To elaborate somewhat on what was just referred to as the entrepreneurial “division of labour” it is worth reiterating that what were once summarised by Schumpeter as four functions have by now been elaborated to at least seven, as follows.. Thus modern entrepreneurship research recognises, apart from the innovator, more than Schumpeter’s four roles in innovation, which were:
the inventor, who invents a new idea;
the entrepreneur who commercializes this new idea;
the banker, who provides the financial resources to the entrepreneur (and bears the risk of the innovation project);
the manager, who takes care of the routine day-to-day corporate management.
These roles are most often executed by different persons (Kenney 1986). Stam (2007) goes further in his review paper on distinctive roles found to be operating around innovation. He observed that nowadays these distinctions designate a complex-systemic (later “ecosystemic”; Stam 2015) - process whose key actors are as follows:
the person who bears uncertainty (Knight 1921);
an innovator (Schumpeter 1934);
a decision maker (Casson 2003);
an industrial leader (Schumpeter 1934);
an organizer and coordinator of economic resources (Marshall 1890);
an arbitrageur, alert to opportunities (Kirzner 1973, 1997);
an allocator of resources among alternative uses (Schultz 1982).
Accordingly, when one hears the somewhat simplistic injunctions that - to grow, regions should innovate – it is salutary to calculate the number and variety of skills and expertise required to actually move a “recombinant idea” into “practical commercialisation” status. This applies even more so to injunctions such as “entrepreneurial discovery.” Moreover, as implied in evolutionary complexity theory (ECT), which ponders novelty and the nature of its embedding economic fabric (Kauffman 2008; Arthur 2009) innovation requires a clear purpose to initiate and energise such a complex project exercise. This is discussed in the fourth main section. Without a core idea on to which knowledge and artifacts may be brought to converge on some novel practical and/or commercial solution or offering to the market-say “manned flight” or “mobile communication”- there can be no innovation. The mistake is over-simplifying “entrepreneurial events” by conceiving them as individualistic practice rather than being embedded in “entrepreneurial ecosystems” of interacting and complementary capabilities and assets (Stam 2015).
As a result of thinking through the interactive logic of key distinctive functions in the EDP it is rapidly evident that entrepreneurship is both more complex than hitherto believed by those who conceive it as the expression of pure individualistic “outsiderdom” and yet simultaneously in a commonsense way “washing its face” in profitability. This introduces the (questionable) concept of the “entrepreneurial ecosystem”. Questionable, because it proposes interactions among diverse skill-sets among enterprises, which are carriers of institutional value rather than atomised units of profit realisation. We shall return to this many times in what follows, tending to prefer the institutionally more accurate label (enterprise ecosystem) over the individualistic one. Thus it makes more sense to connect enterprise to the idea of an ecosystem, which (in economic terms) consists of interacting, value-creating entities embedded in a socio-technical system (STS) or context that sustains both.
It is meanwhile worth reflecting that entrepreneurial interactivity may display constraints of institutional “path dependence” that can habitually and easily cross the boundaries of legality. Enterprise ecosystems are less “privatistic” as Stam (2015) refers to them. Thus, as an illustration, the sale by a British entrepreneur of 1,500 fake bomb detectors at a cost to Iraq’s interior ministry of £52 million occurred during 2008 and 2009. These were subsequently revealed to have been made from a metal aerial and an empty plastic box (“novelty golf ball finders”) and the fraudsters jailed for 10 and 7 years. The devices cost as little as £2 to produce but were sold for as much as £15,000 each, resulting in a trade worth up to £3 m a year.
Responsible British government department administrators and their agents promoted international sale of the devices, which are on record as having cost lives, despite a UK government warning they were useless. Even in 2015 after the Sinai terrorist attacks, tourists trapped in Sharm el-Sheikh continued to be victims of the Egyptian security services using the same bomb detectors that had been exposed as fake over the previous 7 years. Naturally, this is an extreme case, but it is testimony to characteristics of entrepreneurship that are overwhelmingly rent-seeking and exploitative. Accordingly, they are shared to a far lesser degree than the explorative and often “disinterested” features of innovative activity. Yet, to reiterate Stam’s (2015) observation above, the actors involved constituted an entrepreneurial ecosystem of military businesses supported by numerous government agencies, military engineering assessors “experts” and military marketing professionals from overseas trade shows to foreign sales networks.
