Introduction

Nowadays, universities become more innovation-oriented and they aim not only at creating new ideas, but also at turning knowledge into practice. There is a common understanding that innovations can help to solve future problems by combining ideas, and creative efforts of previous experience (Bartel & Garud, 2009). Innovations, previously seen as mainly technological phenomena, may also involve improvements and discoveries that can increase living standards through improving business or organizational activity (Baskaran & Mehta, 2016) and address societal challenges (Cunha et al., 2022; De Silva et al., 2021; Merlin-Brogniart et al., 2022). Innovation requires creativity and interaction (Castillo-Vergara et al., 2021), which is described by the concept of the knowledge triangle, referring to innovation, research, and educational activities of universities (Tercanli & Jongbloed, 2022; Turcinovic, 2013). The literature emphasizes that contemporary universities should focus not only on knowledge creation, but also on participation in its commercialization (Veugelers & Cassiman, 2005; Etzkowitz, 2016; Pereira & Franco, 2022). Moreover, empirical research proves that cooperation between universities and companies enhances creativity of SMEs employees, thus positively affecting their innovativeness and competitiveness (Castillo-Vergara et al., 2021). Shaping the entrepreneurial spirit through research and education is a key element of universities’ third mission that contributes to economic and social development (Kliewe & Baaken, 2019; Stolze, 2021; Vaquero-García et al., 2017). A systematic literature review on the entrepreneurial universities has shown that this paradigm is still in development phase. New propositions, such as “networked university” or “engaged university” that extend this concept have been still emerging (Stolze, 2021). Therefore, there is a need to deliver empirical evidence showing how research, education, and entrepreneurial innovation interact. This challenge is crucial particularly for countries such as the EU members from Central and Eastern Europe (CEE), which still do not belong to the leaders in innovation (European Commission, 2021b). The study compares the countries from CEE region that joined the European Union as a result of three enlargements in 2004, 2007, and 2013. These are Czechia, Hungary, Slovakia, Poland, Estonia, Latvia, Lithuania, Slovenia, Romania, Bulgaria, and Croatia. This group of CEE countries has been selected for the analysis for two reasons. First, all these countries share similar heritage because they underwent transition from centrally planned to market economy. Second, as they all are members of the EU, they share similar values and have similar regulatory framework. Thus, it is a relatively homogenous group in terms of the framework conditions.

The context outlined above sets out the objective of this paper, which is to compare the position of universities from CEE in terms of creativity related to research and educational activity and its translation into innovation pointing out and similarities and differences between these countries. The article consists of the following sections: Introduction, Literature Review, Materials and Methods, Research Results, Discussion, Conclusions, and Policy Implications. The analysis covers the period of 2012–2020 and is based on data from Eurostat and OECD databases.

Literature Review

Creativity is a complex, multi-dimensional concept that can be explained on the basis of many sciences, including psychology, sociology, philosophy, and economic sciences. The term “creativity” may have different meanings, but it is attributed to people (Sawyer, 2012). At least three types of creative people can be distinguished: (1) unusually bright ones who express unusual and stimulating thoughts, (2) personally creative people who experience the world in a novel way and may discover important things, and (3) creative individuals who changed the world’s culture and way of thinking by their discoveries and achievements (Csikszentmihalyi, 1997). Thus, creativity may be found in inspiration of others to discover something new, in abilities to invent, which may be translated in new ideas and discoveries or in making actual discoveries, which change the world.

An interactionist perspective on creativity adds a social context to creativity studies, which implies that new ideas can be generated through interactions. Thus, apart from creativity attributed to individual people (i.e., individual creativity), group creativity and organizational creativity can be distinguished (Woodman et al., 1993). A dynamic nature of interactions between individual, groups, and organizations and various feedback loops make it difficult to measure creative ability and its outcome. Measuring creativity is not an easy task even if the standard definition of creativity is taken into account, which defines creativity using two criteria: originality and effectiveness (Runco & Jäger, 2012). However, to measure creativity using these two criteria, someone has to judge about originality of a discovery, while effectiveness may also take various forms, referring to usefulness, appropriateness, or utility (Runco & Jaeger, 2012). Classification of creative people may also have some implications for measuring creativity as it shows that creativity may be found in inspiration of others to discover something new, in abilities to invent, which may be translated into new ideas and discoveries or in making actual discoveries, which change the world. Some scholars suggest measuring creativity using project and performance-based measures (Sternberg, 2017); others focus on qualitative assessment of creativity identifying problem-solving, evaluation, and naivety and its measurable features (Moruzzi, 2021). Assuming that creativity is reflected in the novelty of science, it can be also measured using publications or patents (Veugelers & Wang, 2019), while creative learning flows can be investigated through patent citations (Giglio et al., 2021; Veugelers & Wang, 2019). Numerous studies on creativity and its various dimensions emphasize the importance of creative thinking in the development of innovation (Berraies, 2019; Gajdzik & Wolniak, 2022; Wang et al., 2022). The economic dimension of this relationship was introduced by Joseph Schumpeter (Schumpeter, 1934). Schumpeter points out that there is a difference between invention (creativity) and innovation, because the latter only appears when the novelty is introduced to the market, followed by its dissemination and imitation. This requires entrepreneurship understood as a process related to the development of something previously unknown (creative) and different (innovative) from existing solutions. Innovation contributes to the development of individuals, organizations, and society (Castillo-Vergara et al., 2021; Freeman & Soete, 1997; Govindarajan, 2016; Howkins, 2002).

