This chapter addresses institutional and organizational support for team science. Following a brief preface, the first section introduces the organizational perspective. The second section focuses on the role of the research university in supporting team science. The third section discusses various organizational contexts for team science. The fourth section addresses how design of physical space may influence team science, and the chapter ends with conclusions and a recommendation.
Factors at the organizational and institutional1 level influence the dynamics and effectiveness of science teams and larger groups, but research on these factors is limited. Recently, several scholars have highlighted the importance of these factors. For example, O’Rourke et al. (2014, p. 291) proposed that “the relationship between a collaborative, interdisciplinary research project and its context is a key determinant to project success.” Stokols et al. (2008b) identified several organizational factors as important for motivating members of science teams—including strong incentives to support collaborative teamwork; non-hierarchical structures to facilitate team autonomy; and a climate of sharing information, credit, and leadership. Bennett and Gadlin (2014) drew on theories of social identity (how people think about themselves relative to a larger community) and procedural justice in organizations to argue that effective interdisciplinary
1 Social scientists define “institutions” as enduring systems of established and prevalent social rules that structure social interactions (Hodgson, 2006). They define an “organization” as a type of institution that has established boundaries, a differentiated division of labor, and an integrated structure of coordination and control, for example, universities and business firms.
collaboration requires establishing trust between scientific teams and the organizations that house them. The authors viewed trust as the foundation for articulating an organizational vision, implementing change supportive of team science, and managing conflict.
However, few of these organizational factors have been scientifically studied to determine their relationship to the effectiveness of team science. It has been noted by several researchers (e.g., Luo et al., 2010) that empirical research into the institutional infrastructure of scientific research is rare. Winter and Berente (2012) argued that it is impossible to understand the goals of team science projects without considering how project goals are related to the goals of project members’ home institutions, for example, academia, medicine, the law, capitalism, and engineering. Although these institutional goals influence project members’ daily practices and their motivation to pursue the project goals, researchers have given “a dearth of attention to the contexts within which teams operate” (Winter and Berente, 2012, p. 443). Similarly, noting that the structures of research organizations have changed dramatically in recent years, Cummings and Kiesler (2011) called for applying organizational theory to these new arrangements, to enhance understanding of them, guide science policy, and refine theory.
Conducting a full review of the large literature on organizations in terms of its relevance to team science was not possible within the time frame of the study. Here, we briefly review a few relevant studies, noting that they are predominately theoretical and case-study based, in contrast to the empirical and larger-scale studies of individual- and team-level factors reviewed in the previous chapters.
One facet of the ongoing debate in the organizational sciences about the relationship between organizational strategy and organizational structure (e.g., Hall and Saias, 1980; Mintzberg, 1990) considers how organizations can foster innovation through research and development. For example, in an early study, Burns and Stalker (1961) argued that “mechanistic” hierarchical organizational forms and management approaches were suitable for stable industries, while “organic” approaches with more fluid definition of functions and lateral interactions among peers were more suited to rapidly changing, research-intensive industries. Lawrence and Lorsch (1967) argued that successful organizations balance differentiation into functional departments (such as manufacturing, marketing, and research and development) with integration and collaboration across departments. Departments performing more stable tasks, such as manufacturing, had a more hierarchical structure than research and development departments performing rapidly changing tasks.
Focusing specifically on science, Shrum, Genuth, and Chompalov (2007) examined large, multi-institution groups of scientists in the fields of space science, oceanography, particle physics, and geophysics. The authors identified four types of organizational structures among these groups: bureaucratic, leaderless, non-specialized, and participatory. They proposed that the type of structure depended partly on the data collection methods and scope of research activities (i.e., the research strategy). For example, the highly participatory structures of particle physics resulted from the very large numbers of scientists who could collect data only by sharing access to a few particle accelerators, and a broad scope of collaborative activities. More generally, Shrum, Genuth, and Chompalov (2007) found that some degree of formal organization and management enhanced success across all four structures, including the non-hierarchical participatory ones. Surprisingly, given the longstanding scientific tradition of individual autonomy, participants in these large groups valued bureaucratic organizational structures that protected their rights to acquire and use data and prevented any one unit or institution from imposing its interests on the others. Such structures also handled purchases of large amounts of instrumentation, freeing scientists to focus on data collection and analysis. Large groups engaged in innovative technology or difficult logistical challenges benefited from employing professional project managers to deal with budgets and scheduling.
Another strand of organizational research relevant to team science has focused on management to foster innovation. For example, Simons (1995) argued that traditional, hierarchical management systems were obsolete and that, to foster innovation and effectiveness, managers should deploy four “levers of control”:
- Belief systems that employees internalize in response to ongoing leadership efforts to communicate core values through mission statements, credos, and vision statements.
- Boundary systems that define the limits of freedom, such as codes of conduct and ethics statements.
- Diagnostic control systems that are the traditional systems firms use to monitor and adjust operating performance, such as business plans, budgets, and financial and cost-accounting systems.
