Adoption & diffusion of knowledge:

1. CAREER: Empirical Studies of Technology Adoption (Pascaline Dupas, Stanford University)

2. Doctoral Dissertation: Innovation by Users in Emerging Economies and Impacts on Innovation Policy: Evidence from Mobile Bank (Serguey Braguinsky and Paul van der Boor, Carnegie-Mellon University)

3. Drivers and Effects of Technology Adoption (Diego Comin, National Bureau of Economic Research)

4. The Initial Career Transitions of Science & Engineering PhDs (Henry Sauermann, Georgia Institute of Technology)

Understanding the impact of structures/process on science:

5. CAREER: Incentives, Diversity, and Scientific Problem Choice (Kevin Zollman, Carnegie-Mellon University)

6. Collaborative Research: BRIDGES: Building Resources through Integrating Disciplines for Group Effectiveness in Science (Theresa Lant, Pace University; Maritza Salazar, Claremont Graduate University)

7. Collaborative Research: Multi-team System Design for Maximizing Scientific, Technological, & Policy Innovation (Stephen Zaccaro, George Mason University; Lorelei Crerar, George Mason University; Leslie DeChurch, Georgia Institute of Technology; Ruth Kanfer, Georgia Institute of Technology)

8. Collaborative Research: Technology, Collaboration, and Learning: Modeling Complex International Innovation Partnerships (Danielle Wood, Johns Hopkins University; Dava Newman, Massachusetts Institute of Technology)

9. Contracting for Innovation: The Governance of University-Industry Partnerships (Steven Casper, Keck Graduate Institute)

10. Doctoral Dissertation: A Global Partnership Approach to Clean Energy Technology Innovation: Carbon Capture and Storage (David Sonnenfeld and Xiaoliang Yang, SUNY College of Environmental Science and Forestry)

11. International Partnerships and Technological Leapfrogging in China's Clean Energy Sector (Joanna Lewis, Georgetown University)

12. The executive science network: University trustees and the organization of university industry exchanges (Sheila Slaughter, University of Georgia)

Advancing understanding of entrepreneurship & innovation:

13. Circling the Triangle: Understanding Dynamic Regional Economies (Maryann Feldman, University of North Carolina; Nichola Lowe University of North Carolina)

New approaches to studying science & innovation

14. EAGER: Understanding Technological Change from the Map of Capabilities (HyeJin Youn, Santa Fe Institute; Aaron Clauset, University of Colorado)

15. Expanding Understanding of the Innovation Process: R&D and Non-R&D Innovation (John Walsh, Georgia Institute of Technology)

16. Research Development Workshop - Atlanta Competitive Advantage Conference 2013- 2015 (William Bogner, Georgia State University)

Implementing science policy:

17. A Transdisciplinary Deliberative Model for Just Research and Policy: Toward Resolving The Crisis of Vanishing Insect Pollinators (Daniel Kleinman, University of Wisconsin-Madison)

18. Advancing Behavioral and Social Science Research for Public Policy: The Policy Roundtable of the Behavioral and Social Sciences (Miron Straf, National Academy of Sciences)

19. Credibility and Use of Scientific and Technical Information in Science Policy Making: An Analysis of the Information Bases of the National Research Council's Committee Reports (Barry Bozeman, Arizona State University; Jan Youtie, Georgia Institute of Technology; Jeffrey Wenger, University of Georgia)

20. ENGAGE - Behavioral responses to advanced energy metering technology: A large scale experiment (Magali Delmas, University of California-Los Angeles; William Kaiser, University of California-Los Angeles; Noah Goldstein, University of California-Los Angeles)

21. Innovation in an Aging Society (NIH co-funded project) (Bruce Weinberg, The Ohio State University; Gerald Marschke, University of California-Davis; Subhra Saha, Cleveland State University)

Measuring & tracking science and innovation:

22. Building Community and a New Data Infrastructure for Science Policy (Jason Owen-Smith, University of Michigan; Julia Lane, American Institutes of Research; Margaret Levenstein, University of Michigan)

23. Discovering Collaboration Network Structures and Dynamics in Big Data (Jian Qin, Syracuse University; Jeffrey Stanton, Syracuse University; Jun Wang, Syracuse University)

24. Planning Meeting on Indicators of Doctoral Education (Connie Citro, National Academy of Sciences)

25. Small Business Programs, Innovation, and Growth: Estimating Policy Effects Using Comprehensive Firm-Level Panel Data (John Earle, George Mason University)

26. The Biographies of Scientific Ideas: What the Content and Structure of Citations Reveal About the Diffusion of Knowledge (Freda Lynn, University of Iowa; Michael Sauder, University of Iowa)



1.CAREER: Empirical Studies of Technology Adoption

Researcher: Pascaline Dupas, Stanford University

Higher adoption of available technology could significantly improve various aspects of wellbeing in developing countries. Two thirds of child mortality could be eliminated through adoption of available technologies, such as vaccines, antimalarial bednets, and oral rehydration salts. Average maize yields in sub-Saharan Africa are three to five times lower than yields attained by agricultural extension workers in the same region using technologies now universal in rich countries, such as improved seed varieties and fertilizer. How can adoption of these and other technologies be increased in developing countries? What barriers do households and providers face? How can these barriers be overcome?

Intellectual Merit. The research under this CAREER award aims to advance our understanding of technology adoption in developing countries through: (a) enabling and performing empirical tests of economic theory on three determinants of technology adoption—subsidies, financial access, and education—through a series of field experiments embedded in longitudinal data collection efforts; (b) enhancing educational opportunities for students and educators interested in development; and (c) filling gaps in the knowledge base available to the practitioners who develop policies and programs to foster technological transition.

The research component has three strands. The first research strand exploits randomized subsidy experiments in Ghana and Malawi, combined with innovation in measurements, to examine when and how subsidies for a new technology can foster learning about its effectiveness and trigger diffusion. Both demand-side and supply-side factors are being considered, in particular: how to target subsidies to those most likely to actually experiment with the new technology, and once a targeting scheme has been established, how to limit corruption and guarantee the subsidy reaches those it targets.

The second research strand exploits randomized variation in access to financial products in Kenya, Malawi and Uganda to estimate how financial exclusion impedes technology adoption. Namely, does the fact that the great majority of the poor in rural Africa have limited ability to borrow and no formal means to save limit technology adoption? What financial products can boost their investments in technology and why does the market not provide them?

The third research strand exploits the randomized assignment of education subsidies to youths in Ghana, combined with a 10-year panel dataset, to estimate the causal impact of secondary education on technology adoption and shed light on the pathways: does secondary education equip individuals with cognitive skills that are complementary with technology, does it enable them to hear about technology more easily, or does the effect of education on technology adoption operate primarily through an income effect?

This research agenda embeds a comprehensive education plan aimed at disseminating the research findings and methods to policymakers from the developing world, enabling better understanding of and greater interest in development issues among high school and undergraduate students, and offering international research opportunities for college students and college graduates, as well as for graduate students wanting to study development issues.

Broader Impacts. This work will generate and disseminate new evidence on questions debated by policymakers and practitioners, not only those in government but also those in institutions that shape global development agendas and resource allocation, from private foundations to bilateral agencies such as USAID and multilateral agencies such as the UN and the World Bank. One such debate is on whether and how new technologies should be subsidized when they are first introduced. This study will inform this debate, potentially impacting the design of subsidies to encourage immediate and long-term diffusion. Another debate is on the relative costs and benefits of expanding banking services to the rural poor. It will also inform this debate, potentially impacting the regulation and incentives of both providers and households in poor countries. Yet another debate is on the importance of secondary education. There is much evidence on the importance of primary education but little on that of post-primary education. The study will contribute evidence on both the private and social returns to secondary education, potentially impacting expansion of secondary education. Finally, study will generate innovative survey instruments and rich panel datasets and make them public, and in doing so will stimulate further relevant research.