The relationship between creativity and innovation is also analyzed in literature from various perspectives, including the perspective of human talent development (Haefele, 1962), organizations (Amabile & Pratt, 2016), science (Demetrikopoulos & Pecore, 2016), education (Hossieni & Khalili, 2011), and regional competitiveness (Garcia-Alvarez-Coque et al., 2019). All these analyses share common conclusion and point out that there is an interdependence between creativity and innovation, and universities play a huge role linking them (Garcia-Alvarez-Coque et al., 2019; Saad et al., 2014). Creativity is the ability of people to generate new ideas, while innovation is associated with transforming these ideas into new solutions used in the economy. As Centobelli et al. (2019) point out, there is a need to balance universities’ exploration activities and exploitation ones, which means transforming creativity (invention) to innovation. Shaping the entrepreneurial spirit through research and education is a key element of universities’ third mission that contributes to economic and social development (Kliewe & Baaken, 2019; Stolze, 2021; Vaquero-García et al., 2017). Entrepreneurial creativity and the effectiveness of entrepreneurship education are strongly positively correlated (Wang et al., 2022). Thus, universities need to twist learning model into entrepreneurial path in order to educate students and shape their ability to be creative as well as encourage young entrepreneurs and scientists to develop creativity and skills and transform them into innovation (Abusamra, 2022; Centobelli et al., 2019; Kalar, 2020; Leite & de Moraes, 2015). The study programs should not only focus on sharing knowledge, but also on shaping the entrepreneurial potential and creativity skills of all university community actors through, among others, volunteering activities and social entrepreneurship (Cunha et al., 2022). The importance of the entrepreneurial university has been studied extensively over the last decade, with the focus on the concept itself, on the creation of entrepreneurial ideas by students as well as on entrepreneurial initiatives in academic institutions (Dabić et al., 2016; Kliewe et al., 2019; Stolze, 2021). It has been observed that although intellectual ability of students is a good predictor of their outstanding performance, it only partially explains success. There are other factors, such as high motivation, self-confidence, or specific skills that matter (Mcclain & Pfeiffer, 2012). These important abilities can be shaped by the entrepreneurial universities, which integrate the entrepreneurial practices between teaching, research, and innovation. To build a proactive academic community, which is able to take risks and generate new solutions that respond to challenges, universities need to become a part of an entrepreneurial and innovative ecosystem (Ruiz et al., 2020), embedded in the regions of their location and properly linked to other regions (Etzkowitz et al., 2022).

The new role of universities is explained by the concept of the knowledge triangle developed over the last decade (Bohashko, 2020; Cervantes, 2017; Unger & Polt, 2017; Unger et al., 2020; Vonortas, 2017). Three vertices of this knowledge triangle describe the tasks of a modern university, which include education/learning, research/discovery, and innovation/engagement (Cervantes, 2017; Sjoer et al., 2015). The interrelationships between these three elements promote multidirectional knowledge flows, which can increase the dynamics of economic growth (Unger et al., 2020).

Functional model of interactions between education, research, and innovation explains various linkages that occur between three key areas of universities activities, i.e., research, education, and entrepreneurial innovations (Cervantes, 2017; Unger & Polt, 2017; Unger et al., 2020) (see Fig. 1).

