Accelerators and incubators are business support programmes that provide co-working-based packages of support to young firms to help them grow. Widely used in the tech sector, they are now increasingly applied in other industries – including retail, fashion and design and household goods – even in the Bank of England.
Accelerator and incubator spaces are also an increasingly visible feature of UK cities. In particular, there’s been an explosion of co-working, incubator and accelerator provision in London: in 2014 there were at least 132 programmes, 50% of which had arrived since 2012. Today there are at least 156 co-working spaces alone in the city, equating to hundreds or thousands of desks. Together with pop-ups, co-working and evolving high streets, these flexible spaces and practices are – arguably – starting to change the wider urban fabric.
We define accelerators and incubators using this table adapted from the Harvard Business Review.
Put crudely, accelerators (like YCombinator or Seedcamp) offer short-term, intensive support to a competitively selected group of firms; while incubators (like TechHub) offer less-intensive, more ad-hoc support to firms on a rolling basis. Accelerators don’t charge, and may take equity stakes; incubators typically charge rent.
In the jargon these are ‘ideal-types’; in practice we see spaces (such as Second Home) which combine features of both.
We found 10 accelerator evaluations that passed our quality filters, and another seven for incubators.
These provide good evidence that accelerators increase employment for firms who take part, compared to losing applicants (or similar non-participants). One of these also looks at firm sales, again finding a positive effect. The evidence for incubators is also positive, though less clear-cut.
We find strong evidence that accelerators help cohort firms to raise external finance post-programme, typically angel or VC money. For incubators, we didn’t – surprisingly – find any studies that tested this.
Strikingly, both types of programme have a pretty mixed impact on firm survival: of the four accelerator studies that test this, for example, we find one positive, one mixed and two negative results. What’s going on here? The most plausible explanation is that accelerators help participants to quickly gauge the quality of their ideas (e.g. via investor / peer feedback on demo days) and encourage those with weak propositions to quit early. That is, the programmes help kill bad ideas: one provider we spoke to told us they run ‘startup funerals’ to commemorate their passing, as founders move on to new things.
It’s rather harder to figure out just how accelerators and incubators achieve these effects – and thus, how to design programmes that reliably get to these outcomes. In part this is because fewer evaluations have explored these issues – so the following results need more caution.
For example, we find no clear differences in outcomes when comparing public and privately-run accelerator programmes, although among the latter group, top programmes in the US (like YCombinator or TechStars) do seem to achieve better outcomes. The evidence for incubators is similarly inconclusive.
We find that more specialist programmes (single industry) help survival compared to more generalist programmes. For incubators, training seems to be more effective than networking, although neither has much impact.
Significantly, what goes on outside the building also seems to matter. For incubators, having university involvement is helpful (although this doesn’t apply when individual academics step in). Two accelerator studies find that programmes in regions with denser entrepreneurial networks and high property values achieve better employment and funding effects. Not surprisingly, firms in these programmes are more likely to get funding from local investors.
Overall, we were impressed by how much high quality evidence already exists for accelerator and incubator impacts. We hope local policymakers will be able to work productively with providers to fill in some of the remaining gaps. Many of these are around how programmes achieve their overall effects, and how to consistently replicate this. More broadly, we also need to test accelerators against incubators, and against traditional business support. We also need a clearer sense of programmes’ cost-effectiveness. We’re not able to find cost data for incubators in the available studies – but we provide some back-of-the-envelope numbers suggesting that accelerators are pretty expensive to run.