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Universities

Tracing the roots of Israel’s technology cluster to agriculture and beyond

The following post is taken from my contribution to the recent Royal Society report on research clusters, republished here under a creative commons license. The full report has eight case studies (see my previous piece on Pittsburgh). Individually, they tell the story of how the actions of leaders, businesses, universities and communities have affected the development of different places with different contexts and histories. Combined, patterns and trends begin to emerge. The story of Israel’s technology sector is closely intertwined with the complex history of Israel itself.

Israel, owing to its prolific track record of establishing innovative information and communications technology (ICT) companies, has earned itself the moniker of ‘start-up nation’. A 2011 book, taking this moniker as its title, described how Israel (with a population of just under nine million) had more companies on the Nasdaq stock exchange than South Korea, Japan, Singapore, India and all of Europe combined, and the highest density of start-ups per person in the world.1

Others describe Israel’s technology cluster as ‘Silicon Wadi’, after the concentration of high-tech firms along the coastal plain. Activity is concentrated in metropolitan Tel Aviv – including the affluent suburbs of Herzeliya, Ramat Gan and Ra’anana – and Haifa in the north (home to Matam Technology Park, Israel’s first and largest high-tech business park), together with the second city of Jerusalem. Including some secondary areas, such as the corridor south from Tel Aviv to Be’er Sheva and the Western Galilee, the cluster covers an area no larger than 6,000 square kilometres – half that of the extended Silicon Valley in the US.2

Around 1,400 start-ups are created every year in Israel and some 800 shut down.3 In total, there is roughly one start up per 1,400 people. In comparison, France has 0.112 startups for every 1,400 people, Germany has 0.056, and the UK has 0.21.4 This growth is not just a recent phenomenon. According to the IVC Research Center, 10,866 high-tech companies were established in the period 2010 to 2019, with 98 listed on the Nasdaq, and 369 accelerators and 24 incubators established. Since 2010, capital raising by Israeli tech companies has risen by 400 percent and the number of deals by 64 percent.5

Amid this explosion of numbers, questions have been asked whether Israel needs to transform from start-up nation to scale-up nation, or if too many young enterprises are being bought out by international companies.6 Others suggest the start-up scene has already matured: Israel’s cluster of high-technology industries emerged in the late 1990s. Since then many companies have grown substantially, and the country hosts large research and development (R&D) sites for many multinational technology companies.

These developments, and the orientation of the Israeli economy, are reflected in statistics for both exports and research and development. ICT services form over 45 percent of Israel’s service exports, compared to 7 percent for the UK, and 9.5 percent for high-income countries as a whole.7 Israel’s research and development expenditure, at 4.58 percent of GDP, towers above the UK (1.67 percent), and the high-income country average (2.57 percent).8 And Israel has 8,250 R&D researchers per million people, compared to 4,377 in the UK and 4,196 in high-income countries.9

The story of Israel’s technology sector is – more so than many other clusters – also a tale of the country’s national development. The emergence of the Israeli ICT cluster is the result of several complex and interrelated factors including culture, geopolitics, state intervention and broader government policies. Some of these factors, as we will see, can be double-edged swords, and few are easy to replicate (despite the Israeli model being cited as inspiration in other countries).10

Development

The emergence of Israel’s technology cluster can best be explained through direct factors – historical decisions shaped through geopolitical circumstances and government interventions – and contributory or enabling factors that include broader government policies, cultural influences and the military.

In an article on ‘Clusters as Innovation Engines’ published in the European Management Review, the authors claim that some of the world’s most powerful innovation clusters, including Tel Aviv, are relatively young and their origins cannot be traced to historical reasons as implied by cluster theory.11 This isn’t quite accurate: whilst the emergence of an Israeli technology cluster took place in a concentrated period of a few decades, the roots of this cluster can be traced to Israel’s founding in 1948.

Two constraints since then have encouraged innovation. First, Israel is resource-poor. According to Shimon Peres, former Israeli President and Prime Minister, ‘high-tech in Israel began with agriculture… technology was 95 percent of the secret of Israel’s prodigious agricultural productivity’.12 Today, the legacy of agricultural kibbutz (collective community) movements is felt in a proclivity for shared working and teamwork, and the converting of municipal facilities such as city libraries into incubator start-up spaces.13 And Israel’s national emphasis on agriculture and agricultural technology helped the transition into what is today a healthy biotechnology and life sciences cluster.14

A second constraint is the geopolitics of the region. Even when Israel has not been at war with its neighbours, the relationship has been uneasy and borders closed to people and goods. This has meant a focus on innovative solutions and high-tech development as a form of protection, and a need to think globally and develop exports for more distant markets; software and services are easier to sell half way around the world than heavy machinery. Israel was then well-positioned to benefit from the global shift towards knowledge- and innovation-based economies.15

The Israel Defence Forces, given a central national role as a direct result of these geopolitical constraints, was a driving force of Israel’s emergence as a technology cluster. Military innovation accelerated following the French embargo imposed on Israel after the 1967 Middle East war, requiring Israel to develop its own military technology.16 Many commercial technologies have emerged from highly-specialised Israeli military R&D, from fibre-optics and voice compression to networking software and devices; Israeli military intelligence had a computer training unit as early at 1960 helping establish world-leading expertise that was later commercialised.17 As important as the technology itself, however, was flow of people with the skills and leadership ability to manage technology companies, and deep experience of working on cutting-edge innovations.18

Israeli high-tech firms began to form in the 1960s, albeit at a slow pace.19 ECI Telecom was founded in 1961, and Tadiran and Elron Electronics in 1962; Elron is seen as the ‘Fairchild of Israel’ after the legendary Silicon Valley firm. Yet the cluster truly emerged in the mid-1990s, as the rate of successful companies grew from 1-2 per year to 10-20. de Fontenay and Carmel attribute this to the emergence of ‘specialised cluster intermediary services’ such as venture capital and legal services, services which also had professional networks in the United States, the major market for Israeli companies. Strong interpersonal networks and direct experience then allowed new firms to grow more quickly.20

Broader developments helped the cluster’s growth. Global telecommunications and internet booms in the 1990s increased demand and led to several high-profile acquisitions of Israeli companies.21 Shifts in the computer industry from hardware to software products greatly benefited Israel, particularly owing to the demand from businesses for security tools – several of which had been well-tested within Israeli military communications networks.22 Finally, the 1993 Oslo accords with the Palestinians encourages large companies such as Cisco, Motorola, IBM, Microsoft and Hewlett-Packard to invest heavily in R&D centres in Israel, helping to build international networks, expand employment opportunities and develop skills.23

Government interventions have directly stimulated the Israeli technology cluster, with the state nurturing the development of a venture capital industry. Several initiatives stand out. Yozma (Hebrew for ‘initiative’) began in 1993 with 100 million USD and established 10 venture capital funds with the aim of attracting foreign direct investment into Israel. Investors were offered matched funding at the rate of two dollars from the government for every dollar committed by a foreign investor. Equally generous was the option of buying out the government’s stake in the fund after five years. The fund has grown to manage billions of dollars of capital today.24

Other important initiatives include the Office of the Chief Scientist (now Israel Innovation Authority) R&D Development Fund, which gives new R&D facilities access to interest-free loans to match private investment, and the Israel-US Binational Industrial Research and Development Foundation (BIRD) fund, financed by both governments. BIRD ‘played matchmaker’ between an Israeli company with innovative technology and a US company who could distribute and market the product. Although the financial incentives were helpful, the largest impact was to teach young Israeli companies how to do business in the US.25 The state has also reduced bureaucracy, simplified tax regulations, and established incubators.26

