importance of research in national development

Importance of Research in Development of Nation

9(7):3215-3218

Sam Higginbottom University of Agriculture, Technology and Sciences

Maulana Azad National Urdu University

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SCIENCE & ENGINEERING INDICATORS

Research and development: u.s. trends and international comparisons.

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Executive Summary

Key takeaways:

The U.S. research and experimental development (R&D) performance reached $667 billion in 2019 and an estimated $708 billion in 2020, reflecting increases in all sectors (business, higher education, the federal government, nonprofit organizations, and others) but mostly in the business sector.
Adjusted for inflation, growth of the U.S. R&D total averaged 3.8% annually from 2010 to 2019, well above the 2.2% growth of U.S. gross domestic product (GDP) over the same period.
The U.S. national R&D intensity (R&D-to-GDP ratio)—a key measure of R&D investment—has also increased, from the highs of recent years of 2.79% in 2016 and 2.95% in 2018 to 3.12% in 2019 and then to an estimated 3.39% in 2020.
The United States remains the global leader in R&D performance (28% of global R&D in 2019), followed by China ($526 billion, or 22% of global R&D). China’s current average annual rate of increase (2010–19), however, is almost double the U.S. rate.
Global R&D performance is concentrated in a few countries. The United States, China, Japan, Germany, South Korea, France, India, and the United Kingdom jointly accounted for about 75% of global R&D performance in 2019. The global concentration of R&D performance continues to shift from the United States and Europe to East-Southeast and South Asia.
Businesses are the predominant performers (75% in 2019) and funders (72%) of U.S. R&D. This sector performs most of U.S. R&D classified as experimental development, more than half of applied research, and a sizable (and increasing) share of basic research (32% in 2019).
Higher education institutions (12% in 2019) and the federal government (9%) are the second- and third-largest performers of U.S. R&D. Higher education institutions are the largest performers of basic research. Both have experienced declines in their shares of the U.S. performance total since 2010.
The federal government continues to be an important source of support for all R&D-performing sectors and remains the largest funder of basic research. The share of federally funded R&D, however, has been on a path of decline since 2010 (from 31% in 2010 to 20% in 2019), and the share of federally funded basic research has also consistently declined (from 52% in 2010 to 41% in 2019). These declines stem, in part, naturally from the large increases in R&D funding and performance by the business sector in recent years. This trend, however, indicates that federal funding has not kept up with the increases in other sectors.

Scientific discoveries, new technologies, and inventive applications of cutting-edge knowledge are essential for success in the competitive global economy and in addressing challenges and opportunities in diverse societal areas such as health, environment, and national security. Consequently, the strength of a country’s overall R&D enterprise—both the public and private sectors—is an important marker of current and future national economic advantage and of the prospects for societal improvements at the national and global levels.

The U.S. R&D enterprise comprises the R&D efforts of various sectors, including businesses, the federal government, nonfederal governments, higher education institutions, and nonprofit organizations. U.S. R&D performance totaled $667 billion in 2019 and an estimated $708 billion in 2020, compared to $407 billion in 2010. (All amounts are reported in current dollars, unless otherwise noted.) These most recent increases in the performance total ($50 billion or more each year in 2018 and 2019) are much larger than the average annual increases over the 2010–16 period ($19 billion each year). The main driver of these sizable increases is business R&D performance. Adjusted for inflation, average annual growth in the U.S. R&D total has outpaced average GDP growth for nearly two decades—3.8% compared to 2.2% average growth in GDP from 2010 to 2019, and 2.1% compared to 1.8% growth in GDP in the prior decade. As a result, the national R&D intensity has been on a rising path, from 2.79% in 2016 (a high point at the time) and 2.95% in 2018 to 3.12% in 2019 (the first time the U.S. exceeded 3.0%), and it is estimated to be 3.39% in 2020.

Globally, R&D expenditures have risen substantially since 2000 to an estimated $2.4 trillion in 2019—a more than threefold increase from $725 billion in 2000 (not adjusted for inflation). This expansion reflects the increasing importance of R&D in contributing to economic growth and competition as well as the significant role of R&D in addressing national and global challenges. Global R&D performance, however, is concentrated in a few countries. The United States leads the world’s nations in R&D performance with a 28% global share in 2019, followed by China (22%). Together with Japan (7%), Germany (6%), South Korea (4%), France (3%), India (2%), and the United Kingdom (2%), these top eight R&D-performing countries account for about 75% of the global total R&D. Other countries with sizable R&D performance are (in decreasing order) Russia, Taiwan, Italy, Brazil, Canada, Spain, Turkey, the Netherlands, and Australia.

In this report, a larger gap is evident between the U.S. and China R&D totals than reported in earlier editions. S cience and Engineering Indicators 2020 puts China’s R&D at 90% (and increasing) of the U.S. level in 2017. Updated data in this report show China’s 2019 R&D total at 79% of the U.S. level, and the 2017 comparison has been revised downward to 76%. These changes resulted primarily from a comprehensive update, released in May 2020, of the purchasing power parity ratios used to convert a country’s R&D expenditures to U.S. dollar expenditures as a common measure across all countries. These latest revisions had a more sizable effect on China than on other major R&D-performing countries.

Even so, the average annual rate of increase in China’s R&D total (10.6% from 2010–19) continues to greatly exceed that of the United States (5.6%) and the European Union (EU-27) (5.6%). China’s notable rise in R&D performance and the strong R&D performance by other Asian countries—Japan, South Korea, India, and Taiwan—are the drivers behind the sustained rise of R&D performance in East-Southeast and South Asia. The combined R&D performance across these Asian regions rose from 25% to 39% of the global total from 2000 to 2019, while the U.S. and EU-27 shares declined from 37% to 28% and from 22% to 18%, respectively. These broad trends in the global geography of R&D have been noted in earlier editions of this report and are reinforced by the latest data, indicating that the prospects for a further global shift remain strong.

In the United States, the business sector is the predominant force behind the R&D enterprise (75% of performance and 72% of funding of U.S. R&D in 2019). Since 2010, about 80% or more of the increase in the U.S. total R&D each year is attributable to businesses. Consequently, annual changes in business R&D greatly influence the overall U.S. R&D total. Business R&D performance is concentrated in five industries: chemicals manufacturing; computer and electronic products; transportation equipment; information services; and professional, scientific, and technical services. Businesses perform most of the R&D classified as experimental development (90% in 2019) and more than half of the applied research (58%). The business share of basic research has been increasing significantly in recent years (from 21% in 2010 to 32% in 2019).

The other sectors also make important contributions to the U.S. R&D enterprise but represent a fraction of the spending by the business sector. Higher education institutions and the federal government are the second- and third-largest performers of U.S. R&D. In 2019, higher education institutions performed 12% of the U.S. R&D total, over 60% of which was basic research. That same year, federal intramural R&D—through federal agencies and federally funded R&D centers—accounted for about 9% of the U.S. total R&D. Both, however, have experienced declines in their shares since 2010. (Higher education institutions performed 14%, and the federal government 13%, of U.S. total R&D in 2010.)

The federal government plays a larger role in R&D funding compared to performance and supports all sectors, particularly higher education institutions and federal intramural R&D. The federal government remains the largest source of support for the nation’s basic research, although the share has dropped from 52% in 2010 to 41% in 2019. The federal government is also a sizable supporter of the nation’s applied research—32% in 2019, compared to 56% of the support from the business sector. Despite its widespread role of funding, the share of federally funded R&D has been in decline for most of the past decade. In 2010, federal funding supported 31% of the total of U.S. R&D performance but dropped to 20% in 2019—and is estimated to drop further in 2020. This decline is, in part, a consequence of the large increases in R&D funding from the business sector in recent years, indicating that federal funding has not kept up with increases in other sectors.

Research in international development: bridging the gap between production and use

importance of research in national development

The recent awarding of the Nobel Prize to Abhijit Banerjee, Esther Duflo and Michael Kremer for their work in developing experimental research methods to assess the impact of development interventions might be seen as a testament to the important role of research in improving development practice. But the perceived value of research in informing policy and practice, in fact, comes and goes as a fad in international development – waxing and waning with the wider political climate.

In many donor countries, a renewed focus on ‘research and learning’ has been apparent since the global financial crisis, influenced by austerity measures and a sense of aid budgets being under attack . A range of donors and governments invest in research and evidence with the intention of delivering more effective aid programs or policy outcomes – putting in place wonky sounding policies and units. There’s DFID’s ‘ Evidence into Action Team ’, USAID’s Monitoring, Evaluation, Research and Learning Innovations (MERLIN) Program , DFAT’s Aid Evaluation Policy and Innovation Strategy , and South Africa’s Department of Planning, Monitoring and Evaluation ‘ Evidence and Knowledge Systems Branch ’.

This interest in research has also trickled down into aid programs. We increasingly see large aid programs supported by ‘learning or knowledge partners’ that undertake research alongside programming to inform it and capture its lessons – such as the Water for Women Fund , or the Australia Pacific Training Coalition .

Yet despite these good intentions, when the rubber hits the road in programming, it is frequently the ‘research and learning’ components that get trimmed first. In this sense, research and learning is a bit of an add on – something that’s nice to have but not necessary. Why is this the case when we know that it should be a valuable investment?

The general consensus on the importance of research masks some differences that – when we start to unpack – contribute to a disconnect between research production and research use . These differences have important implications for what we research, how we research, what questions and findings are valued, and so on. Without clarifying these differing views, the focus on ‘knowledge’ and ‘research’ is likely to be frustrated, as different actors working in support of this agenda confront the reality that they might actually be interested in quite distinct things. There are many ways in which this plays out but let’s just take three.

First, what is the purpose of research? Is it to spend taxpayer money more effectively? To provide a platform for citizen voices? To demonstrate impact? To understand complexity and make more informed decisions? None of these answers is wrong or necessarily mutually exclusive. But they speak to different objectives of why research might be valued in the first place.

Second, what methods are most useful? Often donors want firm answers or solutions with strong lines of causation between inputs and outputs. This can favour econometric methods, such as randomised control trials , which may be suitable in some instances. In others, qualitative methods, such as case studies or ethnographic methods, may be better placed to open up complexity and context specificity; or participatory action research may be used to give voice to the marginalised. While disciplinary battles are ongoing, the point is less that certain methods are better than others and more that they simply do different things and treat different things as relevant evidence.

Third, what research outputs are most important? For academics, professional bodies such as the Australian Research Council and others stipulate that academic publications ‘count’ more than commissioned reports. Yet these are often seen as dense and impractical by aid programs, donors or NGOs which want succinct, easy to comprehend products. Or, if you work with communities directly, you may not want text-based outputs at all but value other forms of ‘ reporting back ’.

These disconnects can mean both that research produced does not always ‘scratch the itch’ for practitioners and policymakers; and that practitioners and policymakers are not always well equipped to integrate the findings from research.

To address this disconnect, the Research for Development Impact (RDI) Network is funding the ‘ Enhancing Research Use in International Development Action Research Project ’, supporting research partners to unpack their internal political economy and ways of working to understand what constrains and enables better research use. The project brings together 12 organisations working in different parts of the international development sector – spanning donor agencies and intergovernmental organisations, NGOs, private sector consultancies and universities.

Over the coming six months, small groups of research advocates in each organisation will undertake their own internal research and trial initiatives to improve research use. While these are still being developed , they range from instituting research and learning strategies within NGOs, to demonstrating the value of research to senior government bureaucrats, to carving out time for investment in research within the cost recovery model of consulting firms, to facilitating greater interdisciplinary research and outreach with non-researchers within universities.

Researchers from La Trobe University’s Institute for Human Security and Social Change and Praxis Consultants will accompany the research advocates, documenting their learning about the obstacles and opportunities to better research use across the international development sector in Australia.

We’ll be sure to report back in the coming six months on what is being learned and how different research partners are addressing the challenge. We’d love to hear from others in the sector too on how they are trying to cultivate a smoother relationship between research and practice.

Education reform and the learning crisis in developing countries: a review
Building capacity for locally led development research
International development research impact: 10 key insights
The call for evidence-based development
Devpol Annual Appeal 2023

Lisa Denney

Lisa Denney is a senior research fellow and Deputy Director of the Institute for Human Security and Social Change at La Trobe University and a research associate with ODI.

The field of program evaluation has a body of literature explaining the different types of evaluation use and factors affecting the take up of evaluation findings.

Thanks for the post, Lisa. DT Global is pleased to be one of the organisations participating in this RDI Network initiative. It is a topic of great importance to us, practically and intellectually, and we recognise that we need to explore better ways to address the research/policy/practice intersect in what we do. We are looking forward to our own exploration and in particular the learning we can take from working with this positively diverse peer group.

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The Power of Partnerships: How to maximise the impact of research for development

Published on 30 March 2020

Part 1. Key Qualities of Research-Policy Partnerships

“The Impact Initiative has really helped explore some of the practical opportunities and approaches for research policy partnerships to make a stronger contribution to development policy and practice. This has important implications for UK funded researchers seeking lasting and beneficial impacts for developing countries.” Mark Claydon Smith, Deputy Director of International Development, UK Research Innovation (UKRI)

1.1 Background

Globally, increasing attention is being given to developing cutting-edge research in collaboration with those most likely to use or benefit from it. In July 2019, the Department for International Development (DFID), Economic and Social Research Council (ESRC), UK Research Innovation, UK Collaborative on Development Research and the Impact Initiative jointly convened a knowledge-exchange event in London . The event built on IDS Bulletin 50.1 ‘Exploring Research–Policy Partnerships in International Development’ , prepared by the Impact Initiative . It brought together a diverse group of more than 20 ESRC-DFID-funded researchers and practitioners from five countries, working on education, disability rights, child poverty, conflict and health reform, inviting them to reflect on their experiences of partnership for development that spanned research, policy and practice. Their case studies and a literature review of development partnership theory was the basis for a set of three inter-related partnership qualities. The case studies and commentaries below are featured in the above-mentioned IDS Bulletin .

“The ESRC-DFID Strategic Partnership has been successful in demonstrating what approaches [to partnership] are effective, being sharply focused on the combination of relevance and academic rigour with targeted, well-planned research uptake methods.” Diana Dalton, Former Deputy Director of DFID’s Research Evidence Division (Excerpt from the Foreword in IDS Bulletin 50.1)

1.2 Defining partnerships for policy change in development

Analysis of partnerships for international development has tended to focus on interactions between donors in the global North and national partners in Southern contexts, whether government, non-governmental organisations (NGOs) or research institutions. This is a crucial field of study, particularly as the movement to ‘decolonise development’ gains momentum. However, our focus was specifically on partnerships between research producers and users in international development settings, given this is an area that has received more limited attention. A framework for such partnerships aimed at achieving impact must consider the dynamics of real-world policy engagement. Useful here are concepts of mutual interdependence that maximise benefits for all. This means mutual commitment to the objectives of the collaboration and a strategy that is compatible with each actor’s mission, values and goals.

1.3 How do inter-sector partnerships maximise impact?

Various perspectives on how research influences policy and practice affect our understanding of the value and ideal design of research–policy partnerships. Concepts range from traditional linear relationships between new knowledge and policy innovation derived from the natural sciences; to complex interactive models intertwining science and society. Donors and researchers have largely settled on 3–4 core definitions or modes of impact. These definitions are useful when thinking about the impact of effective research–policy partnerships beyond academia.

Source: Georgalakis and Rose (2019: 2)

1.4 Is partnership between specialists enough?

Connections between research producers and users, and productive relationships between key individuals and institutions are important, but on their own are inadequate. Policymakers operate in environments full of uncertainty, making decisions based on ambiguous information. Advocates of evidenced-informed policy need to simplify complex problems and frame information to meet policymakers’ demands.

1.5 What are the key qualities of effective research–policy partnerships?

We have identified three inter-related qualities of effective partnerships, testing them with donors, researchers, and civil society and government partners.

Research–policy partnerships analytical framework

Source: Georgalakis and Rose (2019: 10)

Bounded mutuality

Key to successful partnerships is a common understanding of a given problem, and compatible values which underpin collaboration even if partners have different mandates. In research–policy partnerships, this occurs where evidence supply and demand converge. For example, a shared agenda for improving education or health systems may cement relations between policy advisors, who must deliver viable recommendations to decision makers, and practitioners and researchers hoping to inform programme design.

Nonetheless, partnerships are bounded by differences in organisational cultures, priorities and accountability. Partners seek to recognise these differences, sometimes compromising and playing to one another’s strengths. This pragmatic approach need not undermine core values. There are risks, but acknowledging that partners have different objectives and interests can be liberating, providing opportunities for learning and greater leverage.

The Shifting In/equality Dynamics in Ethiopia (SIDERA) project studied the effect of inter-communal violence on pastoralists in south-west Ethiopia. Divisions existed between the Ethiopian research team’s objective of producing rigorous research that empowered communities and the government’s assumptions about the underlying causes of conflict. The research team found that decision makers were not oblivious to the plight of the very poor pastoralist communities. But they assumed that the communities had brought problems on themselves and a state-led remedy was necessary. The team engaged regional officials through informal networks, changing their attitudes. One official remarked: ‘I used to see revenge as the sole reason for pastoralists conflicts but now I understand the main reason is economic.’

The team reflected on the challenges of South–South research and government partnerships, writing: “Government calls on researchers to contribute to national development on various occasions, presuming that “national priorities” and “reality” are uncontested, and that researchers will naturally subscribe to the state’s conceptualisations […] A serious and fruitful partnership between academics and policymakers needs to navigate this contradiction in view of reality and the objective of research”.

Source: Mulugeta et al . (2019: 112, 99–120)

Sustained interactivity

Sustained means building engagement from the outset of the research process and beyond. The most successful research partnerships continue after projects have ended. Partners see value in working together and look for opportunities for longer-term collaboration. Attempts at sustained interactivity may be politically charged. As well as formal structures, such as advisory groups, more iterative and evolving approaches to partnership are essential to building trust.

This approach recognises that research-policy processes are relational and messy, not technical or ordered. The conventional language of supply of evidence by researchers and demand for this evidence by policy actors masks the blurring of boundaries between research producers and users, and how learning and influence go both ways. Traditional policy cycle concepts have been discredited, and social and relational models of research engagement require ongoing interaction among a fluctuating group of partners and boundary partners outside the core partnership.

PRARI, a health-focused social policy research project in partnership with the Southern African Development Community (SADC), focused on regional approaches to reducing poverty. Researchers, public officials and NGOs collectively developed a toolkit to track pro-poor regional health policy. This deliberative process differed greatly from using non-academic partners as vehicles to disseminate results. The partnership pre-dated the project and continued after it ended. A SADC official described how the process helped them: ‘think more analytically about the purposes of […] regional-level action on health.’

Source: Yeates, Moeti and Luwabelwa (2019: 131, 121–142)

Policy adaptability

Adaptability refers to how partnerships identify key influencing spaces and re-frame evidence for specific audiences, adapting to changes in political or social contexts. Diversity among the active members of the partnership informs engagement strategies and even the research process itself, tailoring it to particular contexts. Collaboration with boundary partners, such as policy advocates, or other brokers, such as the media, is essential because they may incorporate evidence into their own campaigns and priorities. Intermediaries expand partnerships’ reach and legitimacy. The ability of research collaborations to provide coherent responses to perceived policy dilemmas resides in more than just the rigour of their research and the inclusivity of their partnership.

Using donors, implementation agencies and policy actors as brokers allows access to otherwise closed policy spaces. Adaptability is not just about fast and furious engagement in live policy processes. It is also necessary for longer-term agenda setting, which may mean deviating from envisaged pathways as new information affects how evidence is understood and used.

The DFID Education Team’s reflections on ESRC-DFID Raising Learning Outcomes projects in Uganda and India set out the central importance of embedding partnerships in-country. For research policy partnerships to achieve impact, they argued a need for ‘supercommunicators’. Depending on the context, this may be an NGO that can pilot innovations and deliver policy advocacy, as in the case of DFID’s collaboration with Ugandan NGO Mango Tree. The team discussed the dynamics of government–donor and government–researcher relations in effective knowledge exchange. The role of donors themselves as knowledge brokers in a research–policy partnership can be crucial.

Source: Hinton, Bronwin and Savage (2019: 43–64)

“Education researchers understand policy and policymakers have got their heads around research” Richard Clarke , DFID’s Director General for Policy, Research and Humanitarian

Part 2. Making research-policy partnerships work: Funders’ and researchers recommendations

At the partnerships framework launch, a diverse group of donors, ESRC-DFID-funded researchers, policy partners and civil society organisations discussed how to use and improve the framework, and its implications for their work. Their conclusions are summarised below.

2.1 Deploy the framework at the design stage of a research process to increase partnership viability

The inception phase of a research programme often entails stakeholder mapping and political economy analysis. The three qualities described above could be used to explore how the partnership relates to wider contextual analysis. Research partnerships are as much a product of social and political norms as the research area being addressed. An inclusive and participatory approach builds trust and mutual understanding around:

Exploiting differences in expertise and networks.
Clarifying roles and responsibilities.
Developing processes to continually exchange ideas.
Sustaining longer-term relations.
Framing evidence for policy audiences.
Identifying boundary partners.

Participants at the launch event agreed that research partnerships can be closely associated with co-production of research. In some cases participatory methodologies are relevant depending on the research objectives and approach. Meaningful engagement with partners may be viewed as an end in itself, empowering those who often lack a voice in international research studies and achieving ‘cognitive justice’. From this perspective, research is development, not for development. Partnership is a democratic tool that promotes equity and inclusivity.

Other valid and epistemically robust approaches to research also exist, including ones that envision a clearer division of labour between different partners in the pathways to impact process and a valid role for ‘independent research’. Such approaches still recognise the importance of engaging with policy actors throughout the research process including, for example, to frame relevant research questions, ensure appropriate interpretation of the data, and promote dissemination of the findings.

“If the question isn’t being asked in the right way, it’s unlikely to be impactful. We often think of the research as the key to impact, but it’s actually as much about whether anyone is asking the right question.” Mike Aaronson , Chair, Global Challenges Research Fund (GCRF)

2.2 Be honest about power dynamics and build trust

Donors and researchers with whom we shared the framework (presented above) agreed with the general view that equitable partnerships are desirable and morally imperative but, as the framework suggests, are not always a necessary pre-condition for innovative research and societal relevance. Tensions, trade-offs and compromises that occur when research and policy come together may still lead to progressive change. Trust is important, though, and some researchers urged caution in partnering with policy actors. Despite converging agendas, each partner is governed by a separate mandate. Other participants mentioned the importance of not underestimating researchers’ power. Government ministers might fear what research says and challenging dominant policy narratives can place enormous pressure on partnerships, so researchers need to be mindful of this in the presentation of their evidence.

“Knowledge is always partial and even rigorous social science is always contestable. It takes long term partnerships and mutual respect to reduce the risk that evidence will be thrown out for being perceived as irrelevant or not useful.” Melissa Leach , Director, Institute of Development Studies

“There are undoubtedly tensions between conducting rigorous research that can take 5-10 years, and the change in policy direction brought on by often much shorter political cycles.” Diana Dalton, Former Deputy Director of the Research and Evidence Division, DFID (Excerpt from the Foreword in IDS Bulletin 50.1)

“Evidence is political and who produces that evidence is political… How do you build from sustained interactivity to systemic change in how evidence is produced and engaged with?” Kate Newman , Head of Research, Evidence and Learning, Christian Aid

“In Kenya – too often, researchers want to mobilise persons with disabilities so they can collect information but without any plans for their further involvement in the research or dissemination.” Anderson Gitonga Kiraithev, United Disabled Persons of Kenya

2.3 Identify boundary partners and work with brokers

The movement to work across scientific disciplines and sectors acknowledges that tackling global challenges requires new forms of research–policy partnership. In global health, for example, there have been attempts to overcome barriers between researchers and policymakers by building multidisciplinary teams of academics, practitioners and government officials.

Although close relations between research and policy actors may be key to success, participants also discussed the importance of relationships with boundary partners and research intermediaries, such as the media, NGOs and civil society. These boundary partners can be mobilised at key moments and may be in a position to engage with audiences beyond the core partners’ reach. Their perceived legitimacy and ability to frame research in non-academic terms can raise awareness and build support for changes in policy direction.

Long-standing partnerships with policy actors who are often mid-level civil servants and advisors do not make it any less important to construct compelling policy-friendly narratives and identify key influencing opportunities in the political sphere. Also necessary are good timing, policy-relevant research, and the ability to contextualise research evidence for live policy issues and having individuals positioned appropriately. Mutual agendas and close working relationships do not automatically generate these qualities and thus deserve special attention.

