Policy and Ecosystem Evolution

Paige Clayton* and Maryann Feldman**

*Georgia Institute of Technology

**University of North Carolina at Chapel Hill

Abstract: We consider how policy might vary over the life cycle of an innovative ecosystem.

This paper reviews the evidence on how ecosystems evolve over time as firms and institutions

develop. For each stage of ecosystem development, we identify a set of organizational logics

that prevail and present evidence about qualitative differences that characterize different stages.

Understanding the factors behind the path of development and the process of changing from one

phase to another is required for both theory development and policy advice. We argue that the

role of policy, either state or local, plays a pivotal but underappreciated role in the creation and

development of ecosystems. We differentiate between the role of sector-specific local policy and

the role of sector-neutral local policies. Rather than mutually exclusive, we explore the ways in

which the two policies may be used alternatively and complementarily in the different stages of

the development of an ecosystem.

Keyword: Entrepreneurial ecosystems; economic development; policy; life cycle

Acknowledgements: Funding from the Kauffman Foundation and the National Science

Foundation (NSF). Paper has benefitted from discussions with Elsie Echeverri-Carroll and from

participants at the 2020 annual Association for Public Policy & Management meeting.

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I. Introduction

Scholars have long noted the processes in the temporal evolution of innovative places,

defined alternatively as clusters, regional agglomerations or entrepreneurial ecosystems (Kenney

2000, Bresnahan & Gambardella 2004, Feldman & Braunerhjelm 2006, Storper et al. 2015,

Spigel 2017). While these constructs are differentiated by subtle nuances, the shared logic is that

co-located firms create innovation and new opportunities, and realize productivity gains, which

results in employment and shared prosperity. Governments around the world make massive

investment in an attempt to create innovative local economies, often without achieving the

desired result (Dewar 1998, Lerner 2010, Martin & Sunley 2003). Policy makers are often left to

make investments without an understanding of process in the academic literature.

The concept of entrepreneurial ecosystems offers a new interpretive lens to inform policy

that is fundamentally different from other related theories of local economic development. The

logic is that economic development can be best created by promoting new local firm formation,

which has the effect of generating new industries with growth potential and also can be more

democratic in sharing wealth broadly. Rather than emerging fully formed like Athena in Greek

mythology, entrepreneurial ecosystems result from a temporal development process, proceeding

through a series of stages. The requirements for firms and industry vary over this emergence

process (Clayton et al. 2020). Most powerfully, there is an opportunity to articulate a prescriptive

role for government policy, targeting specific policy instruments to different phases of the

development of an entrepreneurial ecosystem to increase their impact.

Policy, defined as a course of action adopted and pursued by a government, plays a

pivotal but underappreciated role in the development of innovative places. There is often a

search for best practices, which are uncritically adopted from other successful places without

sufficient consideration of the local context (Pfotenhauer 2019). Variation in the stages of

emergence of a local entrepreneurial ecosystem is an important consideration. Policy

prescriptions are typically based on fully functioning ecosystems without regard to local context:

the number of firms, the number and types of entrepreneurial support organizations, and the state

of the local labor market, among other factors. The appropriate policy response certainly varies.

For example, at the earliest stage the emphasis on supporting the start-up processes will have a

large impact, but as the ecosystem matures the need for human capital development, export

support, and access to growth capital will increase. Policies that are effective at one phase of

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ecosystem development may not only be ineffective at a different phase but may actually be

harmful and waste resources. To use public resources most effectively, we argue that policies

need to be calibrated to the specific context.

This paper examines economic development policy within the context of the temporal

development of geographic entrepreneurial ecosystems. We start by examining prior work on

ecosystem development, which concludes that ecosystems have distinct stages of development

and that policy plays a fundamental role in moving from one stage to the next. Rather than focus

on mature ecosystems, we focus on the ways that local economies emerge over time as

institutions and relationships develop, and firm density increases. For each stage of ecosystem

development, we identify a set of institutional logics that prevail and present evidence about

qualitative differences that characterize different stages. Understanding the factors behind the

path of development, the process of changing from one phase to another, and the role of policy in

this process is required for both theory development and policy advice.

This paper aims to make two contributions. First, we articulate a role for policy and for

government, more generally, as an agent of change in the process of forming an innovation

ecosystem. We advance a set of stages that a developing ecosystem might pass through,

predicated on the resource availability and firm density. Second, this paper provides a schema for

classifying government policy instruments, at the national, state and local level and considering

when specific policies might be most effective given an ecosystem’s phase of development and

dominant sector. While other recent work has attempted to ascribe ecosystem development to a

set of stages, the role of policy, specifically the transformative role of stage-specific policies, is

missing (Spigel et al. 2020).

The next section further explores the concept of ecosystems and provides a rational for

including policy as an instrumental mechanism. Section Three provides a schema for thinking

about policy at the national, state and local levels that are either sector neutral or sector specific,

and then provides a brief description for each policy. Section Four reviews the literature on

stages of development and provides a simple compilation of four primary phases. Section Five

then considers the juxtaposition of policy and stages to consider how different policy

mechanisms may either help or detract from that stage. The paper is populated throughout with

illustrative examples from different, international regions. Finally, we offer reflective

conclusions.

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II. Clusters versus Ecosystems: New Wine in New Bottles

The ecosystem concept originated with practitioners in the mid-1990s. Dissatisfied with

the policy options available to them, the ecosystem offers a biological metaphor and is

predicated on recognizing the importance of complexity, with non-linear and evolving

relationships (Isenberg 2010; Stam 2015; Spigel 2017).1 By definition, ecosystems are “a set of

interconnected entrepreneurial actors, institutions, entrepreneurial organizations and

entrepreneurial processes which formally and informally coalesce to connect, mediate and

govern the performance within the entrepreneurial environment,” (Mason & Brown, 2014, pp.