Finally, two further factors have enabled cluster growth. The first is the influence of the unique Israeli military culture, pervasive in Israeli businesses because of compulsive military service (for at least two years from the age of 18). The Israel Defence Forces have an unusually flat hierarchy, leading to informal communication with superiors (and the willingness to challenge authority), great flexibility, the development of strong leadership skills, and experience of shouldering considerable responsibility at a young age: all skills that translate into strong entrepreneurship and teamwork in business.27 The strong networks formed in the military – often with people from different backgrounds – are then maintained through reserve duty for many years following military service.28 Alumni who met whilst working in the elite military units (particularly in intelligence) have spawned many high-tech companies, and graduates from these units are often the recruitment targets of major US technology companies.29

The second contributory factor was a large stock of human capital. Levels of education and technical skills are high, supported by world-class universities such as the Israel Institute of Technology (called the Technion) and the Weizmann Institute of Science. But the Israeli government’s open immigration policy towards Jews has also provided a significant inflow of talent. When the US tightened immigration in the 1990s, Israel saw a dramatic increase in immigration of often highly-educated Jewish immigrants from former Soviet Union nations – in ten years the population grew by 800,000, or one fifth; the number of engineers in Tel Aviv doubled. Given the traditional strengths of Soviet Union countries in theoretical sciences, Israel became ‘a superpower in mathematics’, as well as gaining knowledge of proprietary technologies and different methodologies.30 These enabling factors helped provide fuel for the Israeli technology cluster, and in turn for the growth of the nation.

Outcomes

By the late 1990s, the Israeli technology cluster was internationally connected and strongly entrepreneurial, based on deep stocks of human capital and local knowledge. The source of this innovation was commercialisation of military technology and university R&D, supported by flows of skilled workers and a government interventions to promote investment and generate capital.31 Although the acquisitions of several Israeli companies and the opening of large R&D plants put the country on the global innovation radar, it was the result of decades of government-led economic development rooted in efforts to secure national security and high-tech growth.

There are several key outcomes of these developments. First, Israel’s technology cluster overcame its geographic isolation to work effectively with distant – primarily US – markets by building on world-leading expertise and targeting business customers who require less face-to-face support.32 Professional ties with other clusters, such as Silicon Valley, are strong and aided by the diaspora concentrated in New York and Los Angeles. Concerns over brain drain, as young Israelis look to study and work abroad, are countered by new networks formed and the return of expatriates – often many years later – to set up regional offices or to champion investment and R&D centres in Israel.33

Second, a mature venture capital industry has emerged in Israel. More than 430 professional investors (including venture capital firms, private equity firms and incubators) have a permanent presence in Israel; just under a quarter of these are non-Israeli. Nearly 1,500 investors, representing more than 30 countries, invested in Israeli companies during 2018.34

Third, the Israeli culture – a somewhat intangible factor that draws on the collectivist origins of Israeli society and the nature of the military – has offered a competitive advantage. In addition to the factors explored in the section above, it has been suggested that collectivism and military service translates into loyalty, strong teamwork and lower turnover in the workplace compared to competitor nations. This might mean, for example, faster development times and greater retained knowledge when designing new computer chips – which often have long development cycles.35 However, despite these considerable advantages, the Israeli technology cluster faces several challenges that spring from each of these three outcomes.

Looking forward

One might imagine that the spectre of instability and violence, which served as the impetus for Israel’s focus on national growth and security, might also undo confidence in the ability of Israelis to innovate, and undermine investment in Israeli companies. Senor and Singer argue in Start-Up Nation that the determination of Israeli entrepreneurs to continue innovating in the face of war makes the country more enticing for investors.36 An analysis of the effect of Palestinian terrorist attacks during the second Intifada (2000-2005) found that despite being profoundly affected by terrorism, Israeli society was not demoralised by it because the public possessed a high level of social resilience – fostered in part by the cohesiveness of Israeli-Jewish society.37 Although violence continues to be a risk factor, more prosaic factors are perhaps of more concern.

First, the cultural attributes that lend themselves to entrepreneurialism may be a double-edged sword. The Israeli high-tech community has been accused of inattention to detail, indifference to quality, an unscalable management culture, and poor customer service. In particular, the management culture may be hindering the growth of companies, with few growing larger than 1,000 employees.38 Others fear that the ‘national characteristic of brusqueness is better suited to the creative process, not the nurturing of long-term projects’.39

Second, there is concern that start-up founders are too focused on buy-outs (and big pay offs) from overseas companies or public listings, instead of growing large businesses.40 Connected to this are perennial fears of brain drain and an exodus of talent to the US.41 These fears are heightened by a shortage of skilled software engineers, with five jobs for every applicant in the sector. Efforts to bridge the gap include alternative training programs such as tech boot camps, and boosting recruitment of women and Arab and ultra-Orthodox Jewish minorities, who are all under-represented in the sector.42

(Photos from Unsplash: street, square, skyline)

