In the year since we released “The Rise of Innovation Districts: A New Geography of Innovation in America,” Brookings has visited or interacted with dozens of leaders in burgeoning innovation districts in the United States and Europe. In so doing, we’ve sharpened our knowledge of what’s happening on the ground and gained some important insights into how cities and metros are embracing this new paradigm of economy-shaping, place-making, and network-building.

Innovation districts capture the remarkable spatial pattern underway in the innovation economy—the heightened clustering of anchor institutions, companies, and start-ups in small geographic areas of central cities across the United States, Europe, and other global-trading regions.

The rise of innovation districts has been situated against the familiar backdrop of suburban corporate campuses and science parks. Accessible only by car, these spatially isolated corridors place little emphasis on the quality of life or on integrating work, housing, and recreation.

By contrast, in our report we found the rise of urban innovation hubs to be the organic result of profound economic and demographic forces that are altering how we live and work. The growing application of “open innovation”—where companies work with other firms, inventors, and researchers to generate new ideas and bring them to market—has revalued proximity, density, and other attributes of cities. At the same time, the growing preference of young talented workers to congregate in vibrant neighborhoods that offer choices in housing, transportation, and amenities has made urban and urbanizing areas increasingly attractive.

We also found that innovation districts uniformly contain a mix of economic, physical, and networking assets. Economic assets are the firms, institutions, and organizations that drive, cultivate, or support an innovation-rich environment. Physical assets are the public and privately owned spaces—buildings, open spaces, streets, and other infrastructure—designed and organized to stimulate new and higher levels of connectivity, collaboration, and innovation. Lastly, networking assets are the relationships between actors—such as between individuals, firms, and institutions—that have the potential to generate, sharpen, and/or accelerate the advancement of ideas. These assets, taken together, create an innovation ecosystem—the synergistic relationship between people, firms, and place that facilitates idea generation and advances commercialization.

One year later, innovation districts continue to rise. What have we learned about how they are evolving?

First, the model of innovation districts has been embraced, co-opted, and (in some cases) misappropriated, further reinforcing the need for grounding this work in empirically based evidence.

A simple Google search will reveal the extent to which the language of “innovation districts” (or “innovation quarters,“ “innovation neighborhoods,” or “innovation corridors”) has rapidly permeated the field of urban and metropolitan economic development and place-making.

In some places, this labeling is being accurately used by globally recognized research institutions (e.g., Carnegie Mellon in Pittsburgh, Drexel University in Philadelphia) that are both experiencing extraordinary growth near their campuses as well as designing intentional efforts to build on their distinctive assets. In communities as diverse as Philadelphia, Pittsburgh, and St. Louis in the United States and Manchester and Sheffield in England, local leaders are conducting deep empirical analysis to understand their competitive advantages and existing weaknesses within their innovation ecosystem. They are exploring what it means to encourage greater collaboration and cooperation across their institutions, firms, and entrepreneurs. And they are exploring ways to better create “place” so as to increase overall vitality, facilitate innovation, and spur the growth of new businesses and jobs.

In other places, the nomenclature reflects an aspiration—and is spurring more deliberate efforts by local stakeholders to grow distinctive innovation ecosystems. In cities like Albuquerque, N.M., Chattanooga, Tenn., Chicago, Ill., Durham, N.C., and San Diego, Calif., local leaders are using the innovation district paradigm as a platform to measure their current conditions, develop strategies for addressing gaps and challenges, and build coalitions of stakeholders that can together help realize a unified vision for innovative growth. Some of these budding districts represent typologies not outlined in our report but that are ripe for future research, including “start-up” enclaves in or near downtowns of cities that lack a major anchor as well as “public markets” that blend locally produced food products and crafts with maker spaces, digital design, and other innovations in the creative arts.

There is one unfortunate trend in the rising use of the "innovation district" lexicon. In a number of cities, local stakeholders have applied the label to a project or area that lacks the minimum threshold of innovation-oriented firms, start-ups, institutions, or clusters needed to create an innovation ecosystem. This appears to result either from the chase to jump on the latest economic development bandwagon, the desire to drive up demand and real estate prices, or sometimes a true lack of understanding of what an innovation district actually is. The motivation for real estate developers to adopt the moniker seems clear: to achieve a price premium for their commercial, residential, and retail rents. Yet these sites are typically a collection of service-sector activities with little focus on the innovation economy. The lesson: labeling something innovative does not make it so.

From all these observations, it is clear that the field needs a routinized way to measure the starting assets of innovation districts—both to separate true districts from “in name only” ones as well as to give individual communities a platform for developing targeted strategies going forward. This means both running the numbers—conducting a quantitative audit—and undertaking a more qualitative assessment of strengths and weaknesses. Irrespective of their phase of development, innovation districts must evaluate the extent to which they have a critical mass of economic, physical, and networking assets to collectively generate the vitality that these districts demand. They need to evaluate the competitive advantages they have in certain economic sectors and learn how to cultivate them. And they need to ensure that they have the connectivity, diversity, and quality of place necessary to create a unique and vibrant environment in which innovation can thrive.

To facilitate this process, we are working in close collaboration with Mass Economics and the Project for Public Spaces to develop an audit template and tool. Over the next year, we intend to sharpen this tool in a subset of innovation districts across the country and then encourage others to employ it in their own established or burgeoning districts.

Second, the core economic assets of innovation districts are not fixed; in fact, many innovation districts are being created or enhanced by the relocation of major anchor facilities as institutions strive to achieve the highest return on investment.

The conventional notion of an “anchor” institution is that it is solidly weighted in a particular place. Yet over the past decade a substantial number of innovative companies and advanced educational and research institutions have moved key facilities and units as a means of generating greater innovation output. Examples of new locations include the University of California-San Francisco’s biotechnology campus in Mission Bay (2003); the University of Washington’s medical research hub in Seattle’s South Lake Union (2005); Brown University’s medical school in downtown Providence, R.I. (2011); Duke’s Clinical Research Institute in downtown Durham (2013); Carnegie Mellon University’s Integrative Media Program in the Brooklyn Navy Yard (2013); and, most famously, the new Cornell Tech campus on Roosevelt Island in New York City (2015).

These “first mover” relocations show how corporate and university leaders are departing from the tradition of building new facilities within their existing footprint and are willing to seek out new areas (and even new cities) to retain, or achieve, competitive advantage in their respective clusters and fields. As Cornell Professor Ronald Ehrenberg said about his school’s isolated Ithaca, N.Y. campus, “It is very, very difficult for us to do the kind of development through tech transfer that a place like Stanford or Berkeley can do in San Francisco or Harvard or MIT can do in Boston.” Our strong sense in talking with leaders around the country is that we are still at the early stage of corporate and university relocations given the extent to which urban areas have been revalued. The physical relocation of key innovation assets has now become a critical competitiveness strategy for companies, universities, and even states.

In some cases, the “unanchoring of anchors” is also compelling local leaders to rethink the traditional borders and boundaries of the innovation economy. In Philadelphia, for example, University City has always been recognized as a settled innovation hub, given the co-location of such anchor institutions as Drexel University, the University of Pennsylvania, the University City Science Center, and others. The recent decision of Comcast to consolidate its corporate presence in the downtown area and build its major new Innovation and Technology Center less than 10 blocks from 30th Street Station and the Drexel Campus is convincing some leaders to “stretch” Philadelphia’s University City district to incorporate this new corporate giant.

Third, almost all innovation districts have significant work ahead to understand the rising value of “place” in the innovation ecosystem and leverage or reconfigure their physical assets to create dense and dynamic communities.

While our paper dissected various types of physical assets to help practitioners understand their individual roles and value, the more important message to convey now is the imperative to combine and activate physical assets in ways that create vibrant “places.” The Project for Public Spaces aptly describes place as “…environments in which people have invested meaning over time. A place has its own history—a unique cultural and social identity that is defined by the way it is used and the people who use it.”¹

Our review of innovation districts, including those cited in our paper, reveals that many have not yet maximized the potential for creating lively communities in which their residents and workers feel invested, reducing the potential innovation output of these communities. When designed and programmed well, a district’s public spaces—whether within buildings or outside of them—facilitate open innovation by offering numerous opportunities to meet, network, and brainstorm. Strong places entice residents and workers to remain in the area off hours, extending the opportunities for collaboration. Strong places create a culturally and educationally enriched environment that strengthens human interaction, knowledge, and motivation.