5). Bennet Harrison, writing in 1992, notes that scholars have attempted to interpret the spatial

clustering of economic activity using many different theoretical lenses, moving to a better and

more nuanced understanding. The initial conceptualization was the Italian industrial district

(Beccatini 2004), which was similar to the Marshallian industrial district (1920) but focused on

high value-added goods and included refinements of considering social and production

relationships. The concept of industrial clusters is attributed initially to the work of Michael

Porter (1990) and a significant literature has developed. The concept captured the imagination of

policy makers but has proven disappointing as the policy prescriptions have not yielded expected

results. Porter’s work has been criticized as being too simplistic and essentially static (Martin &

Sunley 2003; Swords 2013). Thus, there is a need for additional theoretical development,

specifically due to the realization that industrial agglomerations arise over time and the genesis

that endogenously builds resources.

The concept of entrepreneurial ecosystems differs from clusters in three primary ways.

First, clusters are bounded by one industry, technology or sector and are specific to a designated

value chain and a set of vertical related activities (Auerswald & Dani 2017). Entrepreneurial

ecosystems are defined across industries and consider the larger system that supports

entrepreneurship and innovation, without regard to a specific focus. There may be multiple

industrial clusters within an ecosystem and by defying sectoral designation, ecosystems can

accommodate the emergence of new technology fields at the convergence of different industrial

clusters.

1 See Malecki (2018) for a thorough overview of entrepreneurial ecosystems.

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Second, ecosystems reorient the discussion away from relationships between firms and

toward process and dynamic interactions. Clusters focus on relationships among firms, either at

the same point in the value chain (Beccatini 2004) or between suppliers and customers (Porter

1990). In contrast, entrepreneurial ecosystems focus on the environment, and place entrepreneurs

and entrepreneurship at the center of a set of resources and institutions (Auerswald & Dani 2017;

Spigel 2020). A notable limitation of cluster theory has been the inability to account for

heterogeneous growth trajectories of the same industry across different regions over the same

time periods (Martin & Sunley 2011). An ecosystem approach accounts for this heterogeneity by

addressing region-specific dynamics that can create this heterogeneity of outcomes noted in cross

sectional analysis of regional economies.

Third, as a final distinction from clusters, ecosystems better accommodate policy (Witt

2016). In the cluster formulation, policy was a background condition that was treated as

exogenous and operating only to define a static framework by which firms could interact (Porter

1990). Ecosystem development represents a shift from cluster reliance on following static and

deterministic interactions, with policy relegated to the background, to an ecosystem focus on

adaptability and adjustment enhanced by policy.

Ecosystems are complex adaptive systems (Martin & Sunley 2007). The boundary

between a complex adaptive system and its environment is neither fixed nor easy to identify,

making operational closure difficult. Complex adaptive systems are characterized by non-linear

dynamics because of complex feedbacks and self-reinforcing interactions among components.

Complex adaptive systems are also characterized by emergence and self-organization: there is a

tendency for macro-scale structures to emerge spontaneously out of individual (micro-scale)

component behaviors and interactions. This same process of self-organization imbues complex

systems with the potential to adapt. While much consideration has been given to external shocks,

it is equally possible for change to occur through co-evolutionary mechanisms, or as a response

to public policy initiatives.

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Table 2. Characterizations of Stages of Regional Ecosystem Development

Study Focus

No. of

Stages Components

Auerswald and Doni

(2017)

Adaptive Life Cycle 4 Exploitation; Conservation; Release; Reorganization

Cukier et al. (2016) Startup Ecosystem

Maturity Model

4 Nascent; Evolving; Mature; Self-sustainable

Feldman et al.

(2005); Feldman &

Francis (2006)

Entrepreneurs as Cluster

Life Cycle Sparks and

Shapers

3 Emergence; Formation/Development; Industry maturation

Harrington (2016) Development Centered

Scaling Model

4 Early years; Gaining momentum; Scaling; Self-sustaining

Mack & Mayer

(2016)

Evolutionary Model 4 Birth; Growth; Sustainment; Decline

Malecki (2018) Life Cycle Model No clear components offered, but sustainability is end

result; not decline; continually evolving

Mason & Brown

(2014)

Ecosystem Model 3 Emergence; Scale-up; Self-reinforcement

Mathews (1997) Evolutionary Stage Model 4 Preparatory; Seeding; Diffusion; Sustainability

Simmie & Martin

(2010)

Adaptive Cycle Model of

Regional Economic

Resilience

4 Reorganization and Restructuring; Exploitation and Growth;

Conservation; Decline and Release, repeat with

Reorganization and Restructuring, etc.

Startup Genome

(Gauthier et al.,

2017)

Ecosystem Lifecycle

Model

4 Activation; Globalization; Expansion; Integration

ter Wal (2013) Evolutionary Model 3 Emergence; Coherence - Intermediate Crisis; Growth

Clayton et al. (2020) Evolutionary Model 3 Emergence; Growth; Maturity

IV. Characterizing the Life Cycles of Regions

Martin and Sunley (2011) note the literature on the evolution of geographically-defined

industries is based on the concept of a life cycle. While this approach has limitations, it provides

a means to understand regional industrial change. Regional industrial evolution is an adaptive

process based on interactions at the local level yet there are stages or appreciable changes in the

growth trajectory as part of the emergence of a local agglomeration of entrepreneurial firms

(Clayton et al. 2020). Ideally any typology of ecosystem development focuses on dynamic

change within industries and places, with an emphasis on evolution towards a fully functioning

innovative infrastructure. The stages of the regional or ecosystem life cycle follow a biological

metaphor that is popularized in the product life cycle introduced by Abernathy and Utterback

(1978) with the simple extension of a geographic dimension. Table 1 provides a review of 13

prior studies that have attempted to characterize the stages of regional ecosystem development.

Each study has a different focus justified by its theoretical orientation.