  1. Senor, D. and Singer, S., 2011. Start-up nation: The story of Israel’s economic miracle. Random House Digital.
  2. de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40.
  3. https://www.timesofisrael.com/startup-nation-has-grown-into-tech-nation-intel-israel-rd-chief-says/.
  4. https://www.forbes.com/sites/startupnationcentral/2018/05/14/israeli-techs-identity-crisis-startup-nation-or-scale-up-nation/#46c07ad6ef48.
  5. https://www.ivc-online.com/Portals/0/RC/Magazine%20&%20YB/IVC_ANNUAL_ISRAELI_TECH_REVIEW_FEB_2020/mobile/index.html#p=4.
  6. https://www.ft.com/content/e4b5a70a-c903-11e5-a8ef-ea66e967dd44; https://blogs.timesofisrael.com/israel-turns-71-is-the-start-up-nation-ready-to-be-a-scale-up-nation/.
  7. 2017 figures; World Bank data: https://data.worldbank.org/indicator/BX.GSR.CCIS.ZS?locations=IL-GB.
  8. 2017 figures; World Bank data: https://data.worldbank.org/indicator/GB.XPD.RSDV.GD.ZS?locations=IL-GB-XD.
  9. Israel figure 2012, UK figure 2017, high income country average figure 2016; World Bank data: https://data.worldbank.org/indicator/SP.POP.SCIE.RD.P6?locations=IL-GB-XD.
  10. From Ireland to Lithuania: https://www.irishtimes.com/news/what-ireland-has-to-learn-from-israel-s-high-tech-companies-1.683699; https://www.haaretz.com/israel-news/business/1.5109951.
  11. Ferras‐Hernandez, X. and Nylund, P.A., 2019. Clusters as innovation engines: The accelerating strengths of proximity. European Management Review, 16(1), pp.37-53.
  12. Senor, D. and Singer, S., 2011. Start-up nation: The story of Israel’s economic miracle. Random House Digital, p.xii.
  13. Haynes, C. and Langley, V. (2014). Magnet Cities. KPMG.
  14. De Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40.
  15. Gilbert, B.A., Li, Y., Velez-Calle, A. and Crews, M., 2019. A theoretical model of values and behaviors that shape technology region emergence in developing contexts. Small Business Economics, pp.1-13; Senor, D. and Singer, S., 2011. Start-up nation: The story of Israel’s economic miracle. Random House Digital.
  16. A few years later, the the US replaced France as the main supplier of arms. The US has since given billions of dollars in aid and military assistance and as such is a key part of the Israel’s technology story (Devi, S. ‘Business as usual’, Financial Times Magazine, April 13 2007). This stimulation of demand from military and technology projects is also a common characteristic shared with the US (Ferras‐Hernandez, X. and Nylund, P.A., 2019. Clusters as innovation engines: The accelerating strengths of proximity. European Management Review, 16(1), pp.37-53).
  17. Devi, S. ‘Business as usual’, Financial Times Magazine, April 13 2007; de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40.
  18. de Fontenay and Carmel note that, paradoxically, the military protects less of its intellectual property than do commercial firms, thus encouraging greater rates of commercial innovation. de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40.
  19. de Fontenay and Carmel provide a detailed account, summarised here. de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40.
  20. de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40, pp.25-26.
  21. In particular communications tools (again a legacy of military-developed technology). Detailed in Haynes, C. and Langley, V. (2014). Magnet Cities. KPMG. The burst of the dot com bubble in 2000 did, however, lead many companies to make mass redundancies.
  22. de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40.
  23. Devi, S. ‘Business as usual’, Financial Times Magazine, April 13 2007.
  24. Haynes, C. and Langley, V. (2014). Magnet Cities. KPMG; Senor, D. and Singer, S., 2011. Start-up nation: The story of Israel’s economic miracle. Random House Digital.
  25. Senor, D. and Singer, S., 2011. Start-up nation: The story of Israel’s economic miracle. Random House Digital, p.200.
  26. de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40.
  27. Explored in great detail in Senor, D. and Singer, S., 2011. Start-up nation: The story of Israel’s economic miracle, Random House Digital. See also de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40.
  28. They also contribute to a broader national network: ”You are never more than a couple of telephone calls away from anybody else in Israel, and we all like to help each other out if we can”, says one entrepreneur and investor in a Financial Times profile (Devi, S. ‘Business as usual’, Financial Times Magazine, April 13 2007). The size of Israel’s population also makes this a more feasible proposition than in larger countries.
  29. Haynes, C. and Langley, V. (2014). Magnet Cities. KPMG. Senor and Singer describe the IDF’s elite units as Israel’s equivalent of Yale, Harvard and Princeton. Senor, D. and Singer, S., 2011. Start-up nation: The story of Israel’s economic miracle. Random House Digital, p.84.
  30. de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40.
  31. Roper, S. and Grimes, S., 2005. Wireless valley, silicon wadi and digital island––Helsinki, Tel Aviv and Dublin and the ICT global production network. Geoforum, 36(3), pp.297-313.
  32. In common with other nations such as Taiwan and India, where local demand was deemed insufficient (de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40). In this sense, Israel also shares characteristics of other innovation-rich economies such as Ireland and Finland, which are relatively small and have fewer natural resources, and thus have focused on knowledge-intensive industries requiring firms to target export markets (Roper, S. and Grimes, S., 2005. Wireless valley, silicon wadi and digital island––Helsinki, Tel Aviv and Dublin and the ICT global production network. Geoforum, 36(3), pp.297-313).
  33. As was the case for Intel and Microsoft. de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40.
  34. The State of the Israeli Ecosystem in 2018, Start Up Nation Central: Finders Insights Series. (http://mlp.startupnationcentral.org/rs/663-SRH-472/images/Start-Up%20Nation%20Central%20Annual%20Report%202019.pdf).
  35. de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40.
  36. They also show that investment in Israeli hi-tech continued to increase in the face of rising violence in the early 2000s. Senor, D. and Singer, S., 2011. Start-up nation: The story of Israel’s economic miracle. Random House Digital, p.182.
  37. Waxman, D., 2011. Living with terror, not living in terror: The impact of chronic terrorism on Israeli society. Perspectives on Terrorism, 5(5/6), pp.4-26.
  38. de Fontenay, C. and Carmel, E. (2001) ‘Israel’s Silicon Wadi: The Forces behind cluster formation’, Stanford Institute for Economic Policy Research, Discussion Paper 00-40. Note this is dated. To quote from their interviews: ‘“That’s why Israel will never put a man on the moon” [said one]… meaning that a research organisation the size of NASA could never function properly given Israeli organisational culture’.
  39. Devi, S. ‘Business as usual’, Financial Times Magazine, April 13 2007.
  40. Haynes, C. and Langley, V. (2014). Magnet Cities. KPMG; Devi, S. ‘Business as usual’, Financial Times Magazine, April 13 2007.
  41. See, for example, https://www.newsweek.com/2018/05/18/israel-brain-drain-technology-startup-nation-religion-palestinians-economy-919477.html.
  42. https://www.ft.com/content/e4b5a70a-c903-11e5-a8ef-ea66e967dd44; https://blog.startupnationcentral.org/general/israel-high-tech-human-capital-shortage/.
Categories
Universities

Innovators Without Borders

This post originally appeared on the Yorkshire Universities website.

Nesta recently launched a report exploring how cities and regions collaborate internationally on innovation. If done effectively, international collaborations offer the opportunity to hit multiple policy priorities: levelling up regions, boosting investment in R&D towards 2.4 percent of GDP, and strengthening overseas relationships post-Brexit.

Cities and regions have a long history of forging overseas relationships directly with international partners. So-called ‘municipal internationalism’ thrived in the nineteenth century, culminating in the formation of the International Union of Local Authorities in 1913. Today, ambitious city regions across Europe have overseas offices (often in Brussels) and a complex web of relationships around the world. As Shane Ewen and Michael Hebbert put it, ‘the spirit of the Hanseatic League is alive and well in Europe’s town halls’.

There has been renewed interest in the topic in recent years. ‘Decentralised Development Cooperation’ is promoted by the likes of the OECD as means to help cities and regions achieve the UN Sustainable Development Goals. City diplomacy is an established academic field. I even published some musings of my own on the topic back in 2016.

The Nesta report is, however, valuable for considering how international collaborations can boost policy innovation (for leaders and governments), systems innovation (to address longer-term systemic issues of institutional capacity) and partnerships innovation (between government and business, universities, and other institutions) at the local level. The latter, in particular, is significant. Michele Acuto has observed that the average distance between a city hall and the closest major university is just under four kilometres in four of the major city networks. Strong, strategic partnerships at local level can only help strengthen international ones.

One effect of COVID-19 will be a greater role for universities and other civic bodies in regional collaborations. According to the report, ‘these are repeatedly viewed as critical and under-tapped intermediaries in peer-to-peer collaboration, because they have additional and more durable capacity as well as the ability to pedagogically transmit key principles, codify lessons and develop processes for distributed on-the-ground implementation’. Initiatives such as the EUniverCities network, in which medium-sized cities and their universities work together, offer a glimpse at what this may look like as a formalised structure.

For Yorkshire, the relationships that exist in the region between universities and LEPs, Combined Authorities, metro mayors, and local authorities provide a solid base to build upon. Both local government and the region’s universities have a wide set of relationships with counterparts around the world. The extent of city twinning in the region (which exploded in popularity after world war two) provide an insight into the range of partners: Hull is twinned with several cities, including Rotterdam in the Netherlands and Niigata, Japan. York and Bradford both have twins in France and Germany. Sheffield’s twins include Chengdu in China, Kawasaki, Japan and Pittsburgh, United States. Leeds is twinned with several cities including Hangzhou in China, Dortmund, Germany, and Durban, South Africa.

The multiple policy priorities of levelling up, boosting investment in R&D, and strengthening overseas relationships – ambitious even before COVID-19 struck – mean we need to bring universities into the centre of efforts to collaborate internationally on innovation. This would provide a timely boost to the concept of ‘Global Britain’.

