HIGH SKILL ECOSYSTEMS
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University of Southern California
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Oxford Review of Economic Policy
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A decade ago David Soskice and I described Britain as trapped in a low-skill equilibrium:
“a self-reinforcing network of societal and state institutions which interact to stifle the demand
for improvement in skill levels…(resulting in) the majority of enterprises staffed by poorly
trained managers and workers produc(ing) low quality goods and services (Finegold and
Prior to that, the prevailing explanation for the low skill levels of the British workforce was cultural – that
the British class structure had instilled a set of anti-education and anti-industry attitudes that discouraged
investment in the skills needed for a modern economy (Wiener, 1981). We argued instead that the
decision by most British young people to leave school at 16 with no recognized qualification (still the
case in the mid-1980s) could be seen as a rational response to the set of incentives they faced. These
incentives were shaped by an education system that offered few opportunities for the majority who
could not qualify for higher education, and a youth labour market that offered no premium for additional
years of educational investment that did not lead to a degree. Likewise, we showed that most
managers’ decisions to adopt a low-skill form of work organization, even if it hurt the performance of
the British economy as a whole, could be seen as a rational response to the institutional conditions – e.g.
short-term financial markets, an adversarial industrial relations system, a low supply of skills in the
labour market – in which they operated.
One advantage of an institutional over a cultural explanation of Britain’s skills shortfall was that it
suggested that if the incentives facing firms and individuals could be altered, then Britain might be able to
break out of the low-skill equilibrium. Britain, however, has historically lacked effective corporatist
institutions, such as strong employer organizations, capable of overcoming the market failure problems
associated with convincing firms to invest in transferable skills; past government efforts to remedy this
deficiency (the Industrial Training Boards and Manpower Services Commission) have not proved very
successful. Hence, we (Soskice, 1993; Finegold et al., 1990, 1992) have argued for a focus on greatly
increasing the participation in full-time further and higher education as a first step toward making the shift
toward a higher skill economy.
This is in fact exactly what has begun to occur in Britain over the last decade, in part by accident and in
part by design. Britain entered the 1980s with just 7% of the working population possessing a
university degree and one of the lowest levels of participation in post-compulsory education in the
OECD (NEDO/MSC, 1984); by 1995, there had been a dramatic increase in staying-on rates, with
close to 25% of young people obtaining a bachelor’s degree, a level comparable to the U.S.’s mass
higher education system. While Britain has been improving its education participation rates, so too have
most of the advanced industrial countries; as Table 1 illustrates, Britain continues to trail some of its top
competitors in the percentage of young people staying on in education until the age of 18 and obtaining
economically vital intermediate (craft or technical) qualifications.
INSERT Table 1
Ironically, the badly needed reforms of the higher education system that were a key factor contributing
to an improvement in the supply of skills leaving the education system may have inadvertently
undermined Britain’s capacity to create high-skill enterprises (for a more complete discussion of the
factors leading to improved education participation rates see Finegold, 1992). In the late 1980s, the
government merged the polytechnics and universities into a unified higher education sector and
overhauled the funding formulas for post-compulsory education. This channeled additional resources to
those institutions that were able to expand student enrollments most significantly at the lowest unit cost.
While the competition among providers for a smaller cohort of young people
led to a major increase in
the percentage of individuals participating in higher education, this competition tended to favor
institutions concentrating on undergraduate education over world-class research institutions. Just as
universities have a key role to play in fostering a high-skill economy by creating an adequate supply of
highly educated manpower, so too the research that they produce can be a key enabler of new high-
The remainder of this essay will focus on two of the world’s most dynamic and successful economic
regions: California’s dense concentration of biomedical and computer hardware and software firms
clustered between San Diego and San Francisco. It will show how these clusters or industrial districts
have become self-sustaining high-skill ecosystems (HSEs), that once started, generate a positive,
mutually reinforcing dynamic that fuels ongoing knowledge creation and growth and adaptation to
changing competitive conditions. An HSE is a geographic cluster of organizations (both firms and
research institutions) employing manpower with advanced, specialized skills in a particular industry
and/or technology. The basic concepts of the firm, individuals’ careers, and skill development will be
shown to operate differently in these HSEs than in the traditional economy. Among the key questions
the essay addresses are:
• Why are high-skill ecosystems important? What is their impact on wealth and employment
• What are the conditions necessary for creating and maintaining this type of HSE?
• How are the processes of skill-creation and incentives for investing in skills sustained in firms
that experience such high levels of labor mobility?
• What threats exist to the sustainability of these HSEs?
• Can this model be translated to the UK?
II. HIGH-SKILL ECOSYSTEMS
The low/high-skill equilibrium approach remains useful for understanding why Britain suffered from a
skills deficit and the set of institutional changes required to address this problem. The original
formulation of the framework, however, did have several, related shortcomings. First, while the stark
Between 1985 and 1995 the number of young people leaving the school system in Britain dropped by approximately
categorization of a national economy as either a predominantly high or low-skill equilibrium was useful
for theoretical purposes in illustrating the self-reinforcing nature of institutions and the interactions
between the supply and demand side of the skill equation, it entailed a major over-simplification of
reality. Not only are there significant high-skill regions existing within otherwise relatively low-skill
economies (e.g. in the Third Italy), but the classification of sectors or regional economies as either high
or low skill may itself be misleading. International comparisons of economic performance suggest that
there are at least three meaningful skill segments in most countries (intermediate or medium, as well as
high and low skill) and that the requirements for success in each skill segment may be very different
(Crouch, Finegold and Sako, 1999).
Second, like much political economy work of the 1980s, our examples tended to over-emphasize the
strengths of the Japanese and German approaches to skill creation and economic decision-making, and
underestimate the potential of the more market-based systems of the US and UK to compete
successfully in high-skill markets. Despite their recent economic difficulties, Japan’s state education
system and large-company-driven networks, and Germany’s corporatist dual system continue to be
world leaders in solving one of the key skill problems facing industrialized countries: how to get a large
majority of the population to a high foundation level of skills for entering the workforce? And they have
created companies that effectively use and continue to develop this large supply of workers with
intermediate skills to compete successfully in global markets (see Crouch, Finegold and Sako, 1999).
Where they have been less successful, however, is in generating major new research breakthroughs and
new forms of business services and the flexible, high technology start-ups that can turn these ideas into
successful enterprises. Japan and Germany’s relative failure in the highest skill markets, I will argue
later, is a product of the very same set of institutions that have made them successful in generating
supply and demand for intermediate skills.
These high skill, high technology operations are growing in relative importance for the advanced
industrial countries (AICs) for two reasons. First, because of the rapid pace of innovation and high level
of research capability and technical skills they require, the types of jobs in these sectors are the least
likely to move to lower wage nations as global competition intensifies; thus, for example, while
manufacturing and other elements of the value chain are becoming more globally distributed, R&D is still
largely concentrated in the country of origin (Galbraith, 1998). Second, in increasingly knowledge-
based economies it is these high skill firms that are generating the greatest share of wealth. In 1998, for
example, 9 of the world’s 10 corporations with the highest stock market capitalization were American
(none were Japanese or German) and the value of many of these firms (like Microsoft and Intel) was
primarily in intangible knowledge assets. And this wealth generation is no longer confined to an elite
few, but is rather distributed across a wide segment of the population: in 1997, approximately half of all
U.S. households owned stock, much of it in 401k pension plans that did not even exist entering the
1980s; these 401k plans now account for over $1 trillion in investment spread across 25 million
households (Peterson, 1998).