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The similarities are striking: the regional life cycle process generally begins with a stage

of nascency, where the first signs of a new industry appear. The spark is an opportunity to which

entrepreneurs respond, perhaps a new scientific discovery, a technological advance, or a change

in the market. There is certainly an element of serendipity but for an industry to take hold there

needs to be high quality resources and infrastructure (Feldman & Francis 2003). For this first

stage, resources and access are critical. Tacit and sticky knowledge requires geographic

proximity and the ability to tap a variety of external sources of technical, market and financial

knowledge. While the vast majority of businesses start small and stay small, there are certain

firms that will seek to grow more quickly and be able to scale their operations. As these firms

grow, they will attract suppliers and skilled labor; an agglomeration begins to take hold.

The next stage is the take-off stage, when the number of related firms increases and the

ecosystem matures. Sometimes this period is split into two separate stages of emergence and

expansion. During these early stages, there is a high rate of new firm market entry and exit as

firms experiment with the new opportunity and learn from their collective mistakes. With the

low level of market concentration, the market share of individual firms is also volatile.

Ironically, the most successful clusters are associated with lower survival rates of new firms

(Stuart & Sorenson 2003). The logic is that the cluster is made more vibrant through this

evolving process, which suggests that efforts to save marginal firms are not likely to be

associated with higher innovativeness and growth of surviving firms. Rather than the efforts of

one entrepreneur, there is a need for collective action (Feldman et al. 2005).

During the take-off phase, certain places become known as hot or as the place to be for a

certain industry. Klepper (2010, p. 22) describes a process of agglomeration: if initial entrants

become an early leader of the industry, they become a source of spinoffs. And these spinoff firms

have an advantage of learning about the industry from their prominent incumbent and as a result

are more successful. As this process continues, overtime the share of the firms in the industries

and their output and profitability increase. Rather than a zero-sum game, in which the gains of

the spinoffs come at the expense of the parent, spinoffs develop new niches and related products.

This is a critical juncture, representing the point when the cluster can solidify its lead. This is

also the point at which public policy can play the most decisive role in creating conditions

conducive to entrepreneurial endeavors and the success of existing small businesses.

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Life cycle theorists generally consider a subsequent period of maturing growth when an

industry is still strong with a stable growth rate. As industries mature, their knowledge base is

codified and more oriented toward process innovation and incremental product innovation. The

opportunities for local growth are lower unless there is the start of a new product line or new

technological trajectory. For this stage, the emphasis is on sustaining the local technological

advantage while encouraging the exploration and pursuit of new opportunities to diversify the

local economy.

Many studies include decline as a final stage. Ideally, if managed by policy, this decline

phase can be averted. Some of those clusters that have averted the final stage through

diversification include turbine manufacturers in Denmark (Karnoe & Garud 2012), who were

able to literally innovate and turn their airplane turbines on their side to meet the demand for

wind power. Akron redefined itself as a center for polymer research based on scientific research

from corporate R&D labs working with the University of Akron (Mudambi et al. 2016). Decline

is not inevitable, and continued investments in education and public goods can reinvent

industries within cities (Glaeser 2005). In this way, the regional industrial life cycle begins anew,

and the cycle restarts, emphasizing factors and investment important in the initial stage.

Rather than propose a new model of regional industrial life cycle development, we aim

to synthesize existing models in a way that will allow us to structure stage specific policy advice

that can be applied across a variety of regions interested in expanding local industrial dynamism

through entrepreneurship. In so doing, we adopt three-phase model: (1) nascency (2) take-off,

and (3) maturity. We do not include decline as a final stage because while we find the biological

metaphor informative for orienting regional development, we do not believe in a literal

application. Including decline as part of an ecosystem life cycle seemingly proscribes in an

inevitability rather than allowing for reinvention and resilience. A local economy facing a

declining industrial sector often results from factors outside of its control, such as international

trade or corporate strategy. Often these shocks are impossible to predict and their impact can be

devastating. Policy to address decline requires the full economic development toolkit (Blakely &

Leigh 2013) and is beyond the present analysis. We omit this stage from our consideration.

The stages of ecosystem emergences provide a framework for consideration of local

policy aimed towards building an emerging local entrepreneurial ecosystem. Rather than

focusing on policies that directly impact entrepreneurs, the concept of entrepreneurial ecosystem

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focuses on the inter-related nature of all of the elements in the local economy. The objective for

policy and government investment is to move the emerging local industry to the next stage of

development. Considering life cycle stage as an essential element of local context provides a

diagnostic tool.

Table 2. Ecosystem Policies by Sector and Level

High Level: National

Mid-Level:

State

Immediate Level:

Local Government

Sector

Neutral

Policies

Public Inputs

Infrastructure

Education Policy

Intellectual Property Policy

Research investment

Public Inputs

University research initiatives

designed to upgrade capacity

Education expenditures

Non-compete agreements

Public Inputs

Education expenditures

Market-Based

R&D tax credit

Small Business Innovative

Research (SBIR) program

Market-Based

Research parks

Relocation incentives

Export/market support

R&D tax credit

Market Based

Relocation incentives

Expansion incentives

Financing subsidies

Place-making investments

Sector

Specific

Policies

Public Inputs

Research consortium

Antitrust actions

Public Inputs

Creation of industry support

Organizations

University research initiatives

designed to specific sectors

Targeted training programs

Public Inputs

Targeted community college

educational programs

Fostering social

capital/networks

Market-Based Market-Based

Enterprise and emerging

technology investment funds

Market-Based

Shared facilities for start-ups

and expansion

Compiled by the Authors.

III. Ecosystem Policy Mix

Studies of regional innovative ecosystems consider a variety of factors, such as industry

mix and the quality and availability of resources (Greenwald & Stigliz 2013, Moretti 2012),

types of institutions and social capital (Carlino & Kerr 2014) and the presence of local regional

champions and entrepreneurial capital (Feldman & Zoller 2016). There is surprising little

discussion of the effect of policy instruments on the development of industries and the creation

of agglomerations in places. Witt (2016) argues that an evolutionary perspective can make a

difference for economic policy advice due to the fact that problems are framed differently. Many

studies evaluate the impact of a specific government policies. For example, there is significant

consideration of R&D tax credits or government R&D programs but surprising little consensus

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(David & Hall 2000). Most studies are based on cross sections that compare regions at different

stages of their development, and it is not surprising that different conclusions are reached.