“In our case, it was us the practitioners that went to the policymakers in a changing political context where research was just beginning to be engaged in democratic conversations. If the doors are closed, we have to use the windows to get into their offices. We managed to convince the Ministry of Women, Children and Youth to convene a meeting to engage the researchers and young people with the policymakers.” Anannia Admassu , Director, CHADET

2.4 Health-checking existing collaborations

Partnerships change over time: much is taken for granted or not discussed; initial strategies may not be revisited; partners may have very different perspectives on the partnership. Using the framework as part of project learning and adaptation, it is possible to explore these issues non-judgementally, to rekindle initial enthusiasm and optimise partnerships.

“We all have different power, so then the question is how we use our power in the most effective ways” Charlotte Watts , DFID Chief Scientific Advisor

“Timing is important, implementation is time bound. But we must not forget the issue of poor research, not all research is excellent. Recommendations are often not feasible, not based upon the real situation, or they can be far too general.’ Mushtaque Chowdhury , Vice Chair, BRAC

2.5 Enable mutuality, interactivity and adaptability

Research collaborations are a product of pre-existing relationships and power dynamics, shaped by theories of change, perceived mutual benefits, and a competitive funding environment in which there is a rush to secure solid partners deemed to be a good fit. The framework has implications for design and assessment of research calls. Support for interdisciplinarity is already strong, but more could be done to bring together ‘odd bedfellows’ who have little experience of working together or encourage prospective partners to bridge different networks and spheres of influence. Sustained interactivity requires support for iterative planning and ongoing communication; policy adaptability needs flexibility in planning and resourcing activities – this is as much about procurement as research strategy.

“Procurement departments in donor organisations need to take a good hard look at this partnerships framework. It has important lessons for how contracts are set up and managed” Louise Shaxson, Director of Digital Societies – ODI

“We’ve talked a lot about the politics of policy today, but not of the politics of research funding – this plays a big role in framing research partnerships… There is a danger to focusing on partnerships as bounded entities, rather than seeing research collaboration as part of a more complex knowledge ecosystem. If we want to make practice more equitable, we need to examine participation and make changes across the system.” Jude Fransman, Open University

Part 3. Conclusions

The framework for research–policy partnerships presented here is shaped by an understanding of evidence-into-policy processes as fundamentally social and interactive, underpinned by political context, social norms and power. All three partnership qualities: Bounded Mutuality, Sustained Interactivity and Policy Adaptability, are found in the case studies from the ESRC/DFID-funded research. Although there is evidence that these qualities have brought about desired changes in terms of evidence use, capacity, knowledge and relationships, the comparative strength of the qualities in specific partnerships also suggests that even more could be achieved if they were more deeply rooted.

We propose that using this framework at the research design stage could increase partnerships’ viability by taking into account the importance of mutuality, interactivity and policy adaptability from the outset. We hope others will seek to validate this concept with existing methodologies and literature, and apply variations of it to their own work.

To find out more about the framework and how to use it in your own work, go to IDS Bulletin 50.1: ‘Exploring Research–Policy Partnerships in International Development’

Cite this publication

Georgalakis, J. (2020) The Power of Partnerships: How to Maximise the Impact of Research for Development , IDS Digital Essay, Brighton: IDS

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The role of research in national development

Steve Maharey

Comments at a Council Meeting of the Royal Society of New Zealand. Science House, Wellington.

Introduction

Today I welcome the opportunity to speak to you about the role tertiary education, universities in particular, and the importance research has in the continued growth and development of our country. I also welcome the opportunity to respond to any questions you may have, or comments you may wish to make.

Importance of Research

A substantial and vital contribution to New Zealand’s research effort is made by tertiary providers and the role they play is crucial role in the creation and dissemination of knowledge.

The Labour Party's 1999 tertiary education manifesto, 'Nation Building: Tertiary Education and the Knowledge Society', was a vision of a strengthened tertiary education research community harnessed to make a significant contribution to the nation's sustainable development.

This government has strong and long-standing commitment to the development of a prosperous and confident knowledge-based society, which recognises, builds on, and values the special things that make New Zealand and New Zealanders what they are.

That kind of society can provide a sound basis for economic prosperity and social inclusion, but it won’t just happen. It will require a persistent, long-term, focus on quality, innovation, continuous improvement and entrepreneurship. As part of this, the people, the organisations, and the management and funding systems, in the tertiary sector need to stimulate, to facilitate, to demand, and to celebrate the highest standards of excellence in research.

Creating Knowledge

Why? Because creating and sharing knowledge is fundamental to growing New Zealand’s knowledge economy and society. We will only be successful in achieving our national goals when the relationship between research and innovation is fully developed.

The Tertiary Education Strategy sets a clear direction for strengthening research, knowledge creation and uptake for our knowledge society. The Strategy promotes the building of research capabilities and the quality of research as well as more effective linkages with business and other external stakeholders and greater alignment with national goals. High quality research will underpin knowledge creation and technology transfer that is linked to the achievement of New Zealand's national goals.

Our vision is for research to be at the forefront of our economic, social and environmental development. Elevating research to a position of high strategic importance within the tertiary education system is long overdue. Over the last decade tertiary education and research has not been made a priority in the way that it should have been.

Universities as leaders of research

This means our focus must be placed on universities as the key leaders along with crown research institutes of basic and strategic research in New Zealand.

Universities contain some of the best brains in the country. They are a wonderful local and national asset. Universities must take a leadership role in the pursuit of an innovative and highly skilled economy. They are also bridges between businesses and the knowledge that can make a difference to their success.

It is essential that we now reposition universities as the institutions to influence the direction and quality of our research and ensure that they become the elite institutions that they were intended to be.

We should be striving towards a research community, which is defined by increased global connectedness and networks with international research peers.

At the same time our tertiary system here in New Zealand should be dominated by collaboration and the sharing of knowledge between tertiary education organisations and other research providers, and the communities that they serve.

Linkages need to be encouraged between other tertiary providers, industry, and other research users. The tertiary sector must take responsibility for engaging effectively with these communities to disseminate new ideas, products and services that will be relevant.

Distinctive Contributions Paper

The TEC has recently released a consultation paper on the Distinctive Contributions of Tertiary Education Organisations. I welcome this paper because it focuses on significant questions about the broad role and place in the system of the various tertiary education organisations. These are questions that we need to be asking in order to recognise the importance of universities and polytechnics and their significant research and knowledge sharing roles.

I also encourage you to participate in the consultation process. It is through debate and engagement across a range of sectors that we will truly achieve a tertiary education system to be proud of.

In New Zealand, research is at the very core of what defines and distinguishes a university. Universities generate new knowledge. They should also have a key role in supporting communities and national development goals through being a repository of knowledge and expertise, questioning existing knowledge and being innovative.

It is essential that we now think about what particular features will characterise universities and how they will best perform in the future. We must ensure that we maintain a high and internationally credible threshold for our universities.

One of the key issues contained within the consultation paper is whether universities need to have a strong postgraduate profile with a considerable proportion of students in postgraduate research. One way of achieving this could be through the introduction of minimum benchmarks.

Another issue is the level to which our universities should be involved in providing sub-degree programmes. Currently the extent to which sub-degree courses are offered by universities varies extensively. In some locations sub-degree programmes act as bridging courses to familiarise learners with study in a university environment. In different locations other types of tertiary education organisations provide such courses. We need to consider to what extent universities should be funded to provide sub-degree programmes and how such programmes relate to our goals for universities within the tertiary sector.

There is also the question of whether universities should be bound by our legislative requirements. Currently legislation states that degrees must be taught be people mainly engaged in research. The question here is does this enable universities to be responsive to the needs of learners and provide relevant and innovative education.

These questions provide a good starting point for us to think about how we want to distinguish the role of universities from other tertiary education organisations. If we are to reposition universities we must work together to achieve a common understanding of the tertiary education system we are trying to build.

Tertiary education initiatives

The government has introduced a wide range of tertiary education initiatives to help build this system.

In the field of research alone, key initiatives have included the establishment of seven Centres of Research Excellence, the Building Research Capacity in the Social Sciences initiative and the Performance-Based Research Fund (PBRF).

All are central features of the Government's Tertiary Education Strategy 2002/2007.

Investment – Vote Research, Science and Technology

The Government is committed to building the quality and capacity of research. We will invest $212 million of new funding in research, science and technology over the next four years. The funding will increase the number of research partnerships with industry and support New Zealand researchers to participate in international collaboration initiatives.

In particular, this funding will enable research for industry to increase by $75 million over four years effectively supporting the strategic research underpinning the development of new products, services and processes. This commitment to research also means the development of a new International Opportunities Fund available to researchers who have the opportunity to participate in international research initiatives. This will help New Zealand to be a competitive player in the global market for scientific projects.

Advanced Network for Research and Education

My colleague Pete Hodgson has recently announced a new phase of the international super high speed research and education internet link - a super link between tertiary education and research organisations in New Zealand and overseas.

New Zealand Universities, Polytechnics, Wananga and Crown Research Institutes will be the first to benefit from the link.

The link, which will be know as the Advanced Network for Research and Education, will mean users can share information at speeds around 20,000 times faster than dial-up and 400 times faster than domestically available high speed internet. This will enable much greater collaboration between researchers and the multiplication of computing power through the linking of computers across New Zealand and around the globe.

We see this new link helping New Zealand participate at the cutting edge of research, development and education.

Performance-Based Research Fund

This government has also committed an additional $33 million into the PBRF over the next four years – another example of our continued investment in research and research capability. The PBRF is about achieving research excellence in the tertiary sector. It was designed to encourage and reward researchers and institutions at the top of their field.

You will be fully aware that the results of the 2003 Quality Evaluation of the Performance Based Research Fund have put the spotlight firmly on the significance of research. The results are a comprehensive assessment, for the first time of the pattern of quality academic research in New Zealand. Results show that the large numbers of researchers in New Zealand are at a high standard and well recognised internationally. They also reveal strength in many subject areas and in most of our universities, in such diverse areas as philosophy, earth sciences, history, and chemistry. In particular the longer established academic disciplines have extremely productive research cultures.

The 2003 Quality Evaluation provides a sound basis on which to measure improvement to quality and provides excellent information for tertiary education organisations themselves and for their students and stakeholders. It has also raised a number of interesting issues for both government and the tertiary sector about the role of universities and how to further enhance the quality of their research. Looking forward there are a number of opportunities for improvement. We will be working with the sector to support these opportunities.

Building Research Capability in the Social Sciences (BRCSS)

The government has made available $1.5 million per annum for five years to build social sciences capability in New Zealand by filling skills gaps, and producing a larger pool of more highly skilled social science graduates and researchers. This is the Building Research Capability in the Social Sciences initiative (known as BRCSS).

This will link future and emerging researchers to established high quality researchers and provide mentoring and structured development opportunities for emerging social scientists.

It also aims to increase the quality of the social sciences in New Zealand by building a critical mass of research capability and knowledge around focused areas and lift the relevance of social science research by supporting research into areas that underpin national development goals. This initiative has real potential to improve the ability of stakeholders such as industries, communities and the government to understand and tackle issues of national significance.

The TEC has just completed a process of assessing proposals for this new funding. I was pleased to hear that the proposals received not only reflected high quality, but also greater collaboration within the tertiary system and connection with other external stakeholders. These are key change messages of the Tertiary Education Strategy. The TEC is currently negotiating a contract for this funding and I expect to be able to make an announcement shortly on this.

Centres of Research Excellence

Having administered the initial phases, the Royal Society is uniquely aware of government’s commitment to Centres of Research Excellence (CoRE). We will be encouraging CoRE through enabling them to operate at arms length from Government. Ours will be a light-handed approach.

The role of the CoRE is to support leading edge, international-standard innovative research. The CoRE are expected to foster excellence and contribute to New Zealand's national goals – economic transformation, social development, Mäori development, environmental sustainability, infrastructure development, innovation.

The CoRE are expected to transfer the knowledge generated to those who will use it. I believe that the seven new CORE are set up to do that. They cover a range of disciplines – Molecular Ecology and Evolution, Molecular Biodiscovery, Advanced Materials and Nanotechnology, Advanced Bio-Protection Technologies, Mathematics and its Applications, Growth and Development, and Mäori Development and Advancement.

Like BRCSS, the CoRE, too, reflect this desired shift to stronger linkages with external stakeholders, and greater collaboration and rationalisation within the system. The CoRE are primarily, but not exclusively, inter-institutional research networks, with the researchers working together on a commonly agreed work programme. Being familiar with their first annual reports and business plans, I now look forward to future reports on how well they are achieving their objectives.

Growth and Innovation Pilots

In addition to the areas of research, the government is investing in $27 million over the next four years in Growth and Innovation Pilot Initiatives (Growth Pilots). The Growth Pilots have been introduced to help build the capability of Tertiary Education Organisations to underpin the development of the focus sectors for the Growth and Innovation Framework, namely biotechnology. design and information and communications technology. This initiative was established to assist the strengthening of tertiary sector links with business and to foster greater entrepreneurial culture across the system.

Collaborating for Efficiency

We are further supporting new ways of tertiary education organisations working together with business and industry. Objective 34 of the Tertiary Education Strategy seeks "Improved knowledge uptake through stronger links with those that apply new knowledge or commercialisation of knowledge products" with a focus on stronger connections between research providers and end-users. The question of how these stronger links can be encouraged and whether or not this encompasses a more active commercialisation role for TEIs is now an issue being explored by government agencies and other organisations.

A recent study undertaken by the TEC and Tertiary Advisory Monitoring Unit of the Ministry of Education through the Collaborating for Efficiency project suggests that the commercialisation levels of leading New Zealand TEIs are on par with comparable institutions overseas. The study also indicates that there is a significant capability gap between New Zealand TEIs in terms of their ability to pursue commercialisation opportunities.

Commercialisation is only one of the much wider suite of knowledge transfer activities such as the development of new courses and academic publishing in which TEIs are expected to engage. Changing the culture of TEIs is critical to enhancing this role and, in particular, ensuring that TEIs proactively embrace the idea that new knowledge generated should be utilized for the betterment of society.

In conclusion this government is creating a strong infrastructure and providing resources required to assist the New Zealand grow sustainably and participate on the international scene.

A strong tertiary sector and well-developed research infrastructure are just the entry stakes. We are living in turbulent times where economic competitiveness and sustainability are concerned. New Zealand needs to constantly innovate to reach our national goals.

We must not only learn how to learn better, but we must apply what we know in new ways. The basis of any knowledge society is constant innovation and new discoveries.

Localizing the economic impact of research and development

Fifty policy proposals for the trump administration and congress, stephen ezell and stephen ezell vice president, global innovation policy - the information technology and innovation foundation scott andes scott andes former fellow - brookings centennial scholar initiative.

December 7, 2016

109 min read

The following paper is the product of a joint research effort between the Brookings Institution’s Anne T. and Robert M. Bass Initiative on Innovation and Placemaking and the Information Technology and Innovation Foundation .

The investments government and businesses make in basic and applied research and development (R&D) plant the seeds for the technologies, products, firms, and industries of tomorrow. They contribute substantially to the fact that at least one-half of America’s economic growth can be attributed to scientific and technological innovation. 1 But the increased complexity of technological innovation as well as the growing strength of America’s economic competitors mean that it’s no longer enough to simply fund scientific and engineering research and hope it gets translated into commercial results. The U.S. government needs to expand federal support for research and, just as important, it needs to improve the efficiency of the process by which federally funded knowledge creation leads to U.S. innovation and jobs. 2

This report provides 50 policy actions the Trump administration and Congress can take to bolster America’s technology transfer, commercialization, and innovation capacity, from the local to the national level. These recommendations include:

Prioritize innovation districts within federal R&D outlays
Task federal laboratories with a local economic development mission
Create off-campus “microlabs” to provide a front door to labs
Support technology clusters by assessing and managing local-level federal R&D investments
Assess federal real estate holdings and reallocate physical research assets to innovation districts
Allow labs to repurpose a small portion of existing funds for timely local collaboration
Standardize research partnership contracts within cities
Create NIH regional pre-competitive consortia to address national health concerns
Allow DOE labs to engage in non-federal funding partnerships that do not require DOE approval
Dismantle funding silos to support regional collaboration
Incentivize cross-purpose funding based on the economic strength of cities
Expand the national Regional Innovation Program
Support the innovation potential of rural areas
Facilitate regional makerspaces
Introduce an “Open Commercialization Infrastructure Act”

Bolster institutions supporting tech transfer, commercialization, and innovation

Establish a core of 20 “manufacturing universities”
Complete the buildout of Manufacturing USA to 45 Institutes of Manufacturing Innovation (IMIs)
Create a National Engineering and Innovation Foundation
Create an Office of Innovation Review within the Office of Management and Budget
Create a network of acquisition-oriented DoD labs based in regional technology clusters
Establish manufacturing development facilities
Establish a foundation for the national energy laboratories

Expand technology transfer and commercialization-related programs and investments

Increase the importance of commercialization activities at federal labs/research institutes
Allocate a share of federal funding to promote technology transfer and commercialization
Develop a proof-of-concept, or “Phase Zero,” individual and institutional grant award program within major federal research agencies
Fund pilot programs supporting experimental approaches to technology transfer and commercialization
Support university-based technology accelerators/incubators to commercialize faculty and student research
Allow a share of SBIR/STTR awards to be used for commercialization activities
Increase the allocation of federal agencies’ SBIR project budgets to commercialization activities
Modify the criteria and composition of SBIR review panels to make commercialization potential a more prominent factor in funding decisions
Encourage engagement of intermediary organizations in supporting the development of startups
Expand the NSF I-Corps program to additional federal agencies
Authorize and extend the Lab-Corps program
Provide federal matching funds for state and regional technology transfer and commercialization efforts
Incentivize universities to focus more on commercialization activities
Establish stronger university entrepreneurship metrics
Expand the collaborative R&D tax credit to spur research collaboration between industry and universities and labs
Increase funding for cooperative industry/university research programs at universities
Establish an International Patent Consortium

Promote high-growth, tech-based entrepreneurship

Encourage student entrepreneurship
Help nascent high-growth startups secure needed capital
Establish an entrepreneur-in-residence program with NIH
Implement immigration policies that advantage high-skill talent
Implement a research investor’s visa

Stimulate private-sector innovation

Implement innovation vouchers
Incentivize “megafunds” around high-risk research and development
Increase R&D tax credit generosity
Ensure that small and medium-sized enterprises are familiar with available R&D tax credits
Implement an innovation box to spur enterprises’ efforts to commercialize technologies
Revise the tax code to support innovation by research-intensive, pre-revenue companies

Introduction

Innovation is key to increasing economic growth and wages in the moderate to long run. Yet innovation does not fall like “manna from heaven,” as economists once suggested. It is the product of intentional human action, and, to have more of it, we must enact public policies that connect research and development investments to firms and inventors in the communities where they are located.

After seven years of growth following the end of the Great Recession and after over 70 straight months of employment growth, there is a case to be made that the country has rebounded and the main thrust of economic policy should focus on those who have been left behind. But the reason so many Americans aren’t seeing their wages rise fast enough isn’t just because they’ve been left behind, it’s because the country as a whole isn’t moving ahead fast enough.

It’s certainly true the labor market has begun to inch closer to full employment (in fact, in December 2016 the unemployment rate dropped to 4.6 percent), but that’s far from a leading indicator of the health of the U.S. economy. For the reality is the economy still has a long way to go to return to its full potential. Employment growth in the 36 months following the trough of the recession was the slowest of the 11 post-World War II recoveries, and average productivity growth was twice as high in the four decades following World War II as it has been since the end of the Great Recession. 3 Brookings economists Martin Baily and Nicholas Montalbano describe the country’s productivity growth as “weak since 2004 and dismal since 2010.” 4 And as the Information Technology and Innovation Foundation (ITIF) reports, U.S. productivity growth over the last decade is the lowest since the government started recording the data in the late 1940s. 5 Yet if the United States could boost its productivity levels by even just one percentage point, it could make the economy $2.3 trillion bigger than it is otherwise projected to be in 10 years while shrinking the federal budget deficit by more than $400 billion. 6

America’s innovation economy exists at three levels: technological, industrial, and spatial.

Meanwhile, other countries are increasing their technological sophistication, capturing crowded international markets and pushing U.S. firms—and, by extension, U.S. workers—behind. And whereas once America’s leading technology competitors were largely isolated to Western Europe and Japan, today many developing nations are crafting innovation strategies designed to wrest leadership in advanced technology categories such as life sciences, clean energy, new materials, flexible electronics, computing and the internet, and advanced manufacturing. As evidence of these trends, the United States has run a trade deficit in advanced technology products every year since 2002; the cumulative deficit since 2010 is $580 billion. 7 Improving America’s capacity to innovate is a key step toward confronting these challenges.

America’s innovation economy exists at three levels: technological, industrial, and spatial. Much innovation occurs in particular technology areas, for example life science innovation funded by the National Institutes of Health (NIH), additive manufacturing supported by America Makes, and composite and lightweight materials supported by the Institute for Advanced Composites Manufacturing Innovation (IACMI) and the Lightweight Innovations for Tomorrow (LIFT) Institutes for Manufacturing Innovation, respectively. Innovation also occurs across firms in the same industries that collaborate to drive technology advancements (e.g., aerospace and automotive). For this reason, sector- and technology-based innovation policies and programs like Manufacturing USA’s Institutes of Manufacturing Innovation and the Advanced Research Projects Agency-Energy do an effective job targeting R&D dollars.

The spatial level of innovation includes not just hot spots like Silicon Valley; Austin, Texas; or Boston, but also scores of communities throughout the country in places like Chattanooga, Tenn.; Denver; Minneapolis; Mobile, Ala.; and Pittsburgh, Pa. which are intensively developing their innovation ecosystems at the regional level. Indeed, as ITIF has shown, innovation occurs in all of America’s 435 congressional districts. 8

This dispersion matters because regional technology clusters engender concentrated knowledge flows and spillovers, workers with specialized skills, and dense supply chains that improve firm productivity. Many R&D-intensive firms benefit from proximity to innovation resources such as universities and federal laboratories, and this closeness produces myriad “ecosystem” benefits. 9

This is particularly the case for knowledge spillovers—the ability of workers and firms to learn from one another without incurring costs. Recent research shows that the value of proximity for firms and workers to share ideas attenuates extremely quickly with distance. For example, Rosenthal and Strange find that, for software companies, the spillover benefits are 10 times greater when firms are within one mile of each other than when they are two and five miles apart, and by 10 miles there are no more within-city localization benefits. 10

In other words, to be effective, technology policy needs to focus not just on the first two levels, technology and industry, but also on the spatial—the regional. Thus, if America’s innovation economy is to function maximally, Washington needs to promulgate smart policies and initiatives that effectively work in concert at the city, regional, state, and national levels.

The central component of an effective national technology policy system is robust government funding of scientific and engineering research. But in that respect, the United States is failing. If the federal government invested as much in R&D today as a share of GDP as it did in 1983, we would be investing over $65 billion more per year. 11 Unfortunately, given budget and political constraints, the Trump administration and the forthcoming 115th Congress may find it difficult to significantly increase overall federal investment in science and technology. This despite the fact that doing so would be a wise investment, as economists estimate that a 1 percent increase in the U.S. R&D capital stock improves GDP by 0.13 percent. 12 But regardless, one thing on which America should be able to achieve bipartisan consensus is the need to find ways to increase the return on investment from existing resources and programs.

What follows are 50 policy recommendations President Trump and Congress can enact to improve the economic impact of existing resources (with some modest additional investments). Many of these recommendations could be added to the COMPETES-related reauthorization legislation currently being considered in both the House and Senate. The recommendations are divided into five categories: strengthening innovation districts and regional technology clusters; launching or extending institutions supporting America’s innovation economy; facilitating technology transfer and commercialization activities; promoting the formation of high-growth firms; and stimulating private-sector innovation. These recommendations are the output of a joint research effort between the Brookings Institution and ITIF.

Why and how federal R&D policy impacts local economies

The federal government invests $146 billion a year in R&D, and whether these dollars are directed to military bases, federal laboratories, universities, or small technology firms, they come to ground in communities and play a critical role in local technological capacity. Federal investments often drive high-skilled employment, fund local universities and hospitals, support high-tech entrepreneurs, and lead to exports from large companies—all of which bring outside dollars and jobs into a region.