Fig. 1
figure 1

Source: Authors’ elaboration based on Bohashko, 2020; Centobelli et al., 2019; Cervantes, 2017; Dabić et al., 2016; Demetrikopoulos & Pecore, 2016; Haefele, 1962; Kalar, 2020; Kliewe et al., 2019; Leite & de Moraes, 2015; Sjoer et al., 2015; Stolze, 2021; Unger et al., 2020; Unger & Polt, 2017

Creativity in the knowledge triangle concept.

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Research and education interact through skilled human capital. The results of basic and applied research used as the basis for teaching as well as the introduction of a problem-based learning can enable and improve the alignment of graduates’ skills with the needs of enterprises (Unger & Polt, 2017; Unger et al., 2020).

In terms of the linkages between research and innovation, knowledge triangle perspective allows to identify mechanisms for the institutionalization of knowledge transfers from academia to the business sector. Such linkages could occur through various platforms for collaboration, including, but not limited to, foresight and knowledge co-creation solutions (Cervantes, 2017; Unger et al., 2020). Generally speaking, the knowledge that flows among universities, industry, and government is essential to stimulate innovation (de Castro Peixoto et al., 2022).

At least two aspects are of critical importance in terms of the interactions between innovation and education. The first one is the development of an entrepreneurial culture in the framework of university training programs, which plays an important role in the interactions between education and innovations (Unger et al., 2020). The other one is the adaptation of educational programs to satisfy the demand of the business sector for knowledge competences (Cervantes, 2017). Moreover, it has been proved that universities, even with limited resources for innovation, can support innovation through academic entrepreneurship stimulated with the unique, not available elsewhere, human capital of the university community (Roncancio-Marin et al., 2022). This potential, if managed well, creates various open innovation possibilities for universities, including living labs, in which higher education institutions cooperate with variety of stakeholders, such as companies, non-profit, and government organizations and citizens, to address specific problems and find ground-braking, innovative solutions (Tercanli & Jongbloed, 2022). Such community engagement can help universities to focus on research of high societal impact and address societal challenges through social and open innovation (Carayannis & Morawska-Jancelewicz, 2022).

Empirical research on the role of universities in the knowledge triangle shows that there is no single model that describes interactions included in the knowledge triangle framework. This is due to the country-specific characteristics of education systems, the diversity within the universities themselves, the functions that they perform, and sometimes even regional specificities (Cervantes, 2017; Saad et al., 2014). Saad et al. (2014) proved that the specific features of the higher education sector are related to its capacity, which is positively correlated with innovation. University excellence was found to be a contextual factor and would contribute to regional development if combined with other factors, such as a collaborative business structure (Garcia-Alvarez-Coque et al., 2019).

Summing up, the analysis of the knowledge triangle concept allows to add new elements to it. It should be pointed out that the core of this concept is creativity. The role of creativity in the knowledge triangle concept is presented in Fig. 1. The triangle can work smoothly and produce new value only when all three vertices of the triangle—research, education, and innovation—are fed with an adequate new input, which occurs as a results of people’s creativity. Creativity is indispensable to produce new knowledge and develop it further (to conduct research), to turn it into practice (to introduce innovation), and to disseminate it to students (through education). Therefore, the creativity seems to be a relevant link in the analysis of interactions between the vertices of the knowledge triangle. Furthermore, the literature review shows that all three vertices of the knowledge triangle cannot function properly without financial and human resources; however, it seems that these two elements alone are not sufficient for productive interactions between education, research, and innovation. As far as education is concerned, its main function lies in shaping ability of students to learn not only during the degree programs, but also during the whole life as the stock of knowledge develops rapidly nowadays. Therefore, new knowledge absorption and new skills development is indispensable. In case of research, apart from resources, excellence and impact are key elements for fruitful interactions within the knowledge triangle. They occur through publications and their citations as well as through the creation of intellectual property confirmed by patents, industrial designs, etc. (Hou et al., 2022). The third vertex of the knowledge triangle—innovation—can be boosted through various forms of cooperation, which triggers synergy between finance and human resources. Thus, cooperation seems to be an important element for effective interactions with education and research.

Discussing the knowledge triangle concept, one must also point out its main drawback. The concept only partly includes the liaison between academia and citizens, which means an adequate science contribution to the demands of society, in particular finding solutions to societal challenges. Nevertheless, covering three key areas of universities activity, the knowledge triangle concept goes beyond the commercialization of research results and offers an interesting conceptual and normative framework for analyzing a wide spectrum of universities activities and comparing configurations and interactions occurring within universities in different countries.