Shifting the analysis to consider stages of development provides a more defensible base upon

which to design and implement policy.

Further complicating policy discussions is the reality that countries have multiple levels

of governments including local, regional, state, national or federal, with many other

organizations actively taking an interest in policy decisions and outcomes. Table 2 provides a

categorizing of policy instruments along two dimensions: jurisdiction and sector orientation.

Jurisdiction reflects different levels of government that form the multiple layers of overlapping

policies. Flanagan et al. (2011) consider how these different levels of jurisdiction align to form a

credible, comprehensive and coherent policy mix. The idealized case has policy aligned between

jurisdictions, but there are examples where the different levels of policies work at cross-

purposes. For example, national programs promote entrepreneurship, yet individual states have

non-compete agreements that limit the ability of former employees to start new firms (Marx

2011).

We add the additional dimension of public inputs versus market-based policy

instruments. We further differentiate between sector-neutral policies and policies targeted to

build specific sectors. Foray (2019) argues that sector-neutral policies have deployed programs

and instruments to support innovation without any pre-determination of the domains, sectors or

technologies that would benefit. In contrast, sector-specific policies aim to modernize of an older

industry or accelerate innovation to solve certain grand societal problems. Other sector-neutral

state policy initiatives include research parks, university research initiatives designed to upgrade

capacity, education policy, and export/foreign market support. State-level sector-specific policies

include the creation of industry and entrepreneurial support organizations, enterprise and

emerging technology investment funds, university research initiatives that support specific

sectors, and targeted training programs to grow the level of local human capital in a specific

sector.

The national government is not an active builder of local entrepreneurial ecosystems, but

federal policies indirectly impact on and support ecosystem development. Dixit (2009)

enumerates the importance of country level governance for a properly functioning market

economy. Good national governance is associated with property rights, contract enforcement,

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and collective action. When property rights protection is weak, individuals have a disincentive to

engage in entrepreneurial activity.

Federal policies which are sector-neutral include general infrastructure development,

R&D tax credits and grants, and the Small Business Administration’s SBIR and STTR grants

and I-Corps program. Sector-specific policies include the development of research consortium,

such as Sematech or ARPA-E, and antitrust actions. These policies are not place-specific, yet

when combined with local policies they can help nurture an environment conducive to

innovation and start-ups.

States also create policies and invest to develop the economies with their boundaries.

Bartik (1991) advances the argument that sub-national economic development policies can

significantly affect the growth of a state or metropolitan area and benefit the overall national

economy. Since the 1970s, governors have become more active in economic development,

experimenting with a variety of different programs and policies (Coburn 1995). The idea of

fiscal federalism argues that states and local governments are closer to understanding the

specific context and the needs of their citizens. While the stance of state governments has been

characterized by waves with different orientations, from “smoke-stack chasing” to innovation

and entrepreneurship, Lowe and Feldman (2018) advance the argument that these economic

development strategies present different tools that might be meaningfully combined. Viewed

differently, the emphasis may reflect different temporal priorities: in the 1970s industrial

recruitment was grounded in the primacy of manufacturing and large establishments, while the

more recent emphasis has shifted to reflect changing national priorities. Two points are salient.

Industrial recruitment is still actively practiced, even as its negative consequences are widely

recognized (e.g., Good Jobs First). Second, state policies may extend and augment national

policies, yet these policies often rapidly diffuse and are adopted by states until their coverage is

essentially national. For example, many states have matching funds for federal R&D grants

(Feldman & Lanahan 2015, Lanahan 2016). The program started in North Carolina in 2006 and

as of 2013, 45 states had adopted the program.

Of all levels of jurisdiction, local government and non-profits have the greatest focus and

incentive to support the development of their own ecosystem. Peterson (1981) emphasizes that

the American decentralized federalist system orients policy at the local level to be pro-business.

The funding structure of cities is dependent on the health of the local economy, which provides

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the basis for tax revenues. Peterson argues that this reliance drives local policies and create a

systematic bias towards stimulating economic activity and promoting investments that make for

an attractive business location. Too often the definition of an attractive business climate has

been interpreted as reducing factor costs in production processes. Cities adopt these policies to

reduce their costs relative to other cities, for example providing subsidies for firms’ ‘tax

abatements and below market land costs’ (Erickson 1987). This view of favorable business

climate does not seem to resonate with structural economic change that favors amenities and

agglomeration economies (Christopherson & Clark 2007). A new localism is emerging that

focuses on innovation capacity and transaction costs rather than solely focusing on the cost of

the factors of production.

At the local level, sector-neutral policies also include expansion incentives, financing

subsidies, and place-making investments that are open to all firms. Sector-specific initiatives

include targeted community college educational programs, developing shared facilities for start-

ups, such as clean-rooms, and prototype productions, and fostering networks and social capital

through local government-sponsored events.

An important thing to take away from this overview is that no policy is sufficient and not

all policies are necessary. Unlike cluster theory which tried to prescribe a specific mix of factors

that should be present for a cluster to emerge, ecosystem theory is less deterministic and takes a

more holistic view. Coherence and diversity are the guiding factors when considering the

appropriate policy mix. An additional factor we introduce in the next section that also must be

considered, though, is time.

V. Policy over the Regional Life Cycle

The Republic of Korea provides an accessible example of the temporal staging of

economic development policy (Weiss 2011). From the 1950s to mid-1970s, the initial focus on

the production of relatively simple labor-intensive goods provides a local substitute for imports.

In the second stage, from the late 1970s through the 1980s, the focus shifted towards more

capital-intensive activities and the development of industries such as chemicals, shipbuilding and

steel that could be exported. In the third stage, from 1990 to the present, the emphasis shifted

towards higher value-added and knowledge-intensive activities. The different emphases of policy

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over this 60-year period reveal the promise and the challenges at various stages of

industrialization.