It is important to note that at least in the Japanese case, highly productive organizations appear to be generally
confined to certain exposed sectors of the economy, with much lower productivity in non-traded services.
A third shortcoming with the LSE/HSE framework is, as suggested by the term “equilibrium”, that the
analysis was more static than dynamic. Although there are very strong inertial forces slowing any
change in the skill composition of a national economy, the rapid pace of change in technology and global
competition reduces the value of static frameworks. This is particularly the case for the highest skill,
most knowledge-intensive portions of the economy on which this article focuses. Hence, the decision to
change the focus from equilibria to ecosystems. Both concepts highlight the interdependence of actors
in a system, but in the study of ecosystems the focus is on continual evolution; in these high-skill systems,
as we shall see, equilibrium is typically associated with stagnation or death of a sector.
III. THE IMPORTANCE OF HIGH-SKILL ECOSYSTEMS
On any measure of economic performance California’s high-skill regions have been immensely
successful. These are not niche employers of scientists and engineers, but rather constitute the largest
manufacturing sectors in a state which if separated from the rest of the U.S. would rank as the world’s
seventh largest industrial economy. It is difficult to define the precise size of these sectors because they
are changing more rapidly than the official government statistics; software and internet-based
enterprises, for example, that have passed computer hardware and chips as the most dynamic growth
sector in Silicon Valley (SV), do not have separate industry classifications in the official statistics, but
rather fall under the general heading of “computer services” (California Employment Development
Using conservative estimates, the computer and electronic equipment sectors together employs over
300,000 workers in California, while the diversified healthcare technology sector with more than
200,000 employees has recently become the state’s second largest high technology employer (see
Table 2 for employment in California’s largest manufacturing industries).
Interestingly, another of the
state’s largest employer of highly educated workers, the motion picture industry, also appears to
conform closely to the model of an HSE outlined below.
INSERT TABLE 2
The quality, as well as the quantity of jobs that these HSEs are producing is also a clear measure of their
success. The wages of workers in these HSEs are significantly higher than those of the average
Californian or U.S. employee. In the healthcare technology sector, for example, the average wage was
$50,000 in 1997, 54% higher than in the rest of California; biotechnology, which employs the highest
percent of advanced manpower in the healthcare sector, had average wages of $67,000 (California
Healthcare Institute, 1998).
These employment and wage figures greatly understate the overall impact of these HSEs on California’s
economic well-being. These HSEs directly increase the employment in closely related sectors, such as
The healthcare technology sector employment estimate includes individuals engaged in research and distribution of
products in this sector, along with an estimated percentage of individuals working in the healthcare portion of
broader industry categories, such as control and measuring devices. The other employment estimates are for
manufacturing alone at the 3-digit SIC code level.
the finance, legal and other specialized business services that cater to these high tech enterprises;
computer services, for example, employed over 113,000 highly skilled individuals in 1990 that are not
counted with the computer and electronic manufactures in the figure above. And the tremendous wealth
that these sectors have generated for their owners and employees (who are often one in the same
because of the ubiquitous use of stock options for compensation in these sectors), has had a very large
indirect impact on generating employment in a wide array of relatively high-paying service sector jobs in
the region: e.g. high quality restaurants, real estate agents, auto dealerships, travel agencies, etc. It is
important to note, however, that the concentration of high-skill employees in these sectors co-exists with
a large, much lower skilled and lower paid workforce, both working in some segments of manufacturing
within these sectors and providing personal services (gardening, child care, hotel rooms) to the higher
skilled workers (Storper and Scott, 1990). One sign of the scale of this multiplier effect is that
manufacturing jobs now account for only 15% of non-farm employment in California, projected to
decline to 13% by the year 2003 (California EDD, 1998).
On other measures of economic performance, such as balance of trade and growth, these HSEs have
also been extremely successful. Computers and electronics have become the state’s largest
manufacturing export sector, while California’s healthcare technology sector generated over $4 billion in
exports in 1996 (U.S. Department of Commerce, 1998). This represented a 61% growth rate over just
four years earlier.
IV. A MODEL OF SELF-SUSTAINING HIGH-SKILL ECOSYSTEMS
There is a wide variety of research in different fields of economics and across many other disciplines
(e.g. management, history, geography) that have contributed to our understanding of the factors
necessary for the development of high-skill ecosystems. Starting with the seminal work of Marshall
(1920) on industrial districts, economists have been interested in what factors explain the propensity of
firms in a given sector to cluster together in a small geographic area. Krugman (1991) points to three
supply-side externalities – labor market pooling, the provision of specialized intermediate goods and
services, and technology spillover effects – that favor concentration of firms in a common industry even
during a period of increasing economic globalization. The incentives for such clustering are even greater,
when a new technology is just emerging, and the knowledge associated with it is predominantly tacit,
and thus difficult to transmit to those not directly involved in its creation.
In one of the most important recent works in this field, Porter (1990, 71-2) focused on the key factors
that enable certain regions to create and sustain successful clusters. His diamond model has four
elements: demand conditions, factor conditions, firm strategy and structure, and related or supporting
industries. His framework draws heavily on the earlier work of industrial geographers and political
economists, who studied the elements necessary for the creation and continued survival of industrial
districts (Piore and Sabel, 1984; Scott, 1988).
Population ecologists in the management literature (e.g. Hannan and Freeman, 1977, 1989), have used
a different approach, drawn from the study of biological systems, to try to improve our understanding of
the conditions necessary for organizations and the individuals within them to survive and prosper. This
literature focuses primarily on the birth and death rates of individual firms and whether a particular
organizational form will triumph in the “survival of the fittest” in a given set of economic circumstances.
While the biological analogy is useful for understanding the process of dynamic growth and
interdependence among organisms, the way it has been applied has placed too great and emphasis on
competition among firms, underemphasizing the potential for firm cooperative behavior (Schoonhoven
and Eisenhardt, 1992). In the framework developed below, I addresses this deficiency, while shifting to
a higher level of analysis that has largely been ignored by the organizational ecologists. The focus is on
the factors that lead to “the survival or extinction of species of organisms (in this case, clusters of
enterprises and individuals) under different environmental conditions” (Young, 1988). Extending on a
relatively minor part of Porter’s framework, the focus is also the processes of knowledge creation and
diffusion that is central to the development of these high-skill ecosystems.
The framework consists of four elements necessary to create and sustain a high-skill ecosystem:
• A catalyst – some event or external trigger that initiates the living reaction
• A supportive host environment – a set of environmental conditions that enables young
creatures to grow to maturity
• Fuel or nourishment – to sustain the growth of life on an ongoing basis
• A high degree of interdependence – part of what makes this a system, and not simply a
group of separate organisms sharing the same physical space is that they are mutually
interdependent, e.g. part of a single food chain.
Different ways of developing successful clusters of high and/or intermediate-skill enterprises have
evolved to meet the requirements of different sectors and the distinctive institutional features of a variety
of advanced industrial countries (Baptista, 1998; Porter, 1990; Storper and Scott, 1990). In Germany,
state and national government-sponsored applied research and technology transfer institutes have been
the focal points for clusters in different sectors (Grabher, 1993), while in Italy it is the strong family and
community ties that are seen as the glue which binds small, specialized enterprises together (Triglia,
1991). In Japan, by contrast, it has been the giant corporations, such as Toyota, that have served as
the hub for tiers of interconnected suppliers (Sako, 1988). However, all of these different clusters fulfill
some common underlying conditions if they are to survive and prosper. These conditions for an HSE
are summarized in the framework below using examples from California’s high-tech clusters. There are
two key reasons for focusing on the U.S. model: 1) it has arguably been the most successful at creating
rapidly growing, high skill enterprises, and 2) it is best suited institutionally to the UK, which shares the
same strong research base and more free market environment.