Research Questions and Methods

The literature review conducted in the previous section has shown that innovation is associated with creativity, which is affected by, among others, quality of research and education, especially at the university level. The latest study in the efficiency of European universities confirms substantial differences across Europe’s university sector, stressing the need to include in future research, teaching, and third-mission activities (Herberholz & Wigger, 2021). Furthermore, the results of the previous research discussed in the literature review also show that regional specificity should be considered while conducting research on creativity and innovation in universities, which justifies the choice of the CEE region as the focus of this study. Commonalities and differences among eleven CEE countries in knowledge triangle performance will be studied to add to the knowledge triangle discussion a regional perspective. In this context, several questions arise about the role of universities in creating new knowledge in CEE region:

  • What is the contribution of CEE universities to increasing knowledge resources, its protection through patents, and its dissemination in the form of scientific publications?

  • To what extent do changes in creativity of universities from the CEE countries translate into improvements of the innovativeness of their economies?

  • How do the CEE countries perform in terms of the knowledge triangle?

These research questions are integrated around the main objective of this paper, which is to compare universities from the CEE countries in terms of creativity related to research and educational activity and its translation into innovations. We aim to prove that the CEE countries, being quite homogenous in terms of its institutional heritage and current framework conditions, are heterogeneous regarding the role of creativity in shaping research, education, and innovation in universities. Stojčić (2021) pointed out the CEEs are regarded as countries with emerging innovation systems, which are in transition from production-led growth towards innovation-driven growth. However, these countries have insufficient interactive capabilities, which are necessary for technological catching up (Radosevic, 2022). The EU Structural and Investment Funds play a role in the process of innovation system transition; however, while providing substantial resources for development of entrepreneurship, these funds were proved to fail in bringing sustainability to the public research sector (Švarc et al., 2020). Therefore, taking into account that on the one hand the CEE countries are less innovative that their western European peers, and on the other they have a flow of funds from the EU to transform their research sector making it more entrepreneurial through the implementation of the European smart specialization strategies, it is worth looking at the links between research, education, and innovation in these countries. The knowledge triangle offers a good framework to study these links (e.g., Moldovan, 2022).

The data used in this study comes from the Eurostat database (Eurostat, 2021) and covers the period of 2012–2020. This period has been selected for the analysis to keep the consistency of data in the text. As education systems vary between countries in terms of structure and curricular content, to have a comparable data on higher education and employ indicators defined the same way for all these countries, the International Standard Classification of Education (ISCED, 2011) has been used (UNESCO Institute for Statistics, 2012). It provides a unified framework and uses internationally agreed definitions. The latest ISCED 2011 classification was adopted by the UNESCO General Conference in November 2011. The UNESCO-OECD-Eurostat data collection programs have been adjusted according to the new standards in 2014 and earliest available data that follow these standards are for the year 2012. That is why we used the year 2012 as the starting point for our research.

The comparative analysis is carried out using the framework of the knowledge triangle concept discussed above, encompassing involvement of universities in their three main types of activities: education, research, and innovation. A set of indicators was selected to study interactions within the knowledge triangle between research, education, and innovation activities undertaken by universities from the analyzed CEE countries (Table 1). These indicators are grounded in the literature on metrics on entrepreneurial university (European Commission, OECD, 2012; Etzkowitz et al., 2017) and were selected using a functional model of interaction among the three vertices (education, research, and innovation) of the knowledge triangle (see visualization of the knowledge triangle concept on Fig. 1).

Table 1 Knowledge triangle indicators
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To identify the groups of the CEE countries performing similar in terms of knowledge triangle, the divisive analysis (“diana”) hierarchical clustering method was employed. Following Kaufman and Rousseeuw (1990) approach, at the beginning, all observations belong to a single set, which is then divided into subsets. At each stage, a cluster (subset) with the largest diameter is selected alongside which a splinter observation exists. Observations are then either joined with the splinter set or the main cluster is further divided. All data used for clustering was standardized; i.e., mean was subtracted from each value of each variable and the result was divided by the variable’s standard deviation. Technically, one can run the algorithm until all observations form separate clusters. This was done to check at which moment do larger clusters separate.

Research Results

Comparative analysis of creativity in the research activity of the CEE universities based on patent statistics reveals that all CEE countries present relatively low performance. In the years 2012–2020, the number of patent applications per 1 billion of GDP (in PPS) was significantly lower in the CEE (except Slovenia) than the EU average. Some of the CEE countries achieved better results in terms of trademark applications and design applications. Estonia, Slovenia, Lithuania, and Bulgaria stand out in the first of these two categories. Poland, Estonia, and Bulgaria are the leaders in the CEE group in terms of design applications (Table 2). These results show that creativity of the CEE region can be seen in the area of trademark and design, rather than creating new solutions that can be patented on a global scale.

