationality” can shed light is what she calls “social dilemmas.” These are circumstances in which interacting individuals can easily succumb to maximizing their short-term interests to the detriment of their long term interests. To return to our irrigation example, suppose farmers share the use of a creek for irrigation. They face a collective problem of organizing to clear out the fallen trees and brush from the previous winter. Each farmer would like to have the others do it. There are incentives to free-ride on the “public spiritedness” of others – however, everyone may think this way and nothing will get done. Ostrom finds that cooperation will often take place while the “thin” theory of rationality predicts that it will not. She finds that factors such as face-to-face contact (likely when there are small numbers), the equality of each farmer’s stake in the benefits of irrigation, and the ease of monitoring the farmer’s contribution to brush removal all make the likelihood of cooperation greater.

I think this is exactly how social science should be done. We should observe, count, measure and then classify. Only then can we build models and theory. Those first steps are often boring, tedious and difficult but they are the foundation of created usable models. They are also essential for understanding the limits of our models and under which circumstances they will not apply. One of the worst criticisms that economists make of economic research is that it is not ‘theoretically motivated’ – I’ve heard that a few times about my own work. Well, I don’t think it has to be. Instead of doing theory-rich speculation, I think we’d be better off doing observation-grounded theory development. So if you’re interested in researching or managing the innovation process, the first step is to get out there and start counting!

(picture from flickr/gbaku – creative commons license – for the creative commons take on Ostrom, check out this post)

Student and teacher of innovation - University of Queensland Business School - links to academic papers, twitter, and so on can be found here.

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