- Interactive control systems that provide strategic feedback and guidance to update and redirect strategy such as competitive analysis and market feedback reports.
Similarly, O’Reilly and Tushman (2004) described how an “ambidextrous” management approach can help a company become adaptive and innovative, yet at the same time, efficient. Likewise, Adler and Chen (2011) argued that organizations engaged in large-scale creative collaboration need
to help individuals balance the dual challenges of demonstrating creativity and embracing the formal controls that coordinate their creative activities with the activities of others. This suggests that organizations housing science teams (e.g., research centers, national laboratories, universities, private firms) would benefit from helping scientists to think creatively not only about their own, specific research projects, but also about how to best coordinate their efforts with others to advance organizational goals.
Based on an extensive review of the literature on management of research and development and other creative activities, along with motivation theory and identity theory, Adler and Chen (2012) suggested that two types of motivation are most important for creative tasks: intrinsic motivation and identified motivation. Intrinsic motivation refers to the voluntary willingness to engage in a task for the inherent pleasure and satisfaction derived from the task itself (Muyarama et al., 2010). Identified motivation reflects one’s feelings of identity with a group or organization and motivates one to work toward collective goals. The authors proposed that organizations can foster these motivations by adopting human resource policies designed to attract and retain individuals with either high intrinsic motivation or fluid motivation (which is open to organizational influences), and by applying Simon’s (1995) four levers, summarized above.
The authors proposed that organizations wishing to foster collaborative creativity also provide incentives combining individual and team rewards, as team rewards have been shown to encourage creativity (Teasley and Robinson, 2005; Toubia, 2006). They noted an experiment by Chen, Williamson, and Zhou (2012), which found that group-based rewards led to increased creative performance, as well as greater group cohesion and collaboration and increased identification with group objectives.
This brief review of theory and research has potential implication for science teams and for the organizations that house them. The studies reviewed have explored how to manage task uncertainty in rapidly changing environments, which is characteristic of scientific work, particularly in the early stages of developing a research project. Similarly, the various authors highlighted the need to manage interdependence, which is characteristic of science teams, especially interdisciplinary and transdisciplinary teams (Fiore, 2008). However, much further research is needed to more clearly articulate the connections between organizational theory and research and team science.
Experts in higher education studies view universities as complex organizations composed of multiple, loosely coupled subsystems (Austin, 2011). Faculty members work within various contexts and cultures—including the
department, the college, the institution as a whole, and external groups, such as disciplinary societies and accrediting associations—that can be conceptualized as “levels” of the university organization. These various contexts and cultures influence faculty attitudes and choices about research, teaching, and service, including their attitudes and decisions related to team science. Within these complex systems, some of the key factors influencing faculty behavior include evaluation and reward systems, workload allocation, professional development opportunities, and leadership. Multiple factors at multiple levels of the system simultaneously influence faculty member choices and behaviors. Given that higher education institutions are complex organizations, change efforts are most effective when they use both a “top-down” and a “bottom-up” approach, take into consideration the factors at work within the multiple contexts that affect faculty work, and strategically utilize multiple change factors (Austin, 2011). With this perspective in mind, we now turn to a discussion of how universities are working to support team science.
University Efforts to Promote Interdisciplinary Team Science
Many experts view current university policies and discipline-based organizational structures as an impediment to interdisciplinary team science. For example, Klein et al. (2013, p. 1) argued that “obstacles to . . . [interdisciplinary team science] span the entire academic system of organizational structure and administration, procedures and policies, resources and infrastructure and recognition, reward, and incentives.” In an earlier study, Klein (2010) called for a comprehensive, university-wide approach to remove obstacles to interdisciplinary research and teaching among faculty who are part of the entrenched disciplinary culture and organization of research universities.
In contrast to these views, universities around the country have recently launched many efforts to promote interdisciplinary team science (see Duderstadt, 2000; Frodeman et al., 2010; Klein, 2010; Altbach, Gumport, and Berdahl, 2011; Repko, 2011; O’Rourke et al., 2014; among others). University leaders have created new science teams, larger groups, and research centers, encountering the benefits and challenges of diverse membership and deep knowledge integration, while also generating new challenges of goal alignment among the new teams and other entities. One example, among many, is Arizona State University (ASU). In the past decade, under the leadership of President Michael Crow, ASU has become a national pacesetter in restructuring the university to promote interdisciplinary team research and teaching (Crow and Dabars, 2013; Martinez, 2013; see also http://newamericanuniversity.asu.edu [May 2015]). Using a top-down, institutional redesign approach, the university has built new interdisciplinary
schools and research centers, including a School of Biodesign, a School of Sustainability, a School of Human Evolution and Social Change, and a Beyond Center. These efforts have attracted much research funding, many students, and highly qualified faculty to the university, but sometimes with the costs associated with frequent organizational restructuring of academic units.
