The question of task complementarity at work is a broad research topic and has been addressed in fields such as psychology and sociology of work, management studies as well as in labour economics. In terms of the latter, task specialisation has traditionally seen as efficient, and associated with a ‘Tayloristic’ organisation model where specialisation of tasks is seen as the basis for efficiency and productivity in work. According to Lindbeck and Snower (2000), reorganisation of work towards multitasking has become increasingly common, spurred on by development of advanced production technologies, digital tools and increased education in the population. One argument for multitasking is that it increases learning and thereby performance. As a result of increased prevalence of multi-tasking, research has also documented a range of negative effects for the individual (dissatisfaction, burn-out etc.), as well as a negative impact on work performance and overall productivity. Doing several tasks at once is not however the same as performing multiple tasks, and the question of task complementarity does not necessarily entail multitasking—as tasks can be carried out both in parallel and sequentially.
The basic assumption underlying critical perspectives on multitasking is that there is a constraint in having too many work tasks, as attention, time and resources are limited. Further, that negative effects of multitasking are exacerbated when tasks are not complementary. Complementarity exists when there is a spill-over effect and where resources (including knowledge and time) involved in performing one task also can be used in the execution of another. The magnitude of the task in question of course also plays a role, as time is a limited resource for everyone. Task complementarity is hence dependent on both the kind of tasks and the magnitude of the tasks to be performed. Pertinent questions then become whether the work tasks of academics are complementary or not, and whether having a broad portfolio of work tasks is positive or negative for work performance.
As seen above, university professors have long been expected to perform multiple tasks. As professors have a high degree of autonomy in their work and a high level of competences in their work domains, achieving task complementarity might be more feasible for them than for other categories of employees (Pelz & Andrews, 1966). To look at this in more detail, we review existing literature from the higher education and science studies fields to identify how the issue of task complementarity has been addressed in an academic setting. As research has predominantly looked at task complementarity in pairs of activities, such as the relationship between teaching and research, prior research on each pair of tasks is reviewed below. Based on the review, a set of propositions to guide our empirical study is outlined.
Relationship between teaching and research tasks
In most higher education systems, there is a shared view that there should be a relationship between educational responsibilities and research activities. The basic idea, stemming from the notions of Humbolt about the unity of research, teaching and learning (Nybom, 2003), is that research and educational activities should be complementary. The knowledge generated by academics through research activities should spill over to teaching and supervision of students, in the form of deeper knowledge, broader understanding of the literature, advanced analytical and methodological skills etc. Derived from this perspective, a basic assumption would be that academics who are active researchers are also good teachers and educators, due to their more substantial knowledge of the scientific field. The relationship is usually investigated in this direction (i.e. influence of research on teaching), and seldom on the other way around, even though it is assumed that teaching, and particularly supervision of graduate students, have positive effects on research (e.g. Duff & Marriott, 2017).
As the potential synergy between teaching and research in higher education institution is a fundamental question within the field of higher education research, a large number of studies have been performed on this issue. Studies have often formulated the relationship between research and educational tasks as a trade-off (Fox, 1992; Landry et al., 2010; Artes et al., 2017). According to their argument, investing time and resources in research activities means forgoing time that could be invested in education activities, or vice versa. Hattie & March (1996) and Braxton (1996) published early meta-analyses of the evidence about the link between teaching and research and reach similar conclusions. Their meta-analyses indicated that there was no significant relationship between research and teaching performance, neither positive nor negative. A more recent literature review on the same issue discusses this conclusion and finds that it is difficult to systematically assess this question, as the concepts teaching, and research performance are not operationalised in similar fashion and that the variables used in most studies are limited (Verburg et al., 2007). In particular, the operationalisation of teaching varies a lot. Verburg et al. (2007) show the variety of different aspects and measures of teaching used, including: Teaching quality, the time used on teaching, the number of courses taught, the amount of interaction with students, the researchers’ pedagogical approaches, the researchers’ attitudes to teaching, teaching skills, commitment to teaching, investments in teaching, and supervision of students. Student evaluation scores or ranking scores of the institutions have also been used as indicators of academic’s teaching activities (e.g. Bianchini et al., 2016), but they are also criticised (e.g. Wiers-Jenssen, 2015).