So this is, in so many ways, from fraud and corruption to multi-client incompetence, a bad entrepreneurial ecosystem. To be as fair as possible in adjudging the potential for benign, collective exploitation of entrepreneurial ecosystemic behaviour, the following helps to balance up the picture. Here, a widely implemented business model involves social enterprise for employment and skills training. The entrepreneurial aspiration here involved building an online community of computer workers, hired from underemployed communities. The programme trained each of them to undertake, for example, a single language programming exercise or translating of code for a common application program interface (API). Recombining such skilled cohorts of practised entrepreneurs allows them to complete a service for a client that would normally only require 1 or 2 people. Accordingly, this exploits synergies among highly micro-specialized professionals. These reap both scope and scale advantages from divisions of labour which may form a “virtual assembly line” allowing faster task completion, lower service cost and higher quality standards. This scores particularly well over traditional outsourcing by general practice knowledge workers. Incomes and job satisfaction are higher from virtual assembly-line set-ups. This demonstrates that entrepreneurial ecosystems can be profitable, communal, based on learning and socially benign.
Two final points round off this preliminary analysis of the entrepreneurial ecosystem idea before a comparable exercise is conducted for the regional innovation system model. Two things remain to be tied up at this point. First, it is patently clear from the above discussion that entrepreneurship and innovation or their agents, entrepreneurs and innovators, are completely different in nature, skills and outlook. This will become even clearer in discussing the nature of innovation in the context of “novelty”, creativity and the idea of “newness” per se. In brief, the entrepreneur is profit-driven to a far greater degree than the innovator. The latter may be interested in profit-taking but may equally be disinterested in or indifferent to profit and - for example - more actively interested in awards or social respect as expressed in social or academic prizes. Venture capitalists routinely replace, in particular, academics from management roles in scientific start-ups, as a case in point. Entrepreneurial ecosystems, too, are largely driven and governed by market relations and the profit motive. But, second, as demonstrated in the exemplar of the “virtual assembly line” among computer entrepreneurs, such ecosystems are capable of collective, communal or “generative growth” that is not simply reducible to the bare “arm’s-length exchange” of the individualistic pursuit of profit. Accordingly, there is potential for the accumulation of social value and associated economic efficiencies and effectiveness that are superior to the traditionally hegemonic model of individualistic “property rights” entrepreneurship.
Innovation and the regional milieu
In the following sub-section we devote attention to the more established evolutionary economic geography architecture of “regional innovation systems” (RIS) well-rooted in a twenty-five year pedigree of theory, empirical analysis and policy application. Currently such policy implementation became the European Union’s required methodology (RIS3) for all regions in the EU to formulate their bids to the European Regional Development Fund for regional economic development assistance (€185 billion 2014–2020). For the first time since 1988 the EU programme budgetting methodology based on budgetary quantities, while retained as a financial management tool, shifted away from its purely procedural accounting approach to a more substantive, content-driven regional innovation policy (RIP) outlook. However, such are the “assumptive” ties that bind in Brussels that ideologically it remained wedded to a neoliberal economic EDP (entrepreneurial discovery process) model or “chaotic conception” requiring “smart specialisation” as its ideal regional scenario.
This overlooked at least 75 years of regional economic development research and policy analysis which demonstrated that economic variety is superior to specialisation. Forced to recognise this mistake by the EU’s own economic geography advisors, a new RIS3 injunction that specialisation was to be treated as equivalent to diversification (or variety) thus resulted in the “chaotic conception” at the heart of the EU regional innovation strategy. Nevertheless, with its new emphasis on evolutionary economic development processes as the rationale for spatial strategy formulation the RIS approach marks a big step forward in the large-scale financing and policy implementation of the regional “milieu”. Drawing attention to the importance of “regional milieu” emphasis is drawn to GREMI a Francophone RIP and economic geography community that first evolved the concept. It has three important elements, which build upon regional “varieties of capitalism”. To summarise first, GREMI has to explain why the regional level of activity and identity is important. This is notably because some sub-national areas are very distinctive, culturally, democratically and even economically while others are less so, having weak cultural markers, centralised administration and disarticulated economic activities (neither specialised nor diversified).