The University of Southern California (USC) has adopted a more bottom-up approach to supporting team science, creating a fund to provide seed grants to interdisciplinary projects selected by a faculty committee and revising its promotion and tenure policies with faculty involvement, as discussed further below. It will be interesting to see how these different approaches at USC and ASU play out in a longer time perspective, and if one is more effective than the other in promoting academic culture change over time. It also will be important to see how these changes not only directly affect team science research, but also student training, because, as Austin (2011) cogently argued, “doctoral socialization” by Ph.D. advisors in the training of prospective faculty members strongly influences how the next generation of faculty view teaching and research, including team science. M. Duane Nellis, president of the University of Idaho (2013, p. 226), calls for both approaches, arguing that efforts to promote transdisciplinary research “must be led both from administrators at the top and from a broad spectrum of faculty at the base.” However, he also cautions that implementation of administrative policies and procedures is uneven, due to the influence of traditional departmental and disciplinary boundaries and cultures, and the lack of funding for cross-departmental research efforts (e.g., in the form of research assistantships).
Many other examples of efforts to promote interdisciplinary team science can be found at campuses across the United States. Northwestern University, under the leadership of former President Henry Bienen and continuing to today, provides a good example. Bienen fostered ties to the Argonne National Laboratory and to the Chicago biomedical community, as well as stimulating and supporting interdisciplinary team science on campus. In another example, Rutgers University President Robert Barchi is encouraging interdisciplinary research by placing several “catalysts” throughout the university, including creating a new position, director of research development, within the Office of the Vice President for Research (Murphy, 2013). Barchi has also merged two medical schools, a nursing school, and a school of applied health professions onto the main Rutgers campus, fostering an intermingling of faculty that has led to growing interdisciplinary team science efforts.
Promotion and Tenure Decisions and Team Science
Although scientists are motivated by a variety of factors, including prestige and the freedom to pursue their individual research interests (Furman and Gaule, 2013), one important factor is money. Thus, an important way universities can support team science is by recognizing and rewarding individuals for their team-based accomplishments when granting tenure. Decisions about promotion and tenure are typically made by faculty committees within disciplinary departments, with review and approval by the dean of the relevant school and higher-level administrators. These decisions are affected by current trends and more enduring scientific norms.
One important trend is the decline (in real terms) of total federal and state funding for scientific research (National Research Council, 2012a). In biomedicine, for example, based on the expectation that past funding increases for biomedical research would continue indefinitely, universities have created more and more research positions that depend on temporary grants (often referred to as “soft money”). They have continued in an evermore intense competition for a shrinking pool of federal dollars (which do not cover all costs of research) while also responding to federal and state regulatory and reporting requests that impose burdensome monetary and time costs (National Research Council, 2012a; Alberts et al., 2014). These financial problems discourage universities from providing tenure.
Another, partially related trend is the decline of tenure. The percentage of degree-granting institutions with tenure has declined from 63 percent in the 1993–1994 academic year to 45 percent in the 2011–2012 academic year (U.S. Department of Education, 2013). In 1969, 78 percent of faculty members were tenured or in tenure-track positions; by 2009, only 34 percent of faculty members were in tenured or tenure-track positions (Kezar and Maxey, 2013). Tenure rates even within the ranks of only full-time instructors have also declined—from 56 percent in the 1993–1994 academic year to 49 percent in the 2011–2012 academic year (U.S. Department of Education, 2013). Replacing tenured and tenure-track positions are “adjunct” positions, staffed by instructors who may be hired on 1-year contracts or paid by the course (Kezar and Maxey, 2013).
While these two trends reduce tenure prospects for all young scientists, enduring scientific norms may pose special obstacles to candidates seeking tenure for team science.
In his classic studies of the “Matthew Effect,” Merton (1968, 1988) found that more eminent coauthors tended to receive disproportionately more credit for team-authored work than their less eminent coauthors. The Mathew Effect can also work in reverse. Jin et al. (2014) investigated how retractions (papers recalled because of errors) affect trust in an author’s prior work as measured by citations to the author’s prior publications. They
found that scientific misconduct imposes little citation penalty on eminent coauthors, but less eminent coauthors face substantial citation declines to their prior work.
The Matthew Effect suggests that in assessing authors’ contributions to a collaborative paper, the scientific community presumes that the more eminent coauthor deserves the lion’s share of the credit, whereas the other co-authors are relegated to subordinate roles. Merton noted that this pervasive credit assignment mechanism is likely to affect scientists’ career advancement and motivation for working in teams.
Faculty members charged with making tenure decisions are influenced by these current trends and norms. Pressed for time because of the competing demands of service on the tenure committee and their own research and teaching, they may not thoughtfully read the candidate’s scholarly publications, but rather seek shortcuts, in the form of simple metrics to assess the quality and importance of the candidate’s work (Tscharntke et al., 2007). For example, they may focus primarily on whether the candidate has published in the most prestigious journals within the relevant field or on the “impact” of the candidate’s publications (the number of times the publication is cited by others). When asked to evaluate a candidate’s contributions to team research, as reflected in multi-authored publications, committee members face additional challenges, including potential bias resulting from the Matthew Effect (Merton, 1968). Disciplinary norms for assigning credit based on the order of the authors’ names may not help in assigning credit for interdisciplinary publications. In addition, Tscharntke et al. (2007) noted that, beyond the widely accepted norm that the first author should receive most credit, norms for assigning credit in multi-authored publications vary widely across research fields and countries.