As with naturally occurring ecosystems, there is a strong element of historical contingency in how and
where high-skill regions are formed (Arthur, 1989). To start the process, these regions require some
catalyst, or set of catalysts, to trigger the development of successful high-skill enterprises. California’s
computer and biomedical industries grew from a confluence of government demand and investment and
key individuals that helped ignite the explosive growth of new firms.
For Silicon Valley’s computer HSE one key stimulus was a large surge in Department of Defense
funding for research and demand for new military hardware in the new field of electronics in the 1940s
and 1950s. This helped create a cluster of aerospace firms in Southern California (Scott, 1994). As
this cluster grew some of these firms set up new facilities in the Santa Clara Valley, attracted by the
cheap land, access to military bases, and the supply of engineers from the nearby universities. When the
aerospace industry went into one of its periodic downturns, this left an abundance of unemployed
engineers who had settled in the area with cutting edge electronics skills that could be transferred easily
from military applications.
During this period, Fred Terman, a Stanford engineering professor had encouraged two of his students,
William Hewlett and David Packard, to turn their graduate thesis into a commercial product (Aley,
1997). The resulting company not only acted as a magnet for growth and new product innovation in a
variety of electronics sectors, but also helped generations of engineer entrepreneurs who then left to set
up their own enterprises. Terman was a driving force in establishing some of the crucial initial links
between Stanford and industry: the Honors Cooperative Program, that offered part-time degrees to
engineers in industry, and one of the world’s first science parks, the Stanford Research Park, where HP
and numerous other successful high-tech start-ups began and are headquartered.
A very similar set of historical contingencies helped propel the growth of California’s biomedical
clusters. In healthcare technology, even more so than computing, basic research is a key driver of
growth and the location decisions of firms (Prevezer, 1998). A relatively small group of star scientists
has accounted for a high percentage of all biotech start up firms (Zucker and Darby, 1996), many of
which are started by researchers at locations close to their original laboratories (Oakley et al., 1990);
fully one-third of all U.S. biotechnology companies, for example, are located within 35 miles of a
University of California campus (California Healthcare Institute, 1998). The large U.S. government and
private foundation investment in biomedical research, much of it performed in California’s set of world-
class research universities and institutes, led directly to one of the two key discoveries that made the
biotech industry possible. In 1973, Cohen and Boyer, collaborating between Stanford and the
University of California at San Francisco (UCSF), discovered how to recombine DNA, giving rise to
Genentech, the pioneering entrant in this sector. The second discovery came in Cambridge, England,
but the University failed to patent the techniques for monoclonal antibodies and the result was that there
was no incentive for Kohler and Milstein or others to establish a firm near the University to
commercialize their technology, since they lacked the exclusive rights to develop it (Prevezer, 1998).
In recognizing the key role that certain entrepreneurs and world-class researchers and their discoveries
played in jump-starting the evolution of these HSEs, it is also vital to distinguish between historical
contingency and serendipity. The fact that these individuals were located in California and attracting the
substantial public and private research funding necessary for the breakthrough to occur, was not mere
chance, but rather a testament to the vital role that research universities can play as a catalyst for HSEs.
California’s world-class research universities not only provided a powerful initial catalyst for these high
tech regions, but also are the source of the most important nutrient – new talent – that sustains their
growth. Each year these institutions turn out thousands of new bachelors, masters and Phd graduates
who move directly into local companies, and often later start their own firms. And this talent comes not
only from the science and engineering fields, but also from the management field; indeed, Stanford
Business School one of the most selective in the world, recently dropped in Business Week’s MBA
program rankings because so many of its graduates were turning down offers from the traditional
recruiters at large companies and financial institutions (who are surveyed to compile the rankings) to
take positions with more rapidly growing high-tech companies (BusinessWeek, 1998).
Once established, the synergistic relationship between these leading research universities and the
surrounding firms that hire their graduates and support their research can become self-sustaining as the
two act together as a magnet to pull in the brightest students from around the globe. Despite the large
supply of graduates coming from California’s research universities, the state’s high-skill regions are
significant net importers of graduates from other U.S. universities and from foreign countries. Across
the U.S., more than half of all the science and engineering Phds are now awarded to foreign-born
students (North, 1996), and the leading Califronia research universities – University of California
campuses in Berkeley, San Francisco, San Diego, Los Angeles, along with private institutions (Stanford,
USC, CalTech) -- are among the top choices for these applicants. These foreign-born students and
entrepreneurs represent some of the most talented technical manpower from around the world and have
played a key role in fostering the growth of California’s HSEs (Taylor, 1998). In many cases they bring
with them extended family and/or personal business networks that further strengthen the global reach
and viability of the HSEs (Saxenian, 1994).
The magnetic attraction of HSEs for employees, however, is not confined to the highest skill
occupations. As Table 3 illustrates, while close to a third of all engineers working in California’s high-
skill industries were born outside the U.S., 45% of skilled craft workers and a majority of all operators
had emigrated to the U.S. In some of California’s electronic or circuit-board assembly plants, virtually
the entire frontline workforce consists of women from Vietnam or Central America. Even with this huge
influx of talent, the supply of human capital is not sufficient to keep pace with the rapidly expanding
demand; for example, it was estimated that even with immigration, the US would experience a shortage
of approximately 350,000 programmers between 1995 and 2000, with Silicon Valley experiencing
some of the tightest labor markets (US Department of Commerce, 1998).
Insert Table 3
Alongside the steady intake of human capital, the other vital nutrient that sustains the development of
these high risk, but potentially high payoff new enterprises is financial capital. The venture capital
industry, which California helped pioneer, serves the vital function of sharing risk – taking much of the
financial burden off the researcher or entrepreneur who comes up with the a new innovation, and
distributing it among a pool of investors. From an already large base, there has been a dramatic
increase in the supply of U.S. venture capital available in the 1990s; the amount invested in venture
capital deals grew by 66% in just two years, from $6.9 billion in 1995 to $11.5 billion in 1997
(VentureOne Web Page, 1998); and California’s high-skill regions both supply and attract a large
share of this investment. Silicon Valley firms alone received 23% of all new venture capital investment,
by far the largest share of any U.S. region (Herhold, 1998).
Once established, the venture capital process is another part of HSEs that can become self-
perpetuating, as the founders of the first generation of successful start-up firms become “angels” for
subsequent generations. These angels invest some of the money they have made from a successful
public offering or selling off their business into new start-up companies. They often enter the deal at a
very early stage, before the company is ready to approach a venture capital firm. Venture capitalists,
whether “angels” or firms, provide far more than financial advice to new enterprises. They also supply
vital capabilities, e.g. managerial, financial, marketing, legal, and procurement skills, based on years of
experience in the sector that the scientist or often very young engineer who has founded the firm may
lack. And unlike the outside directors on the boards of many large corporations, venture capitalists tend
to play a far more active role in the daily operations of the enterprise, helping to formulate strategy and
brokering partnerships with other suppliers and customers in other parts of the value chain (Conger,
Finegold and Lawler, 1998).
Just as young creatures need a supportive environment free from toxic chemicals and harsh climatic
changes if they are to g row, so too clusters of small enterprises are more likely to thrive if they have the
right set of external conditions. There are at least three elements of an external environment that are
conducive to a HSE: basic infrastructure, a climate that is attractive to knowledge workers, and a
regulatory regime that supports risk-taking.