While some university-led districts have made some improvements over the years, districts anchored by medical campuses have significant work ahead. These spaces were designed as isolated fortresses that valued parking over walking (ironic given their health mission), with little or no attention paid to amenities, cultural activities, retail, or housing. Significantly, some medical campuses are often located in close proximity to downtowns, as part of universities, or near organic entrepreneurial communities (e.g., the proximity of Oklahoma City’s Health District to Automobile Alley). This raises the potential for smart (and related) place-making activities in a nearby area and reinforces the need to rethink traditional geographies and artificial boundaries when considering interventions.

Fourth, the rapid growth and impact of national intermediaries (what we call innovation cultivators) shows real promise in helping innovation districts grow and steward their networking assets and stimulating new innovation opportunities.

The past year has seen substantial growth in multicity intermediaries along with scores of locally grown accelerators and incubators. It appears more than ever that intermediaries are increasingly the catalyst to growing innovation and entrepreneurial energy within local districts and across start-ups, small and medium-sized enterprises, and, even to some extent, large companies and research institutions. They are designed to think and act horizontally, encouraging people and firms to interact and work together in ways and at a scale previously unseen.

A growing and increasingly important role for intermediaries is helping innovation districts evolve from the traditional “research and development” model to a “search and development” one, where crucial answers to their innovation questions and technological challenges are discovered by finding and collaborating with other firms. Some districts immediately recognized this potential and have gone to great lengths to grow, lure, and fund the development of multiple intermediaries across their districts.

The Cortex Innovation Community in St. Louis has, in a short period, clustered new buildings owned and/or supported by a number of well-respected intermediaries. These development and programmatic moves are effectively creating a new focal point for Cortex innovation activities. The new Cambridge Innovation Center, which offers space for start-ups combined with access to venture capital firms, professional services, and a plug-and-play physical environment, is already at 85 percent occupancy. A newly constructed Tech Shop—a do-it-yourself “maker space” equipped with industrial tools, machinery, and technology to support entrepreneurs—is under construction nearby. The near complete renovation of the Center for Emerging Technologies, which provides training, specialized facilities, and technical support, adds yet another layer of support for entrepreneurs and start-ups. Adding more to this mix is a soon-to-be-constructed space for tech-commercial activities combined with new housing, which will exponentially increase the number of people in a very small radius.²

As one can imagine, this clustering was deeply intentional and viewed as a way to stimulate new relationships, new networks, and the cross-fertilization of ideas; Cortex refers to this deliberate process as “innovation engineering.” We anticipate more innovation districts to follow suit, pursuing, if not cultivating, such intermediaries in their own innovation ecosystems.

Finally, the rise of innovation districts takes place in a national and urban political environment that demands inclusive growth and equitable outcomes.

The past year has seen the elevation of income inequality and social mobility as issues of national and urban significance. With the federal government mired in partisan gridlock, cities have become the vanguard of efforts to raise the minimum wage, expand affordable housing, and extend pre-K education, among other initiatives. These efforts come at a time when the civil unrest in Baltimore and Ferguson has refocused national attention on neighborhoods of high poverty.

Because of their location in the cores of central cities, many established and emerging innovation districts are located several blocks away from distressed communities. This proximity creates an enormous opportunity to show the positive impact that innovative growth can have on inclusive outcomes. Innovation districts create employment opportunities that can be filled by local residents and procurement and construction opportunities that can be fulfilled by local vendors and contractors. The districts generate tax revenues that can be used to fund neighborhood services and neighborhood regeneration. And they offer the potential to link the ample expertise and talent in anchor educational institutions with the needs of neighborhood schools and children.

Recognizing these benefits, local leaders are demonstrating a genuine commitment to growing more inclusive districts. In our work, we’ve seen several early models that could be built on and replicated. In the Barcelona 22@ district, for example, leaders are trying to quantify the growth in service jobs accessible to local and regional residents while, at the same time, connecting those residents to training that increases their skills in more innovation-oriented sectors. Last year, Drexel University opened a new “urban extension center” that offers career-building workshops, legal clinics, and other services to residents of the adjacent Mantua Promise Zone. The Evergreen Cooperative in Cleveland’s University Circle district has been working for several years to leverage local purchasing power to create business ownership and employment opportunities for low-income residents. And in Baltimore, the University of Maryland partnered with surrounding neighborhood organizations, residents, and institutions to develop a detailed new plan for building what the Baltimore Southwest Partnership envisions as a “diverse, cohesive community of choice built on mutual respect and shared responsibility.”

These examples represent concrete initiatives to ensure that nearby neighborhoods and their residents connect to and benefit from new growth opportunities in innovation districts and beyond. Scaling such efforts will be critical in the years to come, as the success of these districts will be defined in large part by their broader city and regional impacts.

As Brookings works this year to help unleash more innovation districts across the U.S. and Europe, we will continue to hone our observations and knowledge about trends, challenges, and strategies. We will compile and publish what we have learned for anchor leaders, policymakers, scholars, and practitioners, focusing on many of the issues—accelerating commercialization to improving inclusion—noted above. We will do this work in close collaboration with proven organizations like Mass Economics and Project for Public Spaces. We look forward to contributing to this rapidly changing space via empirical and on-the-ground research, strategy and policy development, convenings, and network building. Stay tuned.

Read The Rise of Innovation Districts: A New Geography of Innovation in America

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Less than two years ago, the Brookings Institution unveiled the research paper, “The Rise of Innovation Districts,” which identified an emerging spatial pattern in today’s innovation economy. Marked by a heightened clustering of anchor institutions, companies, and start-ups, innovation districts are emerging in central cities throughout the world.

A Google search of the term “innovation district” reveals over 200,000 results, indicating the extent to which the phrase has permeated the fields of urban economic development, planning, and placemaking. The term is used to refer to areas, often in the downtowns of cities, where R&D-laden universities or firms are surrounded by a growing mix of start-ups and spin-offs. The term is also increasingly applied to densely populated urban neighborhoods where firms like Google are establishing campuses. But it also pops up to describe new office complexes whose amenities include a few stores or a fashionable coffee shop.

The variation in understanding of the term and its application suggests the need for a routinized way to measure the essential quantitative and qualitative assets of innovation districts. Given this, for the past nine months the Brookings Institution, Project for Public Spaces (PPS), and Mass Economics have collaborated to devise and test an audit tool for assessing innovation districts.

What to count? Considerations in designing an audit

Innovation ecosystems comprise complex, overlapping relationships between firms, individuals, unique spaces, private real estate, public infrastructure, capital, expertise, and conviviality, congregated in a roughly delineated area. To begin to determine how to identify and measure assets, we developed a process that was both rigorous and reflective, drawing together some of the brightest minds in the field, top practitioners on the ground, and a team strong in quantitative analysis.

First, we conducted research across numerous relevant topics including entrepreneurship, real estate development, commercialization, economic geography, city planning, institutional culture, finance, and inclusive development. This exercise generated hundreds of potentially applicable measures for the audit.  

       

Innovative activity and innovation districts are not evenly distributed across cities. Some metropolitan areas may have two or three districts scattered about, while other cities are lucky to have the critical mass to support even one strong district. London, however, a global city with nearly unparalleled assets, can best be understood as not just a collection of innovation districts but as a contiguous “city of innovation.” 

Our understanding of that innovative activity has taken a leap forward with the publication of a new report by the Centre for London called "Spaces to Think". Even for a paragon of innovation, a critique such as this is imperative if the city desires to maximize its assets while continuing to grow in a sustainable and inclusive manner. Much as we have recommended that urban leaders across the United States undertake an asset audit of their districts to identify key priorities, "Spaces to Think" focuses on 17 distinct districts, mapping their assets, classifying their typologies, and identifying governance structures.

The 17 study areas in "Spaces to Think"

The report provides lessons applicable to many cities.

Having identified, across all 17 districts, the three major drivers of innovative activity—talent, space, and financing—it becomes clear that the main hurdle for London, as a global magnet of talent and capital, is affordable physical space: “Increasing pressure for land…risks constraining London’s potential as a leading global city for innovation.” Similar to hot-market cities across the United States, many of the study areas of greatest promise are older industrial areas, such as Here East, Canary Wharf, and Kings Cross, where large plots of underutilized land have been reimagined as innovation districts. 