Current Status of Promotion and Tenure for Team Science
Systematic data about the extent to which candidates do or do not win tenure on the basis of team science research are lacking. However, respondents to surveys conducted as part of an earlier National Academies study (National Academy of Sciences, National Academy of Engineering, and Institute of Medicine, 2005) ranked promotion and tenure criteria the highest of the five impediments to interdisciplinary research. Based on a literature review on promotion and tenure policies and practices affecting interdisciplinary team science (Klein et al., 2013), Professor Julie T. Klein, Wayne State University, told the committee:
The current picture across campuses, however, is more mixed. Risks differ by field and by institution. Furthermore, a growing body of precedents, guidelines, and models are available. Individuals are still too often vulner-
able, however. An old saw continues to haunt prospects for tenure and promotion: “Tenure first, interdisciplinarity later. . . . Its counterpart in team science is ‘Individual reputation first, collaboration later.’”
Echoing similar concerns, the United Kingdom Academy of Medical Sciences has launched a study of incentives and disincentives for participating in team science (Academy of Medical Sciences, 2013). Taken together, these various reports indicate that uneven evaluation of tenure candidates’ contributions to team science projects poses a barrier to their chances of winning tenure.
University Policies for Supporting Team Science Through Tenure and Promotion
No systematic, national data are available on university policies designed to help promotion and tenure committees recognize and reward team science. However, a recent survey by Hall et al. (2013) provides some suggestive evidence. The survey asked 60 institutions receiving Clinical and Translational Science Awards from NIH about their tenure and promotion policies. The authors noted that this is a biased sample, because the center awards are specifically designed to support translational team science and grantee institutions are therefore more likely than other institutions to recognize team science in their policies. Of the 42 institutions that responded, 10 indicated that their promotion and tenure guidelines did not include any language specific to collaborative, interdisciplinary research and/or team science, while 32 did have such language. Among the 32 guidelines with such language, most included small modifications to traditional promotion and tenure criteria and primarily focused on issues of authorship (e.g., suggestions to annotate the candidate’s bibliography to substantiate middle-authorship roles). Only a handful offered alternative criteria meant to capture contributions unique to the team science. These criteria were vague and did not include indicators or metrics of attainment, relying instead on written statements by the candidates and their collaborators. The authors called for further research and development of actionable criteria to assess individual contributions to team science. In particular, they called for research to better understand contributions made by scientists that advance scientific research through actions and roles other than authorship.
As indicated by the survey, some universities are providing more guidance to departments, deans, and tenure and promotion committees than in the past for evaluating scientists involved in interdisciplinary and team science research. In doing so, they face the challenge of not only developing high-level goals or policy statements, but also implementing or aligning these goals with the culture of departments and individual faculty members
at lower levels within the university system. The following example illustrates how USC built a new approach from the bottom up.
The USC (2011) guidelines for assigning authorship and attributing research contributions provide straightforward principles and policies for evaluating individual scholarly contributions to research and publication. Developed by faculty committees following a series of six workshops on collaboration and creativity (see Berrett, 2011) and approved by the university’s academic senate, the guidelines deserve to be the starting point for discussions at campuses around the country. The guidelines (University of Southern California, 2011) commit USC to four strong principles:
- fair and honest attribution of the contributions of each person in the creation of research products and creative works;
- allowance for diversity in the attribution of contributions, which vary across disciplines and dissemination outlets;
- making our research products and creative works readily available to others, so that they may be further developed or implemented; and
- avoidance of disputes over attribution and ownership that may create impediments to the creation and dissemination of significant and impactful research, scholarship, and creative works.
The guidelines further clarify the types of contributions required to qualify as an author and ask team members to decide among themselves about the order of author names, acknowledging that conventions for order of authorship vary across disciplines.
New policies such as those at USC are unusual, and most of the available evidence indicates that university policies typically lack clear criteria for evaluating an individual candidate’s contributions to team-based research. To address this problem, the committee recommends at the end of this chapter that universities and disciplinary associations develop broad principles and more specific criteria for tenure committees’ use when allocating individual credit for team-based work, echoing the recommendation of a recent National Research Council (NRC) report on transdisciplinary research, or “convergence” (2014).