Table 2 Number of patents, trademarks, and design applications per 1 billion GDP (in PPS) in the CEE region: comparison of the years 2012 and 2020
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All countries of the CEE region also significantly deviate from the average in EU28 in terms of the proportion of scientific publications among the 10% most cited publications worldwide (Table 3).

Table 3 Research activity carried out by higher education sector in CEE countries: the years 2012 and 2020 compared (or latest available)
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The analysis of input indicators describing the creativity of universities from the CEE countries seen in their research activity shows that Slovenia and Estonia stand out in the CEE region. Estonia spends the highest in region percentage on R&D conducted by universities, and both countries are regional leaders in terms of the most cited scientific publications (Table 3). Poland and Bulgaria are at the other end of the scale. Poland performs quite well in terms of availability of scientific personnel and has a relatively high and stable share of R&D expenditures carried out by universities. However, this does not mirror the position of Polish universities when it comes to creativity measured by the number of citations nor the number of patents. Both countries, however, have some advantages with regards to creativity in industrial design, but it might not necessarily be attributed to universities’ activity (Tables 2 and 3).

The data reflecting educational potential of the CEE universities shows that this region stands out in the EU in terms of relatively high public expenditures on higher education in relation to GDP and the percentage of people aged 25–34 who completed tertiary education. Despite relatively high public expenditure on higher education, the CEE region is not very attractive to talented PhD students from abroad, which limits the potential of the CEE region to be part of global education and research network. Data shows, however, some differences in the CEE region. Poland, Estonia, and Slovenia stand out in the CEE countries by the highest and relatively stable public expenditure on higher education in 2012–2020. Lithuania shows the strongest position among the EU countries from CEE and also compared to the EU28 average in terms of the percentage of the population who completed tertiary education. The CEE countries that perform better that the EU average also include Slovenia, Latvia, and Estonia (Table 4).

Table 4 Educational activity of CEE countries in comparative perspective in the years 2012 and 2020 (or latest available)
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A way to improve creativity and interactions between education and research is to promote openness of the education system and attract talents from abroad. One of the indicators of the countries’ position in attracting talent from abroad is the share of foreign doctoral students in the total number of doctoral students. The CEE countries that are the most attractive for foreign PhD students include Czechia, Estonia, Hungary, Latvia, Slovenia, and Slovakia. The lowest percentage of foreign PhD students was observed in Poland and, moreover, it remained at the same low level during the 2012–2020 period.

The concept of the knowledge triangle indicates that universities have a huge role to play in enhancing interactions between research, education, and innovation. Cooperation of higher education institutions with enterprises in research as well as teaching and training is necessary to develop these interactions (Kalar, 2020; Unger et al., 2020). How is this cooperation carried out in the CEE countries? Is it sufficient to create talents and drive innovation?

The level of funding provided for R&D activities of universities by the business enterprise sector is one of its measures. Such funding has been very low for many years in Romania, Poland, Slovakia, Croatia Latvia, Hungary, and Bulgaria. In these countries, funds allocated by the private sector to finance research conducted by higher education institutions constitute only 0.01% of GDP or less, while the average indicator in EU28 is three times higher and for comparison, two times higher in Czechia, Slovenia, and Lithuania. Estonia is in this respect the best performing country in CEE, with this indicator being higher than the EU average) (Table 5).

Table 5 Innovation potential: CEE countries compared in the years 2012 and 2018 (or latest available)
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The interactions of universities with business in the field of education can be measured by the employment rates of recent graduates. Estonia has a relatively good position in this area compared to other EU countries from CEE. In the period of 2012–2020, the employment rate of recent graduates aged 25–34 has been systematically increasing exceeded the EU28 average by nearly 10 percentage points. There are also other six CEE countries, i.e., Slovakia, Poland, Romania, Bulgaria, Croatia, and Lithuania, that achieved a better results than the average in the EU (Table 5). In order to compare the involvement of universities and other higher education institutions in cooperation with enterprises and its changes, data from the CIS2012 and CIS2018 surveys available in Eurostat database were studied. In the CEE countries, the share of enterprises cooperating in innovation activities with universities or other higher education institutions varied significantly. Estonia, Croatia, and Slovenia were the CEE leaders in this respect, while Bulgaria, Romania and Poland belong to the laggards. Furthermore, in the 2018 wave of CIS survey, some countries from the CEE region (namely Czechia, Lithuania, and Poland) reported a decrease in cooperation between enterprises and universities or other higher education institutions.

