Predictors of Research Productivity of Academics
Author(s):
Conference:
ECER 2012
Format:
Paper

Session Information

22 SES 08 C, Academic Work and Professional Development

Parallel Paper Session

Time:
2012-09-20
09:00-10:30
Room:
FFL - Aula 27
Chair:
Mari Karm

Contribution

The centrality of research within the role of academics working in the higher education sector is without question. Since the 1980s here has been increasing interest in the research productivity of academics. Indicators of research productivity, such as publication rates, are a determining factor in decisions related to promotion, tenure and the granting of research funding (Ramsden 1994). Research outputs also impact on the reputation of universities and other institutes of higher education as well as affecting the career trajectories of academics. The impact of research at a reputational level is evident in the impetus from management in universities to increase the global standing of their institutions through research outputs and the acquisition of research funding. Furthermore the investment in research has been aligned to the economic goals of countries and is explicitly stated in policy documents at European Union (EU) level. There is worldwide evidence that faculty research productivity is a central component in a number of areas of ascertaining the quality of higher education institutions (Teodorescu 2000).

A predictive model was developed to identify factors associated with research productivity amongst academics working full-time in the university sector in Ireland. Research productivity has been defined as: ‘the totality of research performed by academics in universities and related contexts within a given time period’ (Print & Hattie 1997: 454). A number of models of determinants of publications have been previously developed. Essentially they measure a comparable number of variables that are grouped under three headings: demographic predictors, academic predictors and institutional predictors (Shin and Cummings 2010). For example Shin and Cummings (2010), in their predictive model of research productivity, theorised that research outputs were related to the extent to which academics preferred research over teaching, time spent on research and teaching, research collaboration, research training, rank, time since completion of PhD, gender, number of children and discipline.  Similarly, Porter and Umbach (2001: 181) developed an explanatory model of research productivity that consisted of five variable groupings. They hypothesised that research outputs were a ‘function of human capital, personal tastes, career status, teaching workload, demographics and academic discipline’. Human capital referred to the ability of the academic to do research; personal taste referred to attitudes towards research (emphasis toward teaching or emphasis toward research); career status measured faculty rank and years in post, and workload was identified through number of undergraduate and graduate courses taught during a semester. Demographic variables included gender, age, number of children and marital status. To date there has been no measure of the predictors of research productivity amongst academics working in the Irish higher education sector. Therefore based on previous research a regression model was developed to predict the factors associated with research productivity amongst academics in Ireland. This model consisted of three blocks of variables: demographic variables, individual academic variables, and institutional variables. 

Method

Independent samples were drawn from higher education institutions in Ireland. It was estimated that a sample of at least 800 would be required. 1,185 final responses were achieved. The survey instrument was based on the Changing Academic Profession Questionnaire. Predictors hypothesised to be related to research productivity included: 1) Demographic predictors (age, gender); 2) Individual academic predictors (academic rank, tenure, job satisfaction, workload, level of collaboration, preference for teaching or research); 3) Institutional variables (work environment, rating of the institution, institutional research funding, managerial support). Research productivity in this analysis was measured by a composite variable composing of the average number of books authored and articles published in the three years prior to the survey. The composite variable was log transformed to approximate a normal distribution. The predictors of research productivity of academics were identified by a linear regression model. Variables were entered in three blocks: 1) demographic variables, 2) academic variables and, 3) institutional variables.

Expected Outcomes

Predictors of research productivity were found to be multi-factorial. Initially gender (male) was identified as a factor in research productivity; however this was moderated when individual academic variables such as a preference for research over teaching and involvement with the wider research community were added to the model. Academic predictors identified as being positively related to publication outputs included: holding a tenured position, a stated preference for research over teaching, involvement in the research community through peer reviewing, membership of scientific committees and holding an editorial position. Infrastructural support related to research (satisfaction with facilities, resources and personnel) was also identified as a weak predictor of research productivity.

References

Abramo G., D’Angelo C., Di Costa F. (2009) Research collaboration and productivity: is there correlation? Higher Education, 57: 155-171. Fox, M.F. (1983) Publication productivity among scientists: a critical review, Social Studies of Science, 13: 285-305. Kaya, N, & Weber M. (2003) Faculty research productivity: gender and discipline differences. Journal of Family and Consumer Sciences, 95: 46. Lee, S., & Bozeman, B. (2005). The impact of research collaboration on scientific productivity. Social Studies of Science, 35: 673–702. Marsh, H. W., & Hattie, J. (2002). The relation between research productivity and teaching effectiveness: Complementary, antagonistic, or independent constructs? Journal of Higher Education, 73: 603–641. Porter, S. R., & Umbach, P. D. (2001). Analyzing faculty workload data using multilevel modeling. Research in Higher Education, 42(2): 171–196. Print, M. & Hattie J. (1997) Measuring quality in universities: An approach to weighting research productivity. Higher Education, 33: 453-469. Ramsden P. (1994) Describing and explaining research productivity. Higher Education, 28: 207 – 226. Shin, J. & Cummings W. (2010) Multilevel analysis of academic publishing across disciplines: research preference, collaboration and time on research. Scientometrics, 85: 581-594. Smeby, J., & Try, S. (2005). Departmental contexts and faculty research activity in Norway. Research in Higher Education, 46: 593–619. Teodorescu, D. (2000) Correlates of faculty publication productivity: a cross-national analysis. Higher Education, 39: 201–22.

Author Information

Jonathan Drennan (submitting)
University College Dublin
Dublin
Yurgos Politis (presenting)
University College Dublin
University College Dublin
University College Dublin
Nursing Midwifery and Health Systems
Dublin

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