To maximize and capture the benefits of R&D within regional economies, mayors, regional economic developers, and philanthropic and private-sector leaders should understand their federal research portfolio. Indeed, regions should take stock of their portfolios as they would any other asset class. To do so, regional leaders need to understand how the federal government funds research.

The government allocates R&D through federal agencies. While most agencies have some level of R&D budget, 84 percent of funding flow from the Department of Defense (DoD), the Department of Health and Human Services (DHHS), the Department of Energy (DoE), and the National Science Foundation (NSF). These agencies have different areas of investment and different funding vehicles that impact local economies.

The Department of Defense: With 49 percent of all federal R&D, DoD represents the largest federal investor in research. But DoD’s size is not the only reason the department matters for local communities. No other federal agency has such a quasi-fiduciary relationship with the commercial outcomes of its own R&D funding. DoD pursues basic and applied research through its dozens of labs located in 22 states and then transfers that research to firms that create products and services for the military. For regions, DoD funding often implies near-to-market engineering, computer science, and material research that local firms can utilize to meet defense and civilian needs. Yet research partnerships are conducted predominantly through large defense contractors and less often with small and medium-sized firms. 13

The Department of Health and Human Services : DHHS invests over $32 billion every year in research, the vast majority of which is conducted by and through the National Institutes of Health. The primary vehicle for NIH R&D is competitive grants: currently more than 80 percent of NIH funding is awarded through 50,000 grants to more than 300,000 researchers at universities, medical schools, and other research institutions. NIH research dollars touch every state and almost every city, and so the agency is ideally situated to play an important role in improving the return on investment of federal R&D at the local level. Also, because the lion’s share of investment comes from NIH’s grants to research universities and medical schools, as opposed to being spent at its own labs, NIH is in a unique position to incentivize commercialization across the U.S. university system. Finally, through its investments in teaching hospitals, NIH represents a critical employment driver for local communities.

The Department of Energy: DoE invests heavily in its 17 federal laboratories across the country. Though the labs are not located in dense regional technology clusters, they exist at the frontiers of science and often partner with universities, firms, and other research institutions to improve product development in industries such as aerospace, automobiles, battery storage, and information technology. Regions with companies and institutions that have DoE partnerships are often at the cutting edge of technology and are ideally situated for high-value technology exports.

The National Science Foundation: NSF is an independent federal agency that invests specifically in basic science and engineering and scientific education. Unlike other agencies that focus on specific missions (e.g., defense, health, energy), NSF has a broad mandate to fund discovery, learning, and the research infrastructure across scientific domains. Like NIH, the primary funding vehicle for NSF is its competitive grants that are distributed across the nation’s educational, training, and research institutions. NSF represents roughly one-quarter of federal investments in basic science at U.S. universities and colleges

By understanding what government funding flows to their respective regions and then how to leverage agencies’ distinct funding vehicles, leaders can better maximize the local influence of R&D.

Strengthen innovation districts and regional technology clusters

Regional technology clusters are a key driver of economic growth and should be viewed by the incoming administration and Congress as a critical component of innovation policy. Large-scale manufacturing clusters can be found in suburban research parks and key agriculture technology clusters in many rural areas throughout the United States.

In many technology sectors—particularly life sciences, software and digital design, and robotics—the geography of innovation is changing. Firms in these industries are now beginning to relocate research activities into employment-dense areas of cities (generally the downtowns and midtowns) to be in greater proximity to other firms, universities, and research labs. 14 Companies are also realizing that attracting and retaining talented workers increasingly means situating themselves in amenity-rich places where their workers want to live. The result has been a rise of “innovation districts,” defined by the Brookings Institution as “geographic areas where leading anchor institutions and companies cluster and connect with entrepreneurs. They are physically compact, transit- and broadband-accessible, and offer mixed-use housing, office, and retail. 15

Innovation districts are critical to the nation’s innovation capacity because they are home to some of the country’s leading universities, research labs, and high-value companies and they generate outsized economic output. For example, research universities located within employment-dense areas of cities outperform their rural and suburban peers in terms of number of patents, invention disclosures, licensing revenue, and startups per student. 16 But federal laboratories built in the shadow of World War II are often located far from firms and cities and have difficulty impacting regional economies. And too often cluster policy receives lip service from Washington, with little actual attention paid to how the federal government can accelerate the economic capacity of regional economies. Reconfiguring the federal government’s $146 billion annual R&D investment portfolio to achieve greater economic outcomes should therefore be a prime objective of national policy.

In order to strengthen innovation districts and other regional technology clusters, the next administration should work with Congress on the following goals:

1. Prioritize innovation districts within federal R&D outlays

Federal agencies that fund R&D should prioritize innovation districts because the density of corporate research centers and entrepreneurs increases the likelihood that research will lead to commercial outcomes. Moreover, Federally Funded R&D Centers (FFRDCs) and University Affiliated Research Centers (UARCs) should be assessed in part based on their proximity to corporate research and employment density, and federal grants in engineering, computer science, life sciences, and other similar fields should prioritize academic institutions located within innovation districts. Of course, the geographic location of research assets is not the ultimate determinant of economic impact, but co-location and density are important and should be a consideration for all funding agencies.

2. Task federal laboratories with a local economic development mission

Federal agencies such as DoD, DoE, DHHS, and the NSF that own and fund federal laboratories and FFRDCs should adopt an explicit mission to support the regional economies in which they are located. Many lab managers and agencies approach regional economic development as mutually exclusive from their core missions; this is especially true for weapons labs located within the Departments of Defense and Energy. But defense and weapons labs like Sandia and Los Alamos in New Mexico have successfully integrated regional economic development programs within their broader research objectives.

For example, both labs have partnered with the state of New Mexico on the New Mexico Small Business Assistance Program, which connects small businesses seeking technical assistance with lab researchers. 17 Every federal agency and federal lab should view regional economic development as part of its overarching mission. Moreover, increasing the technical capacity of the regions in which labs are located is mutually beneficial for the labs and the local economy. Moreover, given the mobility of the scientific workforce, creating homegrown talent helps labs address attrition.

3. Create off-campus “microlabs” to provide a front door to labs

Federal funding agencies, state governments, and regional consortia that utilize the lab system should work together to create and co-fund a number of off-campus, small-scale “microlabs”—co-located within or near universities or private-sector clusters—that would cultivate strategic alliances with regional innovation clusters. Microlabs would help overcome the problems that most labs are located outside of technology clusters and that most lab research occurs behind the walls of main campuses. These microlabs could take the form of additional joint research institutes or new facilities that allow access to lab expertise for untapped regional economic clusters. Accessible, off-campus lab space would also help labs engage with small to medium-sized enterprises (SMEs). The next administration should work to create microlabs and require state buy-in, or state governments or regional consortia could create voucher programs in concert with DoE and particular labs.

Several federal labs are already creating microlabs in cities; for example, Argonne National Laboratory has created office space in the Chicago Innovation Exchange, located on the University of Chicago’s Hyde Park campus. Another example is Cyclotron Road, a program of Lawrence Berkeley National Laboratory funded by the DOE EERE Advanced Manufacturing Office, which provides assistance to entrepreneurial researchers to advance technologies until they can succeed beyond the research lab. Cyclotron Road plays a pivotal role in providing entrepreneurs with technology development support (often leveraging technologies coming directly out of the Lawrence Berkeley laboratory) and helps them with identifying the most suitable business models, partners, and financing mechanisms for long-term impact. 18 Beyond external offices, microlabs can serve as funding gateways to align multiple public and private research dollars to meet industry needs.

4. Support technology clusters by assessing and managing local-level federal R&D investments

The $146 billion invested by the federal government in R&D takes place within specific institutions within communities, and these resources often dwarf the research investments and research-driven employment of non-federal companies and institutions. But federal research dollars do not necessarily pass through local political, civic, or private-sector leadership. As such, mayors, chambers of commerce, and philanthropies are often unaware of the innovation portfolio of their regions. The issue is most pronounced in large cities that can have over a billion dollars flowing annually from Washington. Without understanding their regional innovation portfolios, regions cannot coordinate and maximize federal investment for local economic growth.

To address this knowledge barrier, the federal government should help regions understand their research inflows by packaging their federal dollars by institution, areas of science, connections to global markets, and other data points. However, the federal government will never be able to whole cloth catalog what regions need to know about their innovation assets. Therefore, the government should also fund and advise regional innovation asset inventory and management assessments that are tailored to the specific economic development goals of individual communities.

5. Assess federal real estate holdings and reallocate physical research assets to innovation districts

The federal government owns billions of dollars’ worth of real estate that houses operations from post offices to federal laboratories. There is no national registry of these holdings and little information regarding their commercial value. Many of these physical operations were created before innovation districts and other technology clusters came into existence and are poorly placed to take advantage of the agglomeration benefits of cities.

The Trump administration should task the General Services Administration with identifying federally owned real estate parcels and strategically move research-intensive activities into existing federal buildings in cities. Agencies should also be able to register unused space within their own research institutions to identify and allocate vacant space for regional entrepreneurship and private-sector use. Congressional appropriation committees have traditionally been skeptical of allowing federal labs discretion on the use of space, but allowing lab managers to contract out unused space would increase the flexibility and regional responsiveness of the lab system. For example, Amtrak operates an office building in the heart of the Philadelphia innovation district, just a few blocks from Drexel University and the University of Pennsylvania. Amtrak does no research and extracts little benefit from being near major research universities; on the other hand, NIH, DoD, and NSF operate or fund numerous facilities that would greatly benefit from such a location. One mechanism for better allocating physical assets would be to create an intra-governmental auction whereby agencies could identify strategically located federal buildings and bid on these parcels. Agencies like Amtrak that don’t value their legacy locations in cities could sell such buildings to agencies that would benefit, creating a market dynamic within the federal government.

6. Allow labs to repurpose a small portion of existing funds for timely local collaboration

Increasing collaboration between regional universities and tech-based entrepreneurs and corporate partners requires greater flexibility in funding contracts. The next administration should allow federal labs to set aside a small amount—perhaps 5 percent—of fiscal year funding for unexpected research partnerships that may emerge throughout the year and that clearly align with lab mission and research goals. Labs would not be required to reserve these funds, nor be required to invest in regional partnerships, but interested labs would have the option. Similar repurposing rules should be encouraged for all federal funding opportunity announcements (FOAs) intended for federal labs.

7. Standardize research partnership contracts within cities

Virtually all innovation districts cluster numerous research institutions, but each one has its own rules relating to the commercialization of research. Cities should work to develop standardized partnership contracts that all research facilities can adopt to help researchers access the full spectrum of activity within a city. For example, in Philadelphia, the Wistar Institute—a National Cancer Institute-designated Cancer Center—has created a simple, standard contract for research partnerships that has been adopted by a number of medical schools in the city. The federal government should incentivize cities with multiple academic medical centers, federal labs, universities, and research institutions to develop standardized, simple research partnership agreements. Their development could either occur through pilot grants from the Economic Development Agency or directly through federal R&D funding agencies, such as NIH. The latter may be particularly effective given that in many cities research institutions with similar areas of expertise receive federal funding from the same federal agencies.

8. Create NIH regional pre-competitive consortia to address national health concerns

Given that over 80 percent of NIH R&D funding is allocated through its more than 50,000 grants across the country, the agency is ideally situated to support regional technology development. However, most NIH research grants don’t directly incentivize partnerships that lead to collaboration—particularly at the institutional-leadership level (e.g., for universities, the provost of research or president level). Rather, most collaboration around NIH grants occurs at the principal investigator level. While partnerships between researchers are important, more can be done to stimulate research-based partnerships between the public, civic, and private sectors.

To improve the commercial impact of research grants, the next administration should support regional pre-competitive consortia to address national health concerns. When applying for NIH grants, research institutions should be incentivized to coordinate with peers in their region. Making the consortia pre-competitive (i.e., uninvolved in patent development) will help to avoid intellectual property disputes and allow the efforts of its members to dovetail more closely with the academic missions of NIH research grants. One way to further incentivize partnerships would be to give grant proposals extra weight if multiple technology transfer offices, private-sector actors, and others within a city are designated as principal investigators. NIH already supports some pre-competitive consortia at the national level, such as the Accelerating Medicines Partnership and within its Clinical and Translational Science Awards, but doing so even more within technology clusters at the local level would enable research institutions to take advantage of proximity to form more long-lasting partnerships. 19

9. Allow DOE labs to engage in non-federal funding partnerships that do not require DOE approval

Currently, DoE must approve all non-DoE lab funding; this model is out of date, given that external funding is not trivial. For example, Oak Ridge National laboratory (ORNL) and Pacific Northwest National laboratory (PNNL) already receive 50 percent and 80 percent of their respective budgets from outside their DoE offices (though the majority of funding still comes from the federal government from agencies such as DoD). DoE should acknowledge that today’s multidisciplinary lab work requires varied funding sources. As labs increase their relevance to regional technology clusters, DoE should allow non-federal funding partnerships at lab managers’ discretion. Initially, DoE could specify a minimum amount of regional funding to be drawn from non-federal sources without its approval, and then gradually expand the minimum. 20

10. Dismantle funding silos to support regional collaboration

Stove-piped appropriations keep lab research projects unnecessarily compartmentalized and hinder lab managers from responding to regional demands. Labs should be funded to encourage broad, flexible engagements with numerous public- and private-sector actors. To this end, Congress and DoE should reorganize lab funding to mimic the financial design of Manufacturing USA (formerly known as the National Network for Manufacturing Innovation) or DoE’s energy hubs, institutions through which large, unencumbered appropriations are directed to complex, multidisciplinary regional technology and economic issues.

11. Incentivize cross-purpose funding based on the economic strength of cities

Like countries, cities and states specialize in technologies and industries. However, federal R&D funding agencies often ignore the potential interplay between seemingly discrete technologies, and doing so dampens the innovative potential of innovation districts. For example, Houston is an epicenter of the oil and gas and the health care industry, but little of the $160 million DHHS invests annually in the University of Texas MD Anderson Cancer Center considers what the health care field can learn from oil and gas. On the ground, researchers, medical professionals, and industry leaders in Houston recognized the potential for cross-pollination between these two areas of specialization and created “Pumps & Pipes,” an association of medical, energy, aerospace, and academic professions with the stated goal of problem solving through “using the other guy’s toolkit.” 21

Federal agencies should map the research and industrial comparative advantages of cities and create cross-agency funding opportunities in those areas. They should seek similar synergies with state-based technology-based economic development organizations, through which individual states focus on a few core technologies for economic development advantage.

12. Expand the national Regional Innovation Program

Regional innovation programs have proven a highly successful form of economic development for communities across the United States. 22 Programs such as the i6 Challenge and the Jobs and Innovation Accelerator Challenge have helped local, regional, and state entities leverage existing resources, spur regional collaboration, and support economic recovery and job creation in high-growth industries. The Regional Innovation Program operated by the Economic Development Administration identifies and supports regional innovation clusters, convenes relevant stakeholders, creates a cluster support framework, disseminates information, and provides targeted capital investments to spur economic growth. 23 There is great demand for this program from regions all around the nation, but in 2015 just $15 million in grants were awarded. More funding is needed, and more needs to be done to support regional innovation programs in the United States. Accordingly, the next administration and Congress should expand funding for the Regional Innovation Program to as much as $75 million. 24

13. Support the innovation potential of rural areas

While the vast majority of technology development, commercialization, and innovation occurs in cities and metropolitan regions, the innovation potential of more rural areas should not be neglected, both for these areas’ own economic growth prospects and for the contributions they can make to America’s innovation system. For example, consider the Natural Resources Research Institute (NRRI) located at the University of Minnesota Duluth. NRRI is a non-profit applied research organization, chartered by the Minnesota legislature, that works to develop and deliver the understanding and tools needed to better utilize Minnesota’s mineral, forest, energy, and water resources in a way that expands value-added and jobs in rural communities. 25 Other programs that support rural technology entrepreneurship and manufacturing include the Ben Franklin Technology Partners of Central and Northern Pennsylvania, which funds young companies and provides professional assistance in areas like prototype development and customer site visits. 26

But the next administration could support a network of institutes such as NRRI nationwide across more sectors, including aquaculture, agriculture, wind and water energy, and mining. One idea would be to have the U.S. Department of Agriculture (USDA) lead a major technology initiative around getting more value-added out of rural communities, whether from fish, fiber, food, wind, water, etc. Such a program, perhaps in coordination with the U.S. Department of Commerce’s Manufacturing Extension Partnership (MEP), could also build on and support existing rural manufacturing clusters, such as snowmobiles in northern Minnesota, wine in Western New York, or shipbuilding in Michigan. One aspect of this could be supporting rural Internet of Things projects, such as pilot programs for farms and vineyards. 27

14. Facilitate regional makerspaces

Makerspaces are community centers that combine manufacturing equipment and education for the purposes of enabling community members to design, prototype, and create manufactured works that couldn’t be created with the resources available to individuals working alone. 28 But well-staffed and programmed makerspaces are located disproportionately in large cities.

To more fully realize regional innovation potential, especially in manufacturing, the federal government should support a Public Library Makerspace grant program that enables the use of libraries not only for public education but also for economic development. Such a program would democratize the maker movement into communities that are traditional laggards in technology infrastructure, like broadband. This approach would make more widely available so-called lower-level innovation infrastructure (e.g., 3-D printing capability) that could seed innovations that ultimately feed into universities or federal labs. Another proposal to expand access to makerspaces is proposed legislation (in the House, H.R. 1622, in the Senate, S. 1705) that calls for a federal charter to launch a non-profit “National Fab Lab Network” (NFLN). 29 NFLN would act as a public-private partnership whose purpose is to facilitate the creation of a national network of fabrication labs and serve as a resource to assist stakeholders with their operations. The network would be comprised of local digital fabrication facilities providing community access to advanced manufacturing tools for learning skills, developing inventions, creating businesses, and producing personalized products. 30

15. Introduce an “Open Commercialization Infrastructure Act”

Another way to increase the use of America’s national R&D infrastructure would be through an Open Innovation Infrastructure Act, which would permit the private use of public-funded equipment and facilities—including universities, federal labs, and public libraries—for certain activities related to entrepreneurial education and training as well as for economic development and job creation. At present, buildings financed through tax-exempt bonds are not permitted to develop private programming within the facility, even though many private operations—such as incubators, accelerators, and training programs—that benefit entrepreneurs and others are important for broader economic development. For example, a small business that would like to use a 3-D printer in a makerspace at a public library to develop a commercial product is restricted from doing so. Such an Open Innovation Infrastructure Act would remove many such barriers.

Some worry the concept of innovation districts is just the latest urban fad, but there is nothing new about the economics of clusters and agglomeration; they have been studied by economists for over a century. Just as research parks defined much of the geography of innovation over the last half of the 20th century, innovation districts and other technology clusters are becoming emblematic of this century’s spatial science and technology research. The next administration should consider innovation districts and other regional clusters of technology generation (rural, suburban, and urban)—as strategic assets in the same vein as federal laboratories, military research facilities, and the university system. These institutions would not exist as they do without longstanding, substantial support from the federal government. The new president should add innovation districts to the list of national treasures that are supported and nurtured by the federal government, in partnership both with cities and with state technology-based economic development organizations.

In the private sector, firms need to innovate to respond to competition. Likewise, the competition for innovation leadership among nations has only grown fiercer. 31 Throughout its history, the United States has responded to international economic competition by chartering new institutions to bolster its innovation economy. For instance, the Morrill Act of 1862 chartered new universities in the agricultural and mechanical arts. 32 In the 1980s, the United States launched Sematech (a semiconductor research consortium) and the Manufacturing Extension Partnership in part as a response to heighted German and Japanese economic competition. The Obama administration launched Manufacturing USA in part to address the erosion of America’s industrial commons. Meanwhile, America’s global competitors have launched new institutions of their own, as documented in ITIF’s report, The Global Flourishing of National Innovation Foundations, which catalogued the efforts of almost 50 nations in chartering national innovation foundations and articulating national innovation strategies. 33 Yet the United States still lacks a national innovation foundation. Addressing that need and other proposals to expand the institutions underpinning America’s innovation economy are considered below.

16. Establish a core of 20 “manufacturing universities”

Across many American universities, the focus on engineering as a science has increasingly moved university engineering education away from a focus on real-world problem solving toward more abstract engineering questions, leaving university engineering departments more concerned with producing pure knowledge than working with industry to help it solve problems. To address this, the United Sates should designate a core of at least 20 “manufacturing universities” that revamp their engineering programs to focus more on manufacturing engineering and on work that is relevant to industry. 34 This effort would include more joint industry-university research projects, more student training that incorporates manufacturing experiences through co-ops or other programs, and a Ph.D. program focused on turning out more engineering graduates who work in industry.

At these manufacturing universities, criteria for faculty tenure would consider professors’ work with or in industry as much as their number of scholarly publications. In addition, these universities’ business schools would integrate closely with engineering and focus on manufacturing issues, including management of production. The schools would also appoint a chief manufacturing officer, as Georgia Tech has done, to oversee universities’ interdisciplinary manufacturing programs and ascertain how they can maximize their impact on regional economic development. A good model for these manufacturing universities is the Olin College of Engineering in Massachusetts, which reimagined engineering education and curricula to prepare students “to become exemplary engineering innovators who recognize needs, design solutions, and engage in creative enterprises for the good of the world.” Olin’s students now launch more startups per graduate than even MIT.

The Manufacturing Universities Act seeks to establish a competitive grant program for universities that propose to revamp their engineering programs and to focus much more on manufacturing engineering and in particular work that is more relevant to industry. Academic institutions receiving a manufacturing university designation would be eligible for an annual award of up to $5 million for up to four years. 35 The Manufacturing Universities Act of 2015 was incorporated into the 2017 National Defense Authorization Act (NDAA) passed by the Senate in June 2016, but it was not included in the House’s version of the NDAA. Ideally, the conference version of the NDAA that comes out of committee would include the manufacturing universities legislative text. The next administration should make implementation of the manufacturing universities legislation a top priority, directing relevant agencies (notably NSF and the National Institute of Standards and Technology) to implement it swiftly and effectively.

17. Complete the buildout of Manufacturing USA to 45 Institutes of Manufacturing Innovation (IMIs)

Manufacturing USA, launched in 2013 as the National Network for Manufacturing Innovation by the Obama administration and endorsed on a bipartisan basis by Congress through the Revitalizing American Manufacturing Innovation Act, has played a pivotal role in revitalizing America’s industrial commons and helping ensure U.S. leadership across a range of advanced manufacturing process and product technologies. 36 Thus far, nine Institutes of Manufacturing Innovation have been launched, focused on additive manufacturing, digital manufacturing and design innovation, lightweight and modern metals, power electronics, advanced composites, integrated photonics, flexible hybrid electronics, clean energy smart manufacturing, and revolutionary fibers and textiles.

As of December 2016, six more IMIs are under development, including two in a competition to be overseen by DoE (focused on Chemical Process Intensification and Sustainable Manufacturing), two expected to be led by the Department of Defense (focused on Regenerative Medicine and Assistive and Soft Robotics), and two more open topic competitions to be spearheaded by the Department of Commerce. The Obama administration has articulated a vision for a total of 45 IMIs. The Trump administration should collaborate with Congress to provide funding and authorization to build out the 45-institute network of industry-led Manufacturing USA institutes.

18. Create a National Engineering and Innovation Foundation

Science-based discoveries without a commercialization component mute the potential impact of R&D. Connecting discovery with production requires engineering-based innovation, an appropriable activity through which U.S. establishments can add and capture value. 37 And this requires the United States getting better at generating pathways that turn science into U.S.-made high-technology products. Engineering is not science; the two have distinctly different purposes. As Sridhar Kota, formerly assistant director for advanced manufacturing at the Office of Science and Technology Policy, writes, “Science is about analysis and discovery and dissemination of knowledge. Engineering is about synthesis and invention and turning ideas into reality through a process called innovation and through translational research and entrepreneurship.” 38 Both science and engineering are instrumental if American firms are to introduce successful innovations over the long term.

Yet the United States invests significantly more in scientific research than it does in engineering. For example, of the total federal research investments in science and engineering in 2008, approximately 14 percent were allocated to engineering development and the remainder to other scientific fields. 39 NSF invests roughly one-tenth on engineering education as it does on science and mathematics education.

