A Framework for Modern Technology-Based Economic Development

Why TBED matters now

Technology-based economic development (TBED) rests on a long lineage of scholarship and policy. Joseph Schumpeter’s concept of creative destruction emphasized how new technologies and entrepreneurial firms transform economies (Schumpeter, 1942), while Vannevar Bush’s Science, The Endless Frontier (1945) established the postwar federal research system that still anchors U.S. innovation policy. Over time, states adapted the federal model in their own ways, creating seed funds, university partnerships, and business incubators to foster commercialization and regional innovation. In today’s environment of global competition and rapid technological convergence, TBED provides a framework for linking research, entrepreneurship, and workforce development to expand regional opportunity and national competitiveness. New federal programs, including NSF Regional Innovation Engines and the CHIPS and Science Act, demonstrate renewed national commitment to building distributed innovation capacity across the country.

The framework for modern TBED

As demonstrated by 2025 Nobel Economics laureate Joel Mokyr, economic growth is inseparable from technological progress and the cultural and institutional frameworks that enable it (Mokyr, 2016). Modern TBED works best when research institutions, entrepreneurial support organizations, capital providers, and workforce systems communicate in a coordinated manner. In fact, federal initiatives such as the EDA Tech Hubs Program, the Department of Energy’s Manufacturing USA Institutes, and the EDA Build to Scale (B2S) Program require collaborative governance and shared outcomes. The B2S program, in particular, focuses on strengthening entrepreneurial ecosystems and increasing access to capital. State-level institutions such as the Massachusetts Technology Collaborative and the Georgia Electric Mobility Alliance demonstrate how states integrate workforce, capital, and applied research strategies. Venture development models like Innovation Works in Pittsburgh and inclusive workforce intermediaries such as Per Scholas demonstrate how regional partners braid funding streams and support the full innovation pipeline. The TBED framework thus emphasizes systems-building: aligning multiple agencies and institutions around common goals, measurable outcomes, and long-term sustainability.

Innovation infrastructure and ecosystem development

Innovation infrastructure usually refers to the mix of facilities, institutions, and networks that enable research, commercialization, and workforce readiness. Modern infrastructure extends beyond physical labs to include shared testbeds, collaborative research centers, and distributed innovation networks. Examples include the Austin Technology Incubator at the University of Texas, which integrates entrepreneurship into university research culture, and the Penn State LaunchBox Network, which demonstrates how university systems can distribute entrepreneurial support across multiple communities.

State-level coordination through organizations such as Oregon InC shows how strategic investment in applied research centers and industry consortia strengthens regional competitiveness. The Maryland Innovation Initiative (MII) provides another example by funding technologies from university labs into viable companies, directly linking infrastructure investment to commercialization. Federal initiatives, including NSF Engines and DOE Manufacturing USA Institutes, reinforce these investments by pairing infrastructure upgrades with workforce and commercialization goals.

Finance and access to capital

Access to capital is a foundational component of technology-based economic development, enabling entrepreneurs to transform research and innovation into scalable companies. Public programs often fill gaps in early-stage financing where private capital is limited, especially in emerging regions. The State Small Business Credit Initiative (SSBCI 2.0) has expanded state venture and loan programs, while federal initiatives such as the Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs provide non-dilutive funding that helps firms advance early technical milestones.

State-led venture entities illustrate how public capital can catalyze private investment, support technology commercialization, and anchor regional startup ecosystems. Examples include:

MassVentures (Massachusetts): A direct equity investor focused on funding startups in emerging tech sectors.

The Maryland Venture Fund: Invests in early-stage technology companies to promote economic growth.

The One North Carolina Small Business Program: Provides matching grants for federal SBIR/STTR awards.

Effective TBED capital systems rely on blended financing strategies, strong local intermediaries, and coordination among investment, commercialization, and workforce partners.

Entrepreneurship and venture development

Entrepreneurship serves as the mechanism through which innovations become market-ready products, services, and companies. Successful TBED regions cultivate pipelines of entrepreneurs by linking university research, mentorship networks, and early-stage financing.

Venture development organizations accelerate startup growth through technical support, investment readiness, and customer discovery programs. Examples include:

Ben Franklin Technology Partners (Pennsylvania): A long-term, mission-oriented intermediary that provides capital and business expertise.

TechAccel (Kansas City): Focuses on advancing technologies in the agriculture and animal health sectors.

Greentown Labs (Texas): A leading climatetech incubator that provides specialized resources for climate and energy startups.

Effective entrepreneurship systems depend on coordinated programming, strong investor engagement, and integration with regional research, talent, and infrastructure assets.

Workforce and talent development

Modern TBED depends on talent pipelines that support emerging industries in fields such as advanced manufacturing, clean energy, biotechnology, and artificial intelligence. Workforce development is no longer treated as a downstream activity but as an integral pillar of innovation ecosystems.

Regional and state models demonstrate how to create responsive training pathways:

The Michigan New Jobs Training Program (Michigan): Helps community colleges provide customized training for businesses that create new jobs.

The Alabama Federation for Advanced Manufacturing Education (FAME): An employer-led apprenticeship model connecting community colleges and industry.

The BioManufacturing Workforce Initiative (North Carolina): A sector partnership addressing specialized skill needs in the life sciences industry.

The most effective talent systems emphasize employer engagement, stackable credentials, and alignment with R&D and commercialization strategies.