A basic requirement for successful high-skill enterprises in an increasingly global marketplace is good
infrastructure. As the key drivers of wealth in the economy have shifted from mass manufacturing to
high-technology industries, the underlying basis for economies of scale has shifted from physical
concentration of resources natural resources (water, power, iron ore) in a single location to the ability to
design and sell new products or services on a worldwide basis. The only way to justify the multi-billion
dollar investments required to develop a new drug or to construct a new semiconductor fabrication plant
for a chip whose projected life is only 1.5-2 years is to sell the product globally (Galbraith, 1998). This
means easy access to international airports that enable individuals to travel to remote locations within
their organization, as well as to customers, partners and suppliers scattered around the globe. And it
means a good local transportation infrastructure so that individuals can get to and from work efficiently.
Most importantly, high tech industries require a state of the art telecommunications infrastructure to
enable firms and their employees to take full advantage of the new technologies (the intranet,
videoconferencing, electronic data interchange) that make possible effective collaboration on a virtual
basis. While these technologies are not yet a complete replacement for face-to-face interaction in the
early phases of new knowledge generation, they are a vital compliment to them for making a global
organization work effectively.
While possessing a high quality physical and communications infrastructure, California’s most successful
high-skill regions have gone beyond these basics to create more specialized infrastructure tailored to the
needs of new, high-tech enterprises through mechanisms such as incubators, and science or technology
parks. These facilities have been created by universities, public authorities or private developers to
provide an array of services that small firms are likely to need as they develop, but which they are
unlikely to be have developed as in-house capabilities. These services may range from daily
requirements (e.g. shared secretarial support and photocopying) to more specialized services such as
legal advice, financial accounting, consulting and export marketing. Just as important, the co-location
such infrastructure creates can help build informal networks that encourage exchange of lessons learned
and generate new business ideas. The development of this sophisticated infrastructure for Northern
California’s computer industry helped lay the groundwork for the subsequent growth of the region’s
biomedical HSE, that required many of the same specialized services (Prevezer, 1998).
As improvements in telecommunications give knowledge workers and the firms that employ them far
more location options, other elements of the external environment become increasingly important in
determining where high-skill enterprises will cluster. Individuals can focus more on whether where they
want to live, rather than where they have to work. Thus, depending on their stage of life, they place a
premium on factors such as the climate, and the availability of cultural, recreational or other leisure
activities, and/or the availability of affordable housing, safe neighborhoods, and high quality schools.
One important caveat to the above factors, however, is that another clear attraction for knowledge
workers is being close to others who share the same expertise. Hence, regions which originally grew
because they possessed many environmental attractions for knowledge workers, but which no longer
possess some of these attributes because of their explosive growth, may still act as magnets for young
talent because they already have a critical mass of knowledge workers and enterprises. Whether they
can sustain this HSE over the long-term without these environmental conditions in place, however, is an
issue to which we will return in the conclusion.
Another essential requirement for fostering the growth of a HSE is a regulatory and cultural regime that
supports the risk-taking needed to create new enterprises. This entails relatively low levels of
regulations regarding work hours and other company practices that are likely to frustrate entrepreneurs,
along with a set of laws that makes it easy to: a) start a business, b) take the business public if the initial
idea proves successful, and c) go bankrupt without severe penalties if the business does not succeed.
The U.S. in general, and California in particular, meet all of the above criteria. The U.S. has pioneered
the development of new stock markets that make it possible for new businesses to raise capital at an
early phase in their development, and California has retained its pioneering spirit, with a culture that
celebrates the efforts of entrepreneurs, even those that are not successful. This contrasts with Japan and
Germany, where regulations prohibit firms from going public until they have a clear revenue stream and
where there is more stigma attached to being associated with a failed business.
One characteristic that distinguishes an HSE from an agglomeration of high-skill firms that simply is co-
located is the extent of interdependence between the actors in the region. The conditions identified
above -- strong universities, good infrastructure, abundance of human and financial capital – are
common to many urban areas that do not qualify as HSEs. What the firms and individuals in these
regions lack is the shared focus on a common sector and/or technology and a high degree of
cooperation among the actors that facilitates the learning process. . In her comparison of the
development of the computer industry in Silicon Valley and Route 128, Saxenian (1994) identifies the
greater strength of Silicon Valley’s knowledge-sharing networks as a key factor in explaining this
region’s greater growth and dynamism. It is possible to distinguish three different types of
interdependency or networks, each of which can play a vital role in building an HSE: 1) horizontal
linkages among specialized enterprises, 2) vertical connections between firms along different segments
of the value chain, and 3) networks among individuals.
The first type of interdependence stems from the very radical way in which the concept of the “firm” in
Silicon Valley differs from the traditional hierarchical corporation. Firms tend to have very flat, team-
based structures devoted to the development of a small set of distinctive core technical competencies.
This form of specialization requires that companies partner with other organizations that have
complimentary expertise. As companies grow larger, they can adopt this network form of organization
internally; Sun Microsystems, for example, has organized itself as separate enterprises for chips,
hardware, software and system integration, each encouraged to network with other parts of Sun, but
also free to partner with other firms if they feel that can better meet their needs (Galbraith, 1998). In
contrast, the failure of large companies, like DEC and Wang, to grow through external partnerships was
one of the causes of Route 128’s weaker networks (Saxenian, 1994), and may likewise account for the
relative dearth of new enterprises around Microsoft in Seattle (Fefer, 1997).
A second form of interdependence arises when companies replace vertical integration with partnerships
across different segments of the value chain. This is particularly important in biotechnology, where start-
up enterprises generally lack the huge investment dollars or global distribution networks required to get
a new drug through clinical trials and into the marketplace; instead, much like a food chain in a natural
ecosystem, this industry has tended to evolve as a long string of interdependent relationships. A small
firm creates some specialized tool (e.g. DNA sequencing machines and drug modeling software) that
another firm then uses to develop a library of genetic sequences or a specific new drug; this drug may
then be licensed to a large pharmaceutical company that gets regulatory approval, and then
manufactures and distributes the drug to healthcare providers. Similar, but separate chains have
developed in other segments of the biotech industries, e.g. for agricultural and food applications, as well
as many segments of the wider healthcare technology and computer industries. This form of
interdependence highlights the crucial role that demand drivers can play in transmitting signals down the
value chain that stimulate the development of new enterprises (Porter, 1990).
The complex web of networked enterprises that grows from such arrangements fits many aspects of
Piore and Sabel’s (1984) concept of flexible specialization. These predominantly small firms have the
agility to respond quickly to changes in technology or customer demand, and yet together have the
collective capabilities and resources needed to develop new products and manufacture them in large
numbers for the global marketplace. A key to the flexibility of these networks is their capacity for
collective knowledge creation and diffusion. This form of knowledge interdependence is fostered by
intermediate institutions that provide a forum for individuals to meet and exchange learning. Northern
California has a wealth of such institutions. These include employer groups, such as NOVA Private
Industry Council and Joint Venture Silicon Valley, where firms come together to pursue initiatives (such
as improving technical training in community colleges) that are to their mutual benefit. It also includes
numerous ways to build individual networks, like the continuing education courses and alumni
associations of the region’s universities, and the active local chapters of professional associations. San
Diego’s CONNECT network provides a good illustration of how such institutions operate. It was
founded in 1985 to provide a regular meeting where professors and their students could present their
most promising proposals for new biomedical businesses that were then discussed and critiqued by a
group of industry experts, venture capitalists and other specialized service providers.