But who is prepared to undertake new regeneration projects? The report places significant responsibility on London’s many universities—whose expansions already account for much of the large-scale development opportunities in the city—for a “third mission” of local economic development. It is universities, the report notes, that are “devoting increasing amounts of money, resources, and planning to building new or redesigned facilities…pitched as part of a wider regeneration strategy, or the creation of an innovation district.” 

A second concern is the democratization of the innovation economy. Already a victim of rising inequality, London’s future growth must reach down the ladder. As we’ve argued, with intentionality and purpose, innovation districts can advance a more inclusive knowledge economy, especially given that they are often abut neighborhoods of above-average poverty and unemployment. Spaces to Think expands upon four key strategies: local hiring and sourcing practices for innovation institutions; upskilling of local residents through vocational and technical programs within local firms; increased tax yield, especially given recent reforms in which “local authorities retain 100 percent of business rates”; and shared assets and rejuvenation of place. This final lever requires inclusive governance that encourages neighborhood ownership of the public realm.

Finally, the report notes that, while there is much diversity of leadership in the study areas—some are university-led, some are entrepreneurial, some are industry-led—“good governance and good relations between institutions, are at the heart of what makes innovation districts tick.” This issue is at the heart of our work moving forward: identifying and spreading effective governance models that encourage collaboration and coordination between the public, private, and civic actors within innovation districts.

We are pleased that this future work will be strengthened by a new partnership between the Bass Initiative on Innovation and Placemaking and the Centre for London. The ambition of this Transatlantic Innovation Districts Partnership is to increase our mutual understanding of innovation districts found in Europe through additional qualitative and quantitative analysis and to integrate European leaders into a global network, all to accelerate the transfer of lessons and best practices from districts across the world.

       

A Q&A with Dennis Lower, president and CEO, Cortex Innovation Community

As leaders scan the landscape for strong examples of innovation districts, their tour is hardly complete without learning of the Cortex Innovation Community—an innovation district in the heart of St. Louis. We sat down with Dennis Lower, president and CEO of the Cortex Innovation Community to learn what kinds of interventions and instruments are driving their success.

What is the Cortex Innovation Community?

Cortex is the region’s largest innovation hub, generating 3,800 tech-related jobs and over $500 million in investment in the last 14 years. It’s located close to downtown and built on the intellectual assets and resources of St. Louis’ leading universities, a premier health care provider, and the Missouri Botanical Garden. The focal point is the 200 acres of old industrial land that one time separated these institutions but that now stitches them together. At full build-out, Cortex will likely generate $2 billion of development and create 13,000 jobs.

What sets Cortex apart from other innovation districts?

Of course, every district is distinctive and unique, building off its local character, culture, and assets. What sets Cortex apart, I would argue, is that we literally have billions of dollars of academic, cultural, and recreational assets in the neighborhoods that surround the district, which other places simply do not have.

We are bookended by two universities—Washington University and St. Louis University—each a magnet for international students and each with a reputation for research and academic excellence. Washington University, for example, was one of five consortium members funded by the National Institutes of Health to map the human genome. These universities, together with the University of Missouri-St. Louis, are the academic bedrock of our local innovation ecosystem.

Recent demographic analysis tells us we are now the most diverse employment environment in the region no matter how you slice it, including by age, ethnicity, and educational attainment.

Another Cortex advantage is the neighborhood that surrounds us. In addition to historic housing, the Grand Center arts district is to the east, to the west is Forest Park, which contains the St. Louis Zoo, fine arts and history museums, two golf courses, the St. Louis Science Center, abundant walking and biking trails, and the internationally renowned Botanical Garden. Restaurant corridors are to the north and south. I tell you all this to say that Cortex is where innovation, tech, culture, and community collide—and people are hungry for this mix.

Cortex Innovation Community is also a tax-exempt 501(c)3 that oversees the design and development of the innovation district. What makes your nonprofit unique in managing this district?

Cortex has been designated the master developer to transform an old industrial district into a center for innovation and commercialization. We are in a particularly advantageous position because the state and the city have granted the 501(c)3 powers of eminent domain, the power to abate taxes, and the power to approve or reject building plans. From a traditional economic development perspective, these powers have been critical in overcoming obstacles that land speculators sometimes put in our way. We have not had to use this power very often, fortunately. Only a handful of properties were acquired under the threat of eminent domain, and we reached an impasse only twice, sending us to court to purchase those properties. We take this responsibility seriously and only use eminent domain powers sparingly. We have a good reputation with the public as a result.

Can you describe one accomplishment you are particularly proud of?

We knew that to jump-start an innovation district it was essential to build entrepreneurial density. We developed an unorthodox strategy of sorts in that we built a concentration of innovation assets all within a block of each other. Today, we have six innovation centers, each with its own community and programming: the Center for Emerging Technologies, a traditional technical assistance incubator for information technology, bioscience, and consumer/manufacturing products; the BioGenerator, an accelerator with shared wet lab space and $3 million of shared core lab equipment; TechShop, a premier maker work space for prototyping and creating; the Cambridge Innovation Center–St. Louis, a co-working office and lab startup space); Venture Café–St. Louis, a shared public space for the startup community to meet weekly with 8 to 12 unconventional breakout educational sessions; and IdeaLabs/MedLaunch, a unique university graduate/undergraduate incubator that develops new technology to solve clinical problems. This strategy is working beyond our wildest expectations. It’s the “secret sauce” for supercharging our district’s innovation ecosystem. 

Venture Café: one of the six innovation centers that weekly draws together over 500 entrepreneurs from all technology sectors.

Can you highlight one particularly interesting innovation or invention coming out of Cortex? 

Let me highlight two. We have over 200 companies in Cortex—there’s too much innovation happening here to highlight only one!

First, we have a medical device company that is changing the way infectious diseases are diagnosed. Its products can rapidly detect bacterial infections, determine if the infection is resistant to a range of antibiotics, and provide clinicians with patient-specific guidance to treat infections quickly and accurately. Their first product can diagnose urinary tract infections in just three hours.

And then we have a company tackling the biggest challenge in agriculture today—preventing insects, diseases, and weeds from destroying food crops. This company is developing a cost-effective technology to produce and topically deliver RNAi for agricultural crops. Put simply, this technology helps plants develop desired genetic traits without the use of genetically modified organisms, or GMOs. This could be transformative.

Many people have asked us how innovation districts are supporting inclusive growth. There is a concern that innovation districts are focusing on innovation to the exclusion of employment of city residents, who may not possess the skills or education the district’s businesses are seeking.

We look at inclusion as an integral part of our work and mission at Cortex. We currently have six inclusion initiatives and will soon introduce two more. One of those is the development of a magnet high school in the St. Louis Public School District, the Collegiate School for Medicine and Biosciences. Working closely with the school district’s superintendent and an important group of institutional and civic leaders, we have been developing an urban high school centered on one of the major strengths of our Cortex sponsors—bioscience. We recruited our first class in 2013, providing instruction in a small, temporary school, and in 2015 moved to a permanent location that can support 400 students.

The students come from all across the region, representing the largest spread of zip codes of any regional public school. Currently, 53 percent of the students are African American, 23 percent are Asian, and 22 percent are white, representing a great mix. Last year’s proficiency testing in math and English revealed that we ranked first across the entire public school system. I find this particularly gratifying because a number of incoming freshmen were not performing at grade level. What this tells us is given the opportunity, creative teaching approaches, and a supportive structure, these kids will excel quickly. With our incoming 9th grade class this August, we will have a full complement of freshmen to seniors, graduating our first class in 2017.

Perhaps one of these students will find the next cure for cancer. To me, this illustrates an important part of our district’s DNA—to grow and cultivate innovation talent for the future.

       

The tide of uncertainty that has swept the United Kingdom after its vote to leave the European Union has spared few—including its emerging class of innovation districts.

These hubs of innovation—where anchor institutions, such as universities and R&D laden companies cluster and connect with startups, incubators, and a host of public spaces, coffee shops, retail and housing—are now asking themselves important questions that will affect their future. Will the U.K. broker a deal to continue free trade with Europe? Will access to talent across Europe be curtailed? Will the devalued pound keep U.K. advanced manufacturers competitive for the medium to long term? Will European Union legal frameworks be replaced with a regulatory platform that continues to support advanced sectors? What will happen to EU funding on science and innovation, such as Horizon 2020?

