1. Hugo Horta Center for the Advancement of Higher Education, Tohoku University Japan CIES-ISCTE, Portugal

2. Context: why is this important  Academic research adds new knowledge to national and international knowledge pools, which support economic growth and social development.  Higher education is more than ever a key research performer in national S&T systems (mainly of public funded research).  There is the need to foster academic research activities, but in times of public budget constrains; decision making is important and – research is required to inform policymaker decisions.

3. Context: why is this important  Universities are engaged in increasingly multi-level, glonacal activities.  Academic activities becoming very complex.  Globalization and internationalization led to greater institutional cooperation and competition (global rankings contributing to this) increasing levels of uncertainty – research is required to inform university managers strategic decisions.

4. Context: why is this important In this context of challenging times, understanding academic research structures and processes is a necessity and a thematic of interest to both national governments and university managers. This article contributes to explore how research productivity and communication behaviors of academics are impacted by the organizational characteristics of the close research (research units) and academic (the university) environments

5. Context: why is the research question formulated as it is This analysis combines individual and organizational determinants of scientific productivity and academic information exchange practices because: 1) Research is a collective endeavour affected by the technical and institutional environment; the close organizational levels need to be taken into account; 2) Analyses solely based on individual determinants are well established but have a low explanatory power; 3) Analyses at University/Department/Research unit level are recent and still present ambiguous, often contradictory results (e.g.: unit size).

6. Data and Methods  National survey applied by the author in the fall of 2008 to faculty, PhD holders, and working in Portuguese universities (public and private); close fit to the targeted population; Sample error of 2.3% at 95% confidence level.  In the survey, the faculty was asked to identify the research unit where performed research in the last year. Respondents reported belonging to 283 R&D units (representing 71% of all R&D units).

7. Data and Methods  Further data on the R&D units was mined directly from the FCT website, which provided data concerning their size and characteristics (e.g.: number of post-doc fellows).  In Portugal, university based R&D units are formal legal entities recognized by the state to be publicly evaluated and funded. They are generally organized around a structure that includes three distinct human resources: integrados, bolseiros and colaboradores.

8. Data and Methods  Integrados are full members of the research unit and overwhelmingly consist of faculty of the university where the R&D unit is based.  Bolseiros are conducting research at the R&D unit with the support of fellowships. They are mostly post-doc and doctoral fellows.  Colaboradores refer to faculty from other higher education institutions (national and international) that collaborate with the R&D unit academic activities.

9. Data and Methods These groups of human resources permit to establish the following organizational structure in the R&D units analysis: OrganizationResearch unit structure description Org. type 1 (baseline) The research unit consists of full members (i.e.: integrados) only. No bolseiros or colaboradores present. Org. type 2The research unit consists of full members and bolseiros (doctoral student fellows only). No colaboradores present. Org. type 3The research unit consists of full members and bolseiros (post- doctoral and doctoral fellows). No colaboradores present. Org. type 4The research unit consists of full members and colaboradores. No bolseiros present. Org. type 5The research units include all groups (integrados, bolseiros and colaboradores).

10. Data and methods – independent variables  R&D unit variables: total size (86 researchers), percentage of international members with PhD (5%), organization types  University variables: total students taught, teach undergraduates only, teach graduates only, teach both, administrative hours per week  Individual variables: age (46 years), gender (38% are female), R&D funding, research in more than one unit (5%), coordinator (4%), foreign nationality (3%) and participate in collaborative projects (92%).

11. Data and Methods – dependent variables  Scientific productivity focus on: 1) Total output, 2) articles in international journals, 3) books and 4) articles in national journals/book chapters produced in the last 3 years  Academic information exchange intensity (IE) focus on: 1) total intensity, 2) within the R&D unit, 3) with other national institutions and 4) with international institutions in the last 3 years

12. Results – information intensity (organizational variables)  Size of research unit impacts positively IE within the research unit and with peers based at international institutions  Lesser IE with peers based at international institutions when org.2 is in place  Greater IE with peers based at international institutions when org.3 is in place  Teaching and administrative effort has no influence on individual IE  However, teaching undergrads only diminishes IE within the R&D unit, and at national and international levels

13. Results – information intensity (individual variables)  Age and gender are not relevant variables  Foreign nationals favour IE with peers based at international institutions and have lesser IE within the R&D unit (integration problem?)  Coordinator has greater IE within the R&D unit and with international partners  Researchers performing research in more than 1 R&D unit foster IE with peers based at national institutions  Participation in collaborative projects and R&D funding promote greater IE (except funding/national)

14. Results – scientific productivity (organizational variables)  Size of R&D unit only impacts production of articles in international journals.  Org type 3 affects positively the production of articles in international journals while Org type 4 impacts positively the production of books, book chapters and articles in national journals. (the above results suggest that organizational characteristics fostering individual productivity vary by scientific field (as predicted by Latour and Woolgar, 1979).

15. Results – scientific productivity (organizational variables)  Overall effort of teaching does not affect individual productivity; but outputs decrease if the faculty teaches undergrads only.  Administrative effort negatively affects the production of articles in international journals but positively affect the production of articles in national journals and book chapters. (this stresses the different needs across scientific fields)

16. Results – scientific productivity (individual variables)  Gender and nationality do not seem to affect scientific productivity, but age has an impact in the production of books, book chapters and articles in national journals.  Being a coordinator does not lead to a greater scientific productivity neither performing research in more than one R&D unit  Like in the IE analysis, research funding available and participating in collaborative research projects has a positive impact on all scientific outputs

17. Main conclusions  The size of the research unit seems to be particularly beneficial in fostering IE within the research unit and with international peers  If size increases communication, then size matters because has the potential to tackle the “loneliness” problem identified by Von Tunzelman et al.  In terms of productivity, however, size only really matters for the production of articles in international journals meaning that the relevance of size (of the R&D unit) is more important to communication issues rather than to scientific productivity.

18. Main conclusions  The latter result indicates also that R&D unit size matters more for the exact, natural sciences and engineering because it fosters their prefered outlet of scientific disclosure. Size does not affect other outputs.  The org. type 3 also favours the production of this output while org type 4 favours the production of other outputs favored by other scientific fields (social sciences and humanities).  These results are critical because they entail that different scientific areas have different needs, and this needs to be considered by university and R&D unit managers but also government policymakers when conceptualizing evaluation exercises

19. Main conclusions  Post-docs represent key human resources in S&T nowadays and R&D units may want to adopt a org. type 3 rather than a org. type 2.  Teaching effort has no effect on either IE or scientific productivity, but the allocation of that effort does; it would be a good policy not to have faculty members teaching undergraduates only.  Participation in collaborative projects and R&D funding are critical for both IE and scientific productivity

20. Limitations Ongoing work and as such your comments are very welcome Limited generalization: catching-up countries only? No analysis of quality or impact

21. THANK YOU VERY MUCH Hugo Horta (hhorta@he.tohoku.ac.jp)