2. Doctoral Dissertation: Innovation by Users in Emerging Economies and Impacts on Innovation Policy: Evidence from Mobile Bank

Researchers: Serguey Braguinsky and Paul van der Boor, Carnegie-Mellon University

Traditionally innovation has been reserved for firms in industrialized nations, because these firms had access to the resources needed for innovation. However, in the age of globalization, communication is cheap, information is a commodity, and global trade increases technological diffusion. As a result, firms and users in emerging markets get early exposure to the latest technologies and information that, in combination with access to tools such as mobile phones, enables them to customize products to solve local needs. Large latent demand in emerging markets, which results from high need and a sparse offering of products and services, is a reason to expect increasing invention originating from less developed countries in the global South.

Intellectual Merit. This project studies emerging markets as new sources of innovation and discusses implications of the diffusion of these innovations for policy. In particular, it looks at characteristics of emerging markets that enable specific forms of innovation, such as user innovation and frugal innovation, and also analyzes how this encourages technology flows from emerging markets to industrialized nations. This research is structured around three research objectives. First, it explores whether users in emerging markets innovate. A unique hand-collected dataset on innovations in the mobile banking industry is used to understand whether users (as opposed to firms) play a role in service innovation in emerging markets, and whether those innovations are globally meaningful. Second, the project analyzes how new types of innovation such as user innovation and frugal innovation are leading to flows of technology in a reverse direction. In particular it focuses on South-North diffusion of emerging market innovations as well as different typologies of the diffusion of user innovations. Despite evidence that a growing number of new products and services originate in emerging markets, there is a dearth of innovation research on this topic. Third, a model is proposed—based on empirical patterns—that explains how increased access to technology in combination with latent demand can drive innovation and entry in the South and how, subsequently, South-North technology diffusion can occur.

Broader Impacts. The project will provide insight on the mechanisms that govern discovery, adoption and diffusion of technology in emerging markets, a largely understudied area. Because the locus of innovation is no longer unique to firms in Western countries and is shifting to users and firms in emerging markets, this is an important topic for both the academic community and policy makers. This study will contribute significantly because, while there has been significant research on user innovation in products, there exists virtually no research on user innovation in services or their diffusion, yet services often constitute the vast majority of economic activity. Furthermore, this project develops a data-collection and analysis methodology that can be applied to follow-on research, especially empirical studies looking at sources of innovation in services.


3. Drivers and Effects of Technology Adoption

Researcher: Diego Comin, National Bureau of Economic Research

The competitiveness of a country is to a large extent determined by the technology used in production by its companies. For example, recent concerns regarding the competitiveness of the United States can surely be traced to the technology used by American companies and to the fact that the technological advances of foreign competitors may have reduced, or even eliminated, the technological advantage American companies had a few decades ago. Even in advanced countries like the U.S., technology is mainly determined by the adoption decisions of companies. Understanding the drivers of technology adoption is therefore essential for designing and implementing policies that foster economic growth. Unfortunately, we still know relatively little about the technology adoption processes.

Intellectual Merit. This project will shed light on the drivers of technology as well as on how various dimensions of technology contribute to productivity growth. The research is divided in two parts. The first will deepen our understanding of the consequences of technology adoption by studying the role that technology adoption has played in the evolution of the cross-country distribution of per-capita income over the last 200 years. The second part of the project studies the determinants of technology adoption, focusing on three types of factors pinpointed by the existing theoretical literature: financial market development, geographic distance to adoption leaders and political institutions. One significant drawback of the existing literature is that the relevance of these factors for technology is based almost entirely on anecdotal evidence. In contrast, this project will explore the generic importance of these factors by exploiting a comprehensive dataset, the CHAT dataset, that covers the diffusion of more than 100 technologies in over 150 countries during the last 200 years. Taken together, these two complementary lines of research will increase significantly our knowledge about the connection between technology and growth as well as about the fundamental determinants of technology.

Broader Impacts: By developing new empirical approaches to use the CHAT dataset to study technology diffusion, this project will encourage researchers to consider additional factors that influence technology diffusion and use CHAT to evaluate them. Additionally, better understanding of the drivers of technology adoption will provide guidance in the formulation of adequate policies directed to enhancing the productivity and competitiveness of the U.S. economy. Last, but not least, the project will introduce both graduate and undergraduate student assistants to state of the art techniques and datasets that shall shape their training as economists.


4. The Initial Career Transitions of Science & Engineering PhDs

Researcher: Henry Sauermann, Georgia Institute of Technology

Although academic research has traditionally been regarded as the most desirable career path for science and engineering PhDs, the U.S. has witnessed an increasing share of PhDs entering employment in the private sector. While some observers suggest that challenges in securing a tenure-track faculty position push graduates away from academia, others argue that the private sector attracts PhDs by offering higher pay, access to leading edge technologies, and an "open science" atmosphere. Using a novel longitudinal survey, this project follows a national sample of science and engineering PhDs over the course of their graduate training and into their first post-graduate positions to examine why some PhDs enter research careers in academia, while others pursue careers in industry. The first study in this project investigates PhDs' training experiences over the course of their program to assess changes in graduate students' career preferences over time and to examine potential drivers of such changes. The second study contrasts PhDs' career preferences prior to graduation with the positions they actually obtain after graduation. It also probes more deeply which PhDs are able to pursue their preferred career (or not) by examining how individual preferences, ability, and labor market conditions shape initial career transitions.

Intellectual Merit. This project contributes to the research on scientific labor markets and innovative human capital in several ways. First, prior literature often relies on the notion that PhD scientists are socialized during graduate training to aspire to an academic research career. This notion, however, seems at odds with emerging evidence showing that students' interest in academic science declines over the course of graduate training. This project empirically assesses changes in students' career preferences over time and examines how career preferences are shaped by a broad range of factors such as peers and advisors, learning about one's own skills, labor market conditions, and the job attributes associated with particular career paths. Second, this study complements prior work that has described aggregate patterns of labor flows by providing micro-level insights into how scientists' and engineers' initial career trajectories are shaped by their own preferences and ability as well as by labor market opportunities.

Broader impacts. By examining the career preferences and career transitions of science and engineering PhDs, this research provides an important empirical basis for the ongoing debate regarding science and engineering labor market conditions, including the potential "mismatch" between graduates' career aspirations and the positions actually available to them. The results also provide insights regarding how graduate curricula can be improved to better prepare students for a range of academic as well as non-academic career paths. The project's findings regarding changes in career preferences during graduate training have implications for university administrators, graduate student advisors, and policy makers who are concerned with shaping graduate student experiences. They are also important for students, who can benefit from thinking more explicitly about their career goals and from learning about the career opportunities available in different sectors of the economy.


5. CAREER: Incentives, Diversity, and Scientific Problem Choice

Researcher: Kevin Zollman, Carnegie-Mellon University

This CAREER award supports research to develop a more unified theory of scientific incentives using a broadly economic methodology. The educational and training aspects of the project includes a number of activities such as course development, a summer school for undergraduates, and mentoring of graduate students.