Accordingly, it’s time to raise the profile of engineering within our national innovation system. While NSF supports phenomenal work, its primary mission is funding scientific research while its engineering support programs get short shrift. Therefore, the next administration should work with Congress to create a National Engineering and Innovation Foundation as a separate entity operating alongside the National Science Foundation. 40 The new National Engineering and Innovation Foundation would consolidate the current Engineering Directorate within NSF including the ERC and I/UCRC programs, the tech commercialization parts of the National Institute of Standards and Technology (e.g., including MEP and the Advanced Manufacturing Technology Consortia (AMTech) program), DoD’s Manufacturing Technology (ManTech) program, and DoE’s Advanced Manufacturing office into a single entity with an engineering and innovation focus.

19. Create an Office of Innovation Review within the Office of Management and Budget

Because federal agencies often propose regulations with little consideration given to their effect on innovation, Congress should task the Office of Management and Budget’s Office of Information and Regulatory Affairs with creating an Office of Innovation Review (OIR) to review proposed regulations to determine their effect not just on costs in the short term but also on innovation over the long term. OIR would have the specific mission of being the “innovation champion” within agency rule-making processes. 41 It would have authority to push agencies to either affirmatively promote innovation or to achieve a particular regula¨tory objective in a manner least damaging to innova¨tion. OIR would be authorized to propose new agency actions and to respond to existing ones, and could incorporate a “competitiveness screen” in its review of federal regulations that affect globally traded industries.

20. Create a network of acquisition-oriented DoD labs based in regional technology clusters

The Department of Defense is uniquely positioned to commercialize research from its over $70 billion of R&D investments annually because it invests with the intent of deploying R&D outcomes throughout its own operations. According to its own accounting, between 2000 and 2014 DoD paid private companies that had licensing arrangements with its labs $3.4 billion for military technology; during the same period, companies that licensed technology from DoD labs generated $20 billion in sales outside of DoD. 42 This is a positive outcome, because it suggests that even the licensing arrangements companies have with DoD that don’t end in procurement still generate broader economic impact. In other words, companies pay to use technology generated by DoD and then develop products and services around the technological discovery to meet defense as well as market needs.

This continuous cycle of development well positions the department’s R&D to impact the broader economy in general and regional clusters in particular. But the same report finds that the majority of licensing agreements are signed with a few large defense contractors, leaving many regions without such firms out of the game. 43 Moreover, as DoD seeks to acquire technologies beyond munitions, moving into areas such as software, material science, autonomous systems and vehicles, energy, and medical devices, it will need a broader scope of suppliers.

To increase the breadth of R&D-based procurement, the Trump administration should create a network of applied defense R&D facilities around regional technology clusters. 44 The network would be similar to Manufacturing USA but with numerous smaller centers that are highly focused around the virtuous cycle of firms working with DoD labs and creating products and services that meet military needs. DoD is already moving in this direction, in accordance with Secretary of Defense Ash Carter’s Third Offset strategy, which seeks to counter declining force sizes with the development of novel capabilities and concepts. 45 For example, the Defense Innovation Unit Experimental (DIUx) seeks to create bridges between the Pentagon and the commercial technology sector. It currently has locations in Silicon Valley, Boston, and Austin, Texas; last year it awarded 12 contracts worth $36.3 million. While DIUx is a good start, its budget is tiny compared to the changing demands for new technologies within the military. Accordingly, DoD should invest $500 million to develop 50 similar centers as technology platforms across the country. Given that DoD already operates dozens of laboratories across 22 states, in many cases existing labs could shift their research and commercialization strategies to better align with adjacent technology clusters. In other regions, the department would need to develop new assets.

21. Establish manufacturing development facilities

Oak Ridge National Laboratory in Tennessee operates the Department of Energy’s first manufacturing development facility (MDF), which focuses on assisting industry’s adoption of new manufacturing technologies that can lower production costs, speed time to market, and reduce energy consumption in manufacturing processes. The facility focuses on additive manufacturing (3D printing), carbon fiber and other composites, and new battery technologies and is also the location of the Institute for Advanced Composites Manufacturing Innovation, part of Manufacturing USA. 46 The MDF helps bridge basic research at Oak Ridge and the real-time commercial needs of industry. Also, because East Tennessee has historical technical strengths in composites and advanced manufacturing, the MDF is strategically positioned to amplify the region’s economy.

The next administration should create 20 additional manufacturing development facilities to bring to market the fruits of scientific and technical research discoveries made by federal laboratories run by DoD, DHHS, DoE, and other federal agencies. It is important to note that MDFs are not the same thing as manufacturing institutes; rather, they are specific lab departments, offices, or facilities that are either currently located behind the fence or new facilities that would traditionally be developed behind the fence. Therefore, relocating these assets would require less funding than developing new manufacturing institutes (which are also intended to meet different needs).

22. Establish a foundation for the national energy laboratories

A number of agencies—including USDA, the Department of Veterans Affairs, the Department of the Interior, NIH, the Food and Drug Administration, and DoD—have established foundations to provide them with more flexibility to accomplish their missions. These foundations are legally chartered to accept donations from alumni inventors and scientists, philanthropists, and high-wealth individuals to support research efforts in ways that federal and private funding alone cannot. Foundations are often highly capitalized, for example the foundation for the National Institutes of Health has a $100 million endowment and a $500,000 operating budget. Based off of the success of existing research foundations, the next administration should create a foundation for the national energy laboratories. Because many philanthropies are forbidden by their charters to fund overhead, and the federal lab system is congressionally mandated to charge overhead from donations, a foundation for the national energy labs could serve as a funding intermediary between the civic sector and federal labs. The foundation could also endow research chairs around areas of national interest, help support moving translational research to market, and even fund and take equity in startups.

If the United States wishes to keep pace in the increasingly intense competition for global innovation leadership, it will need to evaluate its existing base of institutions underpinning America’s innovation system and consider new ones that can play important roles in bolstering the country’s levels of technology transfer, commercialization, and innovation. In launching the Manufacturing USA network of Institutes of Manufacturing Innovation, the United States has shown a commendable ability to do so, but it alone is not enough and continued institutional innovation will be needed going forward.

Publicly funded research institutions—federal laboratories, universities, academic hospitals, military and space laboratories, and non-profit research centers—represent core assets in the U.S. innovation system. Not only do these institutions push the frontiers of science, they are anchors of regional economic growth. While the charters of many of these facilities are related to mission-oriented, non-economic public priorities, their activities are deeply tied to the future of the American economy. Strong R&D in defense supports aerospace and materials science industries, clean energy research promotes clean technologies such as wind turbines and new batteries, and scientific advances in public health lead to drug discoveries and health information technology platforms, to name but a few examples. These institutions also train and employ current and future generations of scientists and engineers. However, realizing the economic potential of R&D activities is no sure thing. In order for university and lab research to reach the market, these institutions must be supported by strong policies, incentives, and funding streams that collectively make commercialization a priority.

To date, the efficacy of technology transfer mechanisms at federal laboratories and federally supported universities is mixed. 47 Some labs and universities have elevated the importance of technology transfer and put in place creative and impactful policies to promote commercialization in their economic regions. For example, in 2015 the Oak Ridge National Laboratory established an innovation voucher program to enable technical assistance to small and medium-sized manufacturers in the state. And universities such as MIT, Pepperdine, and Carnegie Mellon have strong track records of implementing flexible, business-friendly technology transfer agreements. Unfortunately, as the report Innovation U 2.0: Reinventing University Roles in a Knowledge Economy documents, there is little consistency and insufficient adoption of best practices across universities, federal laboratories, and funding agencies. 48

As the largest funder of federal laboratory and university research, the executive branch has an enormous opportunity to incentivize the commercialization of research. President Obama’s Lab-to-Market Initiative was a step in the right direction, but there is more to be done. In order to unleash the full economic power of federally funded universities and laboratories, the incoming administration should work with Congress in the following areas:

23. Increase the importance of commercialization activities at federal labs/research institutes

America’s federal laboratories are insufficiently incentivized to invest time, energy, and resources in facilitating technology transfer, in large part because technology transfer is not even one of the eight main criteria in the Performance Evaluation and Management Plan (PEMP), a kind of annual report card for the federal labs. 49 Rather, PEMP treats successful transfers of technology to market as an afterthought. Elevating this important function to its own category would have significant impacts on the management of the labs and help to reverse the buildup of decades of skepticism and intransigence toward commercialization. Adding a ninth category to the PEMP for “Technology Impact” would create a mechanism to evaluate the economic impact of lab-developed technology, creating a stronger incentive for lab managers to focus on market implementation of valuable government intellectual property assets and technical capabilities. 50

24. Allocate a share of federal funding to promote technology transfer and commercialization

The current federal system for funding research pays little attention to the commercialization of technology, and is based instead on the linear model of research that assumes that basic research gets easily translated into commercial activity. Yet the reality is that the innovation process is choked with barriers, including institutional inertia, coordination and communication challenges, and lack of funding for proof of concept research and other “valley of death” activities. Accordingly, federal policy should explicitly address this challenge and allocate more funding toward commercialization activities.

The incoming administration should work with Congress to establish an automatic set-aside program that takes a modest percentage of federal research budgets and allocates this money to technology commercialization activities. 51 For instance, the Information Technology and Innovation Foundation has suggested that Congress allocate 0.15 percent of agency research budgets (about $110 million per year) to fund university, federal laboratory, and state government technology commercialization and innovation efforts. 52

Such funds could be used to provide “commercialization capacity-building grants” to organizations pursuing specific innovative initiatives to improve an institution’s capacity to commercialize faculty research as well as “commercialization accelerator grants” to support institutions of higher education pursuing initiatives that allow faculty to directly commercialize research. 53 These funds could also support a variety of different initiatives, including mentoring programs for researcher entrepreneurs, student entrepreneurship clubs and entrepreneurship curricula, industry outreach programs, and seed grants for researchers to develop commercialization plans.

In addition, the incoming administration should broaden beyond universities the number of institutions that are eligible for commercialization funds. At the state and regional levels many organizations outside the university play a critical role in assisting faculty and students in the commercialization of research. Institutions like BioCrossroads in Indiana and TEDCO in Maryland offer mentorship, funding, and access to customers for research entrepreneurs. These organizations should be eligible for federal research dollars specifically aimed at technology transfer.

25. Develop a proof-of-concept, or “Phase Zero,” individual and institutional grant award program within major federal research agencies

The Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs support innovation, but both SBIR and STTR approval are a high bar for early-stage companies. There is often insufficient funding available at universities (or from other sources) to push nascent technologies to the point where these companies are positioned to receive an SBIR or STTR grant. The problem is essentially that researchers and universities do not have the resources available to support the proof-of-concept work, market analysis, and mentoring needed to translate ideas and nascent technologies from the university laboratory into a commercial product.

A national “Phase Zero” proof-of-concept program would not only help more projects cross the “valley of death,” but would also help enhance the infrastructure (e.g., expertise, personnel, support, small business, and venture capital engagement) and facilitate the cultural change necessary for universities, federal laboratories, and other non-profit research organizations to support commercialization activities.

America’s competitors have recognized the need for such an instrument. For instance, the European Research Council (ERC) has announced a new proof-of-concept funding initiative to help bridge the gap between ERC-funded research and the earliest stage of marketable innovations. 54 These awards can be as high as $215,000 for individual researchers, in total, equivalent to about 1 percent of ERC’s budget. 55 Here in the United States, the Wallace H. Coulter Foundation has established Translational Research (for individual researchers) and Translational Partnership (for institutions) Awards for proof-of-concept research in biomedical engineering. 56 The Translational Research Awards are made in amounts of approximately $100,000 per year, while the university grants have a duration of five years at over $500,000 per year.

Similarly, NIH’s Research Evaluation and Commercialization Hub (REACH) program fosters the development of therapeutics, preventatives, diagnostics, devices, and tools that address diseases within NIH’s mission in a manner consistent with business case development. The work supported by the REACH program may include technical validation, market research, clarification of intellectual property position and strategy, and investigation of commercial or business opportunities. 57 Finally, a number of states, such as Kentucky and Louisiana, have developed Phase Zero grants to help firms apply for SBIR grants and support early proof-of-concept research. One way for the federal government to implement such a proof-of-concept-program would be through a grant program for states that agree to match the funds dollar-for-dollar.

26. Fund pilot programs supporting experimental approaches to technology transfer and commercialization

A number of organizations throughout the United States are experimenting with novel approaches to bolster technology transfer from universities and federal laboratories to industry and to accelerate the commercialization of university-developed technologies. For example, the Applied Physics Laboratory (APL) at Johns Hopkins University is considering an Innovation Launch Program that would leverage a $110,000 investment to support 10 entrepreneurial student teams in commercializing intellectual property developed at APL.

Congress could support these types of novel approaches by providing $5 million annually to fund experimental programs exploring new approaches to university and federal laboratory technology transfer programs. This effort could be funded either through one central agency or through the respective R&D mission agencies and managed by the Department of Commerce’s Office of Innovation and Entrepreneurship. Organizations would apply for the grants, and winning proposals would be selected on criteria such as innovative approach to demonstrating a new model, recent documented success of the program, and willingness to publicly disclose best practices learned from the programs. The effort could be thought of as a “Commercialization Experiments Program.”

27. Support university-based technology accelerators/incubators to commercialize faculty and student research

As universities try to develop new pathways to commercialize research, the federal government can do more to support university efforts to promote research-based entrepreneurs. For example, Stanford has created StartX, Johns Hopkins has created Fast Forward, and MIT has created the Deshpande Center as technology accelerators and incubators that assist university students and faculty in establishing entrepreneurial ventures that seek to move university-developed discoveries and inventions into the commercial sector. These programs and co-working spaces provide a range of support services that may include physical space, legal advice on incorporation and preferred treatment of intellectual property, connections to sources of capital, and a range of business, technical, and potential customer contacts important to launching a new business. While these types of accelerators are increasingly proliferating throughout the U.S. university system, additional funding could support development into a wider set of universities and colleges, particularly those that don’t have large endowments or wealthy alumni to self-fund such programs.

28. Allow a share of SBIR/STTR awards to be used for commercialization activities

Billed as “America’s Seed Fund,” the Small Business Innovation Research and Small Business Technology Transfer programs provide over $2 billion per year to qualified small businesses to fund R&D activities through multiple federal agencies. While SBIR accounts for only 3.4 percent of federal extramural research funding, the program punches well above its weight, with as much as 22 percent of America’s top innovations (as reflected by studies of previous winners of R&D Magazine’s R&D 100 innovation awards) coming from companies that received SBIR grants at some point in their history. 58

Yet SBIR’s impact could be even greater, particularly if some facets of the program were geared slightly more strongly toward commercialization. In particular, awardees are currently prohibited from utilizing grant money to fund critical commercialization activities related to building product or service prototypes, acquiring commercial customers, attracting private capital, or accelerating market entry. These activities cover the gamut of important commercial activities, including intellectual property development and prosecution, marketing and market development, and the recruitment of key team members associated with customer acquisition (e.g., marketing and sales)—all critical to commercialization. 59

SBIR awardees should be permitted to expend up to 5 percent of their award funds for commercialization-oriented activities. For Phase 1 awardees this expansion would include a narrow set of allowable activities (such as market validation), while for Phase 2 awardees, who are closer to market, a broader set of allowable activities would include market validation, intellectual property protection, business model development, and market research. The Support Startup Businesses Act (S. 2751) has a similar goal; it would allow SBIR grantees to devote up to $30,000 for commercialization expenses. 60

29. Increase the allocation of federal agencies’ SBIR project budgets to commercialization activities

In addition to permitting SBIR awardees to increase the share of funds they can allocate to commercialization-oriented activities, the federal agencies making SBIR awards should do the same. Though some participating agencies offer SBIR/STTR award “supplements” to awardees to select their own vendors (or offer commercialization programs organized by outside vendors), these are capped at $5,000 per year per awardee for commercialization activities and cannot be used to fund company employees specifically devoted to these activities.

Accordingly, SBIR/STTR-sponsoring federal agencies should increase the share of SBIR project funds that can be allocated toward commercialization. Agencies should be encouraged or required to evaluate the performance of outside vendors in order to ensure quality, and to match outside vendors to SBIR awardees in order to ensure an appropriate fit with respect to sector, stage, region, and other applicable factors. 61 Additionally, agencies should implement their current authority to allow each individual SBIR awardee to choose outside vendors that provide such services to that awardee. This proposal has been incorporated into the SBIR and STTR Reauthorization and Improvement Act of 2016.

30. Modify the criteria and composition of SBIR review panels to make commercialization potential a more prominent factor in funding decisions

All participating agencies consider commercialization potential and plans in their grant funding decisions. However, agencies differ in the weight or emphasis they place on commercialization. In particular, some agencies, such as NASA and DoD, intend to use the commercial products that flow from their own R&D. In agencies where the intended customers are external, a greater portion of the merit review evaluation criteria and scoring should include commercialization factors, such as the company’s understanding of market opportunity, product development timelines, and needed resources. 62 Further, to evaluate these important criteria, the composition of SBIR/STIR review panels at these agencies should include industry experts, investors with relevant industry or technology expertise, and/or representatives from commercialization intermediary organizations or venture development organizations.

31. Encourage engagement of intermediary organizations in supporting the development of startups

While agencies have expanded their commercialization programs through funding services offered by third-party organizations, federal R&D funding agencies should fund and encourage the engagement of science- and technology-oriented intermediary organizations that have been effective in translating science-based plans into commercial opportunities in regions around the country. As a key pillar of economic development, these organizations could more effectively leverage federal funding, engage local resources in various functions, and generate local interest amongst awardees. Therefore, funding agencies should systematically map intermediary organizations within technology clusters and support startup grant awardees in connecting with these institutions. Moreover, these organizations should be eligible for federal R&D funding that relates to technology commercialization.

SBIR/STTR investments that are coupled with guidance from regional intermediaries experienced in helping innovators have greater likelihood for success and long-term stability. 63 Currently, ad hoc consultations occur across the board, but this proposal would help fund and create formal pathways linking the many efforts that have grown in the past few years to the program itself and add a level of higher-touch support to companies than federal agencies are able to provide.

32. Expand the NSF I-Corps program to additional federal agencies

The National Science Foundation’s I-Corps program has successfully helped scientists and researchers translate federally funded technologies into marketable products and services. I-Corps has three distinct components: teams, nodes, and sites. Teams are composed of the principal investigator(s), an entrepreneurial lead, and a mentor. Nodes serve as hubs for education, infrastructure, and research that engage academic scientists and engineers in innovation. Sites are academic institutions that catalyze the engagement of multiple local teams in technology transition and strengthen local innovation. 64

NIH and DoE have created similar programs, but current funding levels are too low to truly impact startup activity across the vast panoply of federal funding agencies. The scale of NSF’s I-Corps program should be increased across the federal government so that it can be made available to scientists and engineers at all federal agencies. For example, the American Innovators and Entrepreneurs Act would provide additional funding for the I-Corps program and encourage collaboration between the NSF I-Corps program and other federal agencies, including the Small Business Administration. The bill would also ensure accountability regarding the I-Corps program by requiring NSF to submit to Congress biennial reports regarding the program’s effectiveness.

The I-Corps program gets paid out of 3 percent administrative funds generated as part of general SBIR program funding, but the current version of the SBIR/STTR Reauthorization of Act of 2016 failed to include a five-year reauthorization of that element of the program, meaning that in theory funding for the SBIR program could lapse in August 2017 (before the following fiscal year begins in October 2017). Congress should reinsert allowance for the 3 percent administrative funding for I-Corps into the SBIR/STTR Reauthorization of Act of 2016, or if necessary provide a fix in subsequent COMPETES or National Defense Authorization Act (NDAA) legislation. Further, ideally, the final SBIR/STTR Reauthorization of Act of 2016 would contain language affirming the permanency of the commercialization pilot program for civilian agencies by omitting the words “pilot program” from current Small Business Act legislation (15 U.S.C. 638(gg)(7) and inserting the words “commercialization development program” instead.

33. Authorize and extend the Lab-Corps program

The Department of Energy created the Lab-Corps pilot program (modeled after NSF’s I-Corps program) for the national labs to support investments in technology maturation, entrepreneurs, mentors, scientists, and engineers. The program has not been formally authorized by Congress, but the Accelerating Technology Transfer to Advance Innovation for the Nation (ATTAIN) Act would authorize the program and expand it to engage all national laboratories as well as entrepreneurs and innovators who are competitively selected through an open solicitation.

34. Provide federal matching funds for state and regional technology transfer and commercialization efforts

Many states and regions fund technology transfer and commercialization efforts between their universities and the private sector; examples include TEDCO in Maryland and the Georgia Research Alliance. These programs have strong track records and are strategically tied to regional technical capabilities. But states underfund these efforts, in part because the benefits can spill over beyond their borders. Federal funds should match these state efforts at some percentage level to bolster their impact.

One example is Senate bill S. 4047, which would create a Federal Acceleration of State Technologies Deployment Program, or “FAST,” a federal funding strategy for accelerating the local commercialization of newly developed technologies by matching cash-poor state programs. 65 The matching federal funds would be available concomitant with a state’s level of investment (pro-rated against state population with a maximum cap) in its technology commercialization programs. States would use the money for direct, merit-based project grants to existing SMEs or to startup companies looking to commercialize new products or technologies (with the expectation that a major source for those technologies would be ones currently untapped at local colleges and universities).

35. Incentivize universities to focus more on commercialization activities

A number of countries have sought to increase their R&D efficiency by using existing funding for scientific research to incentivize universities to focus more on technology commercialization. 66 For example, in Sweden, 10 percent of regular research funds allocated by the national government to universities are now distributed using performance indicators. Finland allocates 25 percent of the research budgets of Finnish universities based on “quality and efficacy,” including the quality of scientific and international publications and the university’s ability to attract research investment from businesses. In other words, without increasing government budgets, these nations are using existing funds to provide an incentive for universities to become greater engines of national innovation. 67

In the United States, federal research funding agencies, particularly the National Science Foundation, should consider allocating a small share (e.g., 5 percent) of university R&D funding based on indicators of universities’ effectiveness in attracting industry funding for university research as well as success at commercialization-oriented activities (e.g., number of faculty and student spinoffs or startups, extent of technology licensing, etc.). As in Sweden, the amount of industry-funded university research should be the first variable used to make such allocation decisions. This goal could be achieved by making a share of NSF institutional support grants (which support infrastructure, research, teaching, etc.) contingent on industry collaboration and commercialization performance.

36. Establish stronger university entrepreneurship metrics

The United States should collect better data regarding new business startups coming out of U.S. universities. For example, Congress could direct the National Science Foundation to develop a metric by which universities report such information annually. Funding agencies could use this data to reward universities—for example, by giving bonus points on research grant proposals. In addition, the Department of Commerce could use data available through the ES-202 form (unemployment insurance tax records), which tracks how many employees an establishment has every quarter. If the form noted the university that the founder of the organization attended, it could reveal which colleges and universities have graduates who are founding and running high-growth businesses.

37. Expand the collaborative R&D tax credit to spur research collaboration between industry and universities and labs

Over the last two decades, firms have increased their collaborations with institutions, particularly universities, in order to lower the cost of research and increase effectiveness by maximizing idea flow and creativity. Recognizing this, at least a dozen nations have established collaborative R&D tax credits designed to incentivize industry investment in collaborative research, often including universities, and enrolling multiple partners to do so. 68 The United States has a collaborative R&D credit, but only for the energy sector: as part of the Energy Policy Act of 2005, Congress created an energy research credit that allowed companies to claim a credit equal to 20 percent of the payments to qualified research consortia for energy research.

The next administration and Congress should allow firms to take a flat credit of 20 percent for collaborative research undertaken in conjunction with universities, research institutes, federal laboratories, or multi-firm consortia. 69 This has been suggested before: in 2006, several bills were proposed which would have allowed all research consortia, not just energy-related ones, to become eligible for a 20 percent credit. 70

38. Increase funding for cooperative industry/university research programs at universities

Industry-university partnerships spur greater levels of commercialization and innovation. In the United States, NSF’s Engineering Directorate operates two kinds of industry-university partnerships: Engineering Research Centers (ERCs) and Industry/University Cooperative Research Centers (I/UCRCs). The ERCs are a group of 19 interdisciplinary centers located at universities, where academia and industry collaborate in pursuing strategic advances in complex engineered systems and systems-level technologies that have the potential to spawn whole new industries or to radically transform the product lines, processing technologies, or service-delivery methodologies of current industries. 71 The 75 I/UCRC programs forge partnerships between universities and industry, featuring industrially relevant fundamental research, industrial support of and collaboration in research and education, and direct transfer of university-developed ideas, research results, and technology to U.S. industry to improve its competitive posture in global markets. 72 In other words, the ERCs are focused on collaborative research among universities in advanced engineering systems, whereas the I/UCRCs bring in the industry component of advanced engineering systems research in collaboration with universities.