Recent Developments in Authorship Attribution
In a recent development that could assist universities in the difficult challenge of allocating credit for team-based work, major journals, such as the Proceedings of the National Academy of Sciences, Nature, and the journals published by the Public Library of Science, have begun to require an “author contributions” section describing each author’s contribution to
the published article. Such sections represent a potential step forward from relying on varying authorship conventions to determine how much credit each author deserves for a publication. Tscharntke et al. (2007) proposed that, when preparing these “author contributions” sections, the authors should explicitly identify the authorship convention to be used in allocating credit for the work, such as stating that the authors are listed in order of importance of contribution or that all authors contributed equally. To simplify and standardize the process of describing all contributions, Allen et al. (2014) developed a preliminary taxonomy of 14 contributor roles, ranging from study conception to providing resources. Such a taxonomy could be included in manuscript-submission software, allowing researchers to easily assign roles in the process of writing and submitting the paper. Two of the authors of the Allen et al. (2014) taxonomy have launched a project to further develop, maintain, and implement it, in collaboration with publishers, funding agencies, researchers, and university administrators (CRediT, 2015).
Another new approach would build on the emerging databases of scientific authors and publications, such as the research networking systems discussed in Chapter 4. Such databases allow scientists to interact, form networks and interest groups, and rate each other’s publications. New software additions to these systems could allow multiple authors of a paper to publish descriptions of each member’s contribution, and each contributor could verify what others contributed (Frische, 2012). If widely accepted, then these types of systems would be helpful to scientific journals, funding agencies, and university promotion and tenure committees.
Individual and Team Rewards
Awarding tenure is only one component within the larger academic and scientific system of rewards and incentives. The questions surrounding how to recognize individual contributions to team-based research in tenure decisions raise related questions about the possibility of recognizing and rewarding teams. As discussed earlier in this chapter, recent research suggests that team-based rewards support team creativity. In addition, Horstman and Chen (2012) have recently studied group-based rewards for individual and group contributions to solving scientific problems. Further research is needed on this topic.
Team science is conducted in a variety of organizational contexts that may be located within, outside, or span the boundaries of the research university. For example, government-university-industry partnerships may be
organized as networks, research centers, or free-standing institutes. Here, we briefly discuss some of these contexts.
Over the past two decades, universities, businesses, and public and private funders have increasingly established research centers and institutes to support multiple, interrelated research projects focusing on a common theme.2 In 2006 (the most recent year for which data are available), there were an estimated 14,000 nonprofit research centers in the United States (D. Gray, 2008). Centers and institutes often house interdisciplinary or transdisciplinary research and university-industry research partnerships. For example, a recent NRC study (2014) focused on “convergence institutes,” which integrate life sciences, physical sciences, and engineering and forge industry partnerships to support the research and facilitate its translation. The study profiled institutes such as Bio-X at Stanford University, the David H. Koch Institute for Integrative Cancer Research at the Massachusetts Institute of Technology, and others. These and other transdisciplinary research centers encounter both the benefits and challenges of diverse membership, deep disciplinary integration, and large size.
Although only limited research is available on the processes and outcomes of research centers and institutes (Bozeman, Fay, and Slade, 2012), evaluations of federally funded centers provide some insights. For example, the National Science Foundation (NSF) launched the Science and Technology Centers (STC) Integrative Partnerships Program in 1987, in response to a call from President Reagan. Solicitations for center awards set the range at $1.5–4 million per year, for a maximum of 10 years. A recent review of this program by the American Association for the Advancement of Science (AAAS; Chubin et al., 2009) found that it was “an effective and distinctive mode of Foundation support for addressing grand challenges and emerging opportunities in science and technology” (p. 79). Based on analysis of multiple measures, including publication counts and participant surveys, the authors concluded that the STC program had succeeded in (1) connecting national priorities in science and engineering with “frontier” academic science and engineering research; (2) encouraging established researchers to venture into more risky areas; (3) bringing together different disciplines; and (4) fostering collaboration between basic and applied scientists. The authors also found that the program positively affected doctoral student training and the centers actively carried out “knowledge transfer” activities, ranging from publishing articles and creating new journals to supporting regional economic development through technological innovation.
2 Chapter 9 provides data on the growth in NSF and NIH funding of research centers.
The review also noted weaknesses of program management. At the time of the review, the STC program did not belong to any single research directorate or office within NSF and was forced to compete for resources not only with the traditional individual-investigator mode of support, but also with directorate-based center programs. The matrix model of the organization was found to impede accountability, and the annual review process—a key tool used by NSF to monitor performance—was “vulnerable to changing, inconsistent and at times idiosyncratic advice from review teams” (Chubin et al., 2009, p. 84). Finally, reflecting the need for this study and the science of team science, the review found that the existing system for collecting and analyzing performance data was poorly suited to evidence-based decision making.
In 2006, NIH launched the Clinical and Translational Science Awards (CTSA) Program to “advance the assembly of institutional academic ‘homes’ that can provide integrated intellectual and physical resources for the conduct of original clinical and translational science” (Zerhouni, 2005, p. 1622).
The program built on the NIH General Clinical Research Centers Program, which had provided clinical research infrastructure funding, as well as funding programs for disease-specific centers. Under it, individual research centers are funded through 5-year cooperative agreements, with site budgets ranging from $4 million to $23 million annually. The Institute of Medicine (2013) found that the program has demonstrated progress in three crosscutting domains that are important to advancing clinical and translational science: training and education, community engagement, and child health research. The IOM committee recommended that the program continue to provide training, mentoring, and education as essential core elements, emphasizing innovative models that include a focus on team science. They also recommended that the program disseminate high-quality online offerings for essential core courses for use in CTSA centers and other institutions. If these recommendations are implemented, then such courses would help to provide the professional development for team science recommended in Chapter 5.
