Discoveries from the Atlas of Innovation Districts

A new science of cities: network theory amplifying the power of urban analytics and design

Ramon Gras Alomà (Urban Innovation researcher at Harvard and Co-Founder at Aretian Urban Analytics and Design)

A core problem facing the cities of our time: how to evaluate the impact of urban design criteria on hindering or fostering inclusive economic growth

The way we live and work is undergoing major upheaval. Our society is facing three major challenges: growing income inequality, sustainability and health concerns due to climate change, and the accelerating effects of a digital revolution that threatens to erode the way we work and relate to one another.

By way of example, inequality rates are greater than ever before. In the 18th century, the wealthiest nation in the world per capita, the Netherlands, was 4 times more prosperous than the poorest country in the world.1 In 2019, the wealthiest countries are 200 times wealthier per capita than the poorest.2 Economic stagnation is affecting more and more cities and regions around the world. This dramatic shift of wealth into the hands of a few has led to a reduction in the resources available to plan proper supportive urban environments for large swaths of the world’s population.

Business-as-usual urban planning techniques and methodologies have proven to be ill-equipped to successfully tackle such complex challenges, reveal the internal hierarchies of cities as complex systems, illuminate the hidden causal mechanisms between urban design criteria and the performance of critical urban systems, and provide solvent solutions to contemporary territorial problems.

To better understand how urban design can contribute to shape a more prosperous, equitable, and inclusive society we could ask ourselves:

- How do different urban development design criteria impact the economic development of a region, thus hindering or fostering opportunities for inclusive economic growth?

- What is the internal hierarchy of the knowledge economy within an urban region?

- Can we develop rigorous methodologies to align strategic urban design interventions can help unleash the latent potential of a society to develop distributed prosperity?

A new science of cities: high resolution of economic complexity at 3 urban scales

A booming field that has experienced vigorous advances during recent years is the combination of complexity science with network theory, to illuminate complex causal mechanisms behind macroeconomic phenomena. Studies led by professors Ricardo Hausmann (Harvard) and César Hidalgo (MIT) shed light on the problem of identifying the ingredients and dynamics that are the motor of the prosperity of the nations.

The Economic Complexity model developed by Hausmann and Hidalgo far exceeds all the previous leading indicators and key performance metrics to depict societal prosperity and predict future economic growth. Their research identified that the main engine of a country's economy is the collective know-how of society. Their model presents solid prospects for accurate growth diagnostics at the aggregate, national scale. However, as of today it suffers from a great limitation: the vast majority of economic decision-making occurs at smaller, sub-national scales: regional, city and company/institution levels.

How can we bridge the gap between their revolutionary macroeconomic complexity model and high-resolution urban modeling? Can we territorialize the economic complexity model at the urban scale? If so, what does that mean to city science and the urban design discipline, in terms of evaluating different design criteria to shape the urban fabric?

Aiming to answer such questions, alongside fellow classmate and research colleague at Harvard, Jeremy Burke, we have devoted the last several years to design a complexity science and network theory-led Urban Analytics and Design Engine. We have territorialized the economic complexity model at three subnational scales: regional, urban, and architectural. To illustrate the power and potential of the methodology we analyzed how economic complexity can be modeled at the urban scale, and how can we extract lessons to better inform urban design criteria and investment decision-making.

The Atlas of Innovation Districts: a network theory application unveiling the relationship between urban design and economic complexity

Innovation is the acceleration at which the collective knowhow is propelled, thus generating cycles of prosperity. In order for us to acquire a deeper understanding of how Economic Complexity unfolds at the urban scale, it is critical to understand the hidden mechanisms behind innovation. Bearing that in mind, how can we unleash the latent economic potential of our cities? Is it within reach for us to strengthen and nurture the key factors that enable communities to thrive?

To answer such questions, we analyzed systematically the top 50 Innovation Districts across the US territory, though the lens of network theory. The results have been revealing beyond what we expected, and we summarized some key insights and takeaways in a white paper report published this last summer: the very first Atlas of Innovation Districts. 

Discoveries from the Atlas of Innovation Districts

We recently published the Atlas of Innovation Districts, a first-of-its-kind systematic study of 50 notable Innovation Districts in the United States: their specialization, economic impact, as well as the urban design characteristics of the urban ecosystems that welcome and enhance them. The Atlas builds on their broader work developing a ‘scientific theory of cities’, bringing together cutting-edge techniques in the fields of data analytics, complexity science, and network theory-driven machine learning to produce high-resolution digital models of cities. 