The Trump administration should work with Congress to increase I/UCRC funding to at least $50 million annually (a considerable increase from the $8 million budgeted in 2016). 73 The National Science Foundation has requested $61 million to fund 18 ERCs in FY 2017, but by 2020 Congress and the administration should look to grow the network of ERCs to 30 with appropriations of $100 million. 74 There is good reason to do so, for the ERC and I/UCRC programs represent some of the most impactful initiatives in the federal government. For instance, each dollar invested by I/UCRC generates an estimated $64.70 in economic impact. 75 While the increased funding being called for here for the two programs is relatively minor (about $80 million), even this need not increase spending, since funds can be reallocated in a budget-neutral manner from other activities. Again, the goal is to prioritize those federal programs and initiatives that have demonstrated the most powerful impacts.

39. Establish an International Patent Consortium

U.S. government and university technology transfer offices cannot afford to file and prosecute foreign patent applications on all their technology inventions. Accordingly, foreign rights to technologies invented at U.S. federal laboratories or universities often go wanting, and so commercialization opportunities are missed in foreign markets.

One solution would be to create an International Patent Consortium, comprising country-specific (or regional) groups of international industry, financial, government, economic development, and technology transfer professionals who would collectively pay the patent expenses for at least two inventions per year from a U.S. technology transfer office in exchange for the exclusive marketing rights to those inventions (within a foreign country or region), with such rights then locally sublicensed by the consortium.

This process could help ameliorate the current practice of filing foreign patents in only a handful of countries. The consortium concept could increase the breadth and value of the intellectual property portfolio of U.S. government labs and provide their U.S. licensees (particularly small companies) with international marketing and distribution partners who could also provide complementary technology, equity, and international business experience.

Given mounting fiscal pressures, both the incoming Trump administration and Congress need to focus on improving the economic return on investment from existing infrastructure and resources. It is clearly time to elevate the importance attached to commercialization-oriented activities associated with federal R&D funding programs as well as raise commercialization’s profile in the missions of federal laboratories and federally funded universities.

One key step the federal government can take to boost the economy is to better support high-growth, tech-based startups because these firms play an important role in job creation and innovation. According to research by MIT economist Scott Stern, 75 percent of employment generated by startups can be attributed to just 5 percent of entrepreneurs. 76

Moreover, the relationship between young firms and larger companies is an essential ingredient for innovation. 77 Large companies house much of the industry knowledge needed for finding new solutions, but they often have tightly controlled product lines and corporate governance structures that can make radical innovation difficult. At the same time, young firms lack the market intelligence to know exactly what solutions can be monetized, but they represent a disproportionate share of radical innovation and are often acquired by large companies better suited to market new ideas. Dense, regional clusters are important to the interplay between young and large firms because economic research shows that entrepreneurs and larger firms collaborate most when they are geographically close. 78

Unfortunately, the job-creating capacity of high-growth entrepreneurial firms has declined over the last 15 years. Decker et al. find that before 2000 the fastest-growing young firms (those in the 90th percentile of all young firms) grew employment at a steady rate of just under 70 percent a year, but by 2012 that rate had declined to 55 percent. 79 The authors also find that the portion of young, high-growth technology firms has declined since 2000, as Figure 2 shows. 80 Figure 2: High-growth firms by firm age and annual employment growth rates, 1980-2012

Line chart showing high-growth firms by firm age and annual employment growth rates, 1980-2012. The chart shows that that the portion of young, highgrowth technology firms has declined since 2000.

While startups once represented a wellspring of employment opportunities in new technology industries, today the flow is smaller. Therefore, supporting high-growth entrepreneurship should be a key pillar of the next administration’s innovation policy priorities.

40. Encourage student entrepreneurship

The next administration should encourage universities to define an entrepreneurial leave policy for undergraduate and graduate students in which students could retain full-time student status for one to two years while launching their own companies. In the United States, for example, federal agencies supporting university research in science, technology, engineering, and mathematics (STEM) education should adopt a policy whereby any graduate or post-doctoral students on an assistantship, fellowship, or other form of federal support can petition for a no-cost one- to two-year extension of their status as they take “entrepreneurial leave.” Another option would be to provide graduates an entrepreneurial student loan deferment when they are attempting to start a business. The deferment could be extended if certain metrics were being met, such as jobs created or venture capital raised.

41. Help nascent high-growth startups secure needed capital

In 1995, Silicon Valley accounted for 22.6 percent of U.S. venture capital, Los Angeles/Orange County 12.5 percent, Boston 9.9 percent, New York 6.4 percent, and all other areas of the United States 48.6 percent. Twenty years later, in 2015, Silicon Valley had more than doubled its share, to 46.4 percent, New York’s share rose to 12.4 percent, Boston moved to 10.2 percent, and Los Angeles to 8.7 percent, while the share for the rest of the United States fell to 22.2 percent. 81 In other words, today just four regions of the United States account for 78 percent of all U.S. venture capital investment, while the remainder of the country fights over the remaining one-fifth.

Thus, a substantial number of promising young businesses scattered throughout all regions of the United States likely have difficulty securing capital, particularly venture capital, because most venture capital investment is concentrated on America’s coasts. The Small Business Jobs Act of 2010 helped to address this problem; it created the State Small Business Credit Initiative (SSBCI), a $1.5 billion fund designed to strengthen state programs that support lending to small businesses and small manufacturers. 82 The SSBCI gave states significant flexibility to design programs to meet local market conditions, with SSBCI supporting 152 small business programs from 2011 to 2015. Approximately 69 percent of the funding supported lending or credit support programs and 31 percent supported venture capital programs. From 2011 to 2015, SSBCI programs supported nearly $8.4 billion in new capital in small business loans and investments. 83

In effect, SSBCI provides an opportunity for states to supplement existing venture capital programs, revitalize programs lacking sufficient state support, and create new programs where state managers perceive unmet needs in evolving entrepreneurial ecosystems. The SSBCI has made a positive impact in expanding high-potential businesses’ access to credit, and so the next administration should reauthorize it and double its funding.

42. Establish an entrepreneur-in-residence program with NIH

While all federal funding agencies should support greater research-driven entrepreneurs, NIH is unique in that health care and life science startups are particularly difficult to grow—but often represent significant economic value when they do. Moreover, among all agencies, NIH distributes the largest share of federal funding to universities, many of which have only recently begun to seriously think about technology transfer through faculty and student-generated businesses. Universities and academic medical centers that receive funding from NIH often follow the narrow and traditional path to commercializing research that revolves around patenting and licensing. In the “classic” model of technology transfer, researchers at universities and medical centers apply for NIH and other federal funds to pursue basic science and patent their discoveries. The technology transfer office at the university/medical center then takes these patents and licenses their use to biotechnology and pharmaceutical firms for the development of products.

While the classic model can be an appropriate vehicle for commercialization, it often lacks strong connections between firms and research organizations. Successfully scaling a life-sciences startup requires social and capital networks, mentorship, public-private partnerships, and access to both scientific and managerial talent. Developing, recruiting, and coordinating these disparate pieces of the medical entrepreneurial ecosystem is difficult but once achieved can spur new economic clusters, firms, and employment.

For years venture capital firms have run entrepreneur-in-residence (EIR) programs, where the firm hires proven entrepreneurs to review its patent portfolio and work with other star entrepreneurs to help them grow. By establishing an entrepreneur-in-residence program at universities that receive NIH research funding, including basic and translational (DHHS already has an EIR program that serves a different purpose), the agency can help universities identify, support, and grow the research efforts best positioned to become high-growth companies. 84

43. Implement immigration policies that advantage high-skill talent

Talent has become the world’s most sought-after commodity. Immigration plays an important role in contributing to a country’s knowledge pool and creative potential by bringing in new perspectives and needed skills. As the report Not Coming to America: Why the U.S. Is Falling Behind in the Global Race for Talent finds, at least nine nations—Australia, Canada, Chile, China, Germany, Ireland, Israel, Singapore, and the United Kingdom—have implemented innovative policies to attract foreign entrepreneurs and investors to their countries as part of a concerted effort to drive economic and employment growth. These countries “see immigration as an integral part of their national economic strategy—a factor in their prosperity as significant as education and infrastructure.” 85 America’s immigration policies should adopt a more open approach toward high-skill talent. One simple way to accomplish this is to grant more work visas to foreign students in American universities after they graduate. In the 2014-2015 school year approximately 975,000 foreign nationals were attending U.S. universities; 57 percent of the students were in STEM fields. 86 Extending a green card to foreign-born students graduating in STEM fields would provide a boost to the U.S. innovation economy. Accordingly, the United States should make it easier for talented individuals from foreign nations who receive a graduate degree in STEM fields to stay in the United States after graduation by making them eligible for permanent residency.

44. Implement a research investor’s visa

The United States should create a research investors’ visa for foreign individuals investing substantially in ongoing federally funded R&D activities at U.S. universities or federal laboratories. 87 Such a visa could make important contributions to U.S. economic and employment growth.

One reason a research investor’s visa could have a particularly powerful economic effect is that it would specifically support the most R&D-intensive sectors of the U.S. economy that are best positioned to compete globally. A potential weakness of the immigrant entrepreneurs’ visa is that it is impossible to know which entrepreneurial activities will grow to global scale and become a source of employment. By specifically focusing on high-value, scientifically focused startups, the new visa would better capture growth-oriented firms. For example, the Kauffman Foundation finds that a general startup visa program would create significantly fewer jobs, perhaps only one-third as many, as a program focused on high-technology or engineering startups. 88

Political economists Peter Hall and David Soskice argue that the United States’ entrepreneurship ecosystem is central to the country’s ability to produce innovations that lead to new industries—automobiles, planes, electronics, software, etc. 89 While other countries such as Germany have strong industrial policies that allow legacy industries to remain competitive through technology adoption, radical innovation through new firms is a unique American strength. To continue to build on this, the next administration will need to create policies that better support high-growth tech-based startups and attract foreign tech-based entrepreneurs while also incentivizing universities, federal labs, and other federally funded institutions to encourage entrepreneurship.

Leveraging federal R&D alone won’t be enough to re-establish U.S. leadership in advanced manufacturing and technology sectors. Because over two-thirds of R&D is performed by the private sector, the administration must also incentivize and support private-sector R&D and create stronger linkages between public and private R&D. Supporting such R&D is crucial because it is a critical input to the private-sector innovations that drive long-term U.S. economic growth.

There are at least four reasons why the government should support private-sector innovation. First, without government incentives for R&D, worker training, and investments in new capital equipment, the private sector would underinvest in innovation because new technologies are often easily replicated and transferred between firms. This is particularly true as technology imitation occurs far more quickly today than in the past, due in part to the global base of technology competitors and the speed of reverse engineering. Consider the iPad, first released in March 2010. At the 2011 Consumer Electronics Show, close to a dozen competing tablets were on display. 90 Effects like these are why the economist Lorin Hitt finds that spillovers to other firms from firms’ investments in information technology are “almost as large in size as the effect of their own investments.” 91 This is good for the economy but bad for the innovative company that cannot reap the full market benefits of its technology.

Second, the gulf between federal and private-sector R&D is widening. Over the last half century, firms have moved away from investing in basic research and toward market-oriented development research; at the same time, the federal government has shifted its R&D portfolio toward basic science. Between 1965 and 2015, the share of federal R&D going to basic research increased from less than 10 percent to 25 percent. 92 Figure 3 shows that federal investment in development-oriented activities (i.e., the “D” in “R&D”) as a share of GDP has trailed off significantly since the mid-1980s. The impact of these trends is that now federal research outcomes leave off far too early for corporate research centers to commercialize. To fix the problem, greater linking mechanisms are needed.

Third, economic research clearly shows that innovation-oriented tax credits work. Bloom, Griffith, and Van Reenen find that R&D tax credits stimulate $1.10 for every dollar lost in tax revenue. 93 Coopers and Lybrand find higher benefits, of between $1.30 and $2.90. 94 Similarly, Klassen, Pittman, and Reed find that, for every one dollar of tax revenue lost, the R&D credit induces $2.96 in private-sector R&D. 95

Finally, the United States now lags far behind many other countries in innovation-incentivizing tax policy. The United States invented the R&D tax credit in the early 1980s, and as late as 1992 ranked first globally in R&D tax incentive generosity. But today the United States ranks 27th. 96 While in 2015 Congress laudably made the R&D tax credit permanent, other countries have raced ahead, creating robust investment tax credits, bridging public and private R&D, and incentivizing workforce training and technology investments by the private sector.

To stimulate private sector innovation, the incoming administration should work with Congress on the following policies.

45. Implement innovation vouchers

Innovation vouchers are low-cost tools for connecting startups with public research institutes or universities to incentivize R&D among young, innovative firms. The main goals of an innovation voucher are to enable knowledge transfers between startups and research institutes, support sectoral innovation in manufacturing, support innovation management and advisory services, speed commercialization of startup ideas, and focus research institutions on the commercial applications of their research. Several countries, including Austria, Belgium, Canada, Denmark, Germany, the Netherlands, Ireland, and Sweden, have begun using innovation vouchers to support R&D, innovation, and new product development in small businesses.

With traditional voucher programs SMEs can typically receive a $5,000-$10,000 voucher for a cooperation project with a university, community college, or research institution for R&D assistance, technology feasibility studies, analysis of technology transfer, or analysis of the innovation potential of a new technology. The voucher creates an incentive to bring SMEs and academia closer together and also empowers innovation at SMEs.

Several U.S. states, including New Mexico, Rhode Island, and Tennessee, are experimenting with innovation vouchers. For example, in 2015, Oak Ridge National lab established an innovation voucher program to enable technical assistance to SME manufacturers in Tennessee. Los Alamos and Sandia national laboratories in New Mexico operate a similar program. 97 And the Energy Efficiency and Renewable Energy office within DoE has created a pilot innovation voucher for its national laboratories. Congress should extend vouchers to entire federal lab system by authorizing $50 million to the National Institute of Standards and Technology to fund a program operated by select states that agree to match the funding dollar for dollar (perhaps through tax credits to national labs within their borders). As a potential source of funds to keep the initiative revenue-neutral, one option would be to reallocate 0.5 percent of the laboratories’ current budgets to fund the vouchers. 98

46. Incentivize “megafunds” around high-risk research and development

In 1960, private-sector R&D was split one-third to research and two-thirds to development. Today, only one-fifth of firm R&D goes to research. One reason companies are moving away from basic and applied research is because of the risk involved in financing. In drug development, for example, it often takes years or decades and hundreds of millions of dollars to produce a profitable product. Individual companies and even venture capitalists often lack the appetite for such long-term, high-risk investments.

This risk could be mitigated through large portfolios that aggregate and manage risk. Mutual funds, pension funds, and 401(k) retirement accounts work this way, and MIT economist Andrew Lo has proposed extending this idea by establishing “megafunds” that utilize financial engineering techniques to fund R&D in long-term, high-risk, high-payoff areas such as drug discovery for cancer or orphan diseases. 99 However, to date, no such megafunds have been created by the market. The government incentives required for the creation of these funds could include one or more approaches from four broad categories: research and investment data streams; clear rules for private foundation program-related megafund investments; federal credit support; and tax incentives for funds investing in technologies with high societal impact (for example through the establishment of schedules and values of basis point step-ups and penalties).

To promote the creation of R&D megafunds, the Trump administration should establish an office within the Department of Commerce to develop and implement the needed incentives and oversight. The office would be tasked with establishing the rules for the funds and coordinating with federal agencies and the private sector to identify the technical areas of national interest where private-sector engagement is needed and the incentives required. The office should work with researchers, industry, and regulators to develop data-reporting and transparency standards that promote the translation of research to the market, provide better understanding of the societal benefits of research and an efficient data stream for regulation, and coordinate with federal funding agencies to enforce the provision and collection of such data.

47. Increase R&D tax credit generosity

R&D tax incentives are one of the most effective policy instruments in spurring a nation’s private-sector R&D investment. Almost all scholarly studies conducted since the early 1990s find R&D tax incentives to be both effective and efficient. Studies of the U.S. credit find even greater benefits, with the research-investment-to-tax-cost ratio falling between 1.3 and 2.9. 100 Yet France and Spain offer R&D tax credits over five times more generous than those of the United States, and even Brazil, China, and India have exceeded the United States in R&D tax credit generosity. Ideally, the United States should increase the rate of the Alternative Simplified Credit from 14 to 24 percent. ITIF has calculated that expanding the R&D tax credit would pay for itself in added revenues from growth after 15 years. 101

48. Ensure that small and medium-sized enterprises are familiar with available R&D tax credits

It is important that America’s SMEs take full advantage of tax incentives, whether for R&D or investment in new machinery and equipment. Congress passed the PATH Act in December 2015 to expand small businesses’ access to the R&D credit by permitting them to claim the credit against their employment taxes or against their alternative minimum tax. But not enough small businesses are aware that this legislation greatly expands their access to the credit. Accordingly, Congress should pass the Support Small Business R&D Act, which would require the Small Business Administration and the Internal Revenue Service to expand knowledge sharing and training on these instruments and provide a report to Congress on their progress.

49. Implement an innovation box to spur enterprises’ efforts to commercialize technologies

A growing number of nations have put in place tax incentives to spur the commercialization of R&D, not just the conduct of R&D. These patent box —also called “innovation box”—incentives allow corporate income from the sale of patented products (or in some countries from innovation-based products) to be taxed at a significantly lower rate than other income. 102 A number of nations—including Belgium, China, France, Ireland, Luxembourg, the Netherlands, Spain, Switzerland, and the United Kingdom—have established patent boxes. The United Kingdom implemented its policy in 2013 with a tax rate of 10 percent on income generated from patented products, compared to the standard rate of 28 percent. France’s patent box reduces corporate income tax from 34 percent to 15 percent on qualifying income.

A patent box that reduces the corporate tax rate on revenue from qualifying intellectual property, coupled with an incentive for corresponding R&D and production to be located in the United States, would provide firms with a much stronger incentive to innovate and to produce in the United States. The Innovation Promotion Act of 2015 calls for creating an innovation box that allows companies to claim an effective 10.15 percent tax rate for income derived from a wide range of qualifying intellectual property, including patents, inventions, formulas, processes, and designs and patterns, as well as other types of intellectual property, such as copyrighted computer software. Innovation boxes have received bipartisan support in the Senate. 103 The incoming administration should work with Congress to develop legislation to implement an innovation box for the United States.

50. Revise the tax code to support innovation by research-intensive, pre-revenue companies

The primary mechanism in the tax code to facilitate innovation is the R&D tax credit, but the credit is less useful for pre-revenue companies because it requires tax liability, which requires income. In other words, the tax credit is designed more for established innovators, not so much for research-intensive, pre-revenue companies that are trying to develop new technologies such as medical devices or biopharmaceutical drugs. These are extremely R&D-intensive companies, which tend to invest 75 percent or more of their expenditures in R&D.

Firms in this position often find it difficult to raise the capital needed to get them through the long development phase until they are near enough to profitability to conduct an initial public offering or be attractive to a prospective buyer. The PATH Act (Protecting Americans From Tax Hikes) of 2015 made the R&D tax credit refundable for small businesses (i.e., it allowed small businesses to take the credit against their payroll taxes). But two additional tax reform proposals could further address these challenges.

The first proposal would amend Section 469 of the tax code to permit passive investors to take advantage of the net operating losses and research tax credits of companies in which they invest. 104 (The Tax Reform Act of 1986 severely limited this ability because it was seen as a way for high-income individuals to reduce their taxes by investing in operations that were never meant to be profitable.) Under this reform, investors could immediately use their share of net operating losses, as well as any credits for research and development. The percentage of losses or credits that could be passed through would be limited to the portion of investment that was specifically targeted for qualified research activities as determined for purposes of the research and development tax credit. In order to qualify, a company would have to devote at least half of its expenses to research and development. The company would also have to have fewer than 250 employees and less than $150 million in assets. A recent study by Ernst & Young estimates that this change would increase investment in such companies by $9.2 billion, allowing them to create 47,000 jobs. 105 The proposal is currently contained in both the Start-Up Jobs and Innovation Act (S. 341) and the COMPETE Act (S. 537).

The second change would make it easier for small companies to carry net operating losses forward even as they continue to attract new investors. Small, research-intensive companies often go through several rounds of financing as they rack up expenses while getting nearer to their goal of profitability. Unfortunately, Section 382 of the tax code prevents companies from carrying net operating losses forward if they undergo an ownership change. This rule eliminates an attraction to investors. It also means that the company will start paying taxes on its revenue long before its total revenues exceed it total expenses. Under the proposed change, Section 382 would not apply to net operating losses generated by qualifying research and development activities conducted by a small business. The Ernst & Young analysis estimated that this change would increase direct investment in these companies by $4.9 billion and boost their employment by 25,000 jobs. 106

Coming out of World War II the United States was the first country to make research and development a national priority. At the time the federal government accounted for over 50 percent of global R&D, public and private. Today, the federal government accounts for 8 percent of global R&D investment. While robust, U.S. federal investments in science represent a shrinking portion of technology development. In order for the United States to remain competitive, firms must find a country to be an attractive location to innovate. The incoming administration should use the tax system and other policy levers to ensure the United States remains the top destination of enterprise R&D.

Conclusion: The American economy in 2025 and beyond

There will be no shortage of pressing issues for the Trump administration to focus on in its first 100 days. But none will affect as many Americans for as long a period as stagnant economic growth. Indeed, the trajectory of the American economy in 2025 and beyond begins on January 1, 2017. Without a multi-decade turnaround of the U.S. economy, neither party will be able to achieve its other economic priorities. In the absence of consistent economic success, those on the left will find the social safety net overburdened and underfunded, while those on the right will find public coffers too diminished to lower taxes. At the same time, American families will continue to be squeezed.

The first step toward fixing America’s economy is correctly diagnosing the problem. It is not automation or globalization. Rather, the United States has a productivity and innovation problem. Both are lacking, and that’s problematic when productivity growth is the fundamental source of economic growth and when innovation drives productivity. Upon entering the White House, President Obama was faced with the 2008 financial crisis and was able to leverage the moment to pass the American Recovery and Reinvestment Act, investing $787 billion in the economy. Bold action will likewise be needed from the incoming Trump administration, and the policy proposals outlined here provide a template to maximize the levels of technology transfer, commercialization, and innovation that will drive America’s economy robustly forward into the future.