Of course, innovation districts are no stranger to uncertainty, if not chaos. These districts thrive on random mixing, on smashing different kinds of disciplines and people together to generate new ideas and new products for the market. In this close-knit, highly networked ecosystem, chaos breeds creativity. At the same time, the backbone of districts is a clear regulatory and legal framework with rules on intellectual property, investment, and funding streams. The twinning of chaos and certainty is what makes these places simply superb spaces to incubate new technology, aggregate talent, and experiment in linking placemaking with innovation.

Yet from the distinctive innovation districts in London to those emerging in the middle of England, such as in Sheffield and Manchester, to those rising in Scotland, such as in Glasgow, this moment of uncertainty could be not only painful—it could be downright dangerous. 

In the face of such uncertain times, the temptation will be to sit back and wait for the cards to fall. But this tempered, conservative approach is ironically the more risky tactic.

We recommend another path.

Now is the time for the institutions and firms that are driving innovation districts to strengthen their competitive position and expand their reach.

Now is the time to try new forms of collaboration between universities, large companies, and local enterprises.

Now is the time to test more democratic modes of innovation with maker spaces, fab labs, and shared infrastructure and equipment.

Now is the time to forge new partnerships with other innovation districts in the United States and Europe to share promising strategies around commercialization, networking, and financing.

Now is the time to apply new energy to creative placemaking, including strengthening the innovation–place nexus around key nodes and applying quick interventions around traffic calming, bike lanes, and pop-up gathering spaces. 

U.S. cities and innovation districts have demonstrated that progress can persist even when higher levels of government are adrift. U.K. cities and districts can do the same.

       

How are two innovation districts in Stockholm successfully melding their tech and life science clusters to create new products?

What can the Wake Forest Innovation Quarter in North Carolina teach us about creating strong, vibrant, and innovative places?

How are innovation districts in Australia leveraging government policies and programs to accelerate their development?

Over the last year, members of the Anne T. and Robert M. Bass Initiative on Innovation and Placemaking team talked with hundreds of local leaders and practitioners advancing innovation districts in almost every global region. These conversations revealed the remarkable level of creativity and innovative, out-of-the-box thinking being employed to grow individual innovation districts.

In the course of our work, we have been intrigued by the question, is there value to be gained from a global network of innovation districts? To this end, we have reached out to successful global networks in Europe, the United States, and Asia to distill what it takes to make a strong and sustainable global network. Among our findings so far:

• Network members are solving on-the-ground challenges by talking with and learning from their peers. Several said that these horizontal exchanges are essential to leapfrogging ahead. 

• Online interaction is growing but network members say that face-to-face contact is critical. Comparing notes, asking questions, and engaging in conversations foster collaboration while maintaining a healthy dose of competition. 

• The right tools and supports can make all the difference. In networks where participants had full schedules, developing new ways to share intelligence, like early morning webinars or virtual conferences, regular e-newsletters, and simple methods to share data helped facilitate their learning. 

To what extent do you feel that a network of innovation districts might supercharge your own efforts and successes?

It would help our work tremendously if you could complete our on-line survey. It will take two minutes or less!

Editor's Note: If you're interested in receiving the latest news from the Bass Initiative, please sign up for our newsletter at this link, http://connect.brookings.edu/bass-initiative-newsletter-signup. Feel free to share it widely.

       

       

       

Innovation is the driver of long-term economic growth and a key ingredient for improvements in healthcare, safety, and security, not to mention those little comforts and conveniences to which we have grown so accustomed. But innovation is not an unqualified good; it taxes society with costs.

The market system internalizes only a portion of the total costs of innovation. Other costs, however, are not included in market prices. Among the most important sources for those unaccounted costs are creative destruction, externalities, and weak safeguards for unwanted consequences.

Creative Destruction and Innovation

Schumpeter described creative destruction as the process by which innovative entrepreneurs outcompete older firms who unable to adapt to a new productive platform go out of business, laying off their employees and writing off their productive assets. Innovation, thus, also produces job loss and wealth destruction. Externalities are side effects with costs not priced in the marketplace such as environmental degradation and pollution. While externalities are largely invisible in the accounting books, they levy very real costs to society in terms of human health and increased vulnerability to environmental shocks. In addition, new technologies are bound to have unwanted deleterious effects, some of which are harmful to workers and consumers, and often, even to third parties not participating in those markets. Yet, there are little financial or cultural incentives for innovators to design new technologies with safeguards against those effects.

Indeed, innovation imposes unaccounted costs and those costs are not allocated in proportion of the benefits. Nothing in the market system obligates the winners of creative destruction to compensate the unemployed of phased-out industries, nor mandates producers to compensate those shouldering the costs of externalities, nor places incentives to invest in preventing unwanted effects in new production processes and new products. It is the role of policy to create the appropriate incentives for a fair distribution of those social costs. As a matter of national policy we must continue every effort to foster innovation, but we must do so recognizing the trade-offs.

Strengthening the Social Safety Net

Society as a whole benefits from creative destruction; society as a whole must then strengthen the safety net for the unemployed and double up efforts to help workers retrain and find employment in emerging industries. Regulators and industry will always disagree on many things but they could agree to collaborate on a system of regulatory incentives to ease transition to productive platforms with low externality costs. Fostering innovation should also mean promoting a culture of anticipation to better manage unwanted consequences.

Let’s invest in innovation with optimism, but let’s be pragmatic about it. To reap the most net social benefit from innovation, we must work on two fronts, to maximize benefits and to minimize the social costs, particularly those costs not traditionally accounted. The challenge for policymakers is to do it fairly and smartly, creating a correspondence of benefits and costs, and not unnecessarily encumbering innovative activity.

Commentary published in The International Economy magazine, Spring 2014 issue, as part of a symposium of experts responding to the question: Does Innovation Lead to prosperity for all?

      

Editors Note: This post is an extended version of a previous post.

Cozzens, Susan and Dhanaraj Thakur (Eds). 2014. Innovation and Inequality: Emerging technologies in an unequal world. Northampton, Massachusetts: Edward Elgar.

Historically, the debate on innovation has focused on the determinants of the pace of innovation—on the premise that innovation is the driver of long-term economic growth. Analysts and policymakers have taken less interest on how innovation-based growth affects income distribution. Less attention even has received the question of how innovation affects other forms of inequality such as economic opportunity, social mobility, access to education, healthcare, and legal representation, or inequalities in exposure to insalubrious environments, be these physical (through exposure to polluted air, water, food or harmful work conditions) or social (neighborhoods ridden with violence and crime). The relation between innovation, equal political representation and the right for people to have a say in the collective decisions that affect their lives can also be added to the list of neglect.

But neglect has not been universal. A small but growing group of analysts have been working for at least three decades to produce a more careful picture of the relationship between innovation and the economy. A distinguished vanguard of this group has recently published a collection of case studies that illuminates our understanding of innovation and inequality—which is the title of the book. The book is edited by Susan Cozzens and Dhanaraj Thakur. Cozzens is a professor in the School of Public Policy and Vice Provost of Academic Affairs at Georgia Tech. She has studied innovation and inequality long before inequality was a hot topic and led the group that collaborated on this book. Thakur is a faculty member of the school College of Public Service and Urban Affairs at Tennessee State University (while writing the book he taught at the University of West Indies in Jamaica). He is an original and sensible voice in the study of social dimensions of communication technologies.

We’d like to highlight here three aspects of the book: the research design, the empirical focus, and the conceptual framework developed from the case studies in the book.

Edited volumes are all too often a collection of disparate papers, but not in this case. This book is patently the product of a research design that probes the evolution of a set of technologies across a wide variety of national settings and, at the same time, it examines the different reactions to new technologies within specific countries. The second part of the book devotes five chapters to study five emerging technologies—recombinant insulin, genetically modified corn, mobile phones, open-source software, and tissue culture—observing the contrasts and similarities of their evolution in different national environments. In turn, part three considers the experience of eight countries, four of high income—Canada, Germany, Malta, and the U.S.—and four of medium or low income—Argentina, Costa Rica, Jamaica, and Mozambique. The stories in part three tell how these countries assimilated these diverse technologies into to their economies and policy environments.