(Photo of Brussels from Unsplash)

Categories
Universities

‘Town by town, factory by factory, job by job’: how Pittsburgh became a research cluster

I wrote the following piece for the recent Royal Society report on research clusters, republished here under a creative commons license. The full report has eight case studies. Individually, they tell the story of how the actions of leaders, businesses, universities and communities have affected the development of different places with different contexts and histories. Combined, patterns and trends begin to emerge. The story of Pittsburgh is one of a slow recovery fuelled by investments with long-term returns, and a slow accumulation of talent and expertise.

The Pittsburgh cluster is perhaps best described as several clusters with some areas of overlap. The Pittsburgh Innovation District lists these as life sciences and digital health, advanced manufacturing, and AI and robotics, whereas the Brookings Institution identifies manufacturing, technology, and health care as key clusters.1 These industries have grown by 8.4 percent, nearly double Pittsburgh’s private-sector growth rate, since the end of the recession in the early 2010s.2

Businesses in these clusters work closely with the university sector. The University of Pittsburgh is recognised as a leader in life sciences research, the University of Pittsburgh Medical Center (UPMC) is a top-ranked hospital system with 89,000 employees and 40 hospitals, and Carnegie Mellon University has specialist expertise in computer science and engineering.3 The metropolitan area outperforms the national average on academic activity, ranking ninth among the largest 100 cities for the amount of university research and development, and performs particularly strongly in fields such as robotics, gerontology, critical care, artificial intelligence, cell and tissue engineering, neurotrauma, and software.4

The Oakland district is the academic and healthcare centre of Pittsburgh, and is an example of two much-vaunted developments: an innovation district home to a dense, walkable hub of economic activity for research and entrepreneurship, and a shift from heavy industry to ‘eds and meds’, with the knowledge-rich ecosystem that accompanies universities, large hospitals and their spinoffs and spillovers.5 As the Brookings Institution has noted, few cities have such a naturally occurring innovation district as Pittsburgh: Oakland represents three percent of the city’s land area, ten percent of residents, 29 percent of jobs, and over a third of the state of Pennsylvania’s university research output.6 As such, challenges remain in ensuring inclusive growth in neighbouring districts (which have some of the highest rates of long-term unemployment and poverty in the city), connecting communities to new opportunities, and addressing regional inequalities.

Pittsburgh’s performance is often framed against the collapse of the steel industry in the city in the 1980s, when the unemployment rate in the city hit 18 percent. Prior to the collapse, manufacturing represented more than a quarter of all employment in Pittsburgh; today manufacturing accounts for under ten percent of employment. More people work in Pittsburgh’s health sector today than in the steel industry at its highest point.7 Although this transformation is remarkable, the seeds for Pittsburgh’s resurgence were planted long before the collapse of the steel industry in the city.

Development

By 1983, Pittsburgh – seen as the industrial powerhouse of the US – was in economic breakdown. The Pittsburgh Press newspaper described it as a tide of change: ‘town by town, factory by factory, job by job’.8 Three quarters of Pittsburgh’s steelmaking capacity and 130,000 manufacturing jobs were lost, and tens of thousands of residents moved away – with knock-on effects for the businesses and services which remained.9

In the following decades, the economy shifted from low- and moderate-value production to technology-driven services and high-value advanced manufacturing. This shift was led by a focus on innovation, driven by federally-funded research at Carnegie Mellon University and the University of Pittsburgh.10 But an overarching theme of Pittsburgh’s story is a slow recovery fuelled by investments with long-term returns, and a slow accumulation of talent and expertise. It is necessary to trace the roots of today’s research clusters to the height of the steel industry in Pittsburgh.11

Important (but some, at the time, seemingly modest) investments were made in three areas in the 1950s.12 The first was a partnership known as ‘Renaissance I’ between local government leaders and Pittsburgh’s business community (under the banner of the Allegheny Conference). The aim was to improve the quality of life in the city and address the region’s environmental and infrastructure issues. Real estate development was channelled through public authorities, deserted train sheds were converted to house and offices, cultural attractions were built, and transport and sanitation improved.

The second investment was a donation of $50 million from the local Mellon family to the University of Pittsburgh to build and run a new medical school. The creation of a world-class medical research institution set a foundation for the region’s biomedical research strengths today. The third set of investments follows from this: that of the philanthropic community who grew wealthy from Pittsburgh’s industry. Funding from philanthropic foundations has ensured the survival of much of the city’s cultural infrastructure from the Symphony Orchestra to community arts organisations – an essential ingredient in creating an environment for attracting and retaining skilled workers. More recently, foundations in the city have tended to view economic development through technological innovation as a core part of their social mission. Philanthropic investment has, for example, helped transfer robotic and automation technology from the lab to the city for real-world testing, and was central to starting programmes of work on machine learning, computational finance, and robotics at Carnegie Mellon University.13 The close relationship between philanthropy and universities has a long history in Pittsburgh, and is central to shaping the city’s development.

These investments bore fruit years after the collapse of Pittsburgh’s steel industry. They are not, however, responsible alone for the creation of Pittsburgh’s research clusters. Upon this foundation, the local universities and local government (and, in particular, their leaders) played a key role, supported by federal and state grants.

As unemployment soared, the heads of Carnegie Mellon University and the University of Pittsburgh – historically competitors – decided to coordinate efforts to diversify Pittsburgh’s economy and drive research and development in the city.14 In 1978 Carnegie Mellon University, led by Richard Cyert, established the Robotics Institute with corporate funding, and planted the seed for the city’s expertise in this area (the CMU Robotics Institute also became the first in the world to offer a PhD in robotics).15 Heaton et al describe the investments made by university and local leaders in new technologies in Pittsburgh – others included biotech and computing – as ‘sensing activities’. These are ‘long-gestation investments’ that are the first stage of a new innovation ecosystem (with no guarantee they will pay off), and which ‘assess internal and external signals about scientific and technological developments that hold promise for the future, then ensure that sufficient financial and faculty resources are available for exploring the most attractive possibilities’.16

In 1986, with University of Pittsburgh Chancellor Wesley Posvar’s guidance, all of the city’s hospitals, teaching hospitals and research facilities were brought together under one not-for-profit roof – known today as UPMC. And as Carnegie Mellon University sought out the best researchers to relocate in Pittsburgh, the University of Pittsburgh persuaded medical experts to join, including pioneers of organ transplantation – helping to establish the city as a world-leading centre in this area.17

The universities have continued to play an important role in shaping Pittsburgh’s research and innovation clusters. When Jared Cohon stepped down as Carnegie Mellon University president in 2013, he identified three key ways the institution helped Pittsburgh’s economic shift: by making it easier for professors to start new companies by changing the technology transfer policy, by collaborating with the University of Pittsburgh to support start-ups, and by building the Robert Mehrabian Collaborative Innovation Centre.18 This centre opened in 2005 and was funded by state, university and private money, allowing companies and researchers to work collaboratively.