Executive Office of the President National Science and Technology Council Advanced Manufacturing National Program Office, National Network for Manufacturing Innovation Program: Annual Report (Executive Office of the President, February 2016), https://www.manufacturing.gov/files/2016/02/2015-NNMI-Annual-Report.pdf .
Robert D. Atkinson, “Leveraging the U.S. Science and Technology Enterprise,” written testimony to the U.S. Senate Committee on Commerce, Science, and Transportation, 2016, p. 1, http://www2.itif.org/2016-senate-competes-act-testimony.pdf .
Gregory Tassey, “Why the U.S. Needs a New, Tech-Driven Growth Strategy” (Washington: Information Technology and Innovation Foundation, February 2016), https://itif.org/publications/2016/02/01/why-us-needs-new-tech-driven-growth-strategy .
Martin Neil Baily and Nicholas Montalban, “Why Is US Productivity Growth So Slow? Possible Explanations and Policy Responses,” Working Paper # 22 (Washington: Brookings Institution Hutchins Center on Fiscal and Monetary Policy, 2016), https://www.brookings.edu/wp-content/uploads/2016/09/wp22_baily-montalbano_final3.pdf .
Robert D. Atkinson. “Think Like an Enterprise: Why Nations Need Comprehensive Productivity Strategies,” (Washington: Information Technology & Innovation Foundation, 2016), http://www2.itif.org/2016-think-like-an-enterprise.pdf?_ga=1.167003194.568129823.1475259628 .
Information Technology and Innovation Foundation, “As Productivity Continues to Lag, ITIF Reiterates Call for Wholesale Shift in Economic Policy Focus,” news release, August 9, 2016, https://itif.org/publications/2016/08/09/productivity-continues-lag-itif-reiterates-call-wholesale-shift-economic .
U.S. Census Bureau, Foreign Trade Division, “Trade in Goods With Advance Technology Products” (1989-2016), https://www.census.gov/foreign-trade/balance/c0007.html .
John Wu, Adams Nager, Joseph Chuzhin, High-Tech Nation: How Technological Innovation Shapes America’s 435 Congressional Districts (Information Technology and Innovation Foundation, November 2016), http://www2.itif.org/technation-2016-report.pdf?_ga=1.139274675.1806060799.1471894729 .
See, for example, Mark Muro and Bruce Katz, “The New Cluster Moment: How Regional Innovation Clusters Can Foster the Next Economy” (Washington: Brookings Institution, 2010). See also S. Rosenthal and W. Strange, “Evidence on the Nature and Sources of Agglomeration Economies,” in J.V. Henderson and J.F. Thisse, eds., Handbook of Regional and Urban Economics, Vol. 4 (Amsterdam, North-Holland: 2004); MaryAnn Feldman and David Audretsch, “Innovation in Cities: Science-Based Diversity, Specialization, and Localized Competition,” European Economic Review 43 (1999): 409–29; and Gregory Tassey, “Competing in Advanced Manufacturing: The Need for Improved Growth Models and Policies” Journal of Economic Perspectives 28 , No. 1 (Winter 2014): 27-48, http://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.28.1.27 .
S. Rosenthal and W. Strange, “Geography, Industrial Organization, and Agglomeration,” Review of Economics and Statistics , 85, no. 2 (2003): 377-93. Similarly, Arzaghi and Henderson study ad agencies in Manhattan and show knowledge spillovers and the value of networking with nearby firms are substantial but the benefits dissipate extremely rapidly. The strongest effects are when firms are within 0-250 meters and decline by 80 percent when two firms are 500 meters apart. See: Mohammad Arzaghi and J. Vernon Henderson, “Networking off Madison Avenue” Review of Economic Studies 75 , No. 4 (2008): 1011-1038, https://ideas.repec.org/a/oup/restud/v75y2008i4p1011-1038.html .
Atkinson, Leveraging the U.S. Science and Technology Enterprise , p. 2.
Bronwyn H. Hall, Jacques Mairesse, and Pierre Mohnen, “Measuring the Returns to R&D,” Working Paper No. 15622 (Cambridge, Mass.: National Bureau of Economic Research, 2009), http://www.nber.org/papers/w15622 .
U.S. Department of Defense, “National Economic Impacts from DoD License Agreements With U.S. Industry: 2000-2014,” (2016).
Smart Growth America, “Core Values: Why American Companies Are Moving Downtown” (Washington, 2015), https://www.smartgrowthamerica.org/app/legacy/documents/core-values.pdf .
Bruce Katz and Julie Wagner, “The Rise of Innovation Districts: A New Geography of Innovation in America” (Washington: Brookings Institution, 2014), https://www.brookings.edu/essay/rise-of-innovation-districts/ .
Scott Andes, “Hidden in Plain Sight: The Oversized Impact of Downtown Universities” (Washington: Brookings, 2016, forthcoming).
New Mexico Small Business Assistance Program, http://www.nmsbaprogram.org/ .
Cyclotron Road, “About Us,” http://www.cyclotronroad.org/ ; Joseff Kolman, “Summary of Federal, State, University, and Private Programs for Supporting Emerging Technology” (Washington, DC: Massachusetts Institute of Technology Washington, DC Office, July 2015), http://dc.mit.edu/sites/default/files/doc/MIT%20Innov%20Orchard%20Summary%20of%20Federal,%20State,%20University,%20and%20Private%20Programs%20for%20Emerging%20Technologies%207.10.2015.docx .
NIH’s Clinical and Translational Science awards are geared towards cross-institution collaboration and have broadly been successful and offer a good example how NIH can extend pre-competitive, collaborative opportunities across its programs.
A significant amount of funding for the federal labs already comes from outside of DoE. At the federal level in FY 2011, the labs received just under $3 billion from the Department of Homeland Security, the National Institute of Standards and Technology, the Centers for Disease Control and Prevention, the intelligence community, the Department of Defense, and NASA. On the other hand, some labs—such as NREL and SLAC—receive over 90 percent of their funding from their funding steward. See National Academy of Public Administration, “Positioning DOE’s Labs for the Future.”
Pumps & Pipes, http://www.pumpsandpipes.com/index.html#rj-who-we-are .
Stephen J. Ezell and Robert D. Atkinson, “25 Recommendations for the 2013 America COMPETES Act Reauthorization” (Washington: Information Technology and Innovation Foundation, 2013), p. 17, http://www2.itif.org/2013-twenty-five-policy-recs-competes-act.pdf .
U.S. Economic Development Administration, “Regional Innovation Clusters Initiative Overview” (2010), http://www.eda.gov/AboutEDA/RIC/ .
Atkinson, Leveraging the U.S. Science and Technology Enterprise , p. 4.
University of Minnesota Duluth Natural Resources Research Institute, “History,” http://www.nrri.umn.edu/about/discover-nrri/history .
Ben Franklin Technology Partners of Central & Northern Pennsylvania, cnp.benfranklin.org.
Joshua New and Daniel Castro, “Why Countries Need National Strategies for the Internet of Things” (Washington: Center for Data Innovation, 2015), p. 14, http://www2.datainnovation.org/2015-national-iot-strategies.pdf .
Makerspace, “What’s a Makerspace?” http://spaces.makerspace.com/ .
“National Fab Lab Network Act of 2015,” H.R.1622, 114 th Cong. (2015-2016), https://www.congress.gov/bill/114th-congress/house-bill/1622/actions?q=%7B%22search%22%3A%5B%22hr+1622%22%5D%7D&resultIndex=1 .
Stephen Ezell, “’Fab Lab’ Bill Would Stimulate Manufacturing Innovation,” The Innovation Files , April 29, 2013, http://www.innovationfiles.org/fab-lab-bill-would-stimulate-manufacturing-innovation/ .
Robert D. Atkinson and Stephen J. Ezell, “Innovation Economics: The Race for Global Advantage” (New Haven, Conn.: Yale University Press, 2012).
Robert D. Atkinson, “The Morrill Act at 150 Years: We Need a New Morrill Act for the 21st Century,” The Innovation Files , July 12, 2012, http://www.innovationfiles.org/the-morrill-act-at-150-years-we-need-a-new-morrill-act-for-the-21st-century/ .
Stephen J. Ezell, Frank Spring, and Katarzyna Bitka, “The Global Flourishing of National Innovation Foundations” (Washington: Information Technology and Innovation Foundation, 2015), http://www2.itif.org/2015-flourishing-national-innovation.pdf .
Robert D. Atkinson and Stephen J. Ezell, “Cut to Invest: Support the Designation of 20 U.S. Manufacturing Universities” (Washington: Brookings Institution and Information Technology and Innovation Foundation, 2013), https://www.brookings.edu/research/papers/2013/01/14-federalism-series-manufacturing-universities .
Sponsored in the U.S. Senate by Senator Coons (D-DE) along with Senators Ayotte (R-NH), Gillibrand (D-NY), Graham (R-SC), and Baldwin (D-WI), and mirrored by House legislation introduced by Representatives Etsy (D-CT) and Collins (R-NY).
David M. Hart, Stephen J. Ezell, and Robert D. Atkinson, “Why America Needs a National Network for Manufacturing Innovation” (Washington: Information Technology and Innovation Foundation, 2012), https://itif.org/publications/2012/12/11/why-america-needs-national-network-manufacturing-innovation .
Ezell and Atkinson, “25 Recommendations for the 2013 America COMPETES Act Reauthorization,” p. 22.
Justin Talbot Zorn and Sridhar Kota, “Engineering an Economic Recovery,” The Huffington Post (blog), January 11, 2013, http://www.huffingtonpost.com/justin-zorn/manufacturing-economic-recovery_b_2662720.html .
Robert D. Atkinson and Howard Wial, “Boosting Productivity, Innovation, and Growth Through a National Innovation Foundation” (Washington: Information Technology and Innovation Foundation, 2008), http://www.itif.org/files/NIF.pdf .
Stuart Benjamin and Arti Rae, “Structuring U.S. Innovation Policy: Creating a White House Office of Innovation Policy” (Washington: Information Technology and Innovation Foundation, 2009), http://www.itif.org/files/WhiteHouse_Innovation.pdf .
Department of Defense, “National Economic Impacts From DoD License Agreements With U.S. Industry: 2000-2014, (2016).
Scott Andes, “Maximizing the Local Economic Impact of Federal R&D” (Washington: Brookings Institution, 2016).
Timothy A. Walton, “Securing the Third Offset Strategy: Priorities for Next US Secretary of Defense” (Washington: Center for Strategic and Budgetary Assessments, 2016), http://csbaonline.org/about/news/securing-the-third-offset-strategy-priorities-for-next-us-secretary-of-defe .
Oak Ridge National Laboratory, “AMO Announces Funding Opportunity for Low-Cost, Energy-Efficient Manufacturing and Recycling of Advanced Fiber-Reinforced Composites,” Innovations in Manufacturing , February 26, 2014, http://web.ornl.gov/sci/manufacturing/nnmi/ .
Scott Andes, Mark Muro, and Matthew Stepp, “Going Local: Connecting the National Labs to their Regions to Maximize Innovation and Growth” (Brookings and Information Technology and Innovation Foundation, September 2014), https://www.brookings.edu/wp-content/uploads/2016/06/BMPP_DOE_Brief.pdf .
Louis G. Tornatzkyand Elaine C. Rideout, “Innovation U 2.0: Reinventing University Roles in a Knowledge Economy” (2014), http://ssti.org/report-archive/innovationu20.pdf .
Matthew Stepp, Sean Pool, Nick Loris, and Jack Spencer, “Turning the Page: Reimagining the Federal Labs in the 21 st Century Innovation Economy” (Washington: Information Technology and Innovation Foundation, Center for American Progress, and The Heritage Foundation, 2013): pp. 23, 45, 53, http://www2.itif.org/2013-turning-the-page.pdf?_ga=1.172902691.1806060799.1471894729 .
Ibid., p. 54.
Ezell and Atkinson, “25 Recommendations for the 2013 America COMPETES Act Reauthorization,” p. 14.
Similar legislation is proposed in Section 8 of the Startup Act 3.0 titled “Accelerating Commercialization of Taxpayer Funded Research.” See Representative Michael Grimm, “H.R.714–Startup Act 3.0,” Congress.gov, https://www.congress.gov/bill/113th-congress/house-bill/714/text#toc-HFE43E635A9674068882957133E8E662C .
European Research Council, “Proof of Concept Grants,” https://erc.europa.eu/proof-concept.
Gretchen Vogel, “Europe Nudges Top Scientists to Market,” Science , March 25, 2011, http://www.sciencemag.org/news/2011/03/europe-nudges-top-scientists-market .
Wallace H. Coulter Foundation, “Translational Research” (Miami, Fla., 2016), www.whcf.org/partnership-award/overview .
Department of Health and Human Services, “National Institute of Health Evaluation and Commercialization Hub (REACH) Awards” (2014), http://grants.nih.gov/grants/guide/rfa-files/RFA-OD-14-005.html .
Fred Block and Matthew Keller, “Where Do Innovations Come From? Transformations in the U.S. National Innovation System, 1970-2006” (Washington: Information Technology and Innovation Foundation, 2008), http://www.itif.org/files/Where_do_innovations_come_from.pdf .
National Advisory Council on Entrepreneurship (NACIE), “Letter to The Honorable Penny Pritzker Offering Recommendations to Improve the Outcomes of the SBIR/STTR Programs” (March 4, 2016).
“Support Startup Businesses Act of 2016,” S.2751, 114 th Cong. (2015-2016), https://www.congress.gov/bill/114th-congress/senate-bill/2751/text?format=txt .
NACIE, “Letter to Pritzker on Improving SBIR/STTR Outcomes,” https://www.eda.gov/oie/files/nacie/meetings/20160303-SBIR-STTR-Recommendations-NACIE.pdf .
“FAST Deployment Act of 2010,” S. 4047, 111th Cong. (2010), http://www.gpo.gov/fdsys/pkg/BILLS-111s4047is/pdf/BILLS-111s4047is.pdf .
Ezell and Atkinson, “25 Recommendations for the 2013 America COMPETES Act Reauthorization,” p. 23.
Jukka Haapamäki and Ulla Mäkeläinen, “Universities 2006” (Helsinki: Finnish Ministry of Education, 2007), pp. 23-24, http://www.minedu.fi/export/sites/default/OPM/Julkaisut/2007/liitteet/opm19.pdf .
Matthew Stepp and Robert D. Atkinson, “Creating a Collaborative R&D Tax Credit” (Washington: Information Technology and Innovation Foundation, 2011), http://www.itif.org/files/2011-creating-r&d-credit.pdf .
Paul R. Sanberg et al., “Changing the Academic Culture: Valuing Patents and Commercialization Toward Tenure and Career Advancement” (Cambridge, Mass.: Proceedings of the National Academy of Sciences, 2014), http://www.pnas.org/content/111/18/6542.long .
The 109th Senate considered versions of HR.4297 (Thomas, [R-CA]), S.14 (Stabenow [D-MI]), S.2199 (Domenici [R-NM]), and S.2357 (Kennedy [D-MA]). S.2357 would institute a flat credit for payments to qualified research consortia.
Engineering Research Centers Association, “About the ERCs,” http://www.erc-assoc.org/ .
National Science Foundation, “I/UCRC Model Partnerships,” http://www.nsf.gov/eng/iip/iucrc/program.jsp .
National Science Foundation, “NSF FY 2017 Budget Request: Directorate for Computer and Information Science and Engineering (CISE),” p. 22, https://www.nsf.gov/about/budget/fy2017/pdf/18_fy2017.pdf .
National Science Foundation, “NSF FY 2017 Budget Request: National Science Foundation Centers,” https://www.nsf.gov/about/budget/fy2017/pdf/46_fy2017.pdf .
Denis O. Gray, Drew Rivers, and George Vermont, “Measuring the Economic Impact of the NSF Industry/University Cooperative Research Center Program: A Feasibility Study” (Arlington, Va.: I/UCRC, 2011), p. 28, http://www.min.uc.edu/me/news_folder/files/EconImpact_IUCRCMtg_June9.2011(final).pdf .
Jorge Guzman and Scott Stern, “Nowcasting and Placecasting Entrepreneurial Quality and Performance,” Working Paper No. 20954 (Cambridge, Mass.: National Bureau of Economic Research, 2015), http://www.nber.org/papers/w20954 .
John Hagedoorn and Nadine Roijakkers, “Small Entrepreneurial Firms and Large Companies in Inter-Firm R&D Networks: The International Biotechnology Industry,” in M.A. Hitt et al., eds., Strategic Entrepreneurship (Cambridge, Mass.: Blackwell, 2002).
Gerald Carlino and William Kerr, “Agglomeration and Innovation,” Harvard Business School Entrepreneurial Management Working Paper, No. 15-007 (Cambridge, Mass., 2014).
Ryan Decker, John Haltiwanger, Ron Jarmin, and Javier Miranda, “Where Has All the Skewness Gone? The Decline in High-Growth (Young) Firms in the U.S.” Working Paper No. 21776 (Cambridge, Mass.: National Bureau of Economic Research, 2016), http://www.nber.org/papers/w21776 .
Decker et al.’s identified industry groups draw heavily from the information sector but also from the information technology industries in the manufacturing sector and from scientific industries in the services sector.
Center for Regional Economic Competitiveness and Cromwell Schmisseur, “Program Evaluation of the US Department of Treasury State Small Business Credit Initiative” (2016), p. 62, https://www.treasury.gov/resource-center/sb-programs/Documents/SSBCI_pe2016_Full_Report.pdf .
U.S. Department of the Treasury, “State Small Business Credit Initiative (SSBCI),” https://www.treasury.gov/resource-center/sb-programs/Pages/ssbci.aspx .
Center for Regional Economic Competitiveness and Cromwell Schmisseur, “Program Evaluation,” p. 1.
Partnership for a New American Economy and Partnership for New York City, “Not Coming to America: Why the U.S Is Falling Behind in the Global Race for Talent,” (2012), http://www.renewoureconomy.org/sites/all/themes/pnae/not-coming-to-america.pdf .
Allie Bidwell, “Foreign Brain Drain a Call for Immigration Reform, Some Say,” U.S. News and World Report , May 7, 2014, http://www.usnews.com/news/articles/2014/05/07/report-33-percent-of-international-students-in-stem-fields .
Stephen Ezell, “A Research Investor’s Visa Would Spur U.S. Economic and Employment Growth,” The Innovation Files (blog), April 30, 2013, http://www.innovationfiles.org/a-research-investors-visa-would-spur-u-s-economic-and-employment-growth/#sthash.LODnPuEu.dpuf .
Dane Stangler and Jared Konczal, “Give Me Your Entrepreneurs, Your Innovators: Estimating the Employment Impact of a Startup Visa” (Kansas City, Mo.: Ewing Marion Kauffman Foundation, 2013), http://www.kauffman.org/~/media/kauffman_org/research%20reports%20and%20covers/2013/02/startup_visa_impact_final.pdf .
Peter Hall and David Soskice, Varieties of Capitalism: The Institutional Foundations of Comparative Advantage , (Oxford: Oxford University Press, 2001).
Bianca Bosker, “Best Products of CES 2011: The Coolest Gadgets from The Consumer Electronics Show,” Huffington Post (blog), May 25, 2011.
Lorin Hitt and Prasanna Tambe, “Measuring Spillovers From Information Technology Investments,” Proceedings of the 27 th International Conference on Information Systems, Milwaukee, Wis., 2006, p. 1793.
The National Science Foundation, Science and Engineering Indicators, 2016.
Nicholas Bloom and Rachel Griffith, “The Internationalization of R&D,” Fiscal Studies 22, no. 3 (2001), 337–55.
Coopers & Lybrand, “Economic Benefits of the R&D Tax Credit” (New York, 1998).
Kenneth J. Klassen, Jeffery A. Pittman, Margaret P. Reed, and Steve Fortin, “A Cross-National Comparison of R&D Expenditure Decisions: Tax Incentives and Financial Constraints,” Contemporary Accounting Research 21, no. 3 (2004), 639–80.
Luke Stewart, Jacek Warda, and Robert Atkinson, “We’re #27!: The United States Lags Far Behind in R&D Tax Incentive Generosity” (Washington: Information Technology and Innovation Foundation, 2012).
New Mexico Small Business Assistance Program, http://www.nmsbaprogram.org/.
Stephen J. Ezell and Robert D. Atkinson, “Fifty Ways to Leave Your Competitiveness Woes Behind: A National Traded Sector Competiveness Strategy” (Washington: Information Technology and Innovation Foundation, 2011): 20-21, http://www2.itif.org/2012-fifty-ways-competitiveness-woes-behind.pdf .
Jose-Maria Fernandez, Roger Stein, and Andrew Lo, “Commercialization Biomedical Research Through Securitization Techniques,” Nature Biotechnology 30 (2012).
The U.S. tax credit has been heavily studied. For example, the former U.S. Congressional Office of Technology Assessment concluded that, “For every dollar lost in tax revenue, the R&D tax credit produces a dollar increase in reported R&D spending, on the margin.” See Bronwyn Hall, “The Effectiveness of Research and Experimental Tax Credits: Critical Literature Review and Research Design” (Washington: Office of Technology Assessment, 1995), http://emlab.berkeley.edu/~bhhall/papers/BHH95%20OTArtax.pdf . See also Coopers & Lybrand, Economic Benefits of the R&D Tax Credit (New York, 1998).
Information Technology and Innovation Foundation, “Winning the Race Memo: Corporate Taxes” (2012), http://www2.itif.org/2012-wtr-taxes.pdf?_ga=1.202252433.1806060799.1471894729 .
Robert D. Atkinson and Scott Andes, “Patent Boxes: Innovation in Tax Policy and Tax Policy for Innovation,” (Washington: Information Technology and Innovation Foundation, 2011), http://www.itif.org/files/2011-patent-box-final.pdf .
See Stephen J. Ezell, “‘Innovation Box’ Proposal Would Stimulate U.S. R&D and Innovation,” The Innovation Files , July 31, 2015, http://www.innovationfiles.org/innovation-box-proposal-would-stimulate-u-s-rd-and-innovation/ , and United States Senate Committee on Finance. “The International Tax Bipartisan Tax Working Group: Final Report,” July 7, 2015, http://www.finance.senate.gov/imo/media/doc/The%20International%20Tax%20Bipartisan%20Tax%20Working%20Group%20Report.pdf .
Joe Kennedy, “Tax Proposals Attempt to Bridge the “Valley of Death” for Small Research Firms,” The Innovation Files , March 24, 2015, http://www.innovationfiles.org/tax-proposals-attempt-to-bridge-the-valley-of-death-for-small-research-firms/ .
Ernst & Young, Economic Impact of Tax Proposals Affecting Research-Intensive Start-Up Businesses and Qualified Small Business Companies (Washington: Ernst & Young, July 2013), http://smallbusinessinnovators.org/userfiles/ey%20csbi%20report%20economic%20impact%20of%20tax%20proposals%20for%20start-ups.pdf .

Nicol Turner Lee

August 8, 2024

Darrell M. West, Roxana Muenster

August 5, 2024

August 1, 2024

Fostering Integrity in Research (2017)

Chapter: 3 important trends and challenges in the research environment, 3 important trends and challenges in the research environment.

By working collaboratively, researchers can hope to answer questions never addressed before, including those with substantial influence on society. At the same time, today’s international, interdisciplinary, team-oriented, and technology-intensive research has created an environment more fraught with the potential for error and distortion.

— Indira Nath and Ernst-Ludwig Winnacker (2012)

Synopsis: A number of the elements in the research environment that were identified in the early 1990s as perhaps problematic for ensuring research integrity and maintaining good scientific practices have generally continued along their long-term trend lines, including the size and scope of the research enterprise, the complexity of collaboration, the growth of regulatory requirements, and the importance of industry sponsorship and entrepreneurial research. Several important new trends that were not examined in the 1992 Responsible Science report have also emerged, including the pervasive and growing importance of information technology in research, the globalization of research, and the increasing relevance of knowledge generated in certain fields to policy issues and political debates. These changes—the growing importance of information technology in particular—have led to important shifts in the institutions that support and underlie the research enterprise, such as scholarly publishing. They also have important implications for the ability of researchers, research institutions, journals, and sponsors to foster integrity and prevent research misconduct and detrimental research practices.

The 1992 report Responsible Science: Ensuring the Integrity of the Research Process devoted a chapter to describing the contemporary research environment and outlining the most important changes that had occurred over the previous decades ( NAS-NAE-IOM, 1992 ). Responsible Science also described several additional features of the U.S. research scene of the early 1990s that had become the subject of discussion and concern due to possible negative impacts on the research environment, including research integrity ( NAS-NAE-IOM, 1992 ). This chapter will first explore the research environment issues identified in 1992—except for the reward system in science, which is covered in Chapter 6 —and describe trends over the past two decades. The second part of the chapter will

explore several important shifts in the research environment that have appeared since 1992 and were not considered in Responsible Science . These shifts carry several important implications for research integrity.

HOW RESEARCH ENVIRONMENT ISSUES IDENTIFIED IN RESPONSIBLE SCIENCE HAVE EVOLVED SINCE THE EARLY 1990s

Size and scope of the research enterprise.

The 1992 report’s overview described growth in the size and scope of the research enterprise. The report observed that research in the pre–World War II United States—academic research in particular—was a mostly small-scale avocation of individual scientists, supported by limited funding from industry, government, and foundations. Following the significant wartime contributions of research efforts such as MIT’s Radiation Laboratory, federal support for science and engineering research increased rapidly. By 1991, research and development (R&D) was a $160 billion (current dollars) enterprise in the United States, employing about 744,000 people in industrial, academic, and governmental laboratories and producing more than 140,000 research articles annually ( NSB, 1996 , 2014b ; OECD, 2015 ).