The second aspect to highlight is the deliberate choice of elements for empirical focus. First, the object of inquiry is not all of technology but a discreet set of emerging technologies gaining a specificity that would otherwise be negated if they were to handle the unwieldy concept of “technology” broadly construed. At the same time, this choice reveals the policy orientation of the book because these new entrants have just started to shape the socio-technical spaces they inhabit while the spaces of older technologies have likely ossified. Second, the study offers ample variance in terms of jurisdictions under study, i.e. countries of all income levels; a decision that makes at the same time theory construction more difficult and the test of general premises more robust.[i] We can add that the book avoids sweeping generalizations. Third, they focus on technological projects and their champions, a choice that increases the rigor of the empirical analysis. This choice, naturally, narrows the space of generality but the lessons are more precise and the conjectures are presented with according modesty. The combination of a solid design and clear empirical focus allow the reader to obtain a sense of general insight from the cases taken together that could not be derived from any individual case standing alone.

Economic and technology historians have tackled the effects of technological advancement, from the steam engine to the Internet, but those lessons are not easily applicable to the present because emerging technologies intimate at a different kind of reconfiguration of economic and social structures. It is still too early to know the long-term effects of new technologies like genetically modified crops or mobile phone cash-transfers, but this book does a good job providing useful concepts that begin to form an analytical framework. In addition, the mix of country case studies subverts the disciplinary separation between the economics of innovation (devoted mostly to high-income countries) and development studies (interested in middle and low income economies). As a consequence of these selections, the reader can draw lessons that are likely to apply to technologies and countries other than the ones discussed in this book.

The third aspect we would like to underscore in this review is the conceptual framework. Cozzens, Thakur and their colleagues have done a service to anyone interested in pursuing the empirical and theoretical analysis of innovation and inequality.

For these authors, income distribution is only one part of the puzzle. They observe that inequalities are also part of social, ethnic, and gender cleavages in society. Frances Stewart, from Oxford University, introduced the notion of horizontal inequalities or inequalities at the social group level (for instance, across ethnic groups or genders). She developed the concept to contrast vertical inequalities or inequalities operating at the individual level (such as household income or wealth). The authors of this book borrow Stewart’s concept and pay attention to horizontal inequalities in the technologies they examine and observe that new technologies enter marketplaces that are already configured under historical forms of exclusion. A dramatic example is the lack of access to recombinant insulin in the U.S., because it is expensive and minorities are less likely to have health insurance (see Table 3.1 in p. 80).[ii] Another example is how innovation opens opportunities for entrepreneurs but closes them for women in cultures that systematically exclude women from entrepreneurial activities.

Another key concept is that of complementary assets. A poignant example is the failure of recombinant insulin to reach poor patients in Mozambique who are sent home with old medicine even though insulin is subsidized by the government. The reason why doctors deny the poor the new treatment is that they don’t have the literacy and household resources (e.g. a refrigerator, a clock) necessary to preserve the shots, inject themselves periodically, and read sugar blood levels. Technologies aimed at fighting poverty require complementary assets to be already in place and in the absence of them, they fail to mitigate suffering and ultimately ameliorate inequality. Another illustration of the importance of complementary assets is given by the case of Open Source Software. This technology has a nominal price of zero; however, only individuals who have computers and the time, disposition, and resources to learn how to use open source operative systems benefit. Likewise, companies without the internal resources to adapt open software will not adopt it and remain economically tied to proprietary software.

These observations lead to two critical concepts elaborated in the book: distributional boundaries and the inequalities across technological transitions. Distributional boundaries refer to the reach of the benefits of new technologies, boundaries that could be geographic (as in urban/suburban or center/periphery) or across social cleavages or incomes levels. Standard models of technological diffusion assume the entire population will gradually adopt a new technology, but in reality the authors observe several factors intervene in limiting the scope of diffusion to certain groups. The most insidious factors are monopolies that exercise sufficient control over markets to levy high prices. In these markets, the price becomes an exclusionary barrier to diffusion. This is quite evident in the case of mobile phones (see table 5.1, p. 128) where monopolies (or oligopolies) have market power to create and maintain a distributional boundary between post-pay and high-quality for middle and high income clients and pre-pay and low-quality for poor customers. This boundary renders pre-pay plans doubly regressive because the per-minute rates are higher than post-pay and phone expenses represent a far larger percentage in poor people’s income. Another example of exclusion happens in GMOs because in some countries subsistence farmers cannot afford the prices for engineering seeds; a disadvantage that compounds to their cost and health problems as they have to use more and stronger pesticides.

A technological transition, as used here, is an inflection point in the adoption of a technology that re-shapes its distributional boundaries. When smart phones were introduced, a new market for second-hand or hand-down phones was created in Maputo; people who could not access the top technology get stuck with a sub-par system. By looking at tissue culture they find that “whether it provides benefits to small farmers as well as large ones depends crucially on public interventions in the lower-income countries in our study” (p. 190). In fact, farmers in Costa Rica enjoy much better protections compare to those in Jamaica and Mozambique because the governmental program created to support banana tissue culture was designed and implemented as an extension program aimed at disseminating know-how among small-farmers and not exclusively to large multinational-owned farms. When introducing the same technology, because of this different policy environment, the distributional boundaries were made much more extensive in Costa Rica.

This is a book devoted to present the complexity of the innovation-inequality link. The authors are generous in their descriptions, punctilious in the analysis of their case studies, and cautious and measured in their conclusions. Readers who seek an overarching theory of inequality, a simple story, or a test of causality, are bound to be disappointed. But those readers may find the highest reward from carefully reading all the case studies presented in this book, not only because of the edifying richness of the detail herein but also because they will be invited to rethink the proper way to understand and address the problem of inequality.[iii]
 

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Policies and initiatives to promote U.S. manufacturing would be well advised to take a value chain perspective of this economic sector. Currently, our economic statistics do not include pre-production services to manufacturing such as research and development or design or post-production services such as repair and maintenance or sales. Yet, manufacturing firms invest heavily in these services because they are crucial to the success of their business. 

In a new paper, Kate Whitefoot and Walter Valdivia offer a fresh insight into the sector’s labor composition and trends by examining employment in manufacturing from a value chain perspective. While the manufacturing sector shed millions of jobs in the 2002-2010 period—a period that included the Great Recession—employment in upstream services expanded 26 percent for market analysis, 13 percent for research and development, and 23 percent for design and technical services. Average wages for these services increased over 10 percent in that period. Going forward, this pattern is likely to be repeated. Technical occupations, particularly in upstream segments are expected to have the largest increases in employment and wages.

In light of the findings, the authors offer the following recommendations: 

• Federal manufacturing policy: Expand PCAST’s Advanced Manufacturing Partnership recommendations—specifically, for developing a national system of certifications for production skills and establishing a national apprenticeship program for skilled trades in manufacturing—to include jobs outside the factory such as those in research and development, design and technical services, and market analysis.
• Higher education: Institutions of higher education should consider some adjustment to their curriculum with a long view of the coming changes to high-skill occupations, particularly with respect to problem identification and the management of uncertainty in highly automated work environments. In addition, universities and colleges should disseminate information among prospect and current students about occupations where the largest gains of employment and higher wage premiums are expected. 
• Improve national statistics: Supplement the North American Industry Classification System (NAICS) with data that permits tracking the entire value chain, including the development of a demand-based classification system. This initiative could benefit from adding survey questions to replicate the data collection of countries with a Value Added Tax—without introducing the tax, that is—allowing in this manner a more accurate estimation of the value added by each participant in a production network.

Whitefoot and Valdivia stress that any collective efforts aimed at invigorating manufacturing must seize the opportunities throughout the entire value chain including upstream and downstream services to production.

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Technical change is advancing at a breakneck speed while the institutions that govern innovative activity slog forward trying to keep pace. The lag has created a need for reform in the governance of innovation. Reformers who focus primarily on the social benefits of innovation propose to unmoor the innovative forces of the market. Conversely, those who deal mostly with innovation’s social costs wish to constrain it by introducing regulations in advance of technological developments. In this paper, Walter Valdivia and David Guston argue for a different approach to reform the governance of innovation that they call "Responsible Innovation" because it seeks to imbue in the actors of the innovation system a more robust sense of individual and collective responsibility.

Responsible innovation appreciates the power of free markets in organizing innovation and realizing social expectations but is self-conscious about the social costs that markets do not internalize. At the same time, the actions it recommends do not seek to slow down innovation because they do not constrain the set of options for researchers and businesses, they expand it. Responsible innovation is not a doctrine of regulation and much less an instantiation of the precautionary principle. Innovation and society can evolve down several paths and the path forward is to some extent open to collective choice. The aim of a responsible governance of innovation is to make that choice more consonant with democratic principles.