Intellectual Merit. Utilizing economic modeling and computer simulation, this project aims to understand how incentives typically faced by scientists (to secure funding, get promoted, publish papers, etc.) facilitate or harm the advancement of science. Policymakers, science commentators, and scientists themselves have begun to worry that such incentives encourage scientists to engage in behaviors that would be counterproductive to science as a whole such as choosing projects that will not significantly advance knowledge, or misrepresenting or even fabricating their findings. Rather than focusing on single case studies, which can sometimes be misleading, this project aims to uncover the underlying relationships between the incentives faced by scientists and their ultimate behavior. The results from the project will help to uncover whether there is reason to worried about the state of contemporary science. Where the incentives are misaligned, the investigators will attempt to suggest alternative methods.

Broader Impacts. The results from this project could eventually help to guide science policymakers in understanding how to create a reward system for science that will make the enterprise of science most efficient. They may serve to suggest recommendations that would make more efficient use of public money by enhancing the rate and reliability of scientific discoveries. The project also includes a number of pedagogical activities such as a freshman seminar, a philosophy of economics course, materials for a summer school course in mathematical modeling for philosophers, and improved dissemination of materials for an undergraduate summer school course in logic and formal epistemology. This sort of work is well suited to getting students involved at a fairly high level in fairly short order.


6. Collaborative Research: BRIDGES: Building Resources through Integrating Disciplines for Group Effectiveness in Science

Researchers: Theresa Lant, Pace University; Maritza Salazar, Claremont Graduate University

Finding solutions for many of society's most challenging problems requires the collaboration and integration of teams of individuals from diverse fields of science. Millions of dollars are spent in the public and private sectors to support research collaborations among scientists who possess the breadth and depth of expertise to address these complex problems. An increasingly prevalent approach to integrating diverse expertise is the use of interdisciplinary science teams.

Intellectual Merit. Although interdisciplinary scientific collaboration has many success stories, it is also true that in many cases these teams fail to successfully integrating the knowledge needed to address a problem. The goal of knowledge integration among diverse scientists is often elusive due to the make-up of the teams, lack of understanding about best practices for managing collaborations, and team leaders who are scientific experts but have not been trained to lead diverse teams of professionals. The consequence can be a costly investment in scientific endeavors that do not reap the expected benefits. It is critical that interdisciplinary science teams have the capability to collaborate and integrate their knowledge. A team's integrative capacity is a core competence necessary for these teams to perform successfully. Integrative capacity is a capability that is sustained through an interactive system linking social, psychological, and cognitive processes and emergent states in the team that can provide them with the resources needed to succeed. This research investigates how the development of a team's integrative capacity and subsequent knowledge outcomes are impacted by: (1) boundary-spanning leadership behaviors and (2) communication structuring interventions. Exposure to these interventions can nurture team members' trans-disciplinary intellectual orientation, the enduring values, beliefs, skills, and behaviors that support collaboration with teammates who have diverse disciplinary backgrounds, which in turn fosters the development of integrative capacity.

Broader Impact. Given the reliance of society on interdisciplinary science teams for advancement in key areas such as medicine, education, security, and technology, the development of theoretical and practical knowledge about how to build and maintain integrative capacity in these teams is imperative. This research directly supports the aims of the SciSIP program and the NSF by investigating the structures, processes, and interventions that facilitate the development of usable knowledge by interdisciplinary science teams. First, this study sheds light on how leader and communication interventions can enhance a team's integrative capacity and team members' transdisciplinary intellectual orientation, both of which can support teams working across boundaries to generate new solutions to complex problems. Second, training material and digital metrics developed in this research can be leveraged to foster improved scientific collaboration in teams beyond those included in this study. The insights gained from this research can foster improved scientific collaboration and the resulting scientific breakthroughs that are the promise of interdisciplinary science teams.


7. Collaborative Research: Multi-team System Design for Maximizing Scientific, Technological, & Policy Innovation

Researchers: Stephen Zaccaro, George Mason University; Lorelei Crerar, George Mason University; Leslie DeChurch, Georgia Institute of Technology; Ruth Kanfer, Georgia Institute of Technology

There is conflicting evidence about the capacity for scientific collectives (i.e., teams, centers) to seed grand innovations. On the one hand, sociological research convincingly argues for the "dominance of teams in the production of knowledge," particularly in the production of "high-impact" knowledge. On the other hand, research shows that many science teams, particularly the ones most prized for their diverse and distributed "dream teams" are especially prone to underachieving when it comes to publications, patents, and commercialization.

Intellectual Merit. This program of research investigates a large number of scientific collectives, from their initial formation to their maturity, in order to uncover the dynamic interplay between structure (i.e., how the collective is designed) and process (i.e., leadership and member interactions). Although collaboration across disciplines and units has been frequently recognized as one of the key obstacles to innovation, research is needed to determine how system design affects the multi-level processes that facilitate collaboration within and across teams and units. This research integrates psychological, organizational, and network science perspectives in a multilevel system model to detail the impact of goals, leadership, and system design on key drivers of collaboration within and across teams in innovation systems. Four empirical studies are being conducted over the course of two years in order to evaluate the impact of variations in the architecture of scientific innovation systems on resulting innovation. This research investigates scientific collectives comprised of students working across two universities, three disciplines, and two countries who must work collaboratively to solve interdisciplinary challenges in environmental sustainability.

Broader Impacts. The project develops an evidentiary-base for informing policy on how to manage scientific collaborations to foster innovation. In particular, this project will enable concrete prescriptions about the optimal integration of science and policy. The project identifies the structural and interactional building blocks of successful collaboration in scientific collective in which teams are distributed, are affected by complex social and motivational forces, and interact through virtual technology to innovate using knowledge across temporal and spatial boundaries. This project will yield greater understanding of how to improve, through design and leadership interventions, knowledge generation and policy implementation in multiteam science. A second set of broader impacts of the project concern the education of four communities: (1) future scientists, (2) science policy leaders, (3) academics, and (4) students. This project is enabling the training of future scientists who will work as part of distributed multidisciplinary international science teams. An estimated 10 PhD students and 10 research-oriented undergraduate students will have the opportunity to work directly on this research, engaging in virtual scientific collaboration. The project will create new curricula in distributed multidisciplinary teamwork at Georgia Tech aimed at computing and engineering students. At George Mason, this project will foster a continuing collaboration between instructors in the Environmental Science & Policy and Psychology programs. This collaboration has as its goal the design of integrated curricula to help students understand how to use both principles of ecology and social psychology to foster greater environmental sustainability. Finally, the project contributes to the teamwork training of more than 2,000 Engineering, Ecology, Psychology, and Business students who will participate in this research.


8. Collaborative Research: Technology, Collaboration, and Learning: Modeling Complex International Innovation Partnerships

Researchers: Danielle Wood, Johns Hopkins University; Dava Newman, Massachusetts Institute of Technology

Intellectual Merit. This project studies Complex International Innovation Partnerships (CIIPs) as an instrument for national technological development through cross-border learning. CIIPs are one approach through which countries seek to improve their technological and innovation capability in specific sectors by partnering with global experts. CIIPs are typically initiated by a learning country that is building capacity in a particular area of science, technology or innovation. When the learning country determines that the requisite expertise is not available in their country, they seek out a foreign expert partner. The two partners engage in a long term relationship during which individuals from both partners spend significant time together, working jointly in collaborative research, engineering or education activities. Typically, the expert partner provides education, mentoring or training services to representatives of the learning partner. Through this sustained interaction, each partner is impacted by the social and cultural context of the other. Many CIIPs occur in public service sectors and are led by government organizations. The project team investigates CIIPS by producing two sets of case studies via international field work. The case studies examine CIIPs that are executed as part of programs to develop space satellite capabilities and international university partnerships that seek to enhance an innovation ecosystem. Using a systems architecture framework, the project analyzes the technological, social, organizational and policy dimensions of these partnerships. The systems architecture approach synthesizes findings that build on four bodies of literature: Innovation Policy, Technology Transfer, Technological Learning, and Science and Technology Studies. The research develops a multi-stage analytic model that describes the evolution and dynamics of CIIPs; explains differences in the implementation of CIIPs; identifies insightful patterns across CIIPs; and provides initial tools to assess the extent to which CIIPs meet stakeholder objectives. The results of the study will advance scientific understanding of how science, technology and innovation can contribute to economic growth and societal progress under conditions that are globalized and necessitate continuous learning. The project is a first step in formulating a theory of CIIPs that combines their international and systemic nature.