Analyzing the economic prosperity of a city through this lens has revealed that building Innovation Districts in cities can lead to distributed wealth for the people who live and work there, unlocking the latent potential of a community. Through our analyses we learned that the most effective Innovation Districts intentionally develop 3 kinds of networks:

• Networks of Talent: composed of individual professionals collaborating within the labor force, 

• Networks of Organizations collaborating together, and 

• Networks of Urban Infrastructure: the physical urban environment these organizations are distributed across, which host and support the economic ecosystem.

By territorializing economic performance metrics throughout the US, we were able to measure the societal surplus generated by knowledge-intensive clusters. Such approach allowed us to discern what role play the networks of talent, industries and urban infrastructure in hindering or propelling the economy. One of the key takeaways of our clustering analysis is that the key component which shapes the nature of innovation districts is the anchor institution that plays a central role within them: whether it is the city government, a research or academic institution, an industry cluster, a governmental research and development agency, or a bottom-up entrepreneurial hub. Each of the five types of anchor institutions conform distinct typologies of urban fabric, employment opportunities, and industry growth patterns. 

The deployment of this new methodology helped us understand the internal hierarchy of urban systems and evaluate different urban design patterns. From a social physics perspective, compact cities tend to outperform urban areas characterized by urban sprawl in fostering innovation-intensive communities. Interestingly, the results of the analysis showed that districts with urban fabric with an intermediate level of density, around 5 to 7 story buildings, achieve much higher levels of innovation intensity and performance than those of high-rise skyscrapers. The results of analyzing different urban topologies, morphologies, levels of entropy and density show that cities structured around scale-free, fractal models clearly outperform not only rigid grids but also radial/concentric models and in enhancing fruitful interaction between professionals, companies and organizations. Moreover, scale-free urban systems with a fractal nature also tend to present a more optimal distribution of amenities, services, and transportation networks. Such urban design patterns also present the top-performing levels of energy, water, and transportation efficiency from a sustainable standpoint.

On average, innovation districts tend to outperform regular business districts in their ability to generate new products, services, and solutions to societal problems. Furthermore, innovation districts present a higher level of meritocracy than average downtown business districts or suburban technology parks.  The most socially egalitarian being the ones led by City Governments and Universities, and the least egalitarian being Governmental Agencies (such as Oak Ridge Supercomputer), still more merit-based than the average district in the US

Innovation districts generate exponential employment, and knowledge-intensive employment opportunities, wealth creation and innovation performance:

• 4x times more innovations per employee (new patents, products, services, processes, R&D, scientific papers)

• 9x time more employment per resident

• 15x times more knowledge-intensive employment per resident

• 20x times more wealth created per resident

On top of that, unemployment rates present inverse relationship with our measure (KPI) for innovation intensity, described as the percentage of employment in knowledge-intensive activities. Such relationship is critical when we consider strategies to mitigate the potential job destruction as a result of automation, AI and robotics. 

From a decision-making standpoint, the methodology also revealed causal mechanisms behind innovation dynamics at the regional, urban, and architectural level. Successful innovation districts provide the proper support at each of the different phases described.

Towards a new science of cities 

Thoughtful design of our urban environments is paramount as we foster and shape our relationship with the natural world and create healthy, sustainable spaces.3 By acquiring a deeper understanding of how cities operate as complex systems, and being able to identify in a rigorous way untapped decision-making and investment opportunities, we can identify what strategic urban design interventions can help unleash the potential of our communities, thus opening the path for creative and solvent solutions to the hard problems of our time. 

From policymakers, urban designers, civil engineers, and architects to technologists, economists, and other professionals, many stakeholders want to understand the drivers of economic growth and how to harness them for the sustainable benefit of their communities.

The lessons learned during the development of the Atlas of Innovation Districts present a promising prospect for further development of a scientific approach to urban analysis, to help support urban design criteria selection, and help us understand how to envision, design, and build the cities of the future, whilst inducing distributed prosperity, and a more humane society.  

Bibliography:

1. Smith, Adam, and NetLibrary, Inc. Wealth of Nations. Hoboken, N.J. : Boulder, Colo.: BiblioBytes ; NetLibrary, 1990.

2. Hausmann, Ricardo. “In Search of Convergence | by Ricardo Hausmann.” Project Syndicate, August 20, 2014. https://www.project-syndicate.org/commentary/ricardo-hausmann-asks-why-growth-rates-are-convergingamong-some-countries-and-diverging-among-others.

3. Cerdà, Ildefons. Vicente Guallart, Angela Kay Bunning, Anne Ludlow, Graham Thomson, Institut D’Arquitectura Avançada De Catalunya, Publisher, Editor, Barcelona . Diputació, and Bloomberg Philanthropies. General Theory of Urbanization, 1867. Barcelona : New York: IAAC - Institute for Advanced Architecture of Catalonia ; Actar Publishers, 201