V. RECONCEPTUALIZING THE KNOWLEDGE DEVELOPMENT PROCESS
The knowledge creation and diffusion process is at the heart of why firms cluster (Baptista, 1998). It is
the difficulty of transmitting tacit knowledge, particularly when it is new and changing rapidly that
encourages enterprises to be in direct and frequent contact with each other and the researchers creating
the new knowledge. Just as firm structure and inter-firm relationships differ in the HSEs and more
traditional settings, so too the process of developing individual capabilities and organizational knowledge
within HSEs is very different from conventional approaches to training and skill development.
Given the high level of employee mobility among tightly clustered firms within an HSE, one might expect
a skills shortfall to develop, as companies are unwilling to pay for skills investment that may be
“poached” by a competitor (Finegold, 1991); Stevens (1996) has shown that firms from a sector
require a set of specialized, but transferable skills (like those skills in demand in these high-tech regions),
there is likely to be just such an under-investment in training. Her work represents an important
advance on human capital theory, and correctly predicts the low levels of employer investment in formal
training that occurs in most firms in these high-technology regions. It is important to recognize, however,
that a lack of company training does not equate with a skill shortage in all cases.
For the scientists and engineers who are the key drivers of knowledge and wealth creation in these high-
skill regions, company-provided formal training is often not the primary vehicle for learning. Rather,
they typically enter the workforce with a high level of specialized preparation acquired through higher
education and/or self-study. They then continue to learn within the firm by seeking and being given
cutting edge technical challenges that often demand the combined talents of a multi-functional project
team in order to develop solutions. If they encounter a problem that they cannot solve, they may turn to
a professional colleague who is part of a wider personal network of outside technical experts. When
individuals do have time to take part in formal courses, it is often in the evenings, in a university
extension or continuing education program, where they can further develop their personal networks,
rather than in formal company training. The costs of such training to the firm are low, even for those
companies that reimburse the employee’s full tuition costs, since the courses are often subsidized
indirectly by the state and the employee is not being paid for the time spent in training.
The greater utility of informal over formal learning for these highly skilled individuals has been shown in
recent research on organizations undergoing rapid change (Tenkasi, Mohrman, and Mohrman, 1998)
and is reaffirmed in our current study of the key drivers of technical performance that includes a survey
of nearly 2,000 technical professionals in 5 global corporations.
These scientists and engineers
indicated that the most useful learning experience for them was not formal courses (inside or outside the
firm) or structured on-the-job training, but rather visits to customers, suppliers or partner companies
(see Table 4). This result is confirmed by an analysis of the relationship between different forms of
development with key measures of organizational performance. This indicates that, creating more
opportunities for learning in the day-to-day work environment – as measured by a three-item scale “my
job assignments provide the opportunity to keep my skills and knowledge up to date” and “we have a
good process for mentoring technical employees” and “developing employees is a high priority for
managers in this company” – explains a high percentage of the variance in perceived organizational
effectiveness (10-16%). In contrast, providing individuals with more days of training explains less than
1% of the variance in organizational performance. The value of informal over formal learning
opportunities is likely to be even greater in the smaller enterprises that populate these HSEs, since many
of these firms lack an in-house training department and the technology is changing so rapidly that it is
hard for many formal courses to keep up with changing skill needs.
Insert Table 4
Within these turbulent, high-skill environments, the responsibility for career development has also shifted
from the firm to the individual and the HSE itself.
Gone is the notion of a corporation that would
provide opportunities for career progression and a high degree of job security in return for employee
loyalty and commitment. In its place is a project-based culture, in which individuals have ownership
over their own career development. Indeed, Silicon Valley is often cited as the archetype of the new
employment relationship in which “employability” – the continuous development of marketable skills --
has replaced “employment security” as the bargain which firms can offer workers in return for their
effort toward achieving business objectives (Finegold, 1998).
The high rate of mobility between the dense cluster of firms and universities “facilitates a collective
learning process, increasing the speed of diffusion by reducing uncertainty. Innovation becomes, first
and foremost, a collaborative social endeavor” (Baptista, 1998, 51). The willingness of individuals to
change firms frequently, on which this collective learning process depends, is made possible by a new
concept of employment security within the HSEs. Highly skilled individuals can feel confident about
These survey questions were part of the first year of a much wider three-year study of the conditions that promote
excellent performance in 10 technology-intensive global companies.
While the importance of firm investment in individual learning decreases with higher levels of individual ability and
mobility, just the reverse is the case for investments in organizational learning. Faced with the reality that their most
valuable assets – their employees -- may leave at any time, firms are making major efforts to become more systematic
about the way in which they manage their knowledge base. Efforts to take the tacit knowledge within key experts’
heads and make it explicit, so that it can be stored, shared and improved on are at the heart of the knowledge
management process (Nohira, 1991; Roth and Senge, 1996). Our research indicates that organizations which have
more clearly documented and easily accessible best practices and standard work processes as well lessons from past
failures are significantly more effective on all key dimensions of performance (Tenkasi, Mohrman, and Mohrman,
buying a house and choosing a school for their children not because they can assume they will be
working for Firm X in three years time, or even that Firm X will still be in business, but because there is
a critical mass of other employers all demanding a similar skill set where they can work without ever
having to move (Saxenian, 1994). Indeed, in this environment, many individuals are concerned that they
may undermine their employment security by staying with a firm for more than 2-3 years and risk not
staying on the cutting edge of the latest technology.
The same institutional features that have made the Japanese and German VET systems so successful at
the creation of large supplies of individuals with intermediate skills, are poorly suited for the
development of this type of individually-driven, collective learning at the most advanced level. In
Germany, there is a strong reliance on formal qualifications, from the state-run and heavily regulated
universities and the tripartite-governed apprenticeship system. The process of creating new
qualifications or updating existing ones is very time consuming, and even with efforts to streamline this
process to meet the needs of new information technology and service sectors, it still has difficulty
keeping up with the pace of change in high technology skills (Culpepper and Finegold, 1999). In Japan,
by contrast, there is very little reliance on formal vocational qualifications, but the low levels of labor
mobility between firms and between academia and industry discourage the flow of tacit knowledge that
is an essential part of the learning within HSEs.
VI. ADAPTIVE CAPACITY -SUSTAINABILITY OF THE HSES
Just as naturally occurring ecosystems may be threatened if they stop changing, so too the economic
well-being of any HSE is threatened if the firms and individuals within it stop the process of growth and
adaptation. One rough estimate has put the typical life of such a high tech cluster until it reaches maturity
and begins to stagnate at 50 years (Swann and Prevezer, 1998). Some high-skill industrial districts,
such as the financial sectors of New York and the City of London, have defied such projections. A
brief look at the history of California’s HSEs, suggests that they have already demonstrated a strong
capacity for adaptation to the changing environment that bodes well for their long-term sustainability, but
may also, ironically, be sowing the seeds for an eventual slowdown in their growth rate.
If we trace the changes in Silicon Valley’s electronic cluster we can see that it has already evolved
through at least three or four generations of different businesses. It began, as noted, with aerospace
applications and Hewlett Packard’s calculation and memory devices. It grew into a huge memory chip
industry personal computer industry. When these products turned into more commodity-like items that
were severely threatened by cheaper foreign imports, Silicon Valley firms gravitated into more advanced
specialized chips, microprocessors, work stations, network systems, and software. The latest wave of
firms is now focused on developing and harnessing the potential of the internet with a vast variety of
software and hardware products.