To address the promotion and tenure challenges discussed earlier in this chapter, IOM recommended that CTSA “champion the reshaping of career development pathways for researchers involved in the conduct of clinical and translational science; and ensure flexible and personalized training experiences that offer optional advanced degrees” (p. 116).
Like the AAAS review of the STC Program, the IOM review of the CTSA Program identified management weaknesses. Specifically, the authors found that program leadership has relied primarily on the efforts of individual centers (awardees) and their principal investigators, leading to a largely ad hoc structure and process for identifying next steps and overall
management. They also found that NIH had provided direction primarily through the funding announcements, which had emphasized different key functions or priorities in different grant cycles. To address this problem, the report recommended that the National Center for Advancing Translational Sciences strengthen its leadership of the program through several steps, including conducting a strategic planning process, forming partnerships with NIH institutes and centers, evaluating the program as a whole, and distilling and widely disseminating best practices and lessons learned.
To more clearly determine the outcomes of its investment in large, transdisciplinary research centers, the National Cancer Institute has supported an ongoing program of research on the effectiveness of team science (e.g., Stokols et al., 2008a). The insights emerging from this research program are discussed throughout this report.
University-Industry Research Partnerships
Earlier sections of this chapter discussed the challenges faced by universities in developing, maintaining, and assessing the success of science teams and larger groups. In university-industry research partnerships, new problems emerge, including proprietary concerns and profit motives in the development of commercial products. Because of the complexity of partnerships between universities and businesses with different motives and organizational structures, Bozeman and Boardman (2013)3 refer to them in a paper commissioned by the committee as “boundary-spanning research collaborations.”
Bozeman and Boardman (2013) conducted an extensive review of the literature on university-industry research partnerships and industry-industry interdisciplinary research partnerships, building on the review by Bozeman, Fay, and Slade (2012) on similar topics. Both types of partnerships are often housed in research centers or institutes.
Bozeman and Boardman (2013) found that the inclusion of multiple disciplines in university-industry research collaborations increased productivity but also was associated with increased diversity of incentives and motivations. Perhaps to address these diverse motivations, partnerships including multiple disciplines were more hierarchical and formally structured than partnerships involving only a single discipline. More generally, the authors found that prior acquaintance and trust were key factors for success in university-industry research partnerships, and, where these elements were absent, creating formal structures and authorities helped to manage conflict
3 After submitting this paper to NRC, the authors subsequently published a paper addressing many of the same issues, titled Research Collaboration and Team Science, A State-of-the-Art Review and Agenda; see http://www.springer.com/series/11653 [May 2015].
and improve effectiveness. However, they also discussed a study focusing on Australian university-industry cooperative research centers that found that the formal legal contracts establishing the centers were rarely enforced (Garett-Jones, Turpin, and Diment, 2010). Instead, researchers and organizations within the centers relied on informal social mechanisms, such as trust and reciprocity, to coordinate work. In the absence of legal sanctions, researchers who perceived breaches of trust became less enthusiastic about the collaborative work and some withdrew from the centers. This study suggests that it is important to enforce the formal structures and authorities created when establishing university-industry research partnerships.
Bozeman and Boardman (2013) identified three major gaps in the research on university-industry partnerships. First, research on effective management of such partnerships is underdeveloped, often identifying best practices that are local, and may not work robustly across different contexts and situations. The scant available literature suggests that managerial practices are “poorly thought out and haphazard” (Bozeman and Boardman, 2013, p. 65). Second, little research focuses on the “dark” side of boundary-spanning research collaborations. Research on the failures of these collaborations is scarce. Failure was most prevalent when both formal and informal management structures were weak or one or the other was absent. Third, although some research suggests that intellectual property disputes are a real source of failures in university-industry research partnerships, there is little empirical research that directly addresses this issue. The limited research available suggests that careful contract monitoring can help to address intellectual property disputes, but such monitoring is sometimes lacking (e.g., Garett-Jones, Turpin, and Diment, 2010).
Bozeman and Boardman (2013) concluded that much remains unknown about university-industry research partnerships. They argued that evaluating the performance of these large groups of scientists is difficult because of measurement challenges (as discussed in Chapter 2), but more importantly to the lack of any baseline comparisons. The authors note that it remains unknown whether the scientists collaborating within a particular partnership or center would be more or less productive working individually or with collaborators other than those involved in the partnership. As noted in Chapter 1, a study by Hall et al. (2012b) begins to address this challenge, using quasi-experimental methods to compare the research productivity of scientists participating in large research centers with that of scientists investigating the same topics, but working individually or in small groups unaffiliated with the centers.