State and federal governments have also played an important role. Both provided grants to research universities and seed funding to entrepreneurs in technology-related fields. As Holstein and Eschenfelder conclude, state-funded accelerator programmes:

reduced information asymmetry and externality problems that inhibit the birth of new enterprises. Their highly selective application process reduced cost to angel investors and venture capital firms of searching for early-stage startups with high commercial potential. The rigorous and short-term duration of these programs accelerated growth of some startups, but also accelerated failure of others enabling resources to move to higher valued uses. These programs also linked potential tech entrepreneurs to a network of mentors who provide the legal, accounting, marketing, and management skills that they lack. As a critical mass of successful tech ventures were established, new accelerator programs began to obtain funding from private sources and the inflow of capital from angel investors and venture capital firms from various parts of the country increased.19

Pittsburgh’s reinvention required the city’s leadership to ‘think like a system and act like an entrepreneur’ – taking stock of assets, cultivating talent, and maintaining a good place to live, whilst taking risks, seizing opportunities and being flexible.20 Tom Murphy, a state representative who later became mayor of Pittsburgh, is regarded as one such leader. Recognising and supporting the role of universities in a post-steel Pittsburgh, he introduced the Ben Franklin Technology Partnership in 1983, dedicated to advancing early-stage startup businesses and the commercialisation of technologies – since described as a state programme run like a venture capital firm.21

After becoming mayor in 1994, Murphy developed more than 25 miles of new trails alongside the river and urban green space, and cleaned up more than 1,000 acres of abandoned industrial land.22 In more recent years, the city has improved its food and art culture, helping to attract skilled workers.23 This, combined with a consistently low cost of living, has helped Pittsburgh’s economic transition.24 Above all, however, this transition has been driven by the long-standing alliance between universities, local leaders, businesses and the civic community – and the return on investments made long ago.

Outcomes

Michael J. Madison, a Professor at the University of Pittsburgh, describes the city’s revitalisation as being less about the ‘grit’ and character of Pittsburghers (a popular narrative to explain the transition) and more about having economic diversification thrust upon it.25 But by building on strong research and innovation assets – UPMC, the University of Pittsburgh, and Carnegie Mellon University – the city has managed to excel in knowledge production. Pittsburgh’s education and technology sectors account for 80 percent of the high-wage jobs in the city.26 Overall, the technology sector accounts for a third of annual payroll in the Pittsburgh region, helping to retain highly educated young people.27 And in 2016 the region’s university research and development spending per capita was nearly two and a half times the national average.28

There are still threads connecting modern Pittsburgh to the rich legacy of manufacturing in the city. The advanced manufacturing clusters in the region are highly specialised: automation and industrial machinery, and metals and metal processing each have more than two times the national employment concentration. New clusters have formed around these industries as technology companies seek access to top engineering and computer science talent.29

However, the acceleration of scientific and technical activity and global expertise headquartered in the city has not translated locally into broad-based growth outside the clusters, and in the neighbourhoods in which they are sited.30 As Madison puts it, ‘steel money was sucked out of one part of the Pittsburgh region; new money is largely being injected elsewhere’.31 The risk is that, without new jobs being created at all skill levels, spatial inequality in the region will increase. The Brookings Institution recommends in particular that the Oakland innovation district needs to be marketed and better connected to the regional economy, with better integration with nearby employment centres.32

Pittsburgh’s history and resurgence has been much studied and analysed. Professor Michael Porter, considered the father of cluster theory, draws several lessons from Pittsburgh for other cities.33 First – and as we have seen – cluster growth is a long-term process with assets taking decades to develop. Second, diversification across several clusters helps strengthen the regional economy and to protect it against economic shocks. Third, research and development investment is critical, but so too is effective commercialisation mechanisms – and Pittsburgh faces challenges in this area (see below). Finally, strong and unified leadership is required to push for a regional cluster development programme.

Looking forward

A 2017 benchmarking report examined the prospects of Pittsburgh’s life sciences cluster, and found great opportunities for developing new solutions and innovations at the intersection with other clusters – automation, robotics, and healthcare – and with other areas of expertise – biomedicine at the University of Pittsburgh and computer science at Carnegie Mellon University.34 The blurring and crossover of disciplinary boundaries extends to collaboration with the private sector. The report gives the example of UPMC partnering with IBM Watson to form Pensiamo, a Pittsburgh-based startup using cognitive analytics to improve supply chain performance in hospitals.35

Pittsburgh’s clusters face several challenges. Commercialisation is lagging, in particular in life science firms, which often take longer to develop. Although investment trends are improving, the region has less venture capital funding than other US innovation hubs.36 Connected to this is a low rate of high-growth startups. One contributing factor is the need for more corporate partners (a barrier to recruiting talent to startups is the lack of backup employment options if the local startup does not succeed – a truly effective cluster, by definition, offers choice).37 And finally, ongoing challenges remain over continuing to build links between the research being conducted in universities and the strengths of industry, and ensuring a pipeline of skills to meet future workforce needs: fundamental concerns that remain constant even for well-established clusters.38

(Photos from Unsplash: bridge, skyline, freeways)

  1. https://www.pittsburgh-id.com/innovation-clusters; Andes, S., Horowitz, M., Helwig, R. and Katz, B., (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Anne T. and Robert M. Bass Initiative on Innovation and Placemaking at Brookings.
  2. Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings.
  3. Pittsburgh Region Life Sciences Benchmarking & Opportunities Analysis May 2017; https://www.upmc.com/about/facts.
  4. Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings.
  5. Madison, M. (2011). Contrasts in innovation: Pittsburgh then and now. In M. Carpenter (Ed.), Innovation and entrepreneurship in evolving economies: The role of law. Pittsburgh, PA: Edward Elgar Publishers; Haynes, C. and Langley, V. (2014). Magnet Cities. KPMG.
  6. Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings.
  7. Madison, M. (2011). Contrasts in innovation: Pittsburgh then and now. In M. Carpenter (Ed.), Innovation and entrepreneurship in evolving economies: The role of law. Pittsburgh, PA: Edward Elgar Publishers; Haynes, C. and Langley, V. (2014). Magnet Cities. KPMG.
  8. https://www.post-gazette.com/business/businessnews/2012/12/23/In-desperate-1983-there-was-nowhere-for-Pittsburgh-s-economy-to-go-but-up/stories/201212230258.
  9. Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings; Madison, M. (2011). Contrasts in innovation: Pittsburgh then and now. In M. Carpenter (Ed.), Innovation and entrepreneurship in evolving economies: The role of law. Pittsburgh, PA: Edward Elgar Publishers.
  10. Gallagher, P. (2017). Pittsburgh myth, Paris reality, Science vol 356 issue 6343; Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings.
  11. Bruce Katz and Jeremy Nowak conclude that ‘Pittsburgh’s emergence has been decades (if not a century) in the making’ (https://nextcity.org/daily/entry/how-the-once-struggling-pittsburgh-is-reinventing-itself-as-innovation-hub).
  12. Drawn from Michael Madison’s study of Pittsburgh’s resurgence which tells the story in greater detail: Madison, M. (2011). Contrasts in innovation: Pittsburgh then and now. In M. Carpenter (Ed.), Innovation and entrepreneurship in evolving economies: The role of law. Pittsburgh, PA: Edward Elgar Publishers.
  13. Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings.
  14. Haynes, C. and Langley, V. (2014). Magnet Cities. KPMG.
  15. https://www.pittsburgh-id.com/robotics. As part of this process, faculties were closed and activity focused on science and technology. Funds released as a result of restructuring were used to lure world-class researchers working elsewhere in the US to the university (Haynes, C. and Langley, V. (2014). Magnet Cities. KPMG).
  16. Heaton, S., Siegel, D.S. and Teece, D.J. (2019). Universities and innovation ecosystems: a dynamic capabilities perspective. Industrial and Corporate Change, 28(4), p.930.
  17. Haynes, C. and Langley, V. (2014). Magnet Cities. KPMG.
  18. Heaton, S., Siegel, D.S. and Teece, D.J. (2019). Universities and innovation ecosystems: a dynamic capabilities perspective. Industrial and Corporate Change, 28(4).
  19. Holstein, A.D. and Eschenfelder, M.J. (2017). Economic Analysis Of Public Support For Tech Startups: A Case Study Of Pittsburgh. Journal of Business and Behavioral Sciences, 29(1), p.100. CMU’s Project Olympus incubator and the University of Pittsburgh’s Innovation Institute are two examples of sources of support to startups. Both also collaborate on successful centres such as the Pittsburgh Life Sciences Greenhouse (https://www.plsg.com/).
  20. The RSA’s Matthew Taylor quoted in https://nextcity.org/daily/entry/how-the-once-struggling-pittsburgh-is-reinventing-itself-as-innovation-hub.
  21. Haynes, C. and Langley, V. (2014). Magnet Cities. KPMG. An evaluation of the Ben Franklin Technology Partnership found returns on investment in terms of generated tax revenue of 3.6:1, with 140,000 new jobs created since 1989 (https://benfranklin.org/what-is-bftp/).
  22. https://www.economist.com/united-states/2011/10/22/smaller-is-more-beautiful.
  23. Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings.
  24. Madison discusses the pros and cons of low property costs in detail. ‘Cheap real estate translates into low local tax revenue and then into poor public services. Unsurprisingly, property-rich communities get wealthier. Property-poor communities lose ground.’ Madison, M. (2011). Contrasts in innovation: Pittsburgh then and now. In M. Carpenter (Ed.), Innovation and entrepreneurship in evolving economies: The role of law. Pittsburgh, PA: Edward Elgar Publishers.
  25. Madison, M. (2011). Contrasts in innovation: Pittsburgh then and now. In M. Carpenter (Ed.), Innovation and entrepreneurship in evolving economies: The role of law. Pittsburgh, PA: Edward Elgar Publishers, p.25.
  26. Heaton, S., Siegel, D.S. and Teece, D.J. (2019). Universities and innovation ecosystems: a dynamic capabilities perspective. Industrial and Corporate Change, 28(4).
  27. Holstein, A.D. and Eschenfelder, M.J. (2017). Economic Analysis Of Public Support For Tech Startups: A Case Study Of Pittsburgh. Journal of Business and Behavioral Sciences, 29(1), p.100.
  28. Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings.
  29. Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings.
  30. https://nextcity.org/daily/entry/how-the-once-struggling-pittsburgh-is-reinventing-itself-as-innovation-hub.
  31. Madison, M. (2011). Contrasts in innovation: Pittsburgh then and now. In M. Carpenter (Ed.), Innovation and entrepreneurship in evolving economies: The role of law. Pittsburgh, PA: Edward Elgar Publishers, p.34.
  32. Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings, pp.8-9.
  33. Porter, M. (2002). Pittsburgh: Clusters of Innovation Initiative. Council on Competitiveness.
  34. Fourth Economy in Collaboration with Warner Advisors (2017). Pittsburgh Region Life Sciences Benchmarking & Opportunities Analysis.
  35. https://www.pensiamoinc.com/.
  36. https://www.geekwire.com/2018/pittsburgh-forges-new-future-remaking-iconic-steel-town-modern-innovation-factory/; Fourth Economy in Collaboration with Warner Advisors (2017). Pittsburgh Region Life Sciences Benchmarking & Opportunities Analysis; Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings.
  37. Fourth Economy in Collaboration with Warner Advisors (2017). Pittsburgh Region Life Sciences Benchmarking & Opportunities Analysis; Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings.
  38. Andes, S., et al (2017). Capturing the next economy: Pittsburgh’s rise as a global innovation city. Brookings.
Categories
Universities