The healthcare technology cluster is newer, and thus has not yet gone through as many stages of
evolution, but it is already possible to detect several successive generations of firms in this sector. To
give just one example, the process of new drug design has evolved rapidly in the last 15 years from the
traditional, laborious method of trying to match diseases with possible new or existing molecular
compounds that was common in the large drug companies. A first generation of start ups pioneered
advances in molecular modeling and genetic sequencing that have led to an explosion in the array of
possible solutions. This triggered the growth of a second set of new start-ups in the early 1990s that
pioneered a “rational drug design” method; this reverses the old drug design process, using computers
to predict possible applications for new protein structures (Prevezer, 1998). Only a few years later, a
new wave of start-ups has emerged devoted to “irrational drug design, using genetic algorithms to mimic
the natural selective process as a method for drug development”. In all of these cases, the new firms
that have pioneered these processes have sprung up around the leading research universities in Northern
and Southern California and Cambridge, Massachusetts. This evolution of new firms not only illustrates
the strong capacity of HSEs to regenerate themselves, even as particular firms fail or technologies
become more standardized or obsolete (Prevezer, 1998).
Part of what fuels the development of new generations of technology is another self-corrective
mechanism embedded within the HSEs. As the most successful firms in one generation prosper and
grow, they inevitably take on some of the bureaucratic features associated with larger organizations.
This bureaucracy can have some very positive features: e.g. fostering career development, building
managerial skills, embedding learning into more standardized routines and processes. But it can also
have elements that are antithetical to radical innovations, particularly those that threaten existing
technology, since the new innovations also threaten the portions of the organization and its employees
that have a stake in the ongoing profitability of the older technology. It is for this reason that most path-
changing technological breakthroughs generally come from new entrants, rather than the R&D labs of
This phenomena is apparent over and over again in Silicon Valley. The
start-up offspring of Fairchild Semiconductor are so ubiquitous, for example, that they’ve been dubbed
the “Fairchildren”. And Hewlett Packard has given rise to dozens of new ventures through the skills it
helped develop in employees that then left the firm. This dynamic has a dual benefit for the HSEs: it not
only creates an ongoing stream of new enterprises that can develop new technologies as older ones
become mature or obsolete, but it also generates strong pressure on larger, more successful companies
to remain as flat and innovative as possible if they are to retain their talent.
A number of the other features of HSEs discussed above can help strengthen the adaptive capacity of a
cluster. First, if the HSE is broadly based, including groups of enterprises in several different parts of
the value chain (e.g. chips, hardware, software, networking systems) it is likely to have greater adaptive
capacity then if it is concentrated in only area, where there is greater risk that the whole cluster could
become obsolete (cite).
Likewise, the greater the strength of interpersonal networks, the more the
opportunity for creative new ideas that come from the intersection of new technologies or the
development of applications for different end users. In addition, the close proximity and interaction with
This logic helps explain why IBM was slow to grasp the importance of the personal computer and why when it
belatedly chose to enter the sector it had to do so by setting up an entirely separate business unit, physically and
organizationally removed from the mainframe business.
Research on the Third Italy suggests that this diversity may be beneficial in even unrelated sectors; for example, the
geographic co-existence of clothing and machine tool clusters is mutually beneficial because they tend to have
counter business cycles, so that when the predominantly male machine tool sector is in recession, the women in the
community are usually busy in the textile factories, and vice versa.
universities gives firms in these HSEs ongoing access to new research breakthroughs and a source for
renewing their human capital stock to help prevent enterprises from becoming stale.
Even with a very strong adaptive capacity, however, no HSE is likely to continue to grow and prosper
forever. One possible threat to an HSE’s sustainability is a major discontinuity in the environment or
technology that undermines the core basis of the HSE. This could take the form of a dramatic shift in
the market, such as the end of the Cold War that devastated the Southern California aerospace cluster
(Schoeni and Dardia, 1998). As this case illustrates, however, industrial clusters can be very resilient –
commercial spinoffs from the defense industry and the surplus engineering talent it generated has helped
spur the development of new Southern California business clusters in multimedia and commercial
satellite technology. In the case of California’s HSEs, the core technologies appear so central to such a
wide variety of different future applications, that it seems unlikely they will become obsolete any time in
the near future.
The central threat to these HSEs, instead, appears to come from within: as HSEs prosper they almost
inevitably become victims of their own success. The wealth and jobs that they generate lead to an
increase in the general cost of living, house prices, and negative externalities such as traffic congestion.
At some point, these negative factors start to counterbalance the benefits of clustering, leading to a
slowing in the growth, if not absolute decline in the size of the cluster (Swann, 1998). While these
downsides of growth may hinder the ability of HSEs to attract top talent, they also have positive
consequences. For the HSE, it places strong pressure on the enterprises to concentrate on only the
most high skill, high value-added activities within the region. When products become more mature or
parts of the value chain no longer demand as high a skill level, such as the shift from pilot plants to more
custom mass manufacturing, then the operations are often shifted outside the region to new locations.
This is already the case in Silicon Valley, where much of the more routine programming and
manufacturing is now located in other parts of the US or around the world (India, Russia), where the
needed talent is available at a lower cost. Likewise, when the growth in an HSE reaches the stage
where it is deterring some new start-ups, this can encourage the development of new clusters in the
same sector. This dynamic is already occurring in the US computer, biotech, and multimedia industries,
as new clusters have formed both adjacent to Silicon Valley (Santa Barbara, downtown San
Francisco), and across the country in other areas that possess leading research universities (Austin, TX,
Salt Lake City, Utah, Raleigh/Durham, North Carolina).
Another way in which HSEs risk becoming victims of their own success is because of the high levels of
individual expectations they have created. As noted, a large part of the reward packages in these start-
ups consists of stock options that can make the employees very wealthy if the firm reaches the stage of
successfully going public. Indeed, the U.S. stock markets’ appetite for hot technology areas like the
internet is so great that companies which were still years from turning a profit, such as Netscape and
Yahoo, were able to generate vast amounts of capital and fortunes for their founders through initial
public offerings (IPOs). If the stock market experiences a prolonged period of decline, something that
hasn’t occurred in the entire history of some of these newer firms, then the attraction of these enterprises
for many talented individuals may diminish. The roller coaster record of many biotech stocks, however,
suggests that even this danger may not be too severe, as the prices of individual companies and the
sector as a whole have experienced major ups and downs, while the HSEs have continued to grow and
VII. HIGH-SKILL ECOSYSTEMS IN THE UK
The U.K. has many of the elements necessary for the generation of HSEs. It has a large and growing
supply of high quality university graduates, relatively good telecommunications and a large supply of
specialized infrastructure (e.g. science parks) to support start-ups, and a culture and set of free market
policies that is generally supportive of new enterprises. Most of all, it has the difficult to replicate
competitive advantage of a set of world-class research universities that can act as a strong catalyst for
the creation of new industries and technologies. In the biotechnology field, for example, the UK has
produced more academic “stars” whose research often serves as the basis for a whole family of new
innovations than all except the world’s two largest economies: Japan and the US (Zucker and Darby,
1996, Table 3).
This set of factors has helped the UK produce among the most successful HSEs in Europe in computers
and healthcare technology. The UK accounted for 45% of all European biotechnology firms in 1994,
with most of them clustered around the research universities in Cambridge, Oxford and London
(Shohet, 1998). And in the electronics and computers, although the scale of the industry is much
smaller in the UK than the US, new research indicates that the extent of clustering of enterprises around
is just as great in Britain as in the U.S (Baptista and Swann, 1998).