Valdivia and Guston illustrate how responsible innovation can be implemented with three practical initiatives: 

1. Industry: Incorporating values and motivations to innovation decisions that go beyond the profit motive could help industry take on a long-view of those decisions and better manage its own costs associated with liability and regulation, while reducing the social cost of negative externalities. Consequently, responsible innovation should be an integral part of corporate social responsibility, considering that the latter has already become part of the language of business, from the classroom to the board room, and that is effectively shaping, in some quarters, corporate policies and decisions.
2. Universities and National Laboratories: Centers for Responsible Innovation, fashioned after the institutional reform of Internal Review Boards to protect human subjects in research and the Offices of Technology Transfer created to commercialize academic research, could organize existing responsible innovation efforts at university and laboratory campuses. These Centers would formalize the consideration of impacts of research proposals on legal and regulatory frameworks, economic opportunity and inequality, sustainable development and the environment, as well as ethical questions beyond the integrity of research subjects.
3. Federal Government: Federal policy should improve its protections and support of scientific research while providing mechanisms of public accountability for research funding agencies and their contractors. Demanding a return on investment for every research grant is a misguided approach that devalues research and undermines trust between Congress and the scientific community. At the same time, scientific institutions and their advocates should improve public engagement and demonstrate their willingness and ability to be responsive to societal concerns and expectations about the public research agenda. Second, if scientific research is a public good, by definition, markets are not effective commercializing it. New mechanisms to develop practical applications from federal research with little market appeal should be introduced to counterbalance the emphasis the current technology transfer system places on research ready for the market. Third, federal innovation policy needs to be better coordinated with other federal policy, including tax, industrial, and trade policy as well as regulatory regimes. It should also improve coordination with initiatives at the local and state level to improve the outcomes of innovation for each region, state, and metro area.

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Tuesday night, President Obama presented four critical questions about the future of America and I should like to comment on the first two:

1. How to produce equal opportunity, emphasizing economic security for all.
2. In his words, “how do we make technology work for us, and not against us,” particularly to meet the “urgent challenges” of our days.

The challenges the president wishes to meet by means of technological development are climate change and cancer. Let’s consider cancer first. There are plenty of reasons to be skeptical: this is not the first presidential war against cancer, President Nixon tried that once and, alas cancer still has the upper hand. It is ironic that Mr. Obama chose this particular ”moonshot”, because not only are the technical aspects of cancer more uncertain than those of space travel, political support for the project is vastly different and we cannot be sure that even another Democrat in the White House would see this project to fruition. In effect, neither Mr. Obama nor his appointed “mission control”, Vice President Biden, have time in office to see fruits from their efforts on this front.

The second challenge the president wishes to address with technology is problematic beyond technical and economic feasibility (producing renewable energy at competitive prices); curbing carbon emissions has become politically intractable. The president correctly suggested that being leaders in the renewable energy markets of the future makes perfect business sense, even for global warming skeptics. Nevertheless, markets have a political economy, and current energy giants have a material interest in not allowing any changes to the rules that so favor them (including significant federal subsidies). Only when the costs of exploration, extraction, and distribution of fossil fuels rise above those of renewable sources, we can expect policy changes enabling an energy transition to become feasible. When renewables are competitive on a large scale, it is not very likely that their production will be controlled by new industrial players. Such is the political economy of free markets. What’s more, progressives should be wary of standard solutions that would raise the cost of energy (such as a tax on carbon emissions), because low income families are quite sensitive to energy prices; the cost of electricity, gas, and transportation is a far larger proportion of their income than that of their wealthier neighbors.

It’s odd that the president proposes technological solutions to challenges that call for a political solution. Again, in saying this, I’m allowing for the assumption that the technical side is manageable, which is not necessarily a sound assumption to make. The technical and economic complexity of these problems should only compound political hurdles. If I’m skeptical that technological fixes would curb carbon emissions or cure cancer, I am simply vexed by the president’s answer to the question on economic opportunity and security: expand the safety net. It is not that it wouldn’t work; it worked wonders creating prosperity and enlarging the middle-class in the post-World War II period. The problem is that enacting welfare state policies promises to be a hard political battle that, even if won, could result in pyrrhic victories. The greatest achievement of Mr. Obama expanding the safety net was, of course, the Affordable Care Act. But his policy success came at a very high cost: a majority of the voters have questions about the legitimacy of that policy. Even its eponymous name, Obamacare, was coined as a term of derision. It is bizarre that opposition to this reform is often found amidst people who benefit from it. We can blame the systematic campaign against it in every electoral contest, the legal subterfuges brought up to dismantle it (that ACA survived severely bruised), and the AM radio vitriol, but even controlling for the dirty war on healthcare reform, passing such as monumental legislation strictly across party lines has made it the lighting rod of distrust in government.

Progressives are free to try to increase economic opportunity following the welfare state textbook. They will meet the same opposition that Mr. Obama encountered. However, where progressives and conservatives could agree is about increasing opportunities for entrepreneurs, and nothing gives an edge to free enterprise more than innovation. Market competition is the selection mechanism by which an elite of enterprises rises from a legion created any given year; this elite, equipped with a new productive platform, can arm-wrestle markets from the old guard of incumbents. This is not the only way innovation takes place: monopolies and cartels can produce innovation, but with different outcomes. In competitive markets, innovation is the instrument of product differentiation; therefore, it improves quality and cuts consumer prices. In monopolistic markets, innovation also takes place, but generally as a monopolist’s effort to raise barriers to entry and secure high profits. Innovation can take place preserving social protections to the employees of the new industries, or it can undermine job security of its labor force (a concern with the sharing economy). These different modes of innovation are a function of the institutions that govern innovation, including industrial organization, labor and consumer protections.

What the President did not mention is that question two can answer question one: technological development can improve economic opportunity and security, and that is likely to be more politically feasible than addressing the challenges of climate change and cancer. Shaping the institutions that govern innovative activity to favor modes of innovation that benefit a broad base of society is an achievable goal, and could indeed be a standard by which his and future administrations are measured. This is so because these are not the province of the welfare state. They are policy domains that have historically enjoyed bipartisan consensus (such as federal R&D funding, private R&D tax credits) or low contestation (support for small business, tech transfer, loan guarantees).

As Mr. Obama himself suggested, technology can be indeed be made to work for us, all of us.

       

A review essay of “Governance of Socio-technical Systems: Explaining Change”, edited by Susana Borrás and Jakob Edler (Edward Elgar, 2014, 207 pages).

Phasing-out a useful and profitable technology

I own a Nokia 2330; it’s a small brick phone that fits comfortably in the palm of my hand. People have feelings about this: mostly, they marvel at my ability to survive without a smart-phone. Concerns go beyond my wellbeing; once a friend protested that I should be aware of the costs I impose onto my friends, for instance, by asking them for precise directions to their houses. Another suggested that I cease trying to be smarter than my phone. But my reason is simple: I don’t need a smart phone. Most of the time, I don’t even need a mobile phone. I can take and place calls from my home or my office. And who really needs a phone during their commute? Still, my device will meet an untimely end. My service provider has informed me via text message that it will phase out all 2G service and explicitly encouraged me to acquire a 3G or newer model. 

There is a correct if simplistic explanation for this announcement: my provider is not making enough money with my account and should I switch to a newer device, they will be able to sell me a data plan. The more accurate and more complex explanation is that my mobile device is part of a communications system that is integrated to other economic and social systems. As those other systems evolve, my device is becoming incompatible with them; my carrier has determined that I should be integrated.

The system integration is easy to understand from a business perspective. My carrier may very well be able to make a profit keeping my account as is, and the accounts of the legion of elderly and low-income customers who use similar devices, and still they may not find it advantageous in the long run to allow 2G devices in their network. To understand this business strategy, we need to go back no farther than the introduction of the iPhone, which in addition to being the most marketable mobile phone set a new standard platform for mobile devices. Its introduction accelerated a trend underway in the core business of carriers: the shift from voice communication to data streaming because smart phones can support layers of overlapping services that depend on fast and reliable data transfer. These services include sophisticated log capabilities, web search, geo-location, connectivity to other devices, and more recently added bio-monitoring. All those services are part of systems of their own, so it makes perfect business sense for carriers to seamlessly integrate mobile communications with all those other systems. Still, the economic rationale explains only a fraction of the systems integration underway.

