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Research centers in transition: patterns of convergence and diversity

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Abstract

Governments continue to play a central role in the way research is conducted and organized by defining new models for research centers. How do existing research centers adapt to changes in their environment? Institutional theory suggests that organizations pursue efficiency and legitimacy by conforming to isomorphic pressures in their organizational field, which will eventually lead to a reduction of diversity in organizational practices and strategies. Resource-dependence theory assumes a more active agency and calls attention to the diverse strategic responses of organizations to institutional processes. Based on funding microdata and qualitative information at center level, this study undertakes to analyze changes in two populations of Spanish research centers (government laboratories and technology centers) in a time of evolving policy paradigms, emergence of new models for research centers, and increasing competition in the field of R&D. We find that a large share of the existing government laboratories and technology centers have progressively conformed to a funding strategy based on diversifying sources and increasing competitive public funding, although both populations are still characterized by some degree of internal diversity regarding funding portfolios. Structural heterogeneity also remains as regards management practices such as research planning and agenda setting.

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Notes

  1. The average government sector share of the total gross expenditure on research and development (GERD) in OECD countries has decreased from 18% in 1980, to 11% in 2007 (OECD 2009).

  2. We will not enter here into the debate about the novelty of this new mode (Weingart 1997; Pestre 2003).

  3. Governments in other countries have promoted changes in research centers, some of them inspired by the New Public Management (Nedeva and Boden 2006; Boden et al. 2006), that have ranged from privatization to implementation of new management practices; examples can be found in the United Kingdom (Boden et al. 2004; Cohen et al. 1999), New Zealand (Liyanage and Mitchell 1993), Canada (Smith 2000), France (Larédo 2001), United States (Jordan 2001) and other countries (Cox et al. 2001). The general transformation of research centers, especially public ones, has also attracted attention from international policy think tanks (OECD 1989, 2003) and academia (Van der Meulen and Rip 1994; Senker 2000; Jansen 2007).

  4. The National Research Center on Cancer (CNIO) is probably, if not the first, the canonical exemplar because of impact and size; it was created at the initiative of the Ministry of Health in 1998. The CNIO was established following the model of a publically controlled but private nonprofit foundation (Barbacid 2008); another is the National Cardiovascular Research Center (CNIC). Additional hybrid centers have been created with the involvement of regional governments (the most active has been the Catalan Regional Government), universities and other public research organizations (including hospitals), in different fields of research; examples include, in the area of biology and biomedical research: the Center for Genomic Regulation (CRG) created in 2000, the Center for Regenerative Medicine in Barcelona (CMRB) created in 2004 and the Biomedical Research Institute (IRB) created in 2005; or in the area of engineering and physical sciences, the Institute of Chemical Research in Catalonia (ICIQ) created in 2000 and the Catalan Center for Telecommunication Technologies (CTTC) created in 2001. The regional governments monitoring these new centers usually establish long term funding and management contracts (Contratos Programa) defining measurable objectives, supplying resources via block grants amounting to no more than 50% of total expenditures, and fixing target objectives for funding from competitive and private sources.

  5. They also appear to be more efficient in terms of competition for funding and recognition; despite their recent creation and small number, the new hybrid research centers have been very successful. For example, in the first call for proposals launched by the European Research Council (ERC), evaluated exclusively on the basis of quality and excellence at the European level, the hybrids have obtained 13 out of the 25 Starting Grants and 6 out of the 13 Advanced Grants awarded to all Spanish institutions, ahead of other government laboratories and universities (information as of 24 April 2009).

  6. In a preliminary analysis of seven hybrids (see footnote 4 above) we found that in all cases the creation of the new center started with the selection of the Director, the development of a research project and the establishment of a multiannual “management contract” with the principal (promoter) fixing funding mechanisms and scientific objectives.

  7. For the purpose of providing an empirical snapshot of the new hybrid centers we have used a group of six hybrid centers [one created under the national government (CNIO) and five under the Catalan regional government (CRG, CMRB, IRB, ICIQ, CTTC)] as a reference. For 2008 on average 56% (σ = 1) of the funding for these six centers was from non-competitive public sources, 29% (σ = 5) from competitive public sources and 15% (σ = 5) from private market sources.

  8. For example, the National Cardiovascular Research Center (CNIC) which has emerged as a model of public–private partnership, has a strong commitment from private industry (13 companies) to contribute 180 million euros over a 10-year period, to cover 32% of CNIC’s expenditure budget (Sanz and Fuster 2008).

  9. For a recent review, see for example Scott (2008) or Organizational institutionalism, edited by Greenwood et al. (2008).

  10. DiMaggio and Powell (1983) defined “organizational fields” as “those organizations that, in the aggregate, constitute a recognized area of institutional life: key suppliers, resource and product consumers, regulatory agencies and other organizations that produce similar services or products” (1983: 148–149). They also highlighted the process of structuration of the field through interactions and connections between members, leading to recognition of their mutual involvement in a common enterprise (1983: 148).