One way of conceptualising this is by means of an approach to innovation governance, suitably adapted, that facilitates understanding (Dosi 1982; Freeman and Perez 1988). Overarching the two key sub-systems in this variant of milieu theory is the “socio-technical system” (STS). A good example of macro-theorising, this is in reference to the dominant socio-economic era which, from the Industrial Revolution to the present day, remains under the hegemony of hydrocarbons. All long waves (after Schumpeter 1934) have been fuelled by carbonised production processes. But within that STS, some regions innovated woollen and cotton textiles, or shipbuilding, or coal and steel, or food processing, furniture, carpets etc. in what Marshall famously called “industrial districts”. These are the forerunners of “regional milieux”. Each milieu has an economic “paradigm” in which innovations (and subsequent “entrepreneurs”) evolve, are fashioned or designed. They may often display diversity or what is nowadays called “related variety”. Examples of this occurred in economic history after stagecoach building mutated towards bicycle manufacture, then motor-cycle manufacture and finally combustion engine vehicles. Often these mutations evolved in the same milieu, using similar raw materials such as steel, rubber and later, glass. Some later became aeronautics “milieux” and modern centres of expertise in systems and software. Together, although of different vintages, such milieux evolved over time by exploration in proximity of diversity. Such interactivity (which associates with “generative growth” most strongly) is based on synergies that derive from industrial relatedness. Together, these contribute in major “path dependent” ways to regional variety.
Complementing such a “regional paradigm” is what in the governance literature is known as a “regime” which in this context refers to the “regional regime”. This is an organisational structure of governance bodies such as ministries and various regional agencies or bodies that receive funding in support of regional innovation policy. Networks of interaction among such RIP actors and “paradigm” actors facilitate “generative growth” but not neoliberal competition in the same way. Such regions nevertheless may display distinctiveness because of this. At a different strata of activity is the “institutional” level, which is more informal or less formal than the organisational structure of the region. Here “assumptive worlds” on reputational, expectation and rules of the game grounds mould the regional “regime” actors into something like a regional institutional culture. This also contributes to regional variety such that industrial character may be isomorphic with regime character in comparable regions, even in different countries. Finally, at a relatively diluted level we introduce the “conventional” level where everyday practice outside institutional and organisational life occurs. So uses of language, trust, exchanging favours, sharing seasonal tasks add to the “regional regime” in the form of specific bonding or bridging capital, which also has some economic value and further contributes to regional related variety.
It now remains to perform a comparable effort for RIS and its associated RIP to that done regarding “entrepreneurial ecosystems”. It will be recalled that a binary good/bad ecosystem was hypothesised and supported with data. In this case, similar forms of disarticulated and articulated “paradigm” and “regime” relations will be explored. One of the most difficult RIS set-ups to deal with is one that has suffered a significant “resilience” shock. A paradigm case of this occurred in my own territory of Wales, the RIP experience of which was written up in Cooke et al. 2004). We can say that, if not a leading STI innovation arena, this complex nevertheless displayed clear DUI innovation features.
Following the deindustrialisation of Wales, which culminated in the Thatcher government’s closure of most of the coal and steel industry, some effort was made at restructuring the economy. Before devolution in 1999, the UK government administration for Wales fashioned a strategy to intensify the level of investment, both domestic and overseas, in automotive and electronic engineering. By the 1990s the restructuring and downsizing of heavy industry had evolved. Accordingly, at that time, with 5 % of the UK's population and GDP, Wales attracted between 15 and 20 % of inward investment (FDI) in the UK (Cooke 1995).
This was not an “entrepreneurial ecosystem” but an “MNC-FDI ecosystem”, for unlike earlier FDI it involved little elaboration of supply chains or “open innovation”. But the influence of Asian and European FDI was different and anticipating supply chain formation from domestic and foreign suppliers. Thus Sony arrived in 1974, followed by Hitachi, Panasonic (Matsushita), Aiwa, Brother, Sharp and Orion, all involved in consumer or office electronics. Later, LG from Korea, wafer fabrication firms International Rectifier (US) and Trikon (UK), and components firms from Hong Kong and Singapore joined the cluster. With the exception of Sony, which transformed itself from a TV and computer screen manufacturer into a leading microcomputer for code-training (Raspberry) in the 2010s. However, Sony employs about 100 compared to 1,400 twenty tears or more ago, while Panasonic, Hitachi, Aiwa and Brother have closed their operations in Wales and LG from South Korea lasted only a few years. Needless to say, “open innovation” and supply chain elaboration came to a grinding halt.