Broader Impacts. The concept of Collaborative International Innovation Partnerships (CIIPs) describes a diverse set of Science, Technology and Innovation Policy initiatives occurring around the world. CIIPs are largely driven by the public sector and frequently relate to public goods such as education, environmental management, basic research and innovation spillovers. However, CIIPs are currently practitioner-driven and under-theorized. Policy-makers, program managers and industrial partners can benefit immediately from a sound theoretical grounding and analytic framework to inform the design and evaluation of current CIIPs. The results will also inform how CIIPs may be strategically deployed to address national priorities. The project will promote understanding across cultures and sectors by elucidating the dynamics that occur when partners from distinct cultures come together to execute a complex, sociotechnical endeavor. The project brings together two independent streams of research on emerging satellite programs and on international university partnerships. The combined effort will provide valuable insights into commonalities across sectors. In the long term, the investigators seek to extend the models and assessment tools developed here to a broad range of countries and technology sectors. This project lays a foundation for a network of researchers studying CIIPs in different contexts.


9. Contracting for Innovation: The Governance of University-Industry Partnerships

Researcher: Steven Casper, Keck Graduate Institute

An important trend in university-industry relationships is the negotiation by companies, particularly within the pharmaceutical industry, of multi-year partnerships with universities. Such partnerships provide significant unrestricted and sponsored research funding to universities, often in exchange for the right of the company to license intellectual property from university discoveries in fields of interest and the opportunity to develop collaborations with university scientists. The performance of university-industry partnerships has varied, though many completed partnerships from the 1980s and 1990s appear to have performed poorly and were not renewed by the industry partner. In recent years several pharmaceutical companies have negotiated new partnerships with universities that have significant changes in governance arrangements. The newer partnerships include formal contracts that replace up-front funding to universities with milestone based funding arrangements based on the performance of the partnership, and emphasize close day to day technical collaboration between university and industry scientists through the co-location of industry laboratories near university campuses.

Intellectual Merit. This project studies the goals, governance, and performance of several university-industry partnerships sponsored by pharmaceutical firms. The project examines whether the performance of university-industry partnerships can be explained by differences in the formal and informal governance mechanisms used within partnerships. It also studies whether the performance of university-industry partnerships can be improved through innovation in the design of governance arrangements. The project implements a mixed methodology case study approach to examine the goals, governance arrangements and performance of partnerships. The research combines descriptive data obtained through bibliometric and patent research with evidence developed through interviews with university and industry alliance managers and scientists involved in sponsored research collaborations within partnerships.

Broader Impacts. Multi-year university-industry partnerships are an important mechanism by which academic science is being commercialized, involving many of the country’s elite universities and science departments. The project contributes to the field of science and technology policy through creating in-depth case studies of the goals, governance, and performance of several multi-year university-industry partnerships. The governance of university-industry partnerships is malleable to policy: the formal contracts, informal norms, and patterns of technical collaboration created within partnerships can be changed to mirror improved practice. The results of the project are likely to be of particular interest to university and government officials involved in creating policy surrounding university-industry relationships and the commercialization of science.


10. Doctoral Dissertation: A Global Partnership Approach to Clean Energy Technology Innovation: Carbon Capture and Storage

Researchers: David Sonnenfeld and Xiaoliang Yang, SUNY College of Environmental Science and Forestry

Innovation does not happen in isolation but rather within interactive systems. Successful innovation leads to economic prosperity and national competence, but additional research is needed on the innovation process itself, particularly on interactive learning dynamics among and between major institutional actors. Emerging global collaboration in innovation of clean energy technologies presents an important opportunity for innovation systems scholarship. The recent emergence of state-led, bilateral research partnerships to develop new technologies for carbon capture and storage (CCS) raises critical research questions: In what ways and to what extent do international collaborations facilitate the innovation process of clean energy technologies? What are the national and international policy implications of the globalization of innovation in the clean energy sector? And what analytical model(s) can effectively explain and be used to evaluate this phenomenon?

Intellectual Merit. Using the US-China Advanced Coal Technology Consortium as a case, this research draws on two approaches: the 'functions of innovation systems', and 'resources-based perspective on research partnerships' approaches, respectively, to more deeply understand the mechanisms and effectiveness of state-led, international technology research partnerships. This field-based, doctoral dissertation research project examines the policy rationales, mechanisms and effectiveness of the Advanced Coal Technology Consortium (ACTC) of the United States-China Clean Energy Research Center, initiated by Presidents Obama and Hu in 2009. Data are gathered from Chinese and American participants in the ACTC through survey research, in-depth interviews, site visits, event participation and other available sources. Secondary, comparative analysis of China's CCS research partnerships with Australia, the European Union, Japan and the United Kingdom is included, as well. This research project will collect new data and develop models of collaborative, international technology innovation that can be used in the analysis of policy options for clean energy technology development.

Broader impacts. Utilizing data collected in China and the United States, this project will create original analytical models that can be used to examine multi- and bilateral technology innovation partnerships, and help policymakers better understand and evaluate the strengths and limitations of international collaboration in the development of clean energy technologies. Key findings will help inform the design of effective public policy related to research and development of large-scale, low-carbon technologies and energy systems, and will help strengthen international partnerships in clean energy technology innovation.


11. International Partnerships and Technological Leapfrogging in China's Clean Energy Sector

Researcher: Joanna Lewis, Georgetown University

Clean energy technology cooperation is an expanding area of international efforts to curb climate change. By harnessing the technical expertise of multiple nations, multilateral and bilateral cross-border collaboration on clean energy research, development, demonstration and deployment promises to speed clean energy innovation and utilization. Because China is the largest national energy consumer and greenhouse gas emitter, energy technology decisions there in the coming decades have implications for both energy security and environmental sustainability, and will shape future technology and policy decisions in the United States and around the world. China has therefore become the primary target of international clean energy collaboration.

Intellectual Merit. This project examines factors that determine the efficacy of cross-national clean energy partnerships. The results of this research will contribute to an improved understanding of how clean energy technology collaboration between various countries and China is occurring, how to improve the effectiveness of international partnerships, and how to measure and evaluate such programs. The focus on partnerships targeting clean energy technologies at different stages of technical maturity and with differing technical characteristics promises to elucidate lessons for intellectual property management within a variety of cross-national research collaborations. Additionally, in measuring the outcomes of existing partnerships, this research will contribute to the development of empirically-grounded innovation metrics and new ways of measuring innovative activity in China, while also informing innovation systems theory in emerging economies. This project will also improve our understanding of China's innovative capacity in critical clean energy technology sectors, and the role of international partnerships in reducing China's greenhouse gas emissions.

Broader Impacts. This project will inform the global management of innovation in an area of technological development that benefits both global society and the global environment. The findings of this work will help to inform policy debates on pathways towards low carbon technology development, the respective capabilities of developed and developing countries in innovation and manufacturing, and concerns about intellectual property rights and competition in a globalizing world. Furthermore, it promises to provide new insight into how productive international technology partnerships occur, and how such partnerships may present new opportunities to curb global carbon emissions and to engage with China.