Moreover, studies have tended to look at the relationship as a linear one, but later studies have indicated that there might be a threshold effect involved (Artes et al., 2017; Bianchini et al., 2016). The latter indicates that research activities up to a certain level is positive for teaching, but when a threshold is met, the positive effects diminish (Garcia-Gallego et al., 2015). It is also important to highlight that most studies reviewed look at the effect of research on teaching. This again could have impact on the expected relationship between the two variables. Research activities might be positive for teaching, but we have limited understanding of whether teaching is positive for research (Landry et al., 2010).
Based on the available insights into relations between these tasks, we expect that there is some degree of complementary between educational responsibilities and research activities, at least up to a certain level of educational responsibilities. Moreover, as educational responsibilities are manifold and varied, they need to be studied as a set of different activities. Supervising students reflect one important part of professors’ work obligations and is also the teaching activity that may be most integrated with research. Due to this, we choose to study supervision activities as an indicator of educational responsibilities. With this in mind, we expect a positive relationship between moderate levels of educational responsibilities, here in the form of supervision of students, and research (proposition 1).
Relationship between third mission activities and research tasks
Considerable research has also been performed on the relationship between research and third mission tasks. Following Sanchez-Barrioluengo (2014) the concept ‘third mission’ activities is here used for a range of different activities performed by academics to utilise their knowledge and expertise outside the academic context. As has been described by others (Molas-Gallart, 2002; Perkmann et al., 2013; Sanchez-Barrioluengo, 2014) this concept is made up of heterogeneous sets of activities, where some are more prevalent across all fields of science and some are exclusive to specific fields. Early research on this issue focused on mostly on activities directed to commercialisation of academic knowledge, such as patenting, licencing, and industry partnerships (Geuna & Nesta, 2006; Gulbrandsen & Smeby, 2005; Lee & Bozeman, 2005), but these are mainly found in sciences, technology and engineering as well as in biomedicine. Later research that widened the empirical focus outside engineering and sciences, and found that academics in most fields of science utilised their knowledge in external communities, through collaborating and communicating with stakeholders and the public in many different ways (e.g. Abreu & Grinevich, 2013; Perkmann et al., 2013; Perkmann et al., 2021).
Following Perkmann et al. (2013), we distinguish between two modes of utilising scientific knowledge and expertise outside academia—research commercialisation and research collaboration. This distinction is also made by Bozeman et al. (2013) who discern ‘property focused’ and ‘knowledge focused’ forms of collaboration. Both kinds of activities entail that academics actively pursue activities to diffuse and make use of scientific knowledge in external communities and contexts. The first in the form of ensuring ownership and transferring the rights to exploit scientific knowledge commercially in the form of patents, licenses or other activities based on proprietary knowledge. The latter research collaboration—entails diffusing knowledge to firms and public sector organisations, in the form of research agreements, partnerships, consulting and advisory activities, etc. In resent research, such activities are often labelled “academic engagement” (Perkmann et al., 2013, 2021) or “academic knowledge exchange” (Hayter et al., 2020) to capture the broader set of activities that academics in different fields of science are involved in.
The relationship between these activities and research is likely different for different kinds of third mission activities (Perkmann et al., 2013). Prior literature that has looked at the impact of participation in commercialisation on research performance, usually measured by publication data, indicates a positive relationship (Buenstorf, 2009; Geuna & Nesta, 2006; Larsen, 2011). There seems to be some degree of complementarity between these tasks, where academics that are active in commercialisation activities also score highly on research productivity. This effect seems to be more prominent in some disciplines, and particularly in the life sciences (Roche et al, 2020), and it also seems to be mediated by the status and age of academic employees, as well as their research orientation (Rothaermel et al., 2007; Perkmann et al., 2013; Abreu & Grinevich, 2013; Bianchini et al., 2016, Fini et al., 2021). It seems that engagement in commercialisation can be associated with high research performance, but the temporal dimension is important as high research performance in most cases precede commercialisation. One might however assume that for academic entrepreneurs that continue to stay in academe, resources from commercialisation activities are channelled back to support new research initiatives, and therefore can enhance future research performance (Breschi et al., 2007; Buenstorf et al., 2009).