There are other examples of countries experimenting with policies to accomplish specific

objectives needed at a specific time. Avnimelech & Teubal (2006) analyze the emergence of the

Israeli venture capital industry and the co-evolution with the technology sector. Most prominent

was the Yozma program, which was designed to jump-start a domestic venture capital industry

and then to phase out as the industry developed. The logic was that developing the industry

required subsidies to induce investment, but once an entrepreneurial ecosystem developed

government funds were no longer needed. In contrast, Witt (2016) argues that continued

subsidies may prevent owners in the industry to reorient, diversify, innovate, or search for

relocating their resources. The subsidy reduces the competitive pressures and eliminates

incentives to innovate or search for new business opportunities. The competitive situation of the

subsidized industry keeps on worsening and the policy of subsidy payments sooner or later

becomes unsustainable. One notable example is the American steel industry, which collapsed in

the 1980s. The logic extends: the state of Washington had an R&D tax credit from 1995 to 2014.

Over that 20-year time period, small home-grown companies such as Microsoft and Amazon

grew to become tech giants. Other tech companies, such as Google and Facebook, were attracted

to the area due to the benefits of location in the technology agglomeration. The subsidy had

served its purpose (Parkhurst 2012) and was dropped despite significant opposition from the

business community.

These examples illustrate the usefulness of time as an orienting logic for understanding

the mechanisms behind ecosystem creation and the role of policy. Next, we consider the three

phases, objectives for industry emergence and examples of policies. We take the stance that the

local industrial structures in many places have now collapsed. Our discussion will focus more

broadly on the development of an entrepreneurial ecosystem. Since federal policy is ubiquitous,

our focus is more on local and state policy. Yet we acknowledge that at the earlier stage of

development, places will not have tax revenue to allow them to make investment and federal

programs are needed.

Phase I: Nascency

In Phase I, the earliest stage, the objective of policy is best focused toward capacity

building. There are multiple examples of entrepreneurs who started firms in locations where an

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industry did not develop for various reasons (Leslie & Kargan 1996). The ecosystem might be

ill-prepared, or the local culture was not accommodating. Appropriate and sufficiently supplied

infrastructure serves to improve access to markets, reduce unit cost of production and generate

consumer surplus. Infrastructure investments reduce costs of consumption, improve the general

quality of life, and attract private investment. Human capital is also a category of infrastructure

and influences the productivity of other factors of production. These are the necessary first

investment opportunities.

The focus in Phase I should be relatively sector-agnostic in building up infrastructure and

capacity and the human capital stock. For better or worse, it is nearly impossible, as with any

complex system, to identify which firms and technologies will succeed in advance. This argues

against the practice of picking winners but suggests the utility of investing in capacity to see

which entrepreneurs will be able to scale their firms. Because high-growth firms in an economic

ecosystem can only be identified in hindsight, entrepreneurial development programs are

generally not limited to high-growth entrepreneurs. There is little point in trying to attract

venture capital at this point—it will not come and even if they come they will be disappointed

unless there is sufficient deal flow. Policy should instead focus on developing services sectors—

the financial and legal backbone required as the basis for future development. Investments in

universities and a focus on industrial recruitment of large facilities make sense for this early

stage.

This is also a phase at which national investment is critically important for both its

magnitude and the legitimacy it entails. For a place that is struggling, there is limited opportunity

to rise up. Federal policies such as infrastructure investment and research grants have

demonstrated results much greater than the relatively small amount spent on the program would

suggest (Furman 2016). For example, the National Science Foundation (NSF) Established

Program to Stimulate Competitive Research (EPSCoR) and the National Institutes of Health

(NIH) Institutional Development Award (IDeA) program are designed to effect lasting

improvements in a state's or region's research infrastructure, R&D capacity and hence, its

national R&D competitiveness. The goal is to stimulate R&D in regions that normally do not get

government funding.

At the state level, relocation incentives, expansion incentives, university research

initiatives, and education policy are paramount during the capacity building and nascency phase.

14

For example, the state of North Carolina reorganized its university system in the 1930s to first

consolidate to create institutions with national distinctions. It then reorganized in 1971 to bring

more institutions under the system to extend the reach of higher education to less developed

regions of the state (Williams 2006). The state of Georgia made extensive efforts to build a

competitive university system from a very weak foundation. An important element of the state’s

program is the Georgia Research Alliance (GRA), a public-private partnership that spent $242

million in state funds and $65 million in private funds during the 1990s, in an effort to foster

economic development by developing and leveraging the research capabilities of the research

universities” (Lambright 2000). The GRA established a consortium of universities that would

work together to build research and innovative capacity and, ultimately, to promote

commercialization and the formation of start-up firms.

At the local level, relocation and expansion incentives, as well as place-making

investments (i.e., developing the services sector) and education programs are also important in

Phase I. The successful attraction of large, technically-oriented corporate research and

manufacturing operations will immediately generate employment. There will be an opportunity

for suppliers to locate nearby. Consider the automobile industry, which has relocated from

Michigan to the American South, with all the suppliers following along. This process can also be

started with homegrown firms. The best example maybe Bentonville Arkansas, home of

Walmart. While complaints about Walmart’s business practices on main street business are well

known (Quinn 2000; Bonanno & Goetz 2012), Walmart has built an industrial agglomeration in

northwest Arkansas, which is the company headquarters.

During Phase I, policymakers should be scanning the landscape and should have a good

understanding of regional assets and capabilities. They should be ready to move policies into the

next stage when there is an indication of emergence. The initial spark will differ from region to

region, and serendipity will be involved. The role of policy is to ready the region—help access

resources that will be required for the spark to take hold.

Phase II: Take-Off

In Phase II, entrepreneurial activity is gaining traction and the motivating role of policy is

to clear a development path for start-ups, provide a soft landing for failed attempts, and encourage

labor mobility. At this point there is growing momentum, and increased recognition in the

national and local press. Policy can capitalize on this momentum. There is a possibility that

15

activity could leave another region, if resources are inadequate. Matti et al. (2017) focus on the

emergence of the wind energy sector in Spain and the multilevel government’s role in providing

market signals and financial support and mechanisms to support the emerging industry. Learning

by doing is a big feature at this stage. National and state policies are implemented at the local

level: while regions and local authorities did not have much input in the formulation of policy,

they were responsible for implementation (Matti et al. 2017: 667).