12. The executive science network: University trustees and the organization of university industry exchanges

Researcher: Sheila Slaughter, University of Georgia

Intellectual Merit. This study explores how the external interests of university trustees and senior university officers influence innovation between academe and industry. Previous research has noted a difference in the composition and function of the trustees of private and public universities belonging to the American Association of Universities (AAU). Trustees of private universities are often heads of science-based corporations and simultaneously members of boards of directors of other corporation(s). Over time trustee research interests and those of the universities of which they are stewards become more similar with regard to areas in which they patent and broad fields of science in which their universities are funded. The trustees and senior university management of private AAU universities form a dense network, in which one member is not more than half a step away from any other, constituting an executive science network that creates channels for innovation between academe and industry. Trustees of public AAU universities are not part of this network. This study gathers additional data extending the temporal coverage of the earlier research while broadening the scope to include trustees of public university foundations (arms-length organizations) because pilot research suggests that these trustees may be part of the network and create channels of innovation between public universities and industry rather than public university trustees who are political appointments. The data are analyzed using network analysis and regression analysis to understand how the network functions (i.e., whether trustees—firms—position in biotechnology networks or sub networks or computer science sub networks predicts success in university research funding; whether trustees—firms—are likely to patent with or have partnerships with the universities of which they are stewards). These quantitative data are augmented by interviews with 60 trustees at 4 universities to gain in-depth understanding of trustees’ corporate exchanges with the universities they govern and how these contribute to technology development and economic innovation. However, if trustees and senior university officers are managing their universities as firms and establishing exchanges with their corporate firms (whether as CEO or member of a board of directors) the possibility of institutional conflict of interest arises. While trustees firms and universities may both benefit by these exchanges, there is a possibility that pursuit of technology development may harm university science (i.e., by emphasizing some types of science over others). Thus, the interviews focus not only on trustee-university exchange with regard to technology development, but also on how trustees and senior management handle institutional conflict of interest.

Broader impacts. First, this project advances our understanding of the part research university trustees play in bringing innovative science to the market place, enhancing U.S. ability to compete internationally. Second, the research compares public and private university trustee channels between academe and industry, identifying trustee characteristics that promote innovation. Third, the project examines how trustees involved in exchanges with the universities they govern manage institutional conflict of interest, suggesting best practices for other research universities. All three of these broader impacts will be helpful in developing policy to enable research universities to better participate in technology development and economic innovation that will lead to economic growth.


13. Circling the Triangle: Understanding Dynamic Regional Economies

Researchers: Maryann Feldman, University of North Carolina; Nichola Lowe University of North Carolina

This project will increase understanding of the processes and institutional supports that promote and sustain regional economic development. Regions are important platforms for promoting entrepreneurial activity; however, there have been few attempts to capture the dynamic processes that affect how innovative organizations work together, adapt and improvise to define a functioning entrepreneurial economy. Through an empirical investigation of North Carolina's Research Triangle Region, the project investigates multiple pathways of entrepreneurial development and considers how combinations of public and private investments affect the survival and growth of firms and industries. A better understanding of the multiple pathways and interventions that support regional entrepreneurship will, in turn, enhance development of policy for innovation and entrepreneurship.

Intellectual Merit. The project studies the entrepreneurial regional economy of the Research Triangle through a comprehensive analysis of both entrepreneurial and established firms, supporting institutions and the myriad transactions that unite them. To support our analysis, the project team has created a unique relational database, which contains longitudinal data on technology-intensive ventures in the region. This database currently contains information on the attributes of over 4,200 companies in the Triangle region, events related to the company's growth and survival and biographic information on the company's founders. For each firm, the database also traces the level and sequence of institutional support from key Federal, state and local entrepreneurial and economic development agencies. These data uniquely capture the universe of regional technology start-ups, including information on companies known to have gone out of business, merged or been acquired, a subset of firms that is frequently unavailable but essential to entrepreneurial dynamics. The database has been designed as a resource for state and Federal policy development, with the goal of further enhancing regional innovative capacity.

Broader impact. Around the world, policy makers search for appropriate economic development policies and investments. Many look to North Carolina's Research Triangle as an example of successful policy-led economic development yet the precise mechanisms and policy levers are not well known. As a result, there is a tendency to downplay the influence of policy interventions and interactions on firm strategy and development. This project offers a data-driven solution by providing an essential resource for tracing the sequence of interventions and facilitating events that contribute to and help sustain entrepreneurial development. It also helps to reveal the existence of multiple entrepreneurial pathways that support new firm formation. For example, the data already collected reveal that entrepreneurial firms are just as likely to emerge from university-based technology transfer systems as they are from large multinational corporations that incubate entrepreneurial talent and skill. The project's objective is to create a transferable framework for analyzing regional dynamics elsewhere. This study of the Research Triangle provides a test case for compiling and collecting data at both the firm and institutional levels that would be transferable to other regions.


14. EAGER: Understanding Technological Change from the Map of Capabilities

Researchers: HyeJin Youn, Santa Fe Institute; Aaron Clauset, University of Colorado

Technology's advance is central to economic growth and development. Furthermore, solutions for many of the planet's most pressing challenges—economic recovery, poverty reduction, climate change, sustainability—require significant additions to society's technological toolkit. Yet, our ability to quantitatively model and forecast technological change is insufficient. The most common perspective on technological change in economics and management science—that it is a search on a space of technological possibilities—is more of a metaphor than a modeling framework. And the numerous case studies of particular innovations do not amount to a formal, quantitative and predictive theory.

Intellectual Merit. This project develops a formal methodology for describing the space of technological possibilities using a systematic, comparative analysis of U.S. Patent data spanning 220 years that explicitly accounts for the interdependencies of technologies at the most basic level. A major outcome of the project is a detailed "map" of technological capabilities in which potential innovation pathways are illuminated both visually and mathematically. The project mathematically formalizes and statistically analyzes this map in a form of network representation by utilizing and developing tools from mathematics, physics, biology and computer science. This quantitative and systematic approach is key to improving our ability to develop a predictive model that can inform decisions on public policy.

Among the fundamental questions the project answers are: (1) What is the appropriate "quantum" (fundamental unit of analysis) of technological capability required to understand invention activities? (2) How can we best construct a technology "map" that illustrates the complex interdependencies of these quanta, and that bridges from micro-scale dynamics to macro-scale patterns? (3) What characteristics define "keystone" (general purpose) technological capabilities in terms of their position within the ecosystem?

Broader impacts: The technology maps produced by the project will be available to the public and to policy makers. This information advances our ability to build a predictive model for technology forecasting and improves the ability of the US Patent and Trademark Office to index and monitor patterns in patent activities through time.


15. Expanding Understanding of the Innovation Process: R&D and Non-R&D Innovation

Researcher: John Walsh, Georgia Institute of Technology

Intellectual Merit. While R&D is an important input to innovation, there is growing evidence that a significant share of innovation is not born from formal R&D activity. Given the importance of innovation for economic growth and the central role of innovation in policy debates, the project will expand the study of innovation to include non-R&D innovations and analyze the drivers and outcomes of non-R&D compared to R&D-based innovations. The project includes three key parts: a detailed review and analysis of new and traditional indicators of innovation, including estimates of the rates of non-R&D innovation; modeling and empirically testing the relation between knowledge environments and innovation type (R&D v. non-R&D); and examining the impact of innovation type on willingness to participate in markets for technology, and how invention idiosyncrasy affects this relationship. The research also addresses more fundamental questions in the science of science and innovation policy on the nature of knowledge in the innovation process and the likely outcomes of inventions embedding different characteristics.