Over the following two decades, the enterprise has continued to grow, with U.S. R&D totaling $456 billion in 2013, R&D employment rising to about 1,252,000, and the number of published research articles reaching more than 412,000 ( NSB, 2014b , 2016 ; OECD, 2015 ). The 1992 report paid particular attention to the growth in academic research and federal support, and this growth has continued. Between 1991 and 2014, academic R&D grew from around $17.5 billion to $67.1 billion, with federal support constituting 60–75 percent of the total ( NSB, 2016 ). 1 The number of science, engineering, and health doctorate holders employed in academia rose from 211,000 in 1991 to almost 309,000 in 2013 ( NSB, 2016 ). The number of PhDs awarded in science and engineering more than doubled, from approximately 19,000 in 1988 to almost 37,000 in 2013, with an increasing percentage of these doctorate recipients going to work outside academia ( NSB, 2016 ).

The 1992 Responsible Science report raised the concern that the increased size of the research enterprise might put stresses on key capabilities, such as the “overall workload associated with critical evaluation” ( NAS-NAE-IOM, 1992 ). The number and capacity of effective peer reviewers might not be keeping pace with the relentless growth in manuscripts and proposals. Concerns also have been raised about the increasing use of bibliometric-based metrics in evaluating

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1 From 2010, the total includes academic R&D outside of science and engineering, which adds several billion dollars.

research as a substitute or replacement for expert judgment ( P. B. Lowry et al., 2012 ).

Complexity of Collaboration

Responsible Science described the growth of collaborative research after World War II, which has continued since the early 1990s. In contrast to earlier times, when articles with more than four co-authors and work involving more than one laboratory or research institution were rare, collaborative research of various types is now very common. The number of authors listed on articles is only one measure of collaboration, but it clearly reveals the overall trend. In an analysis of approximately 20 million research articles published since 1955 and 2 million patents registered since 1975, the number of authors on scientific papers grew from an average of 1.9 in 1955 to 3.5 in 2000 ( Wuchty et al., 2007 ). At the same time, single-author articles are becoming less common, constituting only about 11 percent of the total in 2012 ( King, 2013 ).

Several factors are driving the trend toward larger-scale research in general and in specific fields ( Stephan, 2012a ). These include the need for more elaborate and expensive equipment and the often related requirement for a variety of specialized skills and knowledge. These characteristics of “big science” have long been a given in fields such as high-energy physics and astronomy, in the form of particle accelerators such as the Large Hadron Collider and modern telescopes. They have become more prominent recently in many areas of the life sciences as well. In describing the results of large life sciences research projects such as the Human Genome Project and ENCODE (Encyclopedia of DNA Elements), former Science editor-in-chief Bruce Alberts (2012) noted that “the increased efficiency of data production by such projects is impressive.” In addition, as will be discussed in more detail below, the information technology revolution has radically lowered the costs of communication and collaboration of all types, including research collaboration.

Another factor contributing to the growth of team research has been an increase in the amount of interdisciplinary research. Interdisciplinary research efforts have continued to grow in importance and are extremely diverse ( Derrick et al., 2012 ). Interdisciplinary teams can range from local and informal to transnational and highly structured. They can be composed largely or entirely of researchers accustomed to working within a disciplinary framework, or they can consist partly or wholly of researchers who have been educated and have worked in interdisciplinary fields. Integration of knowledge from multiple disciplines can occur within the mind of a single person or through the collaborative efforts of a large team. For example, with the advent of “big data” and computational science, statisticians are increasingly included on projects where researchers have collected domain-specific data that they do not have the expertise to analyze. Interdisciplinary research is often focused on problems that have important so-

cietal implications. One current example of a growing interdisciplinary field is synthetic biology, which seeks a fundamental understanding of the workings of living systems along with the capability of re-creating living systems for a variety of applications in areas such as medicine and the environment. Synthetic biology research involves “biologists of many specialties, engineers, physicists, computer scientists, and others” ( NRC, 2010 ).

According to one analysis of trends in interdisciplinary research in six research fields, the growth of interdisciplinarity has been modest—about 5 percent—even as the number of authors per article has grown by 75 percent ( Porter and Rafols, 2009 ). This study found that the number of disciplines cited by papers in these six fields—mathematics, neurosciences, electrical and electronic engineering, biotechnology and applied microbiology, research and experimental medicine, and atomic, molecular, and chemical physics—has increased, but the distribution of citations is within neighboring research areas and has only slightly broadened. According to the authors, “These findings suggest that science is indeed becoming more interdisciplinary, but in small steps—drawing mainly from neighboring fields and only modestly increasing the connections to distant cognitive areas.”

Collaborative science requires that researchers focus at least some attention on coordination and interaction, which in theory might detract from the time and effort devoted to research. Yet Wuchty et al. (2007) found that multiauthor teams produced more highly cited work in each broad area of research and at each point in time. In addition, though solo authors in 1955 were more likely to produce papers that were highly cited, suggesting that these papers reported on the most influential concepts, results, or technologies, teams are more likely to produce highly cited papers today. As the authors wrote, “solo authors did produce the papers of singular distinction in science and engineering and social science in the 1950s, but the mantle of extraordinarily cited work has passed to teams by 2000.”

As more researchers work collaboratively and as the size of teams grows, the relationships among team members can become more complex. Team members can be at different research institutions and have different disciplinary backgrounds. Teams can contain researchers at all stages of their careers, from undergraduate and graduate students involved in research to senior researchers. The diversity and geographic spread of people involved in teams can create opportunities for miscommunication, misunderstandings, unrealistic expectations, and unresolved disputes. Whether these opportunities account for part of the increase in reports of undesirable research practices is unclear, but they can make the research environment more complicated and difficult than when teams were smaller, colocated more regularly, and more homogeneous in terms of discipline or nationality.

As research projects are undertaken by larger groups that bring together a greater diversity of expertise, encompass a broader range of disciplines, and strive for a greater degree of synthesis, the potential for misunderstandings can grow. Coordination of research inevitably becomes more complex, and the members

of a team may have less familiarity with the discipline-specific practices of other team members, making it more difficult for each collaborator to check and verify the work done by others. As the number of collaborators increases, there is more scope for disagreements over the allocation of credit. It becomes much more challenging to reward and recognize individual contributions, which has a big impact on junior researchers in particular. In addition, the mentoring of students in responsible research practices can become more impersonal and generic. The mental model of graduate education and training in which mentors work closely with graduate students and are able to take the time and effort to ensure that mentees understand the rules and can follow them may describe a smaller and smaller part of the research enterprise. Interdisciplinary work increases the possibility that the standards and expectations of different fields may come into conflict.

Regulation and Accountability

The 1992 report also noted that research activities were “increasingly subject to government regulations and guidelines that impose financial and administrative requirements” in areas such as laboratory safety, human subjects protection, drug-free workplace assurance, laboratory animal care, and the research use of recombinant DNA and toxic and radioactive materials. Along with the relatively new requirements and regulations related to research misconduct, the development of which is covered in Chapter 4 of this report, ensuring compliance with these expanding regulatory requirements had resulted in an expansion of administrative and oversight functions and staff at universities and required increasing time and attention from investigators. As an increasing percentage of faculty time goes toward fulfilling the requirements of various regulations and reporting requirements, research-related tasks such as mentoring and checking the work of subordinates may be shortchanged.

The administrative and regulatory compliance burden on research institutions and researchers remains significant. For example, respondents to a 2012 survey of 13,453 principal investigators undertaken by the Federal Demonstration Partnership estimated that, on average, 42 percent of the time they spent working on federally funded research projects was devoted to meeting regulatory and administrative requirements ( Schneider et al., 2012 ). According to the survey results, areas of regulation where compliance is particularly time consuming include those related to finances, personnel, and effort reporting. In 2014 the National Science Board issued a report that analyzes the regulatory compliance burden on faculty and makes recommendations for how it might be reduced ( NSB, 2014c ). A 2016 National Academies report evaluated current approaches to regulating academic research and made recommendations for achieving the goals of regulation while reducing financial and time burdens on institutions and faculty ( National Academies of Sciences, Engineering, and Medicine, 2016 ).

Industry-Sponsored Research and Other Research Aimed at Commercialization

Increasingly, the scientific enterprise has been recognized not only as a place to expand knowledge but also as an engine for the creation of new products, novel therapies for disease, improved technologies, and new industries and jobs. To quote President Obama (2009b) , “scientific innovation offers us a chance to achieve prosperity.” The economic potential of science, however, also offers unique challenges to the responsible conduct of research, which were described in Responsible Science . These challenges can be seen in scientific research conducted in an industrial setting, scientific research conducted in university and research institutions in collaboration with industry, and university research that leads to entrepreneurial efforts by the researchers, requiring that they integrate both within themselves and in their professional behavior often divergent cultural understandings about the nature, purposes, and outcomes of research. These challenges include the potential of economic incentives to introduce scientific bias, the perception of conflict of interest due to economic incentives, and the potential effect of intellectual property protection on the timely dissemination of knowledge.

Industry funds and conducts a substantial amount of research in the United States. For both basic and applied research, as defined by the National Science Foundation, industry conducts 40 percent of the U.S. total ( NSB, 2016 ). Even considering just basic research, industry conducts approximately 24 percent, almost 90 percent of which it funds itself. Unlike academic research, corporate research is often driven by the needs of a company to remain financially solvent and to be accountable to shareholders. Corporate researchers often exist under hierarchical chains of supervision where management maintains greater control over the research process.

Only a fraction of the results of industry-funded research is published in the scientific and engineering literature and is thereby submitted to formal peer review. Of the articles published in 2013, authors from industry accounted for only 6 percent of the total, and that percentage has been declining over the past two decades ( NSB, 2014 ). This can be a product of the need to preserve intellectual property interests for trade secrets and obtaining patents. One consequence is that the knowledge gained in such research may not be widely disseminated or evaluated through the peer review process. This is not to say that such industry research is not of high quality or is not carefully reviewed. Companies can have strict protocols regarding the collection, documentation, and storage of data, particularly when there are strong regulatory or economic reasons to do so. Checking mechanisms may be built into industrial research to verify especially critical results ( Williams, 2012 ). And, as with all research, the use of research results in subsequent activities—including the production of commercial products—provides further checks on the validity of results.

However, both industrial research and industry-sponsored research in aca-

demic settings have been found to occasionally show signs of both unintentional and intentional bias. 2 For example, one might observe bias in the lack of publication of results with negative consequences for the profitability of a product or in the restriction of published findings to those that reflect positively on a product. An extreme case is the tobacco industry, which undertook a systematic effort over the course of decades to obscure the harmful effects of smoking ( Proctor, 2011 ). Other examples include episodes of alleged ghostwriting in some medical research, including the Paxil case described in Appendix D and also discussed in Chapter 7 . Such research tarnishes all other research by demonstrating that research agendas and techniques can be manipulated so severely as to subvert truth to other interests. Many journals have moved to reporting the financial interests of authors, whether the work has an industry sponsor or not, so that readers are made aware of the potential for bias.

In addition to collaborations with established industries, academic institutions have increasingly encouraged entrepreneurship and innovation for commercialization, particularly since the passage of the Bayh-Dole Act in 1980, which allowed institutions to hold patents on innovations produced with federal funding. Having seen the success of academic research products such as Gatorade and the Google search algorithm patent in generating revenue, institutions may hope that their researchers can achieve similar results. For fiscal 2011 the Association of University Technology Managers reported that the 186 institutions responding to its annual survey earned a total of $1.5 billion in running royalty income, executed 4,899 licenses, created 591 commercial products, and formed 671 start-up companies from their research (AUTM, 2012).

One result of the commercialization of university-generated technology is that the need to manage possible conflicts of interest has become an important issue in academic settings. A 2009 Institute of Medicine report explores the issue of institutional conflict of interest in more detail ( IOM, 2009 ). Individual conflicts of interest exist if the investigator is also the founder of a company conducting research or has a significant monetary stake in the research. This can also apply to an institution if it owns part of a company or has a financial stake in a faculty member’s research findings. Under the U.S. Financial Conflict of Interest (FCOI) policy, research funded by the Public Health Service requires institutions to maintain and enforce a FCOI policy; manage, reduce, or eliminate identified conflicts; report identified conflicts, the value of the conflicts, and a management plan to the Public Health Service Awarding Component; and publish significant financial interests of any personnel involved in the research on a publicly accessible website ( HHS, 2011b ). Currently, the Department of Health and Human Services does not have institutional regulations in the same manner as investigator FCOI regulations (required disclosure of FCOIs). Strengthened institutional FCOI regulations have been considered, but there is a need for further and separate consideration.

2 This is not meant to imply that research that is not sponsored by industry is necessarily unbiased.

The National Science Foundation policy is consistent with that of the Department of Health and Human Services. Regulations of individual financial conflicts of interest are further discussed in Chapter 7 and are also addressed in the context of best practices in Chapter 9 .

Additional individual conflicts of interest, or secondary interests, can also affect a research study, including political biases, white hat bias, commitment conflicts, career considerations, and favors to others ( IOM, 2009 ; Lesser et al., 2007 ). A political opinion, bias, or long-standing scientific viewpoint toward one position or another may influence the interpretation of findings, despite contradictory evidence ( Lesser et al., 2007 ). Similarly, white hat bias, or “bias leading to distortion of information in the service of what may be perceived to be righteous end,” also has the potential to influence conclusions ( Cope and Allison, 2010 ). An example of a conflict of commitment would be a principal investigator who does not have the time to perform all the duties for which he or she is responsible, such as securing funding, setting the overall direction for research in a lab, administrative responsibilities, and adequately supervising graduate students and postdocs. Secondary interests are rarely regulated, as they are considered a lesser incentive than financial interests.

Closer linkages between research and commercialization have introduced the possibility of financial gain from research more widely across the enterprise. This can pose challenges in terms of defining appropriate behavior and establishing guidelines for dealing with conflicts of interest, and it can complicate collaborations among individual researchers and among organizations.

MAJOR CHANGES IN THE RESEARCH ENVIRONMENT SINCE 1992

Information technologies in research.

The continued exponential rise in the power of information and computing technologies has had a dramatic impact on research across many disciplines. These technologies have not only increased the speed and scope of research but have made it possible to conduct investigations that were not possible before. Information technology advances have enabled new forms of inquiry such as those based on numerical simulation of physical and biological systems and the analysis of massive datasets to detect and assess the nature of relationships that otherwise would go unseen.

The contrast in computing capabilities since the publication of Responsible Science is especially stark. In 1992, use of e-mail was less than a decade old, and the World Wide Web had just been invented and was not widely known. Three-and-a-half-inch floppy disks for data storage had replaced 5-1/4-inch disks just a few years before. People made telephone calls on landlines, used letters to communicate in writing, and circulated preprints via the postal system. For

young researchers, the circumstances in which research was conducted in 1992 are almost entirely foreign.

One effect of information technologies in many areas of research has been to introduce intermediate analyses of considerable complexity between the “raw” data gathered by sensors and observations, and produced by data-creating devices such as DNA sequencers, and the results of research. Re-creating the steps from data to results can be impossible without a detailed knowledge of data production and analyzing software, which sometimes is dependent on the particular computer on which the software runs. This intermediate analysis complicates the replication of scientific results and can create opportunities to manipulate analyses so as to achieve desired results, as well as undermine the ability of others to validate findings.

Digital technologies can pose other temptations for researchers to violate the standards of scientific practice. For example, the manipulation of images using image-processing software has caused many journals to implement spot checks and other procedures to guard against falsification. The inappropriate application of statistical packages can lead to greater confidence in the results than is warranted. Data-mining techniques can generate false positives and spurious correlations. In many fields, the development of standards governing the application of technology in the derivation of research results remains incomplete even as continuing technological advances raise new issues. In a recent paper, two prominent biologists wrote, “Although scientists have always comforted themselves with the thought that science is self-correcting, the immediacy and rapidity with which knowledge disseminates today means that incorrect information can have a profound impact before any corrective process can take place” ( Casadevall and Fang, 2012 ).

The widespread utilization of information technologies in research may also introduce new sources of unintentional error and irreproducibility of results. A survey of researchers who utilize species distribution modeling software found that only 8 percent had validated the software they had chosen against other methods, with higher percentages relying on recommendations from colleagues or the reputation of the developer ( Joppa et al., 2013 ). The latter approaches pose risks of incorrect implementation and error for the research being pursued, particularly if software is not shared or subjected to critical review. Issues surrounding irreproducibility and information technologies are discussed further in Chapter 5 .

Besides affecting the conduct of research, information and communication technologies have transformed the communication of scientific results and interactions among researchers. In theory, if not always in practice, all the data contributing to a research result can now be stored electronically and communicated to interested researchers. This capability has contributed to a growing movement for much more open forms of research in which researchers work collectively on problems, often through electronic media ( Nielsen, 2012 ). However, this trend toward greater transparency has created tasks and responsibilities for research-

ers and the research enterprise that did not previously exist, such as creating, documenting, storing, and sharing scientific software and immense databases and providing guidance in the use of these new digital objects. For example, software produced by scientists in the course of analyzing the data is often carried out as a collaborative online process. This digitization makes it easier than ever to perform very complex analyses that not only lead to new discoveries but create new problems of opacity for the peer review process. And while technology is making many aspects of research more efficient, it may also create new tasks and responsibilities that are burdensome for researchers and that they may find difficult or impossible to fulfill.

The movement toward open science has encouraged the efforts of citizen scientists who are eager to monitor, contribute to, and in some cases criticize scientific advances ( Stodden, 2010 ). Review of scientific results from outside a research discipline can provide another check on the accuracy of results, but it also can introduce questions about the validity of findings that are not adequately grounded in knowledge of the research. Moreover, it can alter the relationship between researchers and the public in ways that require new levels of effort and sophistication among researchers involved in public outreach.

Advances in information technology are transforming the research enterprise, discipline by discipline, by changing the sorts of questions that can be addressed and the methods used to address them. There may be more opportunities to fabricate, falsify, or plagiarize, but there are also more tools to uncover such behavior. Issues related to research reproducibility and related practices are covered in Chapter 5 .

The Globalization of Research

Because knowledge passes freely across national borders, scientific research has always been an international endeavor. But this internationalization has intensified over the past two decades. Nations have realized that they cannot expect to benefit from the global research enterprise without national research systems that can absorb and build on that knowledge. As a result, they have incorporated science and technology into national plans and have established goals for increased R&D investments. They also have encouraged their own students and researchers to travel to other countries to study and work and have welcomed researchers from other countries. At the same time, private-sector companies have increased their R&D investments in other countries to take advantage of local talent, gain access to local markets, and in some cases lower their costs for labor and facilities. These and other trends, including cheaper transportation, better communications, and the spread of English as the worldwide language of science, are producing a new golden age of global science.

Once again, the trend is apparent in the author lists of scientific and engineering articles. Between 1988 and 2013, the percentage of science and engineer-

ing articles published worldwide with coauthors from more than one country increased from 8 percent to 19 percent ( NSB, 2016 ). Also, some countries have dramatically increased their representation in the science and engineering literature. Between 1999 and 2013, the average number of science and engineering articles published by Chinese authors rose 18.9 percent annually, so that by 2013 China, with 18 percent of the total, was the world’s second-largest national producer of science and engineering articles. Authors from China also increased their share of internationally coauthored articles from 5 percent to 13 percent between 2000 and 2010. Other countries that dramatically expanded their number of articles published included South Korea, India, Taiwan, Brazil, Turkey, Iran, Greece, Singapore, Portugal, Ireland, Thailand, Malaysia, Pakistan, and Tunisia, though some of these countries started from very low bases.

Another measure of the increasing internationalization of research is the number of foreign-born researchers studying and working in the United States. More than 193,000 foreign students were enrolled in U.S. graduate programs in science and engineering in 2013, and foreign-born U.S. science and engineering doctorate holders held 48 percent of postdoctoral positions in 2013 ( NSB, 2016 ). Science and engineering doctorate holders employed in U.S. colleges and universities who were born outside the United States increased from 12 percent in 1973 to nearly 27 percent in 2013. The United States remains the destination for the largest number of foreign students at the graduate and undergraduate levels, though its share of foreign students worldwide declined from 25 percent in 2000 to 19 percent in 2013.

Internationalization offers many benefits to the research enterprise. It can speed the advance of knowledge and permit projects that could not be done by any one country working alone. It increases cooperation across borders and can contribute to a reduction in tensions between nations. It enhances the use of resources by reducing duplication of effort and by combining disparate skills and viewpoints. The experiences students and researchers gain by working in other countries are irreplaceable.

But globalization also can complicate efforts to ensure that researchers adhere to responsible research practices ( Heitman and Petty, 2010 ). Education in the responsible conduct of research, while far from universal among U.S. science and engineering students, is nevertheless more extensive in the United States than in many other countries ( Heitman et al., 2007 ). Codes of responsible conduct differ from country to country, despite efforts to forge greater international consensus on basic principles ( ESF-ALLEA, 2011 ; IAC-IAP, 2012 ). In some countries with rapidly developing research systems, research misconduct and detrimental research practices appear to be more common than in countries with more established research systems ( Altman and Broad, 2005 ). Students from different countries may have quite different expectations regarding such issues as conflicts of interest, the deference to be accorded instructors and mentors, the treatment of research subjects, the handling of data, and the standards for authorship. For

example, one issue often noticed with foreign students in the United States is the different standards they apply to the use of ideas and phrases from others, which can lead to problems with plagiarism ( Heitman and Litewka, 2011 ).

As the sizes of individual national research enterprises grow and become more competitive, institutions and sponsors can experience more problems with research misconduct. Differences in national policy frameworks may constitute barriers to cross-border collaboration, but efforts are being made to harmonize or at least make these frameworks interoperable. Collaboration among researchers from different countries and cultures may expose differences in training, expectations, and values that affect behavior.

Relevance of Research Results to Policy and Political Debates

The rapid expansion of government support for scientific research in the decades after World War II was spurred by recognition of the importance of new knowledge in meeting human needs and solving problems. Over the past few decades, the link between scientific knowledge and issues in the broader society has become ever more apparent. Science is a critical factor in public discussions of and policy decisions concerning stem cells, food safety, climate change, nuclear proliferation, education, energy production, environmental influences on health, national competitiveness, and many other issues. Although all these topics cannot be covered here, this section will describe several of the key issues affecting science, policy, and the public and how they affect (and are affected by) research integrity.

To begin with, the federal government itself performs a significant amount of research through government laboratories, some of which is published. Federal agencies that perform research generally have policies and procedures in place to investigate allegations of research misconduct in their intramural programs (see NIH, 2012a , for an example of such policies and procedures, and see Chapter 7 for a more detailed discussion).

In addition, the Obama administration led an initiative on scientific integrity in the federal government starting in 2010 ( Holdren, 2010 ). Executive departments and agencies were instructed by the Office of Science and Technology Policy (OSTP) to develop policies that address a range of issues, including promoting a culture of scientific integrity, ensuring the credibility of government research, fostering open communication, and preventing bias from affecting how science is used in decision making or in communications with the public. The exercise is largely complete, as agencies have developed and implemented policies in response to the Office of Science and Technology Policy guidance ( Grifo, 2013 ; OSTP, 2013 ).

Research also comes into play in debates and decisions over numerous contentious policy issues. Science is not the only factor in these discussions. Many considerations outside of science influence policy choices, such as personal and

political beliefs, lessons from experience, trial-and-error learning, and reasoning by analogy ( NRC, 2012b ). To contribute to public policy decisions, researchers must be able to separate their expertise as scientists from their views as advocates for particular public policy positions. Furthermore, they often contribute to these discussions outside the peer-reviewed literature, whether in public forums, blogs, or opinion articles in newspapers. According to the document Responsible Conduct in the Global Research Enterprise: A Policy Report ( IAC-IAP, 2012 ), “Researchers should resist speaking or writing with the authority of science or scholarship on complex, unresolved topics outside their areas of expertise. Researchers can risk their credibility by becoming advocates for public policy issues that can be resolved only with inputs from outside the research community.”

