351but they also create new blocs and help existing CIBs evolve. If their innovations are sufﬁciently disruptive, they can also cause the demise of existing CIBs (Beltagui et al., 2020). The process frequently begins when an entrepreneur identiﬁes and attempts to develop a potential opportunity into a successfully commercialized innovation together with an inventor and a small number of key personnel. Financing is critical in this uncertain, experimental stage. Early-stage ﬁnanciers like VC ﬁrms usually propel the project into a scale-up phase, during which the conjectured entrepreneurial proﬁts can be realized (assuming the project reaches this point). While VC ﬁrms can substantially reduce uncertainty by concurrently investing in many young ﬁrms, entrepreneurs typically invest all their human capital and most of their ﬁnancial assets into their venture, thus being unable to mitigate any uncertainty through diversiﬁcation (Knight, 1921). A varied and competent VC industry is, therefore, a crucial aspect of the early-stage selection machinery of the CIB.

To scale up the business into a fully grown ﬁrm, entrepreneurs also require more key personnel, permitted and able to act upon the knowledge only they possess to promote intra-ﬁrm discoveries (Foss, 1997). When these conditions are met, the ﬁrm should react quickly to change and encourage innovation by way of intrapreneurship. Eventually, later-stage ﬁnanciers assume responsibility for ﬁnancing, which may be substantial. At this point, the innovation may have resulted in the emergence of new ﬁrms as perceptive competitors begin imitation efforts. The market grows through the operational scaling-up of activities resulting from differential growth and selection (Metcalfe, 1998), ultimately resulting in the emergence of a new industry. Most ideas do not get this far—most business ideas and businesses fail (Hall & Woodward, 2010). Moreover, the ideas that are eventually commercialized may differ substantially from the idea that provided the igniting spark. Especially in the early stages, customers acting as demanding collaborators may be essential sources of information and offer critical inputs and feedback that shape emerging innovations (Bhidé, 2008; von Hippel et al., 2011). Errors are ubiquitous in this process, but so are plan and error corrections, as actors ﬁnd ways to cross technological, economic, social, and institutional hurdles through trial and error and learning by doing, guided throughout this search by markets and prices.

How Do “Modest” Interventions Affect CIBs?

3

Before turning to the issue of how government interventions, especially missionoriented innovation policy, affects CIBs, we should note that most CIBs are subject to an entanglement between the economic and political realms. First, politically N. Elert and M. Henrekson

352instituted rules and regulations fundamentally affect the strength of interactions between the different actor categories, their incentives to acquire and use skills, and ultimately the quality of the collaborations that come about (as discussed in all our previous articles on the subject, most recently Elert & Henrekson, 2021). Moreover, political appointees and state-owned ﬁrms can be big players in a CIB (although they exert inﬂuence rather than control; Wagner, 2016), e.g., as important customers or ﬁnanciers. This is the realm of direct government involvement, the scope of which can differ widely. Before discussing mission-oriented innovation policy, we will devote a few words to more limited interventions.

No speciﬁc agent inside or outside of the innovation bloc is in charge in the CIB—in fact, no one understands more than a fraction of the ecosystem’s inner workings (cf. Autio, 2016). In fact, the uncertainty shrouding all innovative efforts is a central reason why top-down “command-and-control” approaches should be undertaken with great humility. Because we are effectively dealing with a complex system, misguided policy interventions need not only be ineffective; rather, effects can be cascading, spelling doom for the entire CIB. And while the inverse—that good policy interventions may have beneﬁcial spillovers for all actors in the bloc— may also be correct, the likelihood of being wrong in the context of a CIB is arguably at least as large as the likelihood of being right. After all, most business ideas do not survive, hence the strategy of spreading “attempts in as large a number of trials as possible” characterizing much of venture capitalism (Taleb, 2012, p. 235). Those ideas that do survive will usually do so not because they were perfect from the start but because their creators and caretakers responded to ever-changing conditions, adapting their ideas until they became marketable. Adding more (public or private) money does not change these fundamental facts.

Analyzing (fairly) limited state interventions and how they affect CIBs is attractive because they are more tractable, at least on paper, although there is no shortage of such instruments. In a survey, Bloom et al. (2019) argue that the top ﬁve policies for boosting (technological) innovation are as follows: (1) offering tax incentives for R&D; (2) promoting free trade; (3) supporting skilled migration; (4) training workers in STEM ﬁelds; and (5) providing direct grants for R&D. Among other strategies that may boost innovation, meaning the evidence is not yet in, they list the following: (1) providing incentives for university researchers; (2) engaging in intellectual property reform; and, interestingly (3) embarking on mission-oriented projects. While it is encouraging that policy levers (tax incentives and grants) aimed at increasing R&D seem to work, it is noteworthy that Bloom et al. (2019) essentially offer no real deﬁnition of innovations. Instead, they (subconsciously) seem to subscribe to a Schumpeter Mark II view of the world (Malerba & Orsenigo, 1995), effectively equating innovation with R&D except in a few instances. To us, this is obviously a far too narrow and mechanistic view of what innovations are and how they come about. In fact, a key point of the CIB perspective is that R&D is—at best—just an igniting spark to create an innovation that beneﬁts consumers.

353Collaborative Innovation Blocs and Mission-Oriented Innovation Policy: An. . .

How Does Mission-Driven Innovation Policy Affect CIBs?

Mazzucato (2018) argues that mission-oriented innovation policies (should) tackle grand challenges such as climate change, demographic, health, and well-being concerns, and the difﬁculties of generating sustainable and inclusive growth. Her article presents six lessons that policymakers should draw on to make such missions a reality, based on evidence from previous mission-driven innovative projects. It is an informative read, although as Bloom et al. (2019, p. 179) put it when discussing mission-oriented policies under the label moonshots, “it is difﬁcult to bring credible econometric evidence to bear on the efﬁcacy and efﬁciency of moonshots. [They] are, by nature, highly selected episodes with no obvious counterfactuals.”

This seems to us the nature of many economic puzzles of real signiﬁcance.