The communication system of mobile telephony is also integrated with regulatory, social, and cultural systems. Consider the most mundane examples: It’s hard to imagine anyone who, having shifted from paper-and-pencil to an electronic agenda, decided to switch back afterwards. We are increasingly dependent of GPS services; while it may have once served tourists who did not wish to learn how to navigate a new city, it is now a necessity for many people who without it are lost in their home town. Not needing to remember phone numbers, the time of our next appointment, or how to go back to that restaurant we really liked, is a clear example of the integration of mobile devices into our value systems.

There are coordination efforts and mutual accommodation taking place: tech designers seek to adapt to changing values and we update our values to the new conveniences of slick gadgets. Government officials are engaged in the same mutual accommodation. They are asking how many phone booths must be left in public places, how to reach more people with public service announcements, and how to provide transit information in real-time when commuters need it. At the same time, tech designers are considering all existing regulations so their devices are compliant. Communication and regulatory systems are constantly being re-integrated.

The will behind systems integration

The integration of technical and social systems that results from innovation demands an enormous amount of planning, effort, and conflict resolution. The people involved in this process come from all quarters of the innovation ecology, including inventors, entrepreneurs, financiers, and government officials. Each of these agents may not be able to contemplate the totality of the system integration problem but they more or less understand how their respective system must evolve so as to be compatible with interrelated systems that are themselves evolving.  There is a visible willfulness in the integration task that scholars of innovation call the governance of socio-technical systems.

Introducing the term governance, I should emphasize that I do not mean merely the actions of governments or the actions of entrepreneurs. Rather, I mean the effort of all agents involved in the integration and re-integration of systems triggered by innovation; I mean all the coordination and mutual accommodation of agents from interrelated systems. And there is no single vehicle to transport all the relevant information for these agents. A classic representation of markets suggests that prices carry all the relevant information agents need to make optimal decisions. But it is impossible to project this model onto innovation because, as I suggested above, it does not adhere exclusively to economic logic; cultural and political values are also at stake. The governance task is therefore fragmented into pieces and assigned to each of the participants of the socio-technical systems involved, and they cannot resolve it as a profit-maximization problem. 

Instead, the participants must approach governance as a problem of design where the goal could be characterized as reflexive adaptation. By adaptation I mean seeking to achieve inter-system compatibility. By reflexive I mean that each actor must realize that their actions trigger adaption measures in other systems. Thus, they cannot passively adapt but rather they must anticipate the sequence of accommodations in the interaction with other agents. This is one of the most important aspects of the governance problem, because all too often neither technical nor economic criteria will suffice; quite regularly coordination must be negotiated, which is to say, innovation entails politics.

The idea of governance of socio-technical systems is daunting. How do we even begin to understand it? What kinds of modes of governance exist? What are the key dimensions to understand the integration of socio-technical systems? And perhaps more pressing, who prevails in disputes about coordination and accommodation? Fortunately, Susana Borrás, from the Copenhagen Business School, and Jakob Edler, from the University of Manchester, both distinguished professors of innovation, have collected a set of case studies that shed light on these problems in an edited volume entitled Governance of Socio-technical Change: Explaining Change. What is more, they offer a very useful conceptual framework of governance that is worth reviewing here. While this volume will be of great interest to scholars of innovation—and it is written in scholarly language—I think it has great value for policymakers, entrepreneurs, and all agents involved in a practical manner in the work of innovation.

Organizing our thinking on the governance of change

The first question that Borrás and Edler tackle is how to characterize the different modes of governance. They start out with a heuristic typology across the two central categories: what kinds of agents drive innovation and how the actions of these agents are coordinated. Agents can represent the state or civil society, and actions can be coordinated via dominant or non-dominant hierarchies.

	Change led by state actors	Change led by societal actors
Coordination by dominant hierarchies	Traditional deference to technocratic competence: command and control.	Monopolistic or oligopolistic industrial organization.
Coordination by non-dominant hierarchies	State agents as primus inter pares.	More competitive industries with little government oversight.

Source: Adapted from Borrás and Adler (2015), Table 1.2, p. 13.

This typology is very useful to understand why different innovative industries have different dynamics; they are governed differently. For instance, we can readily understand why consumer software and pharmaceuticals are so at odds regarding patent law. The strict (and very necessary) regulation of drug production and commercialization coupled with the oligopolistic structure of that industry creates the need and opportunity to advocate for patent protection; which is equivalent to a government subsidy. In turn, the highly competitive environment of consumer software development and its low level of regulation foster an environment where patents hinder innovation. Government intervention is neither needed nor wanted; the industry wishes to regulate itself.

This typology is also useful to understand why open source applications have gained currency much faster in the consumer segment than the contractor segment of software producers. Examples of the latter is industry specific software (e.g. to operate machinery, the stock exchange, and ATMs) or software to support national security agencies. These contractors demand proprietary software and depend on the secrecy of the source code. The software industry is not monolithic, and while highly innovative in all its segments, the innovation taking place varies greatly by its mode of governance.

Furthermore, we can understand the inherent conflicts in the governance of science. In principle, scientists are led by curiosity and organize their work in a decentralized and organic fashion. In practice, most of science is driven by mission-oriented governmental agencies and is organized in a rigid hierarchical system. Consider the centrality of prestige in science and how it is awarded by peer-review; a system controlled by the top brass of each discipline. There is nearly an irreconcilable contrast between the self-image of science and its actual governance. Using the Borrás-Edler typology, we could say that scientists imagine themselves as citizens of the south-east quadrant while they really inhabit the north-west quadrant.

There are practical lessons from the application of this typology to current controversies. For instance, no policy instrument such as patents can have the same effect on all innovation sectors because the effect will depend on the mode of governance of the sector. This corollary may sound intuitive, yet it really is at variance with the current terms of the debate on patent protection, where assertions of its effect on innovation, in either direction, are rarely qualified.

The second question Borrás and Edler address is that of the key analytical dimensions to examine socio-technical change. To this end, they draw from an ample selection of social theories of change. First, economists and sociologists fruitfully debate the advantage of social inquiry focused on agency versus institutions. Here, the synthesis offered is reminiscent of Herbert Simon’s “bounded rationality”, where the focus turns to agent decisions constrained by institutions. Second, policy scholars as well as sociologists emphasize the engineering of change. Change can be accomplished with discreet instruments such as laws and regulations, or diffused instruments such as deliberation, political participation, and techniques of conflict resolution. Third, political scientists underscore the centrality of power in the adjudication of disputes produced by systems’ change and integration. Borrás and Edler have condensed these perspectives in an analytical framework that boils down to three clean questions: who drives change? (focus on agents bounded by institutions), how is change engineered? (focus on instrumentation), and why it is accepted by society? (focus on legitimacy). The case studies contained in this edited volume illustrate the deployment of this framework with empirical research.

Standards, sustainability, incremental innovation

Arthur Daemmrich (Chapter 3) tells the story of how the German chemical company BASF succeeded marketing the biodegradable polymer Ecoflex. It is worth noting the dependence of BASF on government funding to develop Ecoflex, and on the German Institute for Standardization (DIN), making a market by setting standards. With this technology, BASF capitalized on the growing demand in Germany for biodegradables, and with its intense cooperation with DIN helped establish a standard that differentiate Ecoflex from the competition. By focusing on the enterprise (the innovation agent) and its role in engineering the market for its product by setting standards that would favor them, this story reveals the process of legitimation of this new technology. In effect, the certification of DIN was accepted by agribusinesses that sought to utilize biodegradable products.

If BASF is an example of innovation by standards, Allison Loconto and Marc Barbier (Chapter 4) show the strategies of governing by standards. They take the case of the International Social and Environmental Accreditation and Labelling alliance (ISEAL). ISEAL, an advocate of sustainability, positions itself as a coordinating broker among standard developing organizations by offering “credibility tools” such as codes of conduct, best practices, impact assessment methods, and assurance codes. The organization advocates what is known as the tripartite system regime (TSR) around standards. TSR is a system of checks and balances to increase the credibility of producers complying with standards. The TSR regime assigns standard-setting, certification, and accreditation of the certifiers, to separate and independent bodies. The case illustrates how producers, their associations, and broker organizations work to bestow upon standards their most valuable attribute: credibility. The authors are cautious not to conflate credibility with legitimacy, but there is no question that credibility is part of the process of legitimizing technical change. In constructing credibility, these authors focus on the third question of the framework –legitimizing innovation—and from that vantage point, they illuminate the role of actors and instruments that will guide innovations in sustainability markets.