Bozeman and Boardman (2013) suggested that more research is needed on (1) how scientists, universities, and firms choose research partners; (2) the reasons for failure in university-industry partnerships; (3) the role of partnership participation in developing the human capital of individual
scientists (i.e., their knowledge and social networks); and (4) effective management strategies for these partnerships. To address these and other gaps in the research, the authors called for moving beyond descriptive and taxonomic case studies to more systematic field and quasi-experimental research designs and moving beyond individual impact studies (e.g., individual productivity) to a greater concern with institutional outcomes.
Clearly, further research is needed to improve the management of university-industry research partnerships, as well as centers and institutes that are primarily academic. One study (D. Gray, 2008) pointed to improvement-oriented evaluation approaches as a way to both understand and improve center management. The NSF Industry/University Cooperative Research Program has adopted an improvement-oriented approach that meets the needs of an important internal stakeholder—the center director. The new approach has placed an on-site evaluator at each center. The evaluator (usually a social scientist) is uniquely positioned as both a center participant and an evaluator to identify and share with the director emerging challenges and problems. In addition to serving as consultants to the directors and conducting ongoing surveys, the on-site evaluators have contributed to a volume of best practices that is available to the center directors and the public on the NSF website (Gray and Walters, 1998). The use of ongoing, improvement-oriented evaluation to enhance performance at the center or institute level is somewhat similar to team development approaches at the team level discussed in Chapter 3. For example, the Productivity Measurement and Enhancement System (ProMES; Pritchard et al., 1988) intervention, which measures performance and provides structured feedback, has been shown to improve team self-regulation and performance (Pritchard et al., 2008).
Universities can support university-industry research partnerships and other types of research centers by providing the leaders with formal leadership training, as recommended in Chapter 6. They can also encourage leaders and participants in newly formed research centers or institutes to articulate their expectations through written charters or collaborative agreements (Bennett, Gadlin, and Levine-Finley, 2010; Asencio et al., 2012). Such documents outline how tasks will be accomplished, how communication will take place, and how issues such as finances, data sharing, and credit for publications and patents will be handled.
Inter-Firm Research Partnerships
Research collaborations involving multiple companies may take various forms, including research parks, research and development alliances with formal contracts, and joint ventures. In their literature review, Bozeman and Boardman (2013) found that inter-firm research partnerships shared
many of the challenges of university-industry research centers. For example, in interdisciplinary and transdisciplinary inter-firm research partnerships including multiple firms, a lack of formal authorities and structures was associated with failures and, although careful contract monitoring and enforcement were vital to success, they were not always present. In addition, the authors identified gaps in the literature on inter-firm research partnerships similar to those in the literature on university-industry research partnerships.
Formal and informal research networks play an important role in catalyzing and supporting team science. For example, informal networks of scientists are often based on prior acquaintance, which, as noted above, facilitates rapid development of trust and thus supports the effectiveness of science teams and larger groups. Cummings and Kiesler (2008) found that virtual collaboration among groups of scientists was more likely to be maintained when the scientists collaborated with colleagues they had worked with previously. Disciplinary and interdisciplinary scientific societies provide opportunities for scientists to develop networks of colleagues with similar interests, through conferences, meetings, and online discussion boards, but fewer opportunities are available for scientists to establish professional relationships across disciplines.
Research funders have catalyzed the formation of networks to develop research on interdisciplinary topics, such as the Network on BioBehavioral Pathways in Cancer (National Cancer Institute, 2015). In another example, the MacArthur Foundation used a network approach to foster interdisciplinary research on mental health and positive psychology. Kahn (1993) described the evolution of the network, including the development of close interpersonal and intellectual relationships among the geographically dispersed participants. He reported promising early results, including the development of new data banks and resources available to investigators everywhere, along with validated assessment instruments. One indicator of the promise of this approach was the foundation’s subsequent decision to fund research networks focusing on other topics, including the transition to adulthood.
Regardless of where collaborative scientific research is conducted, it requires supportive physical environments. According to Stokols (2013), the features of team environments can enhance or hinder team members’
capacity to focus their attention on developing shared knowledge, effective communication, and positive affect.
Yet while it appears to be intuitively obvious that physical environments influence the nature of team science, Owen-Smith’s (2013) review of the relevant research found surprisingly little empirical evidence to back up such an impression.
Among the studies that do address this issue, Stokols et al. (2008b, p. S100) noted that a study of interdisciplinary treatment teams in hospitals by Vinokur-Kaplan (1995) found that “members’ ratings of physical environmental conditions at work, such as the availability of quiet and comfortable places for team meetings. . . were positively related to reported levels of interdisciplinary collaboration.” Studies by Kabo et al. (2013a, 2013b) have shown that within buildings (and on particular floors), walking path overlaps among scientists also promote collaboration. There are also numerous studies of corporate workspace design (see, e.g., Steele, 1986; Brill, Weidemann, and BOSTI Associates, 2001; Becker, 2004; and Doorley and Witthoff, 2012, among many others) that relate productivity to architectural design. However, Owen-Smith (2013) argued that many other contextual factors beyond the physical environment, such as organizational reward systems (e.g., promotion and tenure policies), also influence scientists’ motivation to participate in team science and therefore more systematic research is needed before firm conclusions can be drawn.