Research and innovation clusters – new Royal Society policy briefing

The Royal Society launched a policy briefing on research and innovation clusters today – I provided support for the analysis and wrote the case studies for Israel, Pittsburgh, and Uppsala.

The report is online here, and there’s a blog by Professor Richard Jones on Wonkhe introducing the report: can research clusters help level up the country? Research Professional also has coverage (paywalled article).

(Photo of Pittsburgh from Unsplash)

Categories
cities

A directory of Resilient City strategies

The 100 Resilient Cities programme resembled a large-scale urban experiment, with the strategies that many of the cities produced offering a rich source of information for analysis. Over 80 final strategies have been published; although cities from North America are overrepresented, there is broad geographic coverage.

A few of the 80+ strategies published by city governments
A few of the 80+ strategies published by city governments

As the previous iteration of the programme has ended, academic analyses of the strategies have continued to grow. For example, Taylor et al. (2020) use latent content analysis to assess how the resilience strategies of 14 cities in Europe, North America and Oceania conceptualise future uncertainty. Fitzgibbons and Mitchell (2019) examine the extent to which 31 resilience strategies focus on social equity and justice using content analysis; their sample included cities from the Global South and North.

I have compiled a spreadsheet of all the published strategies here (last updated July 2020). Please feel free to add any that I have missed. At the time of writing the 100 Resilient Cities website (home to most of the strategies) appears to be offline, so let me know if you would like access to the complete set of strategies, which I have both as PDFs and plain text files.

(Image credit)

Categories
Universities

New report: a plan for tackling socio-economic inequalities and boosting health outcomes

A new report published today explores how different sectors can work together to improve health outcomes at a regional level. I was delighted to be the lead author for this report with NHS Confederation, the Yorkshire & Humber Academic Health Science Network, and Yorkshire Universities.

Read the report 📖 (PDF), read the coverage in the Yorkshire Post 📰 or visit the campaign website 🌐.

Even before the pandemic, the government had given a clear commitment to ‘level up’ the regions, which means enabling regions to realise their full potential as part of an overall plan to narrow gaps in prosperity across the country. The economic aftershock of COVID-19 will hit communities hard – making the levelling up agenda more challenging but even more vital.

The report welcomes the growing focus nationally on both ‘health’ and ‘place’ – and sets out how we can align these with a bold ambition for improving quality of life and economic opportunities.

There is a particular focus on the tricky but vital mechanics of cross-sector collaboration, bringing together universities, local government, the health and care sector, business and communities. The traditional wisdom of carefully nurturing partnerships over time needs to be balanced by types of rapid response and new partnerships forged in the response to COVID-19. Read the full report here.

(Image credit)

Categories
Universities

Why most university impact studies are flawed

A version of this article also appears in ACEEU Spotlight magazine 📖

I enjoyed speaking on a lively panel yesterday about regional development and innovation as part of the UIIN conference, relocated successfully from Budapest to Zoom. Together with Matthew Guest from GuildHE we discussed how to better understand the local role of small and specialist providers.

The work builds on experimental alternatives to traditional economic impact studies. I first explored the idea of institutional heatmaps on a post here in 2018, and then expanded on this at a workshop in South Africa later that year. Over the past 12 months I have been working with GuildHE to ‘map’ the impact of some of their members. In yesterday’s presentation I set out why I think the traditional ‘big number’ approach to measuring economic impact is out of step with what places need from their universities. Below I go further and list why I feel these studies are, mostly, flawed endeavours. (I should add that these are my personal views, not those of GuildHE!).

You don’t have to look far to see economic impact studies. My former employer had a flagship biennial report with a steadily-increasing figure for the impact of UK universities – £21.5 billion to UK gross domestic product at last count – which it has used successfully for lobbying and campaigning. As long as this figure keeps increasing, everybody is happy. Many institutions have their own studies – £650 million of impact here, £400 million impact there – and often with LEP-level or regional disaggregation. Of course, such studies are not limited to higher education. We’re informed that shooting contributes £2 billion to the UK economy and supports the equivalent of 74,000 full-time jobs. Ornamental horticulture and landscaping contributed £24.2 billion to national GDP in 2017.

Why we need change

There are helpful academic papers which deconstruct the methodologies for calculating economic impact, and the common pitfalls. Instead, I want to challenge the preoccupation we seem to have with ‘one big number’ impact studies and what we lose in the process.