In automotive industries, Ford opened an engine plant in 1978, followed by acquisitions or new, greenfield investments by Calsonic, Valeo, Lucas-SEI, Robert Bosch, Trico, ITT-Alfred Teves, Ina Bearings, Sekisui, Yuasa, Gillet, Grundy and Hoesch-Camford. By 1992 production of 200,000 engines a year by Toyota began as supply to their European assembly plants. Valeo, Robert Bosch and Lucas-SEI have retreated but others have remained and now a thriving “open innovation” set-up has recently been announced as the new location for Aston Martin’s luxury SUV (TVR sports cars also have Wales heading their location shortlist). Unlike electronics, automotives has proved more durable as a supply chain customer and RIP animateur. From 1999, the Ford Bridgend engine plant became the sole Zetec engine source, producing annually 700,000 of these and 55,000 Jaguar AJ26 V8 engines. New ranges of Jaguar and Land Rover engines were frequently announced in the 2000s, to be produced at a rate of 325,000 per year. Subsequently, when these customers were sold to Indian MNC Tata they continued to source relevant engine technologies. Simultaneously, Toyota engine production expanded to 500,000 engines by 2003. Formerly deindustrialising Wales had evolved into a key centre of high-quality, high-skill automotive engine production in Europe, with 2,400 employed at Bridgend and 600 at Deeside in north Wales.
Two shocks occurred amidst these developments. First, much of the demand for MNC-FDI in electronics disappeared with its importance to RIP and the RIS in engineering. Thus losing Hitachi and Aiwa with its local suppliers association shared partly with its parent Sony, meant its supplier links disappeared. Global-scale crisis in Asia at the turn of the millennium meant that the South Korean government enforced LG to sell Microchip assets to Hyundai. So LG could never implement its strategy to support university research. At that crisis time, purchase by Tata of Corus Steel meant closure of its 200-person new materials research laboratory. Embryonic ‘Triple Helix’ relations among universities, businesses and government agencies atrophied with the loss of regional personnel to act as intermediaries and commissioners of research. The second shock was that large numbers of jobs were lost even during this “second restructuring” undermining Wales’ emerging reputation by some 44,000 jobs between 1998 and 2002. This meant that a further readjustment towards a “post-industrial” future and one based on less engineering had to be faced. One consequence of this was that the European Union recognised Wales as justifying the full measure of EU regional industrial and innovation assistance to the tune of some £3-4 billion from 2000 to 2020, a status that RIP has never managed to make significant inroads into in terms of “high-road”, well-paid manufacturing employment. In contrast, Wales has evolved into a “low-road”, “low-income” post-industrial retail and office-services economy. Needless to say, demand for RIP is scarcely buoyant under such circumstances.
RIS without RIP: innovation self-mutates
The most obvious RIS to transmute far more successfully, already by now a platform of intersecting clusters, is Silicon Valley. This is a type of RIS that displays strong, world-beating entrepreneurship rooted in its science and technology (STI) drivers that are primarily invoked by recombinant innovation (Saxenian 1994). It is widely referred to as an “entrepreneurial regional innovation system” (ERIS) because it doesn#t directly rely on the kind of public RIP strategising so common in Europe and many “developmental states” like Singapore and Taiwan, for example, in Asia (where the institutional regional innovation system (IRIS) is more pronounced). As is well-known, only a few of the original Silicon Valley semiconductor fabricators from the early days still have a presence in the core location, two of the best known being Intel and AMD. Alongside their suppliers and other design rather than fabrication plants we can say the original seed crystal survives. As for computer fabrication, clearly Apple, an original Cupertino locator from the early 1970s, and many of its suppliers (though many more are now in Asia) remain or join and - like Intel, a long-term Apple supplier - thrive and grow. Newer entrants, grown to giant scale, like Google and Facebook also thrive in this ICT ecosystem and to an extent diversify in terms of related variety, notably Apple towards electric vehicles (EV) and Google into electric automated vehicles (EAV).