Broader Impacts: The project's goal is to broaden the understanding of innovation and leverage this broader understanding in order to develop theories of innovation and improve the empirical foundation for innovation policy. Findings will contribute to ongoing efforts at NSF to develop more sophisticated innovation measures, as well as make important contributions to understandings of non-R&D innovations and helping organizations build their strategies for innovation related to knowledge environments. In addition, the findings on willingness-to-license by invention type may help firms devise better strategies for commercializing their new technologies. One objective is to broaden understanding of the innovation process and build an empirical base to guide policymaking that would address this broader universe of innovative activity, including building new models of the R&D decision, new metrics (non-R&D innovation, idiosyncrasy) and new results on the innovation process.


16. Research Development Workshop - Atlanta Competitive Advantage Conference 2013- 2015

Researcher: William Bogner, Georgia State University

Intellectual Merit. The Atlanta Competitive Advantage Conference (ACAC) is focused on developing a better understanding of the sources of sustained competitive advantage in market economies. The ACAC Research Development Workshop (RDW) improves the capabilities of emerging researchers working on questions in innovation, strategy, processes of new knowledge search, absorption and diffusion, and the measurement of the impact of innovation on firms and society. Open to late-stage PhD students, the RDW focuses on improving research projects that these students are currently undertaking in their home institutions. This is done by bringing together twenty-four PhD students with a range of scholarly foci and placing them with scholars from outside of their home institution and with whom they that would not otherwise work. By including program modules that address building networks among innovation researchers, the RDW helps the PhD students integrate more broadly into a global community of innovation research scholars across institutions. At the 9th ACAC RDW in 2012 twenty different US PhD programs, two Canadian PhD programs and four European PhD programs sent students to the workshop.

Broader Impacts. Within the US the impact of an improvement in our knowledge base with respect to the management and evaluation of innovation processes is significant. This impact will be felt across a wide range of organizations. In 2012 private, for-profit business in the US spent an estimated $280 billion on R&D. Government, academia and other non-profits combined for about another $130 billion. These numbers are expected to increase in 2013. With over $400 billion, being spent annually on innovation and new knowledge search in the US alone, any improvement in innovation outcomes through better managerial decision-making will have a significant, long-term impact on both economic competitiveness and on social welfare. Managers need to better understand the "how" and "why" aspects of the relationship between the firm's internal innovation and knowledge management activates and the firm's sustained competitive advantage that outputs can give in open markets. These same perspectives apply to not-for-profit and government organizations seeking innovation and change. Improvements in understanding will come only from organization-level decisions based on solid science. Thus, the better the science is behind the prescriptions given to managers for effective and efficient research and innovation processes, the greater the gains will be from those processes. It is in that light that this RDW focuses on impacting the quality of that science in the emerging researchers in the field.


17. A Transdisciplinary Deliberative Model for Just Research and Policy: Toward Resolving The Crisis of Vanishing Insect Pollinators

Researcher: Daniel Kleinman, University of Wisconsin-Madison

This project seeks to use deliberative processes with a wide range of stakeholders to develop an alternative experimental paradigm for field studies to understand the sustainability crisis in honey bees.

Intellectual Merit. Scientists agree that what they call Colony Collapse Disorder (CCD), is caused by a complex combination of factors, including pesticides, pathogens, parasites and/or poor nutrition yet field research is currently dominated by toxicological practices which emphasize the isolation of individual causal factors and experimental control. Analysis of cumulative and interactive effects of pesticides and other ambient environmental factors—an approach that beekeepers tend to embrace—has been precluded. This 2-year project aims to innovate experimental field research methods so as to better incorporate socio-ecological complexity. They plan to experiment with deliberative strategies for enhancing the influence of non-scientists (beekeepers, farmers, ecologists) on research aimed at understanding CCD. They will facilitate face-to-face deliberations using diverse methodological and conceptual tools for place-based analyses, in conjunction with four pilot field studies of mono-cultural crops and poly-cultural crops, managed with or without “reduced risk” insecticides.

Broader Impacts. The environmental and agricultural sustainability of the United States is threatened by steep declines in insect pollinators. This activity seeks to make important contributions to environmental problem solving. It also aims to broaden the participation of primarily affected and often-excluded, non-scientific (non-certified) citizens and to include their varieties of expertise in the production of scientific knowledge and policy. It stands to show that a fairer process, wherein a broader array of stakeholders shapes the research that affects their lives, can lead to better science and policy.


18. Advancing Behavioral and Social Science Research for Public Policy: The Policy Roundtable of the Behavioral and Social Sciences

Researcher: Miron Straf, National Academy of Sciences

The National Academies Policy Roundtable of the Behavioral and Social Sciences is exploring ways in which the behavioral and social sciences can better inform and otherwise contribute to more effective and efficient government policies and programs.

Intellectual Merit. Building upon the recent National Academies report, Using Science as Evidence in Public Policy, the Roundtable brings together those who make or advise on policy, those who conduct policy-relevant research, and those who fund research and data collection in order to provide the interaction necessary for the production of relevant research that policy makers can use. The Roundtable informs policy makers of the relevance and utility of behavioral and social science research and engages researchers in formulating researchable questions that meet their needs. The Roundtable also contributes to the development of research to better understand and advance the use of science to inform public policy and is a source of ideas for future National Academies workshops, conferences, and studies.

Roundtable members discuss priority issues in the use of behavioral and social science research for public policy and engage in dialogue, share information, and suggest ideas for further exploration and further research. A public workshop usually follows with presentations and discussions on identified topics that would further advance the use of science in public policy. About three meetings of the Roundtable are to be held each year. Brief summaries of the Roundtable discussions, or meeting recaps, are provided to members and a summary or proceedings of workshops is to be publicly available.

Broader Impacts . For scientific research to continue to contribute to societal well-being, it is critical that decisions on public policies are informed by relevant scientific knowledge. The creative dialogue within the Policy Roundtable and the presentations and discussions at its workshops will serve this important purpose


19. Credibility and Use of Scientific and Technical Information in Science Policy Making: An Analysis of the Information Bases of the National Research Council's Committee Reports

Researchers: Barry Bozeman, Arizona State University; Jan Youtie, Georgia Institute of Technology; Jeffrey Wenger, University of Georgia

Policy makers and researchers often voice disappointment with the limited extent to which scientific and technical information is used in public policy decision-making. However, does the perception of the limited use of formal scientific and technical information (STI) accord with empirical reality? If STI is not the predominant information base in public policies, what other types of information are employed and how do these types of information compete with STI for inclusion in policy making?

Intellectual Merit. This project focuses on the use of STI in science policy deliberations, an area typically rife with relevant STI and advantaged by a STI user- and a STI producer-base practiced in the use of information. If the role of STI is limited in science policy, one would expect the role to be at least as limited in most other public policy domains. The present study examines the use of STI, and other information types, in National Research Council (NRC) reports of the National Academy of Science and the National Academy of Engineering. These reports seem especially useful for examining STI use. First, the National Academies apparatus is a quasi-public body charged by the U.S. Congress with providing advice about science and technology intensive policy issues. Thus, there is built-in policy demand for the reports produced by committees. Second, the NRC committee work is unusually information rich. The combination of the institutional prestige of the Academies, taken with the typically high level of prominence of NRC committee members, ensures a level of access to a wide variety of person-to-person and informal information resources.