Research has also looked at the relationship between external collaboration and research performance. Early contributions to this literature found a positive relationship between industry partnerships and research performance, but mainly in technology and natural sciences (Abramo et al., 2009; Gulbrandsen & Smeby, 2005; Van Looy et al., 2004). Recent analyses have attempted to look deeper into this issue, by measuring different levels and kinds of collaboration, and their association with research performance. The empirical evidence indicates that the association between the variables is not linear (Muscio et al., 2017; Banal-Estanol et al., 2015), but that up to a certain level, being involved in external collaboration is positive for research performance.
Based on the reviewed literature, we make two expectations about the complementarities between third mission tasks (distinguished by the two different modes, as described above) and research: We expect that there is a positive association between commercialisation and research tasks (proposition 2). As it is a limited number of academics that are involved in commercialisation activities, we do not expect to be able to distinguish between levels of participation on this variable. We also expect a positive relationship between moderate level of external collaboration and research performance (proposition 3). For the latter expectation, prior research indicates that a threshold may be involved, so we have included this in our analysis.
Relationship between educational responsibilities and third mission tasks
This relationship is less well documented (Perkmann et al., 2013; Bianchini et al., 2016) partly because there is a lack of available studies and adequate data, but also because there is limited understanding of how educational activities are connected to research work, as discussed above. Some authors claim that resources, knowledge and networks available through academic entrepreneurship and external collaboration can influence education and instruction positively (Etzkowitz, 1998). For instance, Lin and Bozeman (2006) found that academics who collaborate with industry, support and supervise more graduate students compared to peers who do not collaborate with industry. Bozeman and Boardman (2013) have also found a positive relationship between industry collaboration and support to students at both undergraduate and graduate levels. Other authors claim that the relationship is negative, and that third mission tasks might reduce the time and effort academics spend on teaching and other educational tasks (Gulbrandsen & Smeby, 2005).
Wang et al. (2016) operationalised third mission tasks in two separate models, following Perkmann et al. (2013), and proposed that the two models have different kinds of impact on teaching activities. Wang et al. (2016) assumed that commercialisation is not positive for teaching performance, but that research collaboration would be. They find support for their hypotheses and also that the combined model (high on commercialisation and high on research collaboration) is positive for teaching performance. Contrary to this finding, Bianchini et al. (2016) found that faculty who perform extra-academic tasks (measured by consulting activities) have ‘lower commitment to teaching’. Similar results were also obtained in studies made by Lee and Rhoads (2004) and Sanchez-Barriolungo (2014). Bianchini et al. (2016) highlight that there are substantial disciplinary differences. Landry et al. (2010), on the other hand, find no significant relationship between teaching and commercialisation and other knowledge transfer activities.
Based on these insights, we formulate two expectations to guide research, and we discern third mission tasks directed at commercialisation and collaboration (e.g. Perkmann et al., 2013). We expect that there is a negative relationship between educational tasks and commercialisation (proposition 4). Finally, based on Wang et al. (2016) and the general pattern of threshold effects found in related research, we expect a positive relationship between moderate levels of educational tasks and external collaboration (proposition 5).
Task complementarity and work performance
In the literature on academic work reviewed above, there is an expectance that there is a positive association between tasks, dependent on controlling the volume of each task. Figure 1 illustrates the main concepts and summarises the expected associations between them.
Educational tasks (here measured by supervision) is expected to be positively related to research performance, when the level of supervision duties is not too high (complementarity is moderated by volume) (P1). Similar, engaging in third mission activities (measured by external collaboration and commercialisation of research) is also assumed to have spill over effects that influence research in a positive way (P2 and P3) when moderated by volume (for collaboration). These expectations assumes that there is a possibility of using resources from one task (e.g., involving students in research work or collaborating with an external partner) in such a way that it influences research activity and output.
Whether teaching responsibilities and third mission activities (collaboration and commercialisation) (P4 and P5) are associated in a positive way was however unclear in the literature. We assumed that there is a positive relationship between supervision and external collaboration, but not between supervision and commercialisation. The final expectation is that the combined efforts of being involved in both third mission activities and teaching related tasks will be negatively related to research performance, due to increased overall workload (Proposition 6). Finally, as the model assumes that the variables are interdependent, we introduce interaction terms in the analysis.
To explore the propositions we perform regression analyses, but we do not aim to test a causal model or predict academics’ behaviour. The propositions address the correlation between tasks and the results of the study should not be interpreted in causal terms.