Local and state policy should focus on continued and strategic attraction of large

multinationals–significant investment by large firms headquartered elsewhere who recognize the

benefits of the local agglomeration–can help with labor mobility and strengthen networks. The

accumulation of knowledge externalities and human capital in clusters of innovative firms is the

engine of endogenous regional growth (Lucas 1988, McCann & Ortega-Argilés 2013, Romer

1986). This churn signals that the place has become established.

The role of policy in this early part of Phase II begins to become less pronounced than in

Phase I. Local and state policy should help firms find new markets, fill gaps in seed finance, and

ramp up “emergence” phase programs including fostering social networks. Broader strategies for

attracting and retaining talented people by enhancing the quality of life, like the investment in its

creative community of Austin, Texas, may also have important consequences for entrepreneurship

(Watson 2001). Policy makers should take broad view to assess weaknesses in ecosystem that

could impede further expansion and identify and support a regional champion or anchor

organization.

As Phase II continues, a period of self-organization and expanded growth takes place.

Beacons from Phase I lead to period of expansion. Arthur (1990) provides a model of regional

development described as self-reinforcing expertise: geographic variance in technical progress

exists because regions with innovative activity develop specialized resources that are critical to

the next phase of innovation. Government intervention is less important at this stage, and the

successful policies which have helped bring the ecosystem to this point can be retracted.

The source of start-ups changes: in the early development of the high-tech economy in the

city, most new entrepreneurs had previous experience working for a large company or for the

university. As these entrepreneurial firms grow, they open training opportunities to potential

entrepreneurs. The spawning of founders from large high-tech firms has been an important factor

in the growth of technology-based entrepreneurial systems in the high-tech regions such as the

16

Research Triangle (Clayton et al. 2019, Donegan et al. 2019), Silicon Valley (Burton et al.

2002), and Austin (Echeverri-Carroll & Oden 2016). Thus, new entrepreneurs may not have

worked for a large firm but have worked for a fast-growing firm, learning the art of creating new

businesses. Agglomeration economies really build up now and are due to organizational

reproduction and inheritance. There is a role for institutions, government, and human agency.

The community of entrepreneurs now becomes a source of knowledge on how to create

and grow a successful firm. How do we observe this? There is a critical mass of second-

generation spawns and the building of institutions based on trust. For-profit ESOs emerge that

partner with public organizations and build social capital, and as Granovetter (1985: 490) pointed

out, extends beyond “pure economic motives” and can “become overlaid with social content that

carries strong expectations of trust and abstention from opportunism” (Granovetter 1985: 490).

Trust in a local economy is important because it facilitates inter-organizational cooperation and

reduces transaction costs associated with monitoring the behavior of others (Poppo & Zenger

2002, Zaheer & Venkatraman 1995). Entrepreneurs and other local champions, therefore, begin to

build institutions and define institutional logics. Entrepreneurial recycling begins as entrepreneurs

recycle the human and other capital they acquired while building their firms back into the

ecosystem. The ecosystem experiences enhance efficiencies both in firm successes and failures.

Social networks are now very dense.

Phase III: Maturity

In Phase III, the ecosystem has long been recognized as legitimate by external

stakeholders and growth processes are self-reinforcing as long as there is reinvention and renewal.

Maturity has been reached when the ecosystem can withstand an economic downturn and there

exists a high degree of labor market thickness (Feldman et al. 2005). Resources are established.

The role for state and local policy is to continue to implement and build off of federal

efforts, prevent stagnation and decline, and look for ways to renew growth either in the dominant

or complementary sectors. Another role is to monitor the sustainability of current practices by

industry and the ecosystem and work to make sure there are not inequitable power dynamics

within the ecosystem which could prevent a diversity of individuals and ideas from percolating

through the system. Jane Jacobs (1961) describes that when the distribution of power in a city or

region becomes restricted to a relatively small number of human agents, long-term economic

evolution and development prospects will be harmed. Jacobs argued that the narrow power base

17

existing in cities such as New York in the 1950s and 1960s was a cause of urban and regional

decline, and it is likely that the broadened distribution of power across wider networks of agency

within such cities has led to their very rejuvenation and heightened rates of economic

development. It is local and state policy makers prerogative to monitor power dynamics and

inclusivity, and make adjustments as needed.

VII. Reflective Conclusions

The contemporary emphasis on innovation and entrepreneurship as a source of economic

growth redefines a role for government and provides a rationale for public policy and public

investment. Innovation comprises the complex and multifaceted process under which creativity

leads to practical application, commercialization, and ultimately economic and societal gain.

Considerable effort has been put toward understanding the process of innovation and identifying

the factors that increase economic growth and prosperity for a region. While there is a broad

consensus that innovation serves as an integral catalyst in leading the trajectory of an economy

and even society forward, the emphasis in economic development policy has unfortunately

remained on traditional attraction and retention incentives, often directed at specific businesses.

This is largely a zero‐sum game with little or no broader effects for economic development. In

addition, local governments tend to do more of the same policies over time, adding incremental

changes to preexisting strategies, rather than a wholesale reconsideration of their investment

strategy. There is much to gain by a new look at advances in the academic literature. Further

work could consider archetypes of places to further calibrate policy responses and help build

vibrant economies.

The model we put forward offers intuitive policy ideas to policymakers. Too often, policy

has simply tried to mimic successful industrial clusters, focused primarily on industrial

specialization, and targeted at a core industry such as biotech or information and communication

technology. Policies to build a local industrial cluster often fail due to lack of understanding of

the context and history of the location. Successful industrial agglomerations are socially

constructed and take a long time to realize their potential. Given this reality, we argue that

policymakers should consider the stage of development of the entrepreneurial ecosystem as an

important element of context to help guide investment decisions. Whether initiatives should be

sector-focused or sector-neutral should also be considered. By better understanding the stage of

18

emergence, policymakers can better consider how to overcome disadvantages and reinforce

advantages.