The project's research approach entails developing a sample of 60 reports and subjecting them to intensive bibliometric analysis, determining the proportion of formal STI (defined as studies from peer-reviewed journals) to other type citations (e.g. gray literature, government documents, and expert testimony). The study considers a number of factors possibly related to the use of STI, including the composition of committees' panels, disciplinary backgrounds and the public visibility and controversy of the NRC study topics, as determined in content analyses of media coverage. Finally, the project considers the extent to which the use of STI affects the impacts of reports, determined by content analyses of media, including leading newspapers (e.g. column inches of coverage over time), number of page views on the Internet, citations from Scopus and Web of Science, and, especially, citations to the reports in actual laws and public policy documents.

Broader impacts. The project is expected to provide knowledge not only of the extent of STI use but the factors that affect its use in science policy making and the relationship of STI use to other information resources. Thus, findings have the potential to improve policy information and policy decisions. Study results will be used to develop a workshop conducted at national meetings of the AAAS. The workshop will bring together policy-makers and STEM researchers to discuss respective views about information needs for policy-making.


20. ENGAGE - Behavioral responses to advanced energy metering technology: A large scale experiment

Researchers: Magali Delmas, University of California-Los Angeles; William Kaiser, University of California-Los Angeles; Noah Goldstein, University of California-Los Angeles

Intellectual Merit. Electricity generation accounts for over 40 percent of the carbon dioxide emitted by the United States. This project will investigate how energy usage information provided through advanced metering technology can induce conservation behavior. It tests the long-term effectiveness of real-time feedback on electricity use combined with messages aimed at motivating behavioral change. The interdisciplinary research team will combine innovative electrical engineering and computer science methods with insights from psychology and consumer behavior research to design optimal interventions for changing energy use behavior. The research will involve two experiments. In the first, residents of 120 campus apartments used to test the effectiveness of three different types of messages: pecuniary, pro-social, and pro-self conservation messages. The second experiment will investigate the effectiveness of public recognition of conservation behavior.

Broader Impacts. The results will be applicable to the 65 million smart meters to be installed in the United States by 2015 to provide measurable outcomes for energy management. The research findings will be integrated into undergraduate courses at UCLA including the capstone design courses in Engineering, the Environmental Sciences senior practicum, and the UCLA Sustainability Action Research Teams (ART). This project will also help K12 students gain experience in the energy field through UCLA’s High School Summer Research Program and engineering Tech Camp, and will engage students from underrepresented minorities by offering research opportunities for a freshman class through the Center for Excellence in Engineering Diversity.


21. Innovation in an Aging Society

Researchers: Bruce Weinberg, The Ohio State University; Gerald Marschke, University of California-Davis; Subhra Saha, Cleveland State University

The U.S. scientific workforce is aging – the average age of both US academics and medical faculty has increased to the late 40s from the early 40s in 1970. This aging is troubling because people tend to make important scientific contributions early in their careers. Moreover, the U.S. is turning to innovation as an economic driver and the aging of the population will both increase and shift the demand for biomedical innovation. This perfect storm lead former NIH Director Elias Zerhouni to identify the aging of the scientific workforce as “The number-one issue in American science (Kaiser [2009]).”

Intellectual Merit. This project develops and disseminates an interrelated body of research on the production and impact of research in an aging society along with the data infrastructure and tools necessary to catalyze the development of a dynamic research community studying innovation at the individual-level. Support from the National Science Foundation will contribute to the development of that data infrastructure allowing for the inclusion of information on NSF grants. The project is organized around 3 broad, interrelated questions: (1) How will the aging scientific workforce affect the quantity and quality of innovation? (2) What are the health impacts of and local economic spillovers from research, and how will the aging biomedical research workforce affect health and the economy? (3) What methods, such as accelerating or decelerating retirement, can be used to address the aging of our scientific workforce?

Broader Impact: By assembling the data and infrastructure necessary to utilize the data, This project will catalyze the development of a new scientific field studying innovation at the individual level, greatly advancing our understanding of the production and impact of innovation. At a broader level, it will provide research-backed answers for policy makers seeking to understand the dynamics of the STEM workforce as well as enhance and assess the impact of research funding.


22. Building Community and a New Data Infrastructure for Science Policy

Researchers: Jason Owen-Smith, University of Michigan; Julia Lane, American Institutes of Research; Margaret Levenstein, University of Michigan

This project creates and maintains infrastructure and community to support policy relevant social science research. It uses newly available STAR METRICS data on how universities spend federal research grants to examine the scientific, social and economic impact of federally funded academic research. Infrastructure includes shared research tools and datasets. The community spans researchers in multiple disciplines, academic administrators, and state and federal policy makers.

Intellectual Merit. Employing STAR METRICS data and utilizing infrastructure for its access and use the research community can provide systematic answers to questions such as: What scientific collaborations are directly supported by research funding? What indirect effects do federal grants exert on regional economies and labor markets? The first question can be answered with systematic study of the structure and productivity of scientific collaboration networks using fine-grained information on who is paid to work on the same scientific grants. In doing so, this project is the first to characterize the productivity of campus-wide, federally funded science on 11 large university campuses. The second question can be answered using the same data source to analyze payments to vendors for scientific equipment, supplies, etc. By analyzing the distribution, geographic location, and industry of vendors that supply federally funded research, this project offers the first comprehensive picture of the effects of federal R&D spending on economic resilience and job creation via companies that support university research. These and other community research endeavors provide compelling cases for large scale, sustained research to assess the US science ecosystem and the full public value of federal support for scientific research.

Broader impacts. The community and infrastructure developed by this project support a range of ongoing research projects; the results are of immediate interest to policy makers and academic administrators. Insights derived from this research can inform the allocation of resources on campus, decisions about how to pursue cutting edge scientific research and even the design and allocation of space in research facilities. At the national and state level, this project contributes to the development of a rigorous science of science policy that can inform decisions about how to allocate public resources for R&D by providing systematic evidence about the productivity of different approaches to organizing research and the larger social and economic results of discovery and learning on research university campuses.


23. Discovering Collaboration Network Structures and Dynamics in Big Data

Researchers: Jian Qin, Syracuse University; Jeffrey Stanton, Syracuse University; Jun Wang, Syracuse University

Understanding how individual scientists interact with one another and how such interaction impacts research productivity and knowledge diffusion is important for understanding the dynamics of scientific research collaboration. At the same time, information about patterns of collaboration and their consequences have implications for science policy. In quantitative research on collaboration networks, publication co-authorships and citation-linkages have been the primary source of data. As large data repositories, one of the signposts for cyberinfrastructure-enabled, data-driven science, become increasingly prevalent, however, they offer an alternative source of information about networks of scientific collaboration.

Intellectual Merit. This project investigates research collaboration networks emerging around one such international data repository, GenBank, and develops data products to support data-driven science policymaking and research. By utilizing this novel data source the project provides an unprecedented opportunity to validate and expand the theory of complex networks while generating rich data outputs and products to support science policy research and policymaking. This study fills a number of theoretical and methodological gaps identified by the 2008 roadmap for Science of Science Policy (SoSP), with a specific focus on how scientific collaboration networks form and evolve. The outcomes of this study address the lack of models and tools for network analysis, visual analytics, and science mapping outlined in the 2008 roadmap for SoSP. To accomplish the data collection and processing required for this project new computational programs will be developed to parse, extract, store, transform, split, merge, and filter the data; these will be applicable to the analysis of other similar data sources for science policy and innovation research.

