Actually, this essay on the topic is great and actionable: support Ben's Speculative Technologies project!
I don't think we necessarily need more economic theory related to innovation, unless it's informed by new data and facts (which it is sometimes!). I just feel like we had that in spades for decades.
The biggest blindspot for economists of innovation that I worry about is that, actually, incentives just don't matter as much as we think. Engineering innovation may be much more a problem of finding the right people (not just right skills, but have a creative personality open to novel solutions), bringing the right people together, and so on. I'm not sure the right field to learn from on these topics though; still it's something I think a lot about!
Afraid the implications are limited for the time being. Competition policy and innovation is a big and active research area, and one that I haven't dug into yet. It's too big a topic for one article.
Different kinds of institutions are good at different kinds of things, and you ideally want a portfolio of different institutions.
There are probably other institutional arrangements better suited to different kinds of innovation too; most of these institutional arrangements are not that old, as institutions go! I think, for example, that there are probably ways to improve the organization of academic research. And the private sector has to some extent retreated from basic science, and we may need new institutions to fulfill the kind of role they used to do.
A really good research agenda needs to have two features: it should be an important problem, and you need an angle of attack on it. In the case of the economics of innovation, I think that biases the field towards studying sectors where there is readily available data, whether those are patents, granular data on productivity, approved drugs, or whatever. A lot of low-growth sectors - education, construction, government - are maybe areas where high quality data isn't as readily available. Or in some cases, innovation-relevant data might actually exist, but a critical mass of scholars don't understand it, which makes it hard to study and get good feedback on your work.
That said, there is some work on this. Personally, I'm excited to look into this handbook that examines the pace of entrepreneurship and innovation across a bunch of different sectors. Also check out Brian Potter on the construction industry specifically!
Yeah, this is a hugely important topic that is tough to appreciate from outside. I'm fond of this quote by Duncan Watts:"For 20 years I thought my job was, as a basic scientist, publish papers and throw them over the wall for someone else to apply. I now realise that there's no one on the other side of the wall. Just a huge pile of papers that we've all thrown over."The conventional wisdom is that, at least in the USA, you need a think tank apparatus that specializes in digesting academic literature and packaging it for policy-making. That's one of the roles that the Institute for Progress plays on the metascience front. Also, this general topic is something I hope to look into more as a New Things Under the Sun post.
It's been great that people I respect like the project, but the most important thing about it becoming popular is that I now get paid to do it. People sometimes say if you get paid to do something you previously did for fun, it kind of ruins it for you because it becomes work. That hasn't been my experience, probably because (1) I don't stress about view counts or anything anymore, and (2) I work on it a few hours each M-Th, but it's not my entire professional life (much less my whole identity).The main thing that has changed as the project has become bigger is that it's more ambitious than it was at the outset. Mostly you can see that in the length of the articles, but also a bit in the work I put into the site infrastructure. I still write what I think is interesting, though other stuff I'm working on at the Institute for Progress and now at Open Philanthropy has some influence on what I think is interesting.Probably the hardest part is knowing how much cool stuff is out there that I don't have time to get to!
Probably the most concrete topic I've written the most about is the geographic distribution of an R&D workforce. I think one of my main takeaways is to not assume that everyone working together in the same building is as good as it gets, in terms of innovation, though it depends on the industry. Reasons to consider a more distributed workforce:
That said, a distributed workforce offers its own challenges. You have to be more intentional about facilitating random meetings among different parts of the org for one, or you risk excessive siloing. And I think occasional in-person meetups are also important.
If you think nothing matters as much as getting the right people, then this is all the more important!
Some of my favorite papers on corporate innovation is the works of Ashish Arora and his colleagues, who are actively working on this stuff.
I will cheat and list two ideas, plus one irrelevant one.
First, let's start with some large-scale descriptive statistics of practices!
The goal is to see if there are obvious best practices; what kinds of stuff is correlated with good outcomes? This would be some kind of large-scale survey.
Second, I've always wanted to know more about the political economy of R&D. How do governments decide how much to spend on R&D? I'm not sure the best way to study this though.
Third, my dream research project, after we have sorted out the more important stuff, is to use the decadal Sight and Sound Greatest Movies of All Time poll to study how people's perception of artistic greatness changes over time. Do people change their minds? Or is it all about new (younger) critics embracing newer films?
I think three different things might be true:
I'm pretty confident about #1 and #3, less sure about #2. We certainly are trying harder, but maybe not enough to keep the overall rate of progress steady. I go back and forth on this, but at least think the case for a slowing rate of progress is not nearly as strong as the case for #1.
Why is #1 true? I think it's a combination of things. To a large degree, this just seems to be an inevitable feature of advancing knowledge; the burden of knowledge gets heavy, and maybe we also pluck some of the low hanging fruit. But a non-negligible part of the slowdown is probably due to the way we organize and conduct R&D. Improving that would have really high benefits, even if we're probably not going to go back to the era when a handful of gentleman scientists could make giant advances.