There are two shifts taking place which render the traditional impact study less effective:

  1. A single large number fails to capture what is increasingly important. The shift towards universities being ‘for’ a place, rather than simply ‘in’ or ‘from’ a place, means this data needs to be far more nuanced. We need to know specifically who is benefitting, and how, and who is missed out. We need to know the businesses and the communities behind these numbers. As disillusionment grows with traditional methods of measuring economic success – GDP, GVA – and attention on ‘inclusive’ and social development begins to be translated into policy change, economic impact analysis needs to keep up.
    Traditional impact studies simply don’t do justice to the range of university activities. They measure spending, output and employment, but do not capture the full impact of engaging with communities in a marginalised neighbourhood, or working with small businesses to strengthen their supply chains, for example – activities that may have huge impact but make little difference to a £400 million impact figure. (Accounting for social value can help here).
  2. As we grapple with recovery from Covid-19, it is both tone-deaf and ineffective for universities to be shouting about how good they are, whilst also asking for assistance from government. Rather than communicating about the size of their value-added, university messaging needs to focus on solutions and partnerships. Policymakers need a more sophisticated understanding of impact which moves beyond broad figures to specific information on which communities, businesses and industries have benefited from the university, and who stands to benefit from future support.

What else is wrong with traditional impact studies?

I should note that economic impact studies are not all bad. It is helpful to see returns on investment, and to raise awareness that universities have economic clout and should be seen alongside other major industries. But they risk being a blunt instrument, obscuring what is often highly patchy and inconsistent local impact behind impressively large numbers. Economic impact studies need to be married to a rich understanding of local impact – perhaps through something like an institutional heat map combined with a survey of perceptions or social impact assessments.

Four further shortcomings that come to mind:

  • Uniformity. Despite huge variation in local contexts across the UK, and the individual histories and missions of universities, impact studies all end up looking pretty much the same. As with my engagement strategies test, if you line up five university impact studies and remove the university name, can you tell who (or where) they are talking about? The uniformity of approach, and measuring success against numerical benchmarks, means we lose out on what may be needed. By working towards what is measured and counted, impact ends up converging into a standardised set of headline numbers and we lose the local context.
  • Impact. Slightly tongue-in-cheek, I would like to see an impact study of impact studies. Do they lead to positive change? Or boost perceptions of universities? Quite possibly. But next time you are in a taxi to a university, ask the driver about the impact of the university. You’re unlikely to be quoted an economic impact figure of £450 million a year to the LEP’s economy. You’ll probably be told about the business that decided to open a new site near the university, or the impact of students volunteering with communities (and how the university is good business for the taxi company – at least before lockdown). You might argue that economic impact analysis is aimed instead at funders and policymakers. But should it not also reach residents and businesses?
  • Fatigue. Somewhat cynically, does anyone really care whether the economic impact is £600 or £900 million? Beyond a certain point, big number fatigue sets in. Figures between institutions are not always directly comparable, and the process of reaching the figures is not always transparent (or easily replicable).
  • Unintended consequences. We are not at this point, but I can imagine a league table of economic impact rankings. Universities should be well aware of the limitations of league tables, and the uncanny ability of rankings to shape and warp policies away from what is important – both for the institution and for the place.

Above all, my concern is that economic impact analysis can mask inequalities and ‘cold spots’ in university engagement. Of course, heatmapping as an experimental alternative brings its own set of issues. Consistency between institutions, subjective judgements over the importance and intensity of shading, and the complexity of trying to map such a wide range of activity are issues that need to be resolved. But they may also expose quite starkly where a university is not working, and not having an impact – things that are hidden in the ‘one big number’ approach.

(Image credits: original images from Unsplash here and here.)

Categories
Universities

Reshaping UK regions post-COVID: research and industrial capacity

Yesterday Nesta published a report arguing that some parts of the UK have missed out on £4 billion of public research and development (R&D) funding each year, plus a further £8 billion of private sector investment. Some of these regions never fully recovered from the 2008 Great Recession, and COVID-19 threatens to deepen these divisions.

The Government’s target – set before the pandemic – called for the UK to increase investment in R&D to 2.4% of GDP by 2027, and by 3% in the future. The importance of this target is now greater than before. To meet it means empowering those regions with the lowest R&D intensity and recognising and supporting the vital role of universities and other partners in these regions.

Proposals in the report include devolving a substantial portion (25%) of the promised uplift in the R&D budget to nations, cities and regions, delivered through ‘Innovation Deals’.

The report also recognises how historic policy decisions have led to path dependency for regions, entrenching a set of ‘winners’ and ‘losers’. (This factor is missing in some – otherwise reasonable – recent reports which instead advocate building on existing centres of excellence). As the Nesta authors put it:

The current situation is the result of a combination of deliberate policy decisions and a natural dynamic in which these small preferences combined with initial advantages are reinforced with time.

Industrial capacity

Decisions made by previous generations of policymakers and politicians also play an outsized role in the UK’s industrial policy.

This excellent piece on efficiency and redundancy in the UK, and how we need more of the latter at the expense of the former to ensure resilience, is taken forwards nicely by Andy Westwood in this discussion of building industrial capacity in the UK. Building in redundant capacity is seen as a signature trait of a ‘resilient’ city or region. Andy sets out the case for starting with ‘national self sufficiency’ in health and manufacturing but then rapidly broadening out to other sectors, with a focus on impact at the local level. Movement towards autarky is a balancing act needing careful trade-offs, but there is a strong case for securing – or at least diversifying – supply chains in key industries and sectors.

The pandemic has drastically curtailed trade and investment; a return to previous patterns of international cooperation (which differ across UK regions) following COVID-19, and when trade picks up, is unlikely. More emphasis will be given to secure and resilient supply chains within the UK and near neighbours. This means strengthening industrial capacity and domestic manufacturing in the UK, and ensuring the provision of critical goods and services across the country – with clear implications for spatially-aware policymaking and an opportunity for rebuilding local economies.

These discussions neatly fit with a few themes I have touched on in recent posts – on how discussions over the smart city have morphed into ones about self-sufficient cities, on the risks of poor policymaking for resilience, and why popular narratives around ‘resilient communities’ are dangerous. See also this piece by Yorkshire Universities on The Coronavirus Pandemic: Universities and the Economic Recovery of Place.

(Image credit)

Categories
Universities

When a local economy collapses, we can’t just rely on the grit of communities

This post originally appeared on the Yorkshire Universities website.

I’m a little late in reading Janesville: An American Story, Amy Goldstein’s tale of an industrial Wisconsin town in the depths of the Great Recession. The book received wide praise when published in 2017, telling the story of a community trying to pick itself up in the years following the closure of a major General Motors assembly plant. But the story has particular resonance now, as we stand on the cusp of another wave of economic upheaval. Here are three reflections.

A tale of two towns

Five years after the General Motors plant closed, the shock of vanished jobs has faded. But ‘the ways that time and economic misfortune can rend even a resilient community – a community determined not to lie down and give up – are plain to see’. Goldstein describes the emergence of two Janesvilles: one of business owners that emerged relatively unscathed, and another large group of struggling families. For this group, part of a ‘broad tumbling downhill’, the future is uncertain, incomes have halved, mortgages outstrip house values, food stamps have replaced eating out, and health insurance stops.

Inequality is at the heart of recent work by Yorkshire Universities on health and wealth, including a forthcoming report with NHS Confederation and the Yorkshire & Humber Academic Health Science Network (AHSN). Just before the pandemic struck, Sir Michael Marmot published a report showing widening regional disparities in life expectancy, including falling life expectancy for the poorest. In Yorkshire and the Humber, healthy life expectancy at birth is lower than the national average – with stark variations within the region too. Absence from work because of sickness is greater than the national average. Mortality rates are uniformly higher.