Broader impacts. By making available dataset product prototypes the project will allow researchers, policy makers, and students to explore research networks in GenBank from longitudinal, thematic, geographical, institutional, and author dimensions. The multi-dimensional, interactive presentations of such datasets enable data-intensive science policy research and support science policymaking through filtering, sorting, associating, and visualization capabilities. The datasets and data products will be made available through an open access mechanism, so educators and undergraduate and graduate students have ample opportunities to use these resources for teaching and research. Students enrolled in Syracuse University's newly established Certificate for Advanced Study in Data Science (CAS DS) program will be able to participate in the project and gain skills in programming for data collection and processing, data quality verification, analysis, and visualization. In addition, the collaboration network analysis provides interested doctoral students an opportunity to do independent study or dissertation research. Findings from studying cyberinfrastructure-supported data sharing and knowledge diffusion is expected to advance policymakers' ability to properly assess the outcomes of federally funded research.


24. Planning Meeting on Indicators of Doctoral Education

Researcher: Connie Citro, National Academy of Sciences

Intellectual Merit. The National Research Council (NRC) of the National Academy of Sciences will hold a planning meeting to discuss the creation of a program to collect and disseminate information about research doctoral education. Participants will include representatives of graduate research programs, higher education associations, organizations that provide comparative information on doctoral programs, and others with relevant knowledge and expertise. This meeting will consider the range of data currently available about doctoral education and the potential uses of additional data that could be obtained with a regular program of data collection. The meeting will also consider several practical aspects of such a program, including the willingness of universities to participate and the possible role of the NRC. The goal of the planning meeting is to determine if there is enough interest in and expected value from an ongoing indicators program to warrant further development work.

The NRC has conducted three prior studies of research doctorate programs that were carried out on an ad hoc basis, with reports published in 1982, 1995, and 2010. The planning meeting will consider the results of these prior studies for insights about the types of data that might be included in an ongoing indicators program, the technical challenges in constructing these different types of data, and the potential value to the field of making such data available. In particular, the planning meeting will consider the use of reputational rankings and the production of program rankings, both of which were criticized in the prior NRC studies. In addition the planning meeting will consider the implications for the design of an ongoing program to provide information about research doctoral education of new information sources that have recently become available, including commercial efforts to provide comparative information on publication and citation data across doctoral programs.

Broader Impacts. A set of doctoral indicators could potentially provide the graduate education community with a number of benefits, including benchmarks for institutional self-improvement, data for higher education research, and comparative information for policymakers and prospective students. As a result, an ongoing indicator program could help drive substantial increases in the quality of research doctoral programs.


25. Small Business Programs, Innovation, and Growth: Estimating Policy Effects Using Comprehensive Firm-Level Panel Data

Researcher: John Earle, George Mason University

In an unusual partnership of university and government researchers working together to link and analyze several very large firm-level databases, this project evaluates the growth and innovation effects of small business support programs. Adapting and extending labor market program evaluation methods, the researchers link administrative program data to universal long-panel data and to a variety of survey data. The main estimation method is based on longitudinal matching combined with regression, and besides estimating the basic average treatment effect on the treated, the project investigates treatment intensity (loan/grant size), analyze potential general equilibrium effects, and examine the heterogeneity of effects by type of program, loan conditions, type of firm, and economic context. The results will enable the first rigorous estimates of government program effects on firm-level innovation and growth.

Intellectual Merit. In addition to its direct policy relevance, this project contributes to theoretical and empirical questions about small firms, growth, innovation, finance, and fiscal policy. Do small businesses support programs foster growth and innovation? Innovation is proxied in several ways: sales and employment growth, productivity, skill-biased employment change, patents, R&D personnel, and survey-based measures; the analysis distinguishes market-expanding from business-stealing effects. Results for loan programs will contribute to the growth-finance debate by analyzing specific policy interventions varying at the firm level, which avoids many of the econometric problems plaguing estimates based on aggregate data. Other issues concern the degree to which firms are financially constrained and the size of the government spending multiplier, for which the project uses firm level microdata to estimate the impact of government programs on small business growth (the first-stage effect), and how it varies over the business cycle.

Broader Impacts. The broader impacts of this research appear, first, in the contribution to urgent policy debates. The question is not only whether the support programs on average increase growth and innovation at recipient firms, but whether these benefits are offset by negative spillovers (displacement effects) or enhanced by positive spillovers (e.g., shared innovation), and also whether they are more effective in some environments (e.g., after negative shocks), for some types of firms (e.g., young start-ups), or for some types of program design (e.g., eligibility criteria and loan terms). Romania is included to provide an international replication, because of the interest in microcredit and financial development in transition economies, and because of the excellent data available for analysis. The project also makes methodological contributions of broader usefulness: exploiting the long panel data to extend matching methods, introducing new types of multiple control groups for more credible identification, and developing new approaches for analyzing the general equilibrium effects of economic policies. The project advances the broad research agenda of linking and analyzing diverse sets of microdata, one of the most promising recent developments in empirical economics. The ideas and methods could serve as models for researchers analyzing other policies, both in the US and in many other countries where similar programs and data exist. The specific data generated by the project through linking of many large databases will have considerable value, and another broad impact may result from making the data available to other researchers. PhD students can and will benefit from learning to work with the data, participating in professional conferences, and writing dissertations on the basis of the data and project.


26. The Biographies of Scientific Ideas: What the Content and Structure of Citations Reveal About the Diffusion of Knowledge

Researchers: Freda Lynn, University of Iowa; Michael Sauder, University of Iowa

Currently, more than a million scholarly articles are published per year. Understanding how these journal articles, often the primary unit of scientific research, are consumed over time by the scientific community is essential to understanding the production and dissemination of knowledge. Conventionally, the main strategy used to gauge the impact of scientific research is to count the number of citations received. The central problem with this approach is that citation counts do not distinguish between the context of the citation (e.g., the difference between positive, critical, and symbolic) nor do they consider the source of the citation (e.g., the difference between 100 detailed references from area experts and 100 ceremonial mentions from non-specialists). Citation counts thus reveal very little about how researchers actually use and interpret existing knowledge, which directly impedes our ability to meaningfully gauge the impact of scientific research.

Intellectual Merit. This project develops new insight into how knowledge accumulates by systematically examining how a set of seed publications are incorporated, distilled, and expanded upon by a set of potentially connected citing publications. This entails compiling a large, longitudinal dataset of focal articles and their citation histories, which will then be analyzed as life histories. The methodological strategy is a unique combination of quantitative and qualitative approaches (citation context analysis, co-citation analysis, citation network analysis) that allows for the "thick description" of issues related to time, interpretation, audience, and disciplinary context.

This project focuses on a large sample of flagship journal articles from two disciplines: sociology and medicine. The results will thus inform long-standing questions about how knowledge accumulates in the 'hard' versus 'soft' sciences. In addition, studying the diffusion and incorporation of medical findings has practical implications for health policy makers, addressing recent claims that clinical research studies typically go unchallenged in the medical research community. Finally, the data generated from this project create new opportunities to study the diffusion of innovations, networks, and social influence. First, by following a cohort of papers published at the same time, the research avoids retrospective sampling on "winning" innovations. Second, for each seed article, the timeline and connectedness of its adopters can be directly mapped via direct citation links as well as co-citation links. Third, unlike most kinds of adoption data (e.g., sales data), citation choices give us some insight into how an innovation was adopted. The content of the citation provides new data on whether some citers are more influential than others in publicizing certain aspects of an innovation.

Broader Impacts. This historical study is designed to produce new insights into what advancement in science actually entails. Examining how ideas are used and incorporated provides a foundation for evaluating the logic and efficiency of knowledge accumulation in science. In the long-term, these insights will enable the development of metrics that describe the use-value of the myriad "new" ideas put forth each year in science. The project thus facilitates the creation of new empirically grounded tools that science and innovation policy makers can use to gauge the scientific impact of research publications and individual scholars.