Commercialization and technology transfer

Technology commercialization links academic and corporate research to entrepreneurial activity and industry adoption. Universities and research institutions increasingly employ structured models to guide this process, using proof-of-concept funds, licensing teams, and industry partnerships to advance promising discoveries.

Examples of successful commercialization engines include:

The University of Michigan’s Innovation Partnerships program accelerates the movement of technologies toward market through IP management and startup support.

The Johns Hopkins FastForward initiative combines internal resources with external partnerships to launch new ventures based on university research.

The University of Utah’s Technology Licensing Office is known for its successful startup creation and licensing performance.

Recognizing that most researchers are not trained as entrepreneurs, federal programs such as DOE’s Lab-Embedded Entrepreneurship Program (LEEP) and NSF’s I-Corps help scientists translate research insights into commercially relevant solutions. Effective commercialization systems focus on reducing barriers for researchers, strengthening incentives for industry engagement, and maintaining a pipeline of investable innovations.

Cross-program integration and system coordination

TBED success increasingly depends on the ability of institutions to coordinate across programs, agencies, and funding streams. Integration ensures that investments in research, capital, and workforce development reinforce one another rather than operate in isolation.

Federal initiatives such as NSF Engines, EDA Tech Hubs, DOE Manufacturing USA Institutes, and EDA Build to Scale encourage alignment by requiring multi-institution partnerships and shared outcome tracking.

States such as Colorado, North Carolina, and Iowa demonstrate strong system coordination models through unified governance and aligned funding:

Colorado demonstrates a horizontal integration strategy in which the Colorado Workforce Development Council provides a high-level, multi-stakeholder platform for aligning workforce, education, and economic development. The Advanced Industries Accelerator reinforces this by requiring applicants for funding to demonstrate partnership and non-state matching funds, structurally enforcing collaboration between industry, researchers, and regional partners.

North Carolina’s community college network and the University of North Carolina (education and talent providers) are tightly connected to the Department of Commerce (economic development and business recruitment). This integration ensures that talent pipelines are immediately responsive to the needs of specific, high-growth industrial sectors.

The Iowa Economic Development Authority Board includes representatives from government, education, and business, allowing it to coordinate and administer the state’s programs across entrepreneurial support, business attraction, targeted industry assistance, and workforce training. This centralized structure minimizes internal agency friction and provides a unified TBED strategy.

Effective cross-program coordination relies on clear governance structures, common metrics, and durable partnerships among universities, industry groups, and public agencies.

Evaluation, metrics, and continuous improvement

As TBED systems mature, evaluation has become central to accountability and helping regions learn what’s actually working. Modern practice uses a balanced approach of both quantitative and qualitative measures to assess ecosystem health and program effectiveness.

Quantitative measures are critical for tracking direct economic and innovation outputs and providing objective, comparable data. Key metrics include venture investment, patenting and licensing, employment growth, startup survival rates, and R&D expenditure.

Qualitative measures capture the health, maturity, and connectivity of the ecosystem. Things like partnership strength, institutional capacity, inclusivity, and effective governance are important for understanding the local ecosystem but can be difficult to quantify.

Continuous improvement is not merely about compliance; it is about strategic, adaptive program design. Effective regions deploy shared dashboards, independent assessments, and longitudinal tracking to understand how interventions influence ecosystem development over time. This approach treats TBED investments as hypotheses to be tested, with built-in flexibility to adjust program features or resource allocation based on evidence.

Ohio Third Frontier is a state-level program that combines funding with mandatory, structured evaluation. It links continued funding to clear, measurable performance indicators (e.g., detailed reporting on follow-on funding and new jobs).

The NSF Engines program mandates detailed metrics spanning research, translation, workforce development, and ecosystem health, with the expectation that the consortium will use this data to inform an adaptive management strategy over its anticipated 10-year lifespan.

Federal and state TBED policy landscape

The U.S. TBED landscape is shaped by a mix of federal programs, including SSBCI 2.0, SBIR/STTR, EDA Tech Hubs, NSF Engines, DOE Manufacturing USA Institutes, and DOL apprenticeship initiatives. These programs reflect a significant shift toward place-based, ecosystem-oriented approaches. This new focus recognizes that innovation is fundamentally geographically concentrated and dependent on the dense network of relationships within a specific region. This dependence on relationships necessitates collaboration across institutions and levels of government, requiring universities, private industry, state agencies, and local government to co-create strategies. For instance, the NSF Engines program mandates regional consortia, and the EDA Tech Hubs require comprehensive regional development plans, compelling stakeholders to align their goals for shared regional prosperity.

States amplify and complement federal efforts through various organizations. Each example cited illustrates a different model of state-level TBED execution:

The Oklahoma Center for the Advancement of Science and Technology serves as a central hub for providing research grants, seed funding, and R&D support to diversify the state's economy.

The Kentucky Cabinet for Economic Development integrates TBED priorities, such as advanced manufacturing or aerospace, into broader economic development and business attraction strategies, including offering incentives and supporting site development.

The Washington State Clean Energy Fund is a sector-specific, mission-driven public investment vehicle. It uses state resources to spur private investment in clean energy technologies, aligning economic strategy with climate goals.

The Choose New Jersey program focuses on business attraction and often works in tandem with the state's technology and innovation funding mechanisms. It demonstrates how TBED relies on an external-facing body to market the state's established innovation infrastructure and talent base to potential businesses.

Understanding the interplay among programs helps practitioners design strategies that leverage federal resources, align state priorities, and build sustainable regional capacity.