The danger is that the long-term economic impact of coronavirus exacerbates these inequalities. A briefing paper from the Institute for Fiscal Studies makes uncomfortable reading, referencing a study that showed a 1% fall in employment leads to a 2% increase in the prevalence of chronic illness:

To put this in context, if employment were to fall by the same amount as it fell in the 12 months after the 2008 crisis, around 900,000 more people of working age would be predicted to suffer from a chronic health condition. Only about half this effect will be immediate: the full effect will not be felt for two years. The shock to employment from the coronavirus pandemic is likely to be much larger than this and so we may expect a larger rise in poor health.

The poorest in society are hit hardest by recessions, driving wider inequalities in health and wealth, and splitting towns and cities into two.

The challenges of retraining

‘It isn’t simple to take someone with a high school degree and a factory job and help lead them into new work’, reflects Bob Borremans. Bob is a community leader and head of Janesville’s job centre, and faces an uphill battle despite enthusiastic trainees and injections of federal cash.

Retraining and re-skilling are obvious responses to job losses and economic restructuring. But promised jobs at the end of retraining do not always materialise, and the path to graduation is tough. In Janesville, many former factory workers turned to courses at Blackhawk Technical College funded by federal grant programmes. Despite the laudable work of the college, the average pay of those who graduate is a shadow of their pre-recession wages.

The UK’s What Works Centre for Local Economic Growth concludes that employment training programmes for adults can have a positive, although modest, impact on earnings and employment. The key to success is designing appropriate programmes. A review of the evidence by the Centre found shorter programmes (below six months) are more effective for less formal training activity, and that longer programmes generate employment gains when the content is skill-intensive. On the job training programmes tend to outperform classroom-based ones. Further and higher education providers should bear this in mind in the months and years to come.

Phoenixes vs. Planting Seeds

Janesville is proud of its ‘can-do spirit’, a trait that can be traced back generation to generation, to the industrious and hard-working communities that first attracted the likes of General Motors to the town. The problem is that a can-do spirit is, by itself, rarely enough to save a town struck by economic upheaval.

In another project, I have been exploring how world-leading research clusters have emerged in certain places – from advanced manufacturing in Pittsburgh, to life sciences in the Stockholm-Uppsala region, to the high-tech industry in Israel. Many of these have a popular ‘origin story’, often spun by an enthusiastic local press. The story usually goes something like this. The town has a proud past rooted in a particular industry. Economic calamity strikes due to wider structural forces. The proud industry is obliterated. There’s mass unemployment, and, temporarily, hope is lost. But the community is resilient and bounces back through sheer determination and hard work, attracting a new industry and forging a new, bright future – a high-tech phoenix rising from industrial ashes.

The reality is often messier, and the roots of any revival go back much further than the economic calamity. Take Pittsburgh. The steel industry in the city collapsed in the 1980s and the unemployment rate hit 18 percent. The city’s revitalisation is often explained by the grit and character of Pittsburghers, whereas the seeds of revival were planted decades before when the steel industry was at its height. Philanthropic investment led to specialist expertise being developed at the University of Pittsburgh and Carnegie Mellon University, including a new medical school, forming the foundation of Pittsburgh’s research and innovation clusters today.

There is a similar story in Sweden. When Pharmacia, then one of the largest pharmaceutical companies in Europe, merged with the US company Upjohn in 1995, around 200 research and managerial positions were moved out of Uppsala; the move was initially seen as striking a huge blow to the region. The popular narrative is that the vacuum left by the company’s withdrawal led to a frenzy of entrepreneurial start-ups and innovative ideas. But the emergence of the Uppsala cluster is the result of industrial and academic collaboration over at least 70 years.

The message here is not that people and communities are not important. Specialisation builds on rich legacies, and new clusters form around old industries. Some people – especially the highly-skilled – will thrive; employment in automation and industrial machinery in Pittsburgh is more than twice the national average. But people need to be empowered by structures and institutions that support them. Some places are fortunate to have seeds planted long ago, such as a strong university. Despite the challenges such institutions will be facing themselves, they will need to step up. For places those without, relying on grit will not be enough.

(Photo by Science in HD on Unsplash)

Categories
Process

How to do quick and dirty literature surveys

What follows is a simplified version of this workflow. It’s great for rapid literature surveys, and I’ve done a few recently for non-academic projects. No reference managers or specialist software are required. I use Ulysses for Mac to do my writing in the workflow below, but any text editor on any platform will do.

1. Gather everything in one place

Save all the documents you will be reviewing in a folder. Optionally, split by type: in the example images below I have a folder for academic articles, and another for assorted reports, website pages and other publicity material.

Academic source documents

Number these sequentially, as in the images. As you work through them, you may wish to label them as read (I’ve used a green tag to remember which ones I have reviewed).

Non-academic source documents

(Skip to the bottom if you’re a Mac user and want to know how to find articles on Google Scholar incredibly quickly).

2. Create loose headers or categories (optional)

If it will save sorting time later, create headers in a text document corresponding to the final output. For example, in my latest project this was simply ‘introduction’, ‘development’, ‘outcomes’, ‘future’.

3. Scan the documents

As you read each document, copy and paste the key information into your text file. The less you copy, the easier the final review becomes. Before each extract, put the document number or letter from step 1. Add comments if helpful.

Pasting extracts from source documents. ‘F’ and ‘6’ refer to difference sources

Ulysses offers advantages for taking notes: you can quickly navigate between headers using keyboard shortcuts, and you can easily distinguish comments from pasted text. But other programs will work fine.

4. Sort into sub-categories (optional)

In this example, after working through 19 documents I had over 7,000 words of notes, which was a little unwieldy. To speed things up later, I had identified themes and quickly moved text around within new sub-categories (two or three within each of the four main headers). This should be a quick and crude exercise; don’t worry about missing things as the next stage will capture these.

Adding sub-categories. This should be a quick and crude process

5. Duplicate, write and delete

Create a copy of your notes. Name it something like ‘DELETABLE’ so you don’t mix it up with your main notes.

You now begin writing. As you draw from your notes, cite the source with the number of the document, preceded by any unique character (in the image below, the footnote would contain the text “@3” to indicate source document number 3, for example, with the page number included if needed). The reason for the unique character will become clear in the next step.

Writing the final output

When you’ve included content from your notes, delete it from the copy. If you decide you no longer want or need to use an extract, delete it. As you proceed, the copy of your notes will get shorter and shorter.

In Ulysses, I have a second editor open with the deletable notes on the left, and the final output being written on the right.

6. Tidy up references

When you’ve finished writing, do a find and replace on each source reference (e.g. “@3”) with the full reference. Saving this until the end means you aren’t distracted with referencing when you should be writing. And using the unique character before the source number (e.g. “@”) means you aren’t searching through every number in the document.

As with the previous longer workflow, the flow in workflow is important. For effective results, do all of the above quickly. Any wait between collecting extracts from documents and writing means the broader context (information that you haven’t copied and pasted, but will be in your mind), is likely to fade.

Bonus: searching Google Scholar from your Mac

I use the excellent Alfred application for quick keyboard control of my computer. A custom search allows me to search Google Scholar from Alfred, by typing ‘scholar’ followed by the search term.

Custom search for Google Scholar using the Alfred MacOS application

Here is how custom searches work, and here is my custom search (if you have Alfred installed, clicking this should import to your library).

(Image credit)