This somewhat imitates the earlier move of former PayPal entrepreneur Elon Musk who established the successful Tesla premium EV brand in Palo Alto in 2003. But, of course, before these mutations from ICT into EV and other renewable energy applications, Silicon Valley had also become a favoured site in which biotechnology start-ups and spin-offs could thrive. Accordingly, early movers, like Cetus and Genentech located in south San Francisco, arguably close to but not right in Silicon Valley, started the earliest California biotech cluster. In such science-driven (STI) innovation, proximity to the “mother-ship” in this case the University of California Medical School, was essential. Nevertheless, venture capital from nearby Palo Alto was also available and, in any case, the biotech funding model is different, with a large patron like Swiss giant Hoffmann LaRoche (now Roche) being a normal funding and research partner and, since 2000, owner of Genentech, the early dedicated biotech firm (DBF) in question. Other incumbents in the Silicon Valley biotech ecosystem have included firms like Gilead, Amgen (HQ Los Angeles) and AbbVie (former Abbott Labs). Though these are biopharmaceuticals firms, 40 % are in biomedical diagnostics, directly utilising ICT advances from their advanced electronics neighbours in many cases.
Up to the present Silicon Valley ICT and - to a lesser extent - biotechnology firms have undergone a third mutation into renewable energies, notably alternative fuels based on algae and other types of agro-food derived combustibles. Also moves were made - as noted - into EVs and other applications. Major green industries with a significant presence in the state are: Solar, Wind, Biofuels, Smart Grid, Energy Storage, Fuel Cells, Hydro, Geothermal, Green Building, Energy Efficiency, Sustainability and Electric Cars. The top ten occupations for green jobs in California by the number of green jobs in each occupation are: Carpenters involved in green activities filled 46,150 jobs; followed by hazardous materials removal and remediation workers at 43,470 jobs; 43,110 people were employed in green, sustainable or organic agriculture; there were 40,350 assemblers working in green manufacturing; 36,060 recycling centre operators; 24,750 electricians worked in green sector jobs; there were 23,000 plumbers, pipefitters, and steamfitters working in green economy related jobs; 21,670 architects (excluding landscape) worked in green economy related positions; 20,340 industrial production managers found employment in green sector areas; and 19,330 construction managers worked on green projects. Jobs also grew in the Silicon Valley (& San Francisco) smart grid sector from 1995 to 2011. Thus between 1995 and 2011, smart grid employment more than doubled to 17,800, up from 12,560 in 2009, and more than double the number of those jobs in 1995 (Cooke 2015).
It may briefly be concluded that Silicon Valley displays the two key modern-day forms that combine both innovation systems and entrepreneurial ecosystems. Historically, as Saxenian (1994) shows it displayed the kind of communality, shared communities of practice and, strikingly, a dynamic transformational “platform”- like interactivity based on recombinant innovation. In the absence of public economic governance more typical of RIS set-ups, community action was capable of being activated by the economic community who often co-inhabited the “silicon localities” in proximity with their workforces from whom they recruited. Nowadays, a new wave of less benign, excess-driven entrepreneurialism sees the San Francisco skyline changing wth luxury skyscrapers and infrastructure of a far more exclusive kind represented by “Google Buses”. One of the key facilitators of this transition is the absolute social polarisation that has occurred by the awarding of huge shares of entrepreneurial wealth to an undeserving minorities of --“super-entrepreneurs”. Thus we may conclude that there is some symmetry in the conceptual and empirical vignettes that have been mobilised in support of our thesis that innovation tends to be communal while entrepreneurship tends ultimately to be individualistic and exclusive. Accordingly, while both display system or eco-system type qualities, those associated with innovation are less inegalitarian, less market-reifying and more attached to the disinterested pursuit of knowledge for its own sake. This inclines innovation towards the recombinant and interactive side of the equation while the entrepreneurial ecosystem is, in general, more imitative and profit-motivated with a relatively lower-profile moral business posture.