From these simple steps we hope to increase the dialogue around policy initiatives, which

all too often now is dominated by incentives, leaving other instruments unused. Economic

development requires a portfolio approach and a full and complete toolbox to provide for

widespread prosperity. Our work focuses on the U.S. context and further work could add

typologies of places. Another salient dimension is the urban and rural distinction as well as

consideration of the demographic and labor force characteristics of population of a place. Our

context is more applicable to the developed counties. Further work might adapt this framework

for places in developing countries.

References

Abernathy, W. J., & Utterback, J. M. (1978). Patterns of industrial innovation. Technology

Review, 80(7), 40-47.

Arthur, W. B. (1990). ‘Silicon Valley’ locational clusters: When do increasing returns imply

monopoly? Mathematical Social Sciences, 19(3), 235-251.

Auerswald, P. E., & Dani, L. (2017). The adaptive life cycle of entrepreneurial ecosystems: the

biotechnology cluster. Small Business Economics, 49(1), 97-117.

Avnimelech, G., & Teubal, M. (2006), Creating venture capital industries that co-evolve with

high tech: Insights from an extended industry life cycle perspective of the Israeli

experience. Research Policy, 35, 1477–1498.

Bartik, T. J. (1991). Who benefits from state and local economic development policies?

Kalamazoo, MI: W.E. Upjohn Institute for Employment Research.

Becattini, G. (2004). Industrial Districts: A New Approach to Industrial Change. Edward Elgar

Publishing.

Blakely, E., & Leigh, N. (2010). Planning Local Economic Development: Theory and Practice

(4th ed.). Thousand Oaks, CA: SAGE Publications Ltd.

Bonanno, A., & Goetz, S. J. (2012). Walmart and local economic development: a survey.

Economic Development Quarterly, 26(4): 285–297.

Braunerhjelm, P., & Feldman, M. P. (2006). Cluster genesis: Technology-based industrial

development. Oxford, United Kingdom: Oxford University Press.

Bresnahan, T. F., & Gambardella, A. (2004). Building high-tech clusters: Silicon Valley and

beyond. Cambridge, United Kingdom: Cambridge University Press.

Burton, M. D., Sorensen, J. B., & Beckman, C. K. (2002). Coming from good stock: Career

histories and new venture formation. In Research in the Sociology of Organizations:

Social Structure & Organizations Revisited, Vol. 19. JAI Press: Greenwich, CT; 229–262.

Carlino, G., & Kerr, W. R. (2014). Agglomeration and innovation. National Bureau of Economic

Research, No. w20367.

Christopherson, S., & Clark, J. (2007). Remaking regional economies: Power, labor, and firm

strategies. New York, NY: Routledge.

Clayton, P., Donegan, M., Feldman, M., Forbes, A., Lowe, N., & Polly, A. (2019). Local prior

employment and ecosystem dynamics. ILR Review, 72(5), 1182-1199.

Clayton, P., Feldman, M., & B. Montmartin (2020). Financing regional industrial emergence.

Working paper.

Coburn, C., ed. (1995). Partnerships. Columbus, OH: Battelle.

David, P. A., Hall, B. H. (2000) Heart of darkness: modeling public–private funding interactions

inside the R&D black box. Research Policy, 29(9), 1165-1183.

Dewar, M. E. (1998). Why State and Local Economic Development Programs Cause So Little

Economic Development. Economic Development Quarterly, 12, 68–87.

Dixit, A. (2009). Governance institutions and economic activity. American Economic Review,

99(1) 5–24.

Donegan, M., Forbes, A., Clayton, P., Polly, A., Feldman, M., & Lowe, N. (2019). The tortoise, the

hare, and the hybrid: effects of prior employment on the development of an entrepreneurial

ecosystem. Industrial & Corporate Change, 28(4), 899-920.

Erickson, R. A. (1987). Business climate studies: A critical evaluation. Economic Development

Quarterly, 1(1), 62-71.

Feldman, M. P., Francis, J. A., & Bercovitz, J. (2005). Creating a cluster while building a firm:

Entrepreneurs and the formation of industrial clusters. Regional Studies, 39: 129-141.

Feldman, M. P., and Zoller, T. D. (2016). Dealmakers in place: Social capital connections in

regional entrepreneurial economies. In Handbook of Social Capital and Regional

Development. Edward Elgar Publishing.

Flanagan, K., Uyarra, E., & Laranja, M. (2011). Reconceptualising the ‘policy mix’ for innovation.

Research Policy, 40(5), 702-713.

Foray, D. (2019). On sector-non-neutral innovation policy: towards new design principles.

Journal of Evolutionary Economics, 29, 1379–1397.

Feldman, M. P., & Francis, J. L. (2003). Fortune favours the prepared region: the case of

entrepreneurship and the capitol region biotechnology cluster. European Planning

Studies, 11(7), 765-788.

Furman, J. (2016). The Economic Benefits of Investing in U.S. Infrastructure, Chapter 6 in The

2016 Economic Report of the President. GAO, Washington, D.C.

Glaeser, E. L. (2005) Reinventing Boston, 1630–2003. Journal of Economic Geography, 5,

119–154.

Greenwald, B., & Stiglitz, J. E. (2013). Industrial policies, the creation of a learning society, and

economic development. In The Industrial Policy Revolution I (pp. 43-71). Palgrave

Macmillan, London.

Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness.

American Journal of Sociology, 91(3), 481-510.

Harrison, B. (1992). Industrial districts: old wines in new bottles, Regional Studies, 26, 469–483.

Hart, D. (2003). The emergence of entrepreneurship policy : governance, start-ups, and growth in

the U.S. knowledge economy. New York, Cambridge University Press

Isenberg, D. J. (2010). How to start an entrepreneurial revolution. Harvard Business Review, 88(6),

40-50.

Jacobs, J. (1961). The death and life of great American cities. New York, NY: Random House.