The weakness of some key elements in the ecosystem, however, appears to be preventing the UK from
capitalizing fully on these assets. A clear sign of the underutilization of the research base is that the UK
has one of the highest levels of outflow of scientific “stars”, with the net migration rate (emigration –
immigration/stars ever publishing in the country) equal to one third, a net loss of key manpower
exceeded only by Switzerland (Zucker and Darby, 1996). One possible cause of the problem appears
to be the weakness of the venture capital industry and opportunities for going public for high tech firms;
the UK has a healthy capital market for firms that are already profitable, but a scarcity of funds available
for companies in the prior stages of development, where large resources are required to get the first
product to market. The relative lack of venture capital funds and banks insistence on collateral for any
business loans to new high tech enterprises, means that a heavy share of the risk for new firms falls on
the individual entrepreneur. And the potential offsetting benefits are less certain because the efforts to
create a new EASDAQ market for start-up firms have not yet taken hold.
The contracts for British university faculty appointments also appear to increase the individual risk of
starting a new firm, since it is more difficult than in the US for faculty to get leave or part-time positions,
while still retaining their university appointment and benefits. This may contribute to the weakness of
individual networks between British academics and industry relative to the US; under 10% of British
star researchers have formal ties with a new business enterprise, compared to one third of US stars
(Zucker and Darby, 1996).
The UK has also historically had relatively weak institutional linkages among firms and between firms
and education and training providers that have hindered the pursuit of collective, high-skill strategies
(Crouch, Finegold and Sako, 1998). There have been a wide array of policy initiatives to try to
address this weakness; indeed, part of the problem appears to have been too many separate initiatives
relating to science, industrial, regional or education and training policy, emerging from different
departments, without any overarching strategy for promoting the growth of HSEs in particular regions.
These initiatives have generally taken two forms. The first have attempted to build local or regional
networks, but generally have had no specific focus on specific sectors or the highest skilled workers.
Among these are:
• Training and Enterprise Councils (Local Enterprise Councils in Scotland) -- are charged with
building the local skill base, but have, to date, predominantly concentrated on training the
• Business Links – provides a coordinating mechanism, or “one stop shops,” for a bundle of services
to small and medium-sized businesses
• Chambers of Commerce – groups of local employers that are often, but not always involved in
Business Links and/or TECs
The second set of programs have been national or European efforts at cooperative research:
• The Alvey Program – which fostered collaborative research efforts, but has now largely given way
to European cooperative research programs such as ESPRIT and EUREKA
• The Foresight Process – that brought industry leaders and academics together to identify key
priorities for future research
Despite the benefits of some of these efforts, the consensus of research on UK’s high-skill sectors
suggests that weak links between academia and industry and inter-firm networks continues to slow the
growth of HSEs (Temple, 1998; Zucker and Darby, 1996; Soskice, 1993).
As indicated at the outset, the UK’s capacity to generate HSEs may have been further undermined in
the last two decades due to the changes in the research environment. While all of the six largest
advanced industrial economies have experienced a sharp increase in the R&D intensity of
manufacturing, the UK’s relative position has declined, from the second most R&D intensive in 1973,
behind the US, to the fifth most R&D-intensive in 1991, falling behind Japan, France and Germany
Britain was also the only one of the major OECD nations to have reduced
government spending on research in the early 1990s (Sharp and Walker, 1994). The shift within higher
education resources from research toward broadening student participation has further weakened the
attractiveness of British universities for leading researchers.
VIII. POLICY IMPLICATIONS FOR THE UK
As measured by business R&D spending as a % of total manufacturing value added.
Given the vital role HSEs can play in wealth and job creation and Britain’s still strong, if somewhat
diminished, research base, there is a clear case for taking policy steps to fill those gaps that may be
hindering the growth of HSEs. In attempting to foster HSEs, it is crucial to recognize that the same
policies and preconditions that have worked in California cannot be transferred directly to the UK
(Finegold et al., 1993). Instead, the policy options outlined below attempt to adapt the more generic
lessons from the US to the UK’s distinctive institutional and cultural context.
Increase Funding for Basic Research and Pre-Venture Capital
The state has a vital role to play in stimulating HSEs through its funding of research in science and
technology. Individual private firms are unwilling, by themselves, to fund basic research at societally
optimal levels because of its high risk and public good characteristics. Yet basic research not only
generates the innovations that provide the catalyst for new industries, but this research also provides a
learning process for highly trained manpower to staff these new industries. When cooperative
mechanisms exist for the state and firms to join together to share the costs of this investment, however,
the entire industry can benefit. The U.S. semiconductor industry recognized this with the formation of
Sematech in 1987 and the more recent launch of a 10-year, $600 million cooperative research program
between leading chipmakers, the US Department of Defense and 14 leading research universities to
develop the next generation of semiconductor technology (Kehoe, 1998). The Labour Government
appears to have recognized the need for renewed investments in Britain’s science and technology base,
substantially increasing state research funding in its 1998 budget, but more could be done to build true
cooperative research partnerships with industry and education.
If Britain is to keep the talented individuals and the innovations generated by this research support, then
a vital hole needs to be filled at the next stage of funding for new technologies. The state could establish
a pre-venture capital investment fund, chartered to provide seed money to promising new technology
innovations that emerge from British universities until they have reached the stage where they have a
revenue stream or clearly demonstrated product. This fund could be under private management and
invite financial participation from large pension funds and other institutions that are in a position to make
high risk, high potential return investments. Like any venture capital fund, it would not be providing
grants to these new ventures, but rather investments in exchange for an ownership stake that would be
cashed out when a firm goes public or sells out to a larger enterprise. While many of the start-ups
would fail to reach this stage, the high payoff to those that do can produce a good return on investment.
In this way, the initial state funding should be more than self-sustaining, with profits reinvested in new
enterprises. Private venture capital or pre-venture funds would, of course, still be free to compete to
fund these new enterprises.
Expand the Supply of Entrepreneurial Skills
There are clear differences among individuals and across cultures in the extent to which talented people
have the desire, motivation and capabilities to be a successful entrepreneur. The supply of
entrepreneurial skills, however, is not something policymakers have to take as given. There are clear
ways in which the government and educational institutions can expand the potential supply of high-tech
• Offer more courses on how to start new businesses to scientists and engineers. Many of the
lessons associated with creating a successful start-up firm are generic and providing training on them
can help prospective entrepreneurs save time and avoid costly mistakes. Courses of this type are
among the most popular offerings in both Stanford’s business and engineering schools. These
courses are typically taught in an inter-disciplinary manner, bringing real-world industrialists or small
business experts to co-teach with leading technical experts
• Expand the numbers of foreign students and highly skilled immigrant professionals. Thanks
to the legacy of the British empire, the UK has very strong historical ties with countries like India,
Hong Kong and Singapore that contain some of the worlds’ greatest supply of engineering and
entrepreneurial skills. There is sometimes concern expressed that these highly skilled immigrants are
taking the university place or job of native students or that encouraging them to come the UK is
siphoning off the most talented people from these developing economies. The evidence from the
US HSEs, however, appears to suggest that such international exchange of talent is a positive sum
game, fostering growth in US high-skill regions linked to expanding high-tech regions in the students’
countries of origin.