Anecdotally, it would appear that physical spaces that encourage interaction among scientists, from regular interchanges to chance encounters, help stimulate collaborative thinking and work. The Santa Fe Institute, for example, provides open spaces with plenty of comfortable chairs, sofas, and white boards; offices with glass windows facing open spaces; offices shared with scholars from different disciplines; abundant glass walls with available markers to encourage scientists to write algorithms they are discussing on the glass and not wait to return to their offices; and lunches and teas shared by everyone in common spaces. Directors of other research centers share similar impressions. For example, at the NRC workshop on Key Challenges in the Implementation of Convergence, Carla Schatz, director of the transdisciplinary BioX Institute at Stanford University, emphasized the value of creating a physical home for core faculty, with a good cafeteria and high-quality coffee. The building, she said, serves as both a gathering point and a recruiting tool for attracting scientists across disciplinary boundaries to join the Institute and advance human health.4
However, the relationship of these physical design factors with successful team science remains impressionistic and unconfirmed by rigorous study.
Two recent studies that used experimental designs point toward the type of research needed on this topic. First, Catalini (2012) exploited the fact that multiple academic departments at the University of Pierre and Marie Curie (UPMC) in Paris were relocated over a 5-year period because of an asbestos removal project to examine the role of location on collaboration patterns in a precise way that enabled him to identify the casual influence of location on research collaboration. He found that random relocations that resulted in co-location encouraged collaborations and also breakthrough ideas across academic fields. Boudreau et al. (2012) undertook a similarly creative effort to understand the role of location in collaboration by conducting a field experiment in which they randomized researcher locations, finding that those in even briefly co-located environments were more likely to collaborate.
The research to date, which has primarily examined correlational relationships, suggests several findings: spatial design that emphasizes functional zones where scientists’ walking paths consistently overlap (Kabo et al., 2013a) leads to increased interaction; increased interaction can lead to stronger collaborations; and such collaborations can help lead to scientific successes. There are growing data to support these general correlations (see recent studies by Toker and Gray, 2008, Rashid, Wineman, and Zimring, 2009, and Sailer and McCulloh, 2012, all cited by Owen-Smith, 2013), but translating these correlations to proven causal relationships generally remains to be achieved. In particular, further research is needed that considers the role of physical space as one factor among many that influence the extent and quality of team science.
Science teams and larger research centers and institutes are often housed within universities. In these complex organizations, faculty members’ decisions about whether and when to participate in team science are influenced by various contexts and cultures, including the department, the college, the institution as a whole, and external groups, such as disciplinary societies. Formal rewards and incentive structures, reflecting these various cultures, currently tend to focus on individual research contributions. Some universities have recently sought to promote interdisciplinary team science by, for example, merging disciplinary departments to create interdisciplinary research centers or schools, providing seed grants, and forging partnerships with industry. However, little is known about the impact of these efforts, while the lack of recognition and rewards for team science can deter faculty members from pursuing it.
CONCLUSION. Various research universities have undertaken new efforts to promote interdisciplinary team science, such as merging disciplinary departments to create interdisciplinary research centers or schools. However, the impact of these initiatives on the amount and quality of team science research remains to be systematically evaluated.
CONCLUSION. University policies for promotion and tenure review typically do not provide comprehensive, clearly articulated criteria for evaluating individual contributions to team-based research. The extent to which researchers are rewarded for team-based research varies widely across and within universities. Where team-based research is not rewarded, young faculty may be discouraged from joining those projects.
In a few isolated cases, universities have developed new policies for attributing individual contributions to team science. At the same time, research has begun to characterize the various types of individual contributions and develop software systems that would identify each individual’s role during the process of submitting and publishing an article. This work can inform new efforts by universities and disciplinary associations.
RECOMMENDATION 6: Universities and disciplinary associations should proactively develop and evaluate broad principles and more specific criteria for allocating credit for team-based work to assist tenure and promotion committees in reviewing candidates.
This chapter illuminates the limited evidence about team science from an organizational perspective. For example, at a time of many university efforts to promote interdisciplinary and transdisciplinary team science, Jacobs (2014) argued that there are dangers attached to a wholesale move away from traditional disciplines. He suggested that the growing volume of research makes specialization inevitable, and he viewed disciplines as broad and dynamic, in contrast to interdisciplinary research, which may be narrow and specialized. Finally, he argued that research universities based upon interdisciplinary principles may be more centralized, less creative, and more balkanized than current, very successful research universities. Such views highlight the need for more research on the outcomes and impacts of current university efforts to promote team science.
Further research is needed to more clearly understand how alternative organizational structures, management approaches, and funding strategies influence the processes and outcomes of research centers and other large groups of scientists. In addition, further research is needed that moves beyond correlations to consider how the physical environment interacts with other environmental factors (e.g., reward structures, time pressures) to motivate and/or discourage collaborative team science.