  11. There are exceptions such as Ashworth et al. (2009).

  12. Scholars have identified several organizational attributes that are subject to isomorphism, and whereas initial concerns were with structures and practices, more recently, strategies have also become a focus of analysis (Fligstein 1991; Haveman 1993; Deephouse 1996).

  13. We adopt the definition of organizational field given in footnote 10 but the hypotheses are tested on two populations of centers which are knowledge producers.

  14. The total income and number of employees of the 62 technology centers affiliated to FEDIT in 2007 that had also been members in 2006 increased 17 and 10%, respectively between 2006 and 2007 (source: FEDIT database).

  15. FEDIT had 61 affiliated centers in 2002 and 67 in 2007, but not all of the initial 61 centers remained until 2007 and some new centers joined the federation after 2002.

  16. For the calculation of income by funding sources, CSIC institutes were considered as independent entities. CSIC central headquarters expenditures (68 million euros in 2007, 8.95% of the total expenditure budget) were neither taken into account, nor proportionally attributed to analyzed institutes.

  17. To break down external funds into those coming from public competitive calls and those coming from market sources (such as R&D contracts with industry) we made use of additional data available at the center level on external income broken down into fourteen different categories, four of them are related to public competitive calls (national general, national health-related, regional and European).

  18. We have excluded social sciences and humanities CSIC centers (16), representing 10% of CSIC research staff and budget. The reason is twofold. Firstly, there are no technology centers operating in those areas. Secondly, none of the new hybrid centers that we are taking as the reference model belong to those fields. We therefore believe their exclusion does not bias the analysis and facilitates the comparison with the technology centers.

  19. Three of these research centers belong to the area of physics, one to biology and one to chemistry. We conducted 13 interviews, 4 with department directors, 5 with directors of research groups, and 4 with other tenured researchers.

  20. We identified two basic types of technology centers. On the one hand, those technology centers which were strongly tied or oriented to an industrial sector in particular, and, on the other hand, those with a broader technological scope. We covered this variance when selecting the interviewees.

  21. T-tests on the difference of the means for shares of income by funding source indicate that there are significant differences between both populations for all three sources every year, except for competitive public funds in 2004 (see Table 3 in the Appendix).

  22. We have used 2 year averages to reduce short term fluctuations.

  23. Paired samples T-Tests for the difference of average bi-annual funding shares at the beginning and at the end of the period were only found significant for the decrease in non competitive public funding (t = 2.236, p = 0.03) and the increase in competitive public funding income shares (t = −3.062, p = 0.003) in technology centers. Thus, changes over time were not statistically significant for funding shares from market sources at technology centers or for any of the three funding shares at government laboratories.

  24. Appendix Table 4 sets out the results of the six cluster analyses of funding changes undertaken, one for each population and type of funding share. We consider that a technology centers or government laboratory included in a specific cluster by the K-means clustering algorithm has adopted the change indicated by the value of the “final cluster center”. For example, we consider that all the 33 technology centers included in Cluster 1 of non competitive public funding changes have experienced a low decrease in non competitive public funding. Two possible changes are accounted for in view of the results, decreases (negative final cluster center) and increases (positive final cluster center), of two different levels each (low: less than one percentage point change; and high: more than one percentage point change), although to facilitate the presentation of results, both low and high changes are added together in Fig. 3.

  25. Two of the center directors highlighted that although this approach involves greater market risks, it can also yield potentially higher returns in case of success because it implies the future selling of generic technologies to broader markets.

  26. Meyer and Rowan (1977) use the term “decoupling”, which consists in adopting a structure for purposes of legitimacy but not implementing it in practice. It is too early to assess whether the development of strategic plans at our government laboratories under study, an action they were legally obligated to undertake, will evolve as an example of decoupling.

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Acknowledgments

The authors acknowledge very useful comments and suggestions from Craig Boardman, Barry Bozeman, Denis Gray, Arie Rip and JTT anonymous reviewers. We thank FEDIT, CSIC and CERCA for providing the raw data. Financial support is acknowledged from the Spanish Government through the Ministry of Science and Innovation (CSO-2008-03100/SOCI) and AECID (A/8159/07, A/018795/08).

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  1. CSIC Institute of Public Goods and Policies (IPP-CCHS), Consejo Superior de Investigaciones Científicas (CSIC), C/Albasanz 26-28, 28037, Madrid, Spain

    Laura Cruz-Castro, Luis Sanz-Menéndez & Catalina Martínez

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  1. Laura Cruz-Castro
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Correspondence to Laura Cruz-Castro.

Appendix

Appendix

See Tables 3 and 4.

Table 3 Descriptive statistic for funding shares by source
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Table 4 Clusters of changes in funding shares by source (differences between average funding share in 2006/07 and average funding share in 2002/03)
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Cruz-Castro, L., Sanz-Menéndez, L. & Martínez, C. Research centers in transition: patterns of convergence and diversity. J Technol Transf 37, 18–42 (2012). https://doi.org/10.1007/s10961-010-9168-5

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