Foster Regional Networks
The analysis of California’s computer and healthcare technology clusters along with research on other
successful models for high-skill industrial districts in Europe confirms the essential role that forums for
cooperation among firms and the other key actors in a region can play in the development of HSEs.
These cooperative institutions can perform two vital functions: a formal role is to guide strategy and pool
public and private investments for goods – e.g. infrastructure, vocational training, applied research – that
have positive externalities for all of the members of the HSE. The more informal role is to facilitate the
exchange of knowledge and building of individual networks that increase the rate of innovation within the
area. The development of an HSE’s collective strategic capacity is becoming all the more important in
the context of the growing strength of the European Union, which is providing a growing percentage of
public funding for basic research and economic development.
The UK would benefit from the creation of regional institutions that can bring together the wide array of
competencies and actors to focus on the commercial development of particular technologies in which
UK universities have already established or have the clear potential to develop a leading research
position. These networks should be open to enterprises which share a common geography and industry
focus, as well as to the array of specialized service providers (venture capital, legal and business advice,
export marketing) needed to help commercialize ideas. They should also include education and training
providers, not only the research universities, but also the colleges of further education that can provide
the wider base of technically-trained manpower needed to help test the feasibility and produce new
technologies as they move into more commercial applications. Encouraging sub-groups of employer-led
institutions such as the TECs to act as hosts for such networks might help shift the TECs’ focus from
provision of short, low-skill government-funded training for the unemployed to the generation of both a
supply and demand for knowledge workers.
Foster Individual Networks
Strengthening employer associations and other intermediate institutions can play a vital role in building
regional infrastructure and positioning Britain to operate more effectively in a European context. But the
UK’s historically weak record in this area suggests that these form of corporatist policy should not be
the sole, or even primary mechanism for fostering more high-skill regions in the UK (Soskice, 1993).
Rather, the success of the more market-oriented Silicon Valley model, with which the UK shares many
important similarities, suggests a complimentary way forward: an individual-based network model.
The research universities, as we have seen, can play a vital role at the hub of such networks. Among
the concrete ways in which they can strengthen the ties between basic research and industry are:
• Establishing academic contracts that make it easier for professors and students to take leave or
work part-time in industry. This should be a two-way transfer, with leading high-tech entrepreneurs
teaching in science, engineering and business school programs, as well as academics spending more
time in industry.
• Expanding the offerings of evening, weekend and distance learning courses to shift from the idea that
universities are a place for study once, early in a career toward fostering the real delivery of lifelong
learning. Just as important, these courses can strengthen ongoing industry-research links and
provide key networking opportunities for the participants and their instructors.
• Developing alumni networks for scientists and engineers in particular disciplines that can foster
similar networks as continuing education courses, though typically with a more social, rather than
academic focus. As US universities have clearly demonstrated, these networks can also play a vital
part in fund-raising, as the strong ongoing ties with the institution encourage entrepreneurs to give
back to their universities.
• Creating student competitions for the best new business ideas, where the finalists are judged by
leading venture capitalists; less important than whether the specific ideas are turned into successful
businesses, are the publicity and excitement such competitions can generate to encourage future
entrepreneurs and the contacts that are fostered during these competitions within and between the
academic and industrial worlds.
All of these above initiatives are small ways that help reinforce the notion of an interdependent
ecosystem for the different participants in the system. As one SV venture capitalist who was judging
such a competition at Stanford remarked when asked how she could spare so much time to come back
to university (Aley, 1997): “I love this. It’s all part of a great food chain.”
Even if Britain is able to replicate the success of Califonia's HSEs, it will not fully solve the low-skill
equilibrium problem. While such HSEs generate numerous high-paying service sector and technician-
level jobs, they have also contributed to the general U.S. trend of widening income inequality between
college graduates and those with only a high school education. The policy solutions to this problem is
not to curtail the HSEs, but rather to redistribute some of the wealth they generate to create living-wage
jobs for lower skilled individuals in both public and private service sectors that are in sheltered sectors
(see Crouch, Finegold and Sako, 1999 for more details on employment policy options).
Aley, J. (1997), “Why Stanford—the Nexus of Capital, High Technology, and Brainpower—is the
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OECD EDUCATION PARTICIPATION RATES (SELECTED COUNTRIES (1995)
AGE 17 AGE 18 AGE 19
Canada 69 34 11 17 10 17 25
United States 75 22 14 19 4 17 21
Australia 77 32 10 24 20 10 24
Japan 94 2 --- --- 1 --- ---
Korea 90 23 13 18 3 16 23
New Zealand 74 33 6 18 17 7 24
Austria 88 56 1 6 22 2 12
Belgium 99 54 14 19 31 23 21
Denmark 82 71 --- --- 52 --- 3
Finland 90 80 1 --- 28 4 10
France 91 60 --- --- 34 --- ---
Germany 93 82 2 1 57 3 6
Greece 56 14 12 22 6 10 29
Ireland 74 46 --- 27 12 --- 35
Italy --- --- --- --- --- --- ---
Luxembourg 78 70 --- --- 54 --- ---
Netherlands 91 69 --- 13 47 --- 23
Portugal 71 45 2 8 27 4 13
Spain 75 43 --- 19 26 1 26
Sweden 96 87 --- 1 24 --- 11
United Kingdom 73 31 4 18 15 6 24
Source: OECD, Education at a Glance, 1997.
California’s Largest Manufacturing Employers
SECTORS 1983 1990 1997
Manufacturing Total 1,927,000 2,068,800 1,913,800
§ Durable Goods 1,312,100 1,357,700 1,186,200
§ Non-Durable Goods 614,800 711,000 727,600
§ Computer & Office Equipment 108,700 100,800 94,100
§ Electronic Components 138,100 138,900 149,400
§ Aircraft & Parts 131,800 162,300 84,300
§ Preserved Fruits & Vegetables 51,400 52,900 45,800
§ Women's & Misses Outerwear 62,400 88,800 107,900
§ Commercial Printing 50,100 62,800 60,600
§ Measuring & Control Devices 47,000 69,500 66,700
§ Other Instruments & Related 55,500 52,200 53,100
§ Drugs 19,300 22,900 29,300
TOTAL HEALTHCARE RELATED: 121,800 144,600 149,100
All Heathcare Technology
--- --- 209,980 *
Source: California Employment Development Department, web page, 1998
*Includes: Researchers in non-profit institutions and estimate of healthcare-related sales and distribution
workers (California Healthcare Institute, 1998)
California’s High Tech Workforce:
Country of Birth
% Foreign % US
High Tech Industries 27.5 72.5
§ Managers 16.7 83.3
§ Engineers 31.9 68.1
§ Scientists 25.9 74.1
§ Technicians 28.8 71.2
§ Skilled Craft 45.0 55.0
§ Operators 54.5 45.5
Source: 1990 Census
HUMAN RESOURCE PRACTICES AND PROCESSES
A. During the past year, approximately how many days (half days can also be included) have you spent participating in
B. USEFULNESS: How useful has it been to you in developing skills and knowledge that help you contribute to
achieving the company’s objectives?
(1 = Not Useful, 2 = Somewhat Useful, 3 = Useful, 4 = Very Useful)
(AVG 5 C0S)
DEVELOPMENT ACTIVITIES AND USEFULNESS
• Attending formal courses and programs
• Participating in company seminars, conferences and learning
• Participating in external conferences and learning networks
• Structured on-the-job training
• Special assignments (e.g., participation on task teams)
• Visiting with customers, suppliers, and partner companies
Source: Center for Effective Organizations study of “Technical Excellence,” publications forthcoming.