Karnoe, P., & Garud, R. (2012). Path creation: Co-creation of heterogeneous resources in the

emergence of the Danish wind turbine cluster. European Planning Studies, 12(5), 733–

752.

Kenney, M. (2000). Understanding Silicon Valley: The anatomy of an entrepreneurial region.

Stanford, CA: Stanford University Press.

Klepper, S. (2010). The origin and growth industry clusters: The making of Silicon Valley and

Detroit. Journal of Urban Economics, 67, 15-32.

Lambright, W. H. (2000). Catalyzing Research Competitiveness: The Georgia Research Alliance,

Prometheus, 18, 4 (2000): 357-372.

Lanahan, L. (2016). Multilevel public funding for small business innovation: a review of US state

SBIR match programs. Journal of Technology Transfer, 41(2), 220-249.

Lanahan, L., & Feldman, M. P. (2015). Multilevel innovation policy mix: A closer look at state

policies that augment the federal SBIR program. Research Policy, 44(7), 1387-1402.

Lerner, J. (2010). The future of public efforts to boost entrepreneurship and venture capital. Small

Business Economics, 35(3), 255-264.

Leslie, S., & Kargan, R. (1996). Selling Silicon Valley: Frederick Terman’s model for regional

advantage. Business History Review, 70, 435– 472.

Lowe, N., & Feldman, M. (2018). Breaking the waves: Innovative innovating at the intersections

of local economic development planning. Economic Development Quarterly, 32(3), 183–

194.

Lucas, R. (1988). On the mechanics of endogenous growth. Journal of Monetary Economics, 22, 3-

42.

Marx, M. (2011). The firm strikes back: non-compete agreements and the mobility of technical

professionals. American Sociological Review, 76(5), 695–712

Malecki, E. J. (2018). Entrepreneurship and entrepreneurial ecosystems. Geography

Compass, 12(3), e12359.

Martin, R., & Sunley, P. (2003). Deconstructing clusters: Chaotic concept or policy panacea?

Journal of Economic Geography, 3(1), 5-35.

Martin, R., & Sunley, P. (2007). Complexity thinking and evolutionary economic geography.

Journal of Economic Geography, 7(5), 573-601.

Martin, R., & Sunley, P. (2011). The new economic geography and policy relevance. Journal of

Economic Geography, 11(2), 357-369.

Mason, C., & Brown, R. (2014). Entrepreneurial ecosystems and growth oriented

entrepreneurship. Final report to OECD, Paris, 30(1), 77-102.

Matti, C., Consoli, D., & Uyarra, E. (2017). Multilevel policy mixes and industry emergence.

The case of wind energy in Spain. Environment and Planning C, 35(4), 661–683.

McCann, P., & Ortega-Argilés, R. (2013). Modern regional innovation policy. Cambridge Journal

of Regions, Economy and Society, 6(2), 187-216.

Moretti, E. (2012). The New Geography of Jobs. New York: Houghton Mifflin Harcourt.

Mudambi, R., Mudambi, S. M., Mukherjee, D., & Scalera V. G. (2016). Global connectivity and

the evolution of industrial clusters: from tires to polymers in Northeast Ohio. Industrial

Marketing Management, 61, 20-29.

Quinn, B. (2000), How Wal-Mart is destroying America and the world and what you can do

about it. Berkeley, CA: Ten Speed Press.

Parkhurst, E. (2012). Seattle Ranks No. 1 in tech sector job growth. Puget Sound Business

Journal.

Peterson, P. (1981). City Limits. Chicago, IL: University of Chicago Press.

Poppo, L., & Zenger, T. (2002). Do formal contracts and relational governance function as

substitutes or complements? Strategic Management Journal, 23(8), 707-725.

Porter, M. E. (1990). The competitive advantage of nations. Harvard Business Review, 68(2),

73-93.

Pfotenhauer, S. M. (2019). Building Global Innovation Hubs: The MIT Model in Three Start-Up

Universities in M Wisnioski, Does America need more Innovators? Boston: MIT Press,

191-220.

Romer, P. M. (1986). Increasing returns and long-run growth. Journal of Political Economy, 94(5),

1002-1037.

Spigel, B. (2017). The relational organization of entrepreneurial ecosystems. Entrepreneurship

Theory & Practice, 41(1), 49-72.

Spigel, B. (2020). Entrepreneurial Ecosystems: Theory, Practice and Futures. Cheltenham, United

Kingdom: Edward Elgar Publishing.

Spigel, B., Kitigawa, F., & Mason, C. (2020). A manifesto for researching entrepreneurial

ecosystems. Local Economy, https://doi.org/10.1177/0269094220959052.

Stam, E. (2015). Entrepreneurial ecosystems and regional policy: a sympathetic critique.

European Planning Studies, 23(9), 1759-1769.

Storper, M., Kemeny, T., Makarem, N. P., & Osman, T. (2015). The Rise and Fall of Urban

Economics—Lessons from San Francisco and Los Angeles. Stanford: Stanford

University Press.

Stuart, T. & Sorenson O. (2003). The geography of opportunity: spatial heterogeneity in founding

rates and the performance of biotechnology firms. Research Policy, 32(2), 229-253.

Swords, J. (2013). Michael Porter’s cluster theory as a local and regional development tool: The

rise and fall of cluster policy in the UK. Local Economy, 28(4), 369-383.

Watson, Kirk. 2001. The Austin Experience. Presentation to the Kennedy School-National

Commission on Entrepreneurship Conference on Entrepreneurship and Public Policy, April

10.

Weiss, J. (2011). The Economics of Industrial Development, London: Routledge.

Williams, W. J. (2006). University of North Carolina System. NCpedia.

https://www.ncpedia.org/university-north-carolina-system.

Witt, U. (2016). 'Economic policy making in evolutionary perspective', in Rethinking Economic

Evolution, reprint of article in Journal of Evolutionary Economics, 13(2): 77-94.

Zaheer, A., & Venkatraman, N. (1995). Relational governance as an interorganizational strategy:

An empirical test of the role of trust in economic exchange. Strategic Management

Journal, 16(5), 373-392.