While standards are instruments of non-dominant hierarchies, the classical instrument of dominant hierarchies is regulation. David Barberá-Tomás and Jordi Molas-Gallart tell the tragic consequences of an innovation in hip-replacement prosthesis that went terribly wrong. It is estimated that about 30 thousand replaced hips failed. The FDA, under the 1976 Medical Device Act, allows incremental improvements in medical devices to go into the market after only laboratory trials, assuming that any substantive innovations have already being tested in regular clinical trials. This policy was designed as an incentive for innovation, a relief from high regulatory costs. However, the authors argue, when products have been constantly improved for a number of years after an original release, any marginal improvement comes at a higher cost or higher risk—a point they refer to as the late stage of the product life-cycle. This has tilted the balance in favor of risky improvements, as illustrated by the hip prosthesis case. The story speaks to the integration of technical and cultural systems: the policy that encourages incremental innovation may alter the way medical device companies assess the relative risk of their innovations, precisely because they focus on incremental improvements over radical ones. Returning to the analytical framework, the vantage point of regulation—instrumentation—elucidates the particular complexities and biases in agents’ decisions.

Two additional case studies discuss the discontinuation of the incandescent light bulb (ILB) and the emergence of translational research, both in Western Europe. The first study, authored by Peter Stegmaier, Stefan Kuhlmann and Vincent R. Visser (Chapter 6), focuses on a relatively smooth transition. There was wide support for replacing ILBs that translated in political will and a market willing to purchase new energy efficient bulbs. In effect, the new technical system was relatively easy to re-integrate to a social system in change—public values had shifted in Europe to favor sustainable consumption—and the authors are thus able to emphasize how agents make sense of the transition. Socio-technical change does not have a unique meaning: for citizens it means living in congruence with their values; for policy makers it means accruing political capital; for entrepreneurs it means new business opportunities. The case by Etienne Vignola-Gagné, Peter Biegelbauer and Daniel Lehner (Chapter 7) offers a similar lesson about governance. My reading of their multi-site study of the implementation of translational research—a management movement that seeks to bridge laboratory and clinical work in medical research—reveals how the different agents involved make sense of this organizational innovation. Entrepreneurs see a new market niche, researchers strive for increasing the impact of their work, and public officials align their advocacy for translation with the now regular calls for rendering publicly funded research more productive. Both chapters illuminate a lesson that is as old as it is useful to remember: technological innovation is interpreted in as many ways as the number of agents that participate in it.

Innovation for whom?

The framework and illustrations of this book are useful for those of us interested in the governance of system integration. The typology of different modes of governance and the three vantage points from which empirical analysis can be deployed are very useful indeed. Further development of this framework should include the question of how political power is redistributed by effect of innovation and the system integration and re-integration that it triggers. The question is pressing because the outcomes of innovation vary as power structures are reinforced or debilitated by the emergence of new technologies—not to mention ongoing destabilizing forces such as social movements. Put another way, the framework should be expanded to explain in which circumstances innovation exacerbates inequality. The expanded framework should probe whether the mutual accommodation is asymmetric across socio-economic groups, which is the same as asking: are poor people asked to do more adapting to new technologies? These questions have great relevance in contemporary debates about economic and political inequality. 

I believe that Borrás and Edler and their colleagues have done us a great service organizing a broad but dispersed literature and offering an intuitive and comprehensive framework to study the governance of innovation. The conceptual and empirical parts of the book are instructive and I look forward to the papers that will follow testing this framework. We need to better understand the governance of socio-technical change and the dynamics of systems integration. Without a unified framework of comparison, the ongoing efforts in various disciplines will not amount to a greater understanding of the big picture. 

I also have a selfish reason to like this book: it helps me make sense of my carrier’s push for integrating my value system to their technical system. If I decide to adapt to a newer phone, I could readily do so because I have time and other resources. But that may not be the case for many customers of 2G devices who have neither the resources nor the inclination to learn to use more complex devices. For that reason alone, I’d argue that this sort of innovation-led systems integration could be done more democratically. Still, I could meet the decision of my carrier with indifference: when the service is disconnected, I could simply try to get by without the darn toy.

Note: Thanks to Joseph Schuman for an engaging discussion of this book with me.

       

       

In 2015 the international community agreed on a set of ambitious sustainable development goals (SDGs) for the global society, to be achieved by 2030. One of the lessons that the implementation of the Millennium Development Goals (MDG s) has highlighted is the importance of a systematic approach to identify and sequence development interventions—policies, programs, and projects—to achieve such goals at a meaningful scale. The Chinese approach to development, which consists of identifying a problem and long-term goal, testing alternative solutions, and then implementing those that are promising in a sustained manner, learning and adapting as one proceeds—Deng Xiaoping’s “crossing the river by feeling the stones”—is an approach that holds promise for successful achievement of the SDGs.

Having observed the Chinese way, then World Bank Group President James Wolfensohn in 2004, together with the Chinese government, convened a major international conference in Shanghai on scaling up successful development interventions, and in 2005 the World Bank Group (WBG ) published the results of the conference, including an assessment of the Chinese approach. (Moreno-Dodson 2005). Some ten years later, the WBG once again is addressing the question of how to support scaling up of successful development interventions, at a time when the challenge and opportunity of scaling up have become a widely recognized issue for many development institutions and experts.

Since traditional private and public service providers frequently do not reach the poorest people in developing countries, social enterprises can play an important role in providing key services to those at the “base of the pyramid.”

In parallel with the recognition that scaling up matters, the development community is now also focusing on social enterprises (SEs), a new set of actors falling between the traditionally recognized public and private sectors. We adopt here the World Bank’s definition of “social enterprises” as a social-mission-led organization that provides sustainable services to Base of the Pyramid (BoP) populations. This is broadly in line with other existing definitions for the sector and reflects the World Bank’s primary interest in social enterprises as a mechanism for supporting service delivery for the poor. Although social enterprises can adopt various organizational forms—business, nongovernmental organizations (NGOs), and community-based organizations are all forms commonly adopted by social enterprises—they differ from private providers principally by combining three features: operating with a social purpose, adhering to business principles, and aiming for financial sustainability. Since traditional private and public service providers frequently do not reach the poorest people in developing countries, social enterprises can play an important role in providing key services to those at the “base of the pyramid.” (Figure 1)

Figure 1. Role of SE sector in public service provision

Social enterprises often start at the initiative of a visionary entrepreneur who sees a significant social need, whether in education, health, sanitation, or microfinance, and who responds by developing an innovative way to address the perceived need, usually by setting up an NGO, or a for-profit enterprise. Social enterprises and their innovations generally start small. When successful, they face an important challenge: how to expand their operations and innovations to meet the social need at a larger scale. 

Development partner organizations—donors, for short—have recognized the contribution that social enterprises can make to find and implement innovative ways to meet the social service needs of people at the base of the pyramid, and they have started to explore how they can support social enterprises in responding to these needs at a meaningful scale. 

The purpose of this paper is to present a menu of approaches for addressing the challenge of scaling up social enterprise innovations, based on a review of the literature on scaling up and on social enterprises. The paper does not aim to offer specific recommendations for entrepreneurs or blueprints and guidelines for the development agencies. The range of settings, problems, and solutions is too wide to permit that. Rather, the paper provides an overview of ways to think about and approach the scaling up of social enterprise innovations. Where possible, the paper also refers to specific tools that can be helpful in implementing the proposed approaches. 

Note that we talk about scaling up social enterprise innovations, not about social enterprises. This is because it is the innovations and how they are scaled up that matter. An innovation may be scaled up by the social enterprise where it originated, by handoff to a public agency for implementation at a larger scale, or by other private enterprises, small or large. 

This paper is structured in three parts: Part I presents a general approach to scaling up development interventions. This helps establish basic definitions and concepts. Part II considers approaches for the scaling up of social enterprise innovations. Part III provides a summary of the main conclusions and lessons from experience. A postscript draws out implications for external aid donors. Examples from actual practice are used to exemplify the approaches and are summarized in Annex boxes.

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