One example of an area where science, public debate, and policy making have been closely tied and contentious in recent years is climate science. This has raised challenges for researchers and the institutions through which scientists provide policy advice. According to a recent National Research Council report, “Climate change is occurring, is very likely caused by human activities, and poses significant risks for a broad range of human and natural systems. The environmental, economic, and humanitarian risks of climate change indicate a pressing need for substantial action to limit the magnitude of climate change and to prepare to adapt to its impacts” ( NRC, 2011 ). The global climate is a highly complex system, and there is considerable uncertainty about the timing and magnitude of climate change, the effect of measures to reduce greenhouse gas emissions from human activities, regional impacts, and many other issues. Effectively limiting greenhouse gas emissions presents economic and technological challenges and affects countries and industries differently, making policy changes by individual countries difficult. The development of the United Nations Framework Convention on Climate Change and its evolution over time illustrate the barriers to collective action on a global level. 3

In this environment of significant uncertainty on key scientific questions, difficult policy choices, the possibility of large impacts on powerful economic interests, and highly mobilized advocacy operations on all sides of the climate change issue, the climate science community has faced challenges in maintaining its credibility and public trust as it contributes its expertise. This experience might provide lessons on what researchers and scientific institutions need to do and what they need to avoid as highly charged issues arise with important scientific components. For example, the Intergovernmental Panel on Climate Change (IPCC), which was awarded the Nobel Peace Prize in 2007, is an international body that undertakes periodic scientific assessments of climate science and constitutes the primary mechanism for scientists to inform policy makers at the global level. In November 2009 the unauthorized leak of e-mail conversations among climate researchers, a number of whom were heavily involved with the IPCC process,

3 See http://unfcc.int./meetings/warsaw_nov2013/meeting/7649.php .

appeared to reveal a number of questionable actions, including efforts to limit or deny access to data, failure to preserve raw data, and efforts to influence the peer review practices of journals. While subsequent investigations cleared the researchers of misconduct, the “Climategate” scandal and subsequent discovery of errors in IPCC’s most recent assessment raised questions about the quality and impartiality of the organization’s work. A 2010 study by the InterAcademy Council recommended a number of reforms in IPCC governance and management, review processes, methods for communicating uncertainty, and transparency ( IAC, 2010 ). One possible lesson from the recent climate change experience is that researchers, institutions, and fields whose work becomes relevant to controversial policy debates will need to consciously examine and upgrade their practices in areas such as data access and transparency ( NAS-NAE-IOM, 2009a ).

Recent high-profile international cases in which scientists have been criticized and even prosecuted based on their advisory activities include the statements of scientists in the aftermath of the Fukushima earthquake and tsunami in 2011, and the manslaughter convictions of seismologists whose statements were misconstrued by a government official, Bernardo De Bernardinis, to mean that there was no risk of danger immediately prior to an earthquake in L’Aquila, Italy, that killed more than 300 people ( Cartlidge, 2012 ; Jordan, 2013 ; Normile, 2012 ). An appeals court overturned the convictions 2 years later for the six seismologists involved, but not for De Bernardinis ( Cartlidge, 2014 ).

Other issues involving science and policy that raise questions about integrity seemingly appear in the media on a weekly basis. During 2012, controversy erupted over a University of Texas sociologist’s research findings that adult children of parents who had same-sex relationships fared worse than those raised by parents who had not had same-sex relationships; his research methodologies have been severely criticized, but an institutional inquiry cleared him of research misconduct ( Peterson, 2012 ). A federal appeals court upheld a South Dakota statute requiring doctors to tell women seeking abortions that they face an increased risk of suicide; despite extremely weak research evidence to support the statute, the court decided not to strike it down as an undue burden on abortion rights or on First Amendment grounds ( Planned Parenthood Minnesota, N.D., S.D. v. Rounds, 2012 ). A French paper found that rats consuming genetically modified corn developed more tumors and died earlier than a control group, although food safety agencies have stated that the sample sizes were too small to reach a conclusion ( Butler, 2012 ). And a criminal investigation of a Texas state agency established to fund research on cancer prevention and treatment revealed that some awards were made without scientific review, which led to a wave of resignations among staff and oversight board members ( Berger and Ackerman, 2012 ). Needless to say, these cases underscore the salient role of scientific research in policy discussions.

For researchers, exercising responsibility in relations with society encompasses an increasing array of issues. For example, health and social science research in some communities, such as Native American tribes, requires adher-

ence to community rules for gaining approval. Research on people’s behavior on social networking websites raises questions about how human subject protections apply. Some emerging areas of research, such as crisis mapping and monitoring, raise human rights issues ( AAAS, 2012 ). Finally, researchers in the life sciences are being asked to exercise responsibility in the area of preventing the misuse of research and technology ( IAP, 2005 ).

Research findings are increasingly relevant to a broader range of policy-relevant questions, raising the magnitude of possible negative consequences of research misconduct and detrimental research practices. Researchers in a variety of fields are faced with more complicated choices with ethical dimensions. In this environment, maintaining rigorous peer review processes in scientific journals is a critical task. Decisions based on science suffer when non-peer-reviewed science, or science that was not well reviewed, is used.

TRENDS IN RESEARCH AND IMPLICATIONS FOR AUTHORSHIP

Decisions about the authorship of research publications are an important aspect of the responsible conduct of research. Although many individuals other than those who conceive of and implement a research project typically contribute to the production of successful research, authors are considered to be the person or persons who made a significant and substantial contribution to the production and presentation of the new knowledge being published. A number of the conventions and practices that constitute scientific authorship have been influenced by the trends discussed previously in this chapter. Tracing how trends in research such as globalization and technology are affecting authorship provides a useful window into how research is changing more broadly.

Authorship practices have evolved to support the development and distribution of new knowledge, engaging the powerful human motivation to discover and receive credit for discovery. Researchers are often evaluated, rightly or wrongly, by the quantity and quality of their work, as measured by the number of their publications, the prestige of the journals in which their publications appear, and how widely cited their publications are. Authorship also serves to establish accountability for published work. For example, authors are responsible for the veracity and reliability of the reported results, for ensuring that the research was performed according to relevant laws and regulations, for interacting with journal editors and staff during publication, and for defending the work following publication ( Smith and Williams-Jones, 2012 ).

Authorship practices vary between disciplines. Professional and journal standards and policies on authorship also vary. For example, in some disciplines the names of authors are listed alphabetically, while in other disciplines names are listed in descending order of contribution. In some disciplines, senior researchers are listed last and in others they are listed first.

At least three significant factors have changed authorship practices in recent

decades. First, the degree to which researchers make use of technology and the ways in which they use technology have changed dramatically. Researchers now frequently rely on computer software and hardware for many of the processes and analyses they undertake. They rely more on sophisticated software and computer models both in the analysis and in the presentation of results. The extent to which researchers understand how these tools affect data and results is a topic of concern in 21st-century research. Second, as a result of new information and communication technologies, especially the Internet, researchers engage in much more collaboration at a distance. This facilitates national and global collaboration and can lead to larger, more broadly scoped projects. Data gathering and analysis can be parsed out to different locations, with information potentially easily accessed and shared regardless of location. Researchers are able to electronically maintain frequent contact, have group meetings, and coauthor documents. Third, as a result of software and hardware developments, huge databases of information can be gathered and used, and researchers have access to and must deal with much more information than ever before. Consequently, researchers have to manage data in new ways and may be held to higher standards of knowing and understanding other research that has been done in their area.

These changes raise a variety of challenges to researchers and the research enterprise. For example, in part because of the increased scale of research, the number of authors listed on papers in some disciplines has grown considerably. Extreme examples include the 1993 Global Utilization of Streptokinase and Tissue Plasminogen, or GUSTO, paper in the New England Journal of Medicine , which involved 976 authors ( GUSTO Investigators, 1993 ), and a 1997 Nature article on genome sequencing that had 151 authors ( Kunst et al., 1997 , from Smith and Williams-Jones, 2012 ). The recent joint paper from the two teams collaborating on the mass estimate of the Higgs boson particle lists more than 5,000 authors ( Castelvecchi, 2015 ). The original papers reporting the discovery of the Higgs boson had approximately 3,000 authors each ( Hornyak, 2012 ). How can the primary author or authors be responsible for the work of a hundred individual researchers who are geographically dispersed and come from a wide range of disciplines? When an error is found or an accusation of wrongdoing is made, the problem has to be traced back to the component of the research that is called into question. In the process of tracing back the possible wrongdoing, the primary author or authors, while accountable, may not understand the area or have had much control over the researchers involved. The primary author or authors may be accountable but not blameworthy. These challenges are complicated by disciplinary differences in authorship conventions.

Chapter 7 explores the challenges to research integrity arising in the area of authorship, and Chapter 8 considers alternatives for addressing them.

The integrity of knowledge that emerges from research is based on individual and collective adherence to core values of objectivity, honesty, openness, fairness, accountability, and stewardship. Integrity in science means that the organizations in which research is conducted encourage those involved to exemplify these values in every step of the research process. Understanding the dynamics that support – or distort – practices that uphold the integrity of research by all participants ensures that the research enterprise advances knowledge.

The 1992 report Responsible Science: Ensuring the Integrity of the Research Process evaluated issues related to scientific responsibility and the conduct of research. It provided a valuable service in describing and analyzing a very complicated set of issues, and has served as a crucial basis for thinking about research integrity for more than two decades. However, as experience has accumulated with various forms of research misconduct, detrimental research practices, and other forms of misconduct, as subsequent empirical research has revealed more about the nature of scientific misconduct, and because technological and social changes have altered the environment in which science is conducted, it is clear that the framework established more than two decades ago needs to be updated.

Responsible Science served as a valuable benchmark to set the context for this most recent analysis and to help guide the committee's thought process. Fostering Integrity in Research identifies best practices in research and recommends practical options for discouraging and addressing research misconduct and detrimental research practices.

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The importance of measures undertaken to improve the quality of life in the problem areas: a case study in warmia and mazury region in poland.

1. Introduction

2. materials and methods, 2.1. study area, 2.2. methods and data.

Construction, repairs and conversion of residential and commercial buildings, technical infrastructure facilities and other real property transferred without prior restoration to a proper technical condition;
Construction, repairs or conversion of energy, water supply and sewerage, heating and telecommunication devices, facilities or systems transferred prior to their restoration to a proper technical condition;
Educational, cultural and tourist projects carried out in rural areas.

3.1. The Role of State Institutions in the Development of Problem Areas

3.2. non-repayable financial support provided by the nsca branch olsztyn, 3.3. survey research, 4. discussion, 5. conclusions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Click here to enlarge figure

Ordinal	NSCA Branch	Non-Repayable Financial Support in Years [%]
Ordinal	NSCA Branch	2017	2018	2019	2020	2021	2022	2023
1	OT Białystok	0.00	0.00	0.00	0.00	0.00	0.00	0.00
2	OT Bydgoszcz	0.77	0.00	2.80	1.78	3.79	1.93	6.91
3	OT Częstochowa	0.00	0.00	0.00	0.00	0.00	0.00	0.00
4	OT Gorzów Wielkopolski	0.29	0.55	2.80	0.92	4.17	5.81	3.58
5	OT Kielce	0.00	4.08	2.39	0.55	0.90	3.52	1.18
6	OT Koszalin	0.00	0.24	0.00	1.53	3.57	0.00	1.95
7	OT Kraków	0.00	0.00	0.00	0.00	0.00	0.00	0.00
8	OT Lublin	0.25	0.17	2.14	0.00	1.71	0.58	4.94
9	OT Łódź	0.00	0.46	0.74	0.47	1.90	1.77	1.77
10	OT Olsztyn	43.36	34.23	27.69	50.06	42.09	43.37	41
11	OT Opole	1.31	4.41	4.33	2.66	4.24	2.70	1.29
12	OT Poznań	7.58	0.41	0.00	0.20	0.00	0.00	0.00
13	OT Pruszcz Gdański	8.88	17.09	21.73	7.73	6.57	8.17	2.23
14	OT Rzeszów	5.22	5.61	1.83	5.64	1.16	12.53	9.51
15	OT Szczecin	7.23	10.58	8.27	5.22	3.38	6.11	4.50
16	OT Warszawa	9.60	2.04	3.26	2.90	1.79	0.97	5.40
17	OT Wrocław	11.46	12.79	14.57	15.14	4.29	6.47	6.69
18	NSCA Head Office	4.05	7.35	7.46	5.19	20.43	6.06	9.25
TOTAL [%]		100	100	100	100	100	100	100
TOTAL [thousands of EUR]		6909	4873	4836	4562	4543	3912	6487

Chi-Square Value	p-Value	Degrees of Freedom
61.08	0.0021 (statistically significant)	33

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Kryszk, H.; Kurowska, K.; Marks-Bielska, R. The Importance of Measures Undertaken to Improve the Quality of Life in the Problem Areas: A Case Study in Warmia and Mazury Region in Poland. Sustainability 2024 , 16 , 6786. https://doi.org/10.3390/su16166786

Kryszk H, Kurowska K, Marks-Bielska R. The Importance of Measures Undertaken to Improve the Quality of Life in the Problem Areas: A Case Study in Warmia and Mazury Region in Poland. Sustainability . 2024; 16(16):6786. https://doi.org/10.3390/su16166786

Kryszk, Hubert, Krystyna Kurowska, and Renata Marks-Bielska. 2024. "The Importance of Measures Undertaken to Improve the Quality of Life in the Problem Areas: A Case Study in Warmia and Mazury Region in Poland" Sustainability 16, no. 16: 6786. https://doi.org/10.3390/su16166786

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An Overview of Research and Development in Academia

First Online: 03 February 2022

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Elias Baydoun 4 ,
Joelle Mesmar 4 ,
Abdul Rahman Beydoun 5 &
John R. Hillman 6

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This overview chapter encompasses the main underpinning themes of research and development (R&D) of universities around the world. Our observations and opinions apply equally to public-sector university-linked research institutes that conduct mainly original research as opposed to policy research. After an Introduction that includes defining the terms used in the chapter and scoping the topic, the main 13 sections of the chapter cover (a) R&D as a fundamental feature of human development reflecting the inherent curiosity of humans and their ability to learn and implement their knowledge. (b) The rationale for modern governments to invest in R&D, referring to the New Growth Theory and meeting the needs of modern societies. (c) The rationale for private-sector organisations to invest in R&D to ensure their long-term sustainability and competitiveness. (d) The various definitions and concepts of R&D. and Research & Experimental Development. (e) The roles and implications of the rapidly expanding number of transformative technologies that are not only profoundly transforming virtually all R&D but also the operation of modern societies including universities. (f) The need for specialist facilities, staffing, and learned societies for R&D to thrive. (g) The importance of international collaboration. (h) Funding sources for R&D. (i) The actuality of academic R&D, including both good practice and deleterious effects of poor management. (j) The pivotal wide-ranging roles of governments. (k) Impediments to successful R&D in both the public and private sectors. (l) Geopolitical aspects of R&D, and (m) Future of R&D. The Conclusions Section considers recommendations on R&D policies for the Arab world as well as for developing economies based on our global analysis of R&D.

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Baydoun, E., Mesmar, J., Beydoun, A.R., Hillman, J.R. (2022). An Overview of Research and Development in Academia. In: Badran, A., Baydoun, E., Hillman, J.R. (eds) Higher Education in the Arab World: Research and Development. Springer, Cham. https://doi.org/10.1007/978-3-030-80122-9_2

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New Research Is Shaping the Future of Education

Policymakers are benefitting from greater understanding of human development and technology, including ai..

Ulcca Joshi Hansen future of education Summit 2024

Author Ulcca Joshi Hansen sees an important role for state legislators in the future of education.

Education goes beyond just academics.

“It’s not because academics and content don’t matter,” Ulcca Joshi Hansen says, “but they have to be the vehicles through which young people learn to deal with ambiguity and to adapt.”

Hansen, an author and education expert, was joined by Vicki Phillips, CEO of the National Center of Education and the Economy, for a session on the future of education at NCSL’s Legislative Summit. Both see an important role for state legislators in that future.

“Policymakers and education leaders in top-performing systems help their communities revisit core assumptions about how, when, where and by whom education is delivered,” Phillips says.

“Successful systems know that they can only go as far as their teachers and leaders can take them.” —Vicki Phillips, National Center of Education and the Economy

The future of education has changed because of what researchers know about human development and technology, including AI. There is now a more holistic and “human-centered” approach to education issues, Hansen says.

“Our current systems are not designed to support human-centered education, so when schools try and do something different, they are brought back through accountability, grade levels,” Hansen says

To create a system that engages students beyond the classroom, legislators can support research groups in finding solutions. Once these solutions are more developed, they can draft policy to support them, Hansen says.

Philips is also working to create a system that benefits students in every aspect of their lives. Her group has a four-point blueprint of “interdependent” ideas that can help create a strong system. The first point is to prepare people for “long-life” learning.

“Long-life, rather than lifelong, (is) a nod to the reality that we are all living longer, and our young people will need the kinds of skills and education that will help them over that extended lifetime,” Phillips says.

The full blueprint is not public yet, but it includes concepts that relate to educator support, student well-being and the role of leadership in education, Phillips says.

“I think it’s not one step at a time, it is doing a lot of these things simultaneously,” Phillps says.

There is no one-size-fits-all solution, and it cannot be predicted what young people will need because the world is rapidly changing, Hansen says.

“We have to improve our existing system for the kids in it, and we also need a new infrastructure for public education that is more ecological in nature and supports human-centered education,” Hansen says.

These issues require time and energy to fix, and leaders must create momentum for the short-term solutions but always keep the big picture in mind, Phillips says.

“Successful systems know that they can only go as far as their teachers and leaders can take them,” Phillips says.

However, legislators don’t need to reinvent a completely new system; rather, they should try to “understand the field and build on and springboard from what people are doing,” she says.

Both Hansen and Phillips say that multiple parts of the community should be consulted in education discussions, including civic leaders, community advocates and those involved in all types of education.

Young people and teachers should also be at the table during these conversations, Phillips says.

Hannah Edelheit is an intern in NCSL’s Communications Division.

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Research and Economic Development
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Published May 7, 2024

MS drug candidate research carries on after scholar's death

Release Date: May 7, 2024

The late M. Laura Feltri

BUFFALO, N.Y. – The Empire Discovery Institute has entered into a collaborative research partnership with the National Multiple Sclerosis Society and its commercial development program Fast Forward, LLC.

The partnership builds on drug development research initiated by the late M. Laura Feltri, MD, SUNY Distinguished Professor of biochemistry and neurology in the Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo.

EDI was awarded $791,933 from Fast Forward along with technical support from its network of key opinion leaders in multiple sclerosis (MS).

EDI is a nonprofit drug discovery and development accelerator created to translate promising scientific discoveries into new breakthrough treatments and cures, support vital upstate New York pharmaceutical research efforts, and foster the development of a vibrant biotech startup communities in New York State.

It was made possible through a New York State seed grant from Empire State Development and through a research partnership with the University at Buffalo, University of Rochester and Roswell Park Comprehensive Cancer Center.

Pioneering work on MS drug design and development

Fast Forward provides research funding to commercial entities who develop promising new therapies for the treatment of MS, a demyelinating disease of the central nervous system impacting the brain, spinal cord and optic nerves.

EDI has been incubating an early-stage drug discovery project that originated from Feltri, an internationally renowned pioneer in the study and treatment of myelin diseases of the nervous system, who passed away in late 2023 after a long battle with cancer.

Feltri and the institute’s scientific team discovered novel small molecules which have the potential to stimulate the repair of nerve damage by promoting remyelination in MS and other white matter injuries. The Fast Forward award will support continued optimization of these small molecule drug candidates.

“We look forward to working with our National MS Society partners at Fast Forward to advance this work toward human clinical studies,” says Ron Newbold, PhD, CEO of the Empire Discovery Institute. “By combining scientific innovation and pharmaceutical industry expertise, EDI’s goal of promoting the efficient translation of fundamental scientific discoveries from academia into important new medicines is becoming reality.”

Venu Govindaraju, PhD, vice president for research and economic development at UB and EDI board member, says “Empire Discovery Institute is deeply grateful to Fast Forward for its support.”

He adds: “We are honored by this award and look forward to continuing our esteemed colleague Dr. Feltri’s life’s achievements, legacy and the institute’s important work in advancing drug treatments for MS patients around the world.”

National MS Society founded in 1946

For Fast Forward, this partnership represents a continuation of its dedication to support novel research efforts aimed at advancing promising treatments for MS patients. “Fast Forward is pleased to provide significant financial and intellectual support to this Empire Discovery Institute program, as it offers the potential to slow or stop the progression of demyelination in people who have progressive forms of MS,” says Walter Kostich, PhD, associate vice president, translational research at the National MS Society.

“We look forward to collaborating with EDI on this program as it aligns closely with the Pathways to Cures Roadmap, in particular to stop progression and to promote myelin repair and protection.”

The National MS Society, founded in 1946, is the global leader of a growing movement dedicated to creating a world free of MS. It funds cutting-edge research for a cure, drives change through advocacy and provides programs and services to help people affected by MS live their best lives.

Media Contact Information

Media Relations (University Communications) 330 Crofts Hall (North Campus) Buffalo, NY 14260-7015 Tel: 716-645-6969 [email protected]

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BUFFALO, N.Y. - The Empire Discovery Institute has entered into a collaborative research partnership with the National Multiple Sclerosis Society and its commercial development program Fast Forward, LLC.. The partnership builds on drug development research initiated by the late M. Laura Feltri, MD, SUNY Distinguished Professor of biochemistry and neurology in the Jacobs School of Medicine ...

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The Power of Partnerships: How to maximise the impact of research for development

Part 1. Key Qualities of Research-Policy Partnerships

1.1 Background

1.2 Defining partnerships for policy change in development

1.3 How do inter-sector partnerships maximise impact?

1.4 Is partnership between specialists enough?

1.5 What are the key qualities of effective research–policy partnerships?

Bounded mutuality

Sustained interactivity

Policy adaptability

Part 2. Making research-policy partnerships work: Funders’ and researchers recommendations

2.1 Deploy the framework at the design stage of a research process to increase partnership viability

2.2 Be honest about power dynamics and build trust

2.3 Identify boundary partners and work with brokers

2.4 Health-checking existing collaborations

2.5 Enable mutuality, interactivity and adaptability

Part 3. Conclusions

Further reading

Cite this publication

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Opening the Black Box of Participatory Action Research in Response to the Worst Forms of Child Labour in Nepal and Bangladesh

Abundant Life

The role of research in national development

Localizing the economic impact of research and development

Bolster institutions supporting tech transfer, commercialization, and innovation

Expand technology transfer and commercialization-related programs and investments

Promote high-growth, tech-based entrepreneurship

Stimulate private-sector innovation

Introduction

Strengthen innovation districts and regional technology clusters

1. Prioritize innovation districts within federal R&D outlays

2. Task federal laboratories with a local economic development mission

3. Create off-campus “microlabs” to provide a front door to labs

4. Support technology clusters by assessing and managing local-level federal R&D investments

5. Assess federal real estate holdings and reallocate physical research assets to innovation districts

6. Allow labs to repurpose a small portion of existing funds for timely local collaboration

7. Standardize research partnership contracts within cities

8. Create NIH regional pre-competitive consortia to address national health concerns

9. Allow DOE labs to engage in non-federal funding partnerships that do not require DOE approval

10. Dismantle funding silos to support regional collaboration

11. Incentivize cross-purpose funding based on the economic strength of cities

12. Expand the national Regional Innovation Program

13. Support the innovation potential of rural areas

14. Facilitate regional makerspaces

15. Introduce an “Open Commercialization Infrastructure Act”

16. Establish a core of 20 “manufacturing universities”

17. Complete the buildout of Manufacturing USA to 45 Institutes of Manufacturing Innovation (IMIs)

18. Create a National Engineering and Innovation Foundation

19. Create an Office of Innovation Review within the Office of Management and Budget

20. Create a network of acquisition-oriented DoD labs based in regional technology clusters

21. Establish manufacturing development facilities

22. Establish a foundation for the national energy laboratories

23. Increase the importance of commercialization activities at federal labs/research institutes

24. Allocate a share of federal funding to promote technology transfer and commercialization

25. Develop a proof-of-concept, or “Phase Zero,” individual and institutional grant award program within major federal research agencies

26. Fund pilot programs supporting experimental approaches to technology transfer and commercialization

27. Support university-based technology accelerators/incubators to commercialize faculty and student research

28. Allow a share of SBIR/STTR awards to be used for commercialization activities

29. Increase the allocation of federal agencies’ SBIR project budgets to commercialization activities

30. Modify the criteria and composition of SBIR review panels to make commercialization potential a more prominent factor in funding decisions

31. Encourage engagement of intermediary organizations in supporting the development of startups

32. Expand the NSF I-Corps program to additional federal agencies

33. Authorize and extend the Lab-Corps program

34. Provide federal matching funds for state and regional technology transfer and commercialization efforts

35. Incentivize universities to focus more on commercialization activities

36. Establish stronger university entrepreneurship metrics

37. Expand the collaborative R&D tax credit to spur research collaboration between industry and universities and labs

38. Increase funding for cooperative industry/university research programs at universities

39. Establish an International Patent Consortium