Summing up this comparative analysis of the knowledge triangle vertices, it should be pointed out that the universities from the CEE countries have relatively good positions in the EU with regard to educational activities but there is a creativity gap vis-a-vis the EU average visible in indicators describing the research output produced by universities (e.g., publications, patents) as well as in those indicators reflecting interaction within knowledge triangle. It shows that educational potential seems to be not sufficiently linked to research and innovation. This confirms the hypothesis stating that universities in the CEE countries do not fully use their potential in creation of knowledge and its application.

Furthermore, the hierarchical cluster analysis revealed differences among the CEE countries regarding their performance and allowed to distinguish five clusters (Fig. 2):

  • Cluster 1: Estonia and Slovenia

  • Cluster 2: Lithuania

  • Cluster 3: Bulgaria and Poland

  • Cluster 4: Croatia, Latvia, and Slovakia

  • Cluster 5: Czechia, Hungary, and Romania

Fig. 2
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Source: Authors’ elaboration based on data from Eurostat, 2021

“Diana” cluster separation into 5 clusters.

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The cluster analysis has shown diversity of the CEE countries regarding knowledge triangle performance. Similarities in knowledge triangle performance allow to group the CEE countries into five clusters. Slovenia and Estonia are the leaders in the CEE region. In these two countries, the knowledge triangle works well, and creativity in research and education interacts with business and smoothly translates into innovation. Lithuania forms a separate cluster. This is mainly due to the specifics of the university system introduced during the reforms of Lithuanian higher education (Bileviciute et al., 2019). Czechia and Hungary form another cluster, also with Romania, which is similar to these two countries with some basic knowledge triangle dimensions mainly characterizing its input side (size of public expenditure on higher education, share of scientists and engineers in the working population, share of employees with a tertiary education, share of enterprises cooperating in innovation activities with universities), but different when it comes to the output side indicators. Three other, rather small, countries, i.e., Croatia, Latvia, and Slovakia, come as the next cluster (with Slovakia being a little apart) showing much weaker performance of their knowledge tringle. Another cluster is formed by Poland and Bulgaria that are quite similar as they perform poorly in many indicators and on average in some. Poland and Bulgaria have similar strengths in terms of creativity manifesting themselves in high ratio of industrial design applications. Nevertheless, this does not change the fact that the effects of interactions within the knowledge triangle between research, education, and innovative entrepreneurship are in these countries insufficient to stimulate creativity and broaden the involvement of national actors in global research and innovation networks.

Discussion

This paper explores creativity of universities from CEE using the knowledge triangle concept and identifies factors that significantly influence interactions between research, education, and innovation. The paper shows there is a creativity gap between the CEE countries and the rest of the EU, in particular regarding research and innovation functions of universities. This conclusion is also supported by the study of Lilles et al. (2020), in which CEE countries (especially various regions in Romania and Poland) are classified as lagging regions, in which knowledge translation capabilities need to be developed. The contribution of CEE universities to increasing knowledge resources, its protection through patents, and its dissemination in the form of scientific publications is much lower than the EU average in majority of these countries. Only Slovenia and Estonia stand out, and in the period of 2012–2020 they nearly managed to catch up with the EU average in terms of the most cited scientific publications as well as PCT patent applications. The latter country even surpassed the EU averages for trademark and design applications. It should be however pointed out that in the period of 2012–2020, the CEE countries (except Bulgaria) made some progress in catching up with the EU average values of indicators describing creativity of universities, despite the decreases of financial and human resources available for higher education sectors in some countries (e.g., some declines in financing of higher education research in relation to GDP in Czechia, Estonia, Lithuania, Hungary, Romania, Slovenia, and Slovakia). Looking from this angle, even small improvements in the results produced by universities with relative decreases in financing may indicate more effective interactions within the knowledge triangle and some gains due to synergies between these three areas of universities’ activities. To check whether it is true, in this paper, we searched for an answer to the question how changes in creativity of universities from the CEE countries translate into innovation improvements. The paper proves that innovation potential of the CEE universities is quite low and did not change much in the years 2012–2020. Both financing of university research by the business sector and cooperation between higher education and business in innovation activity stand at low levels, the latter indicator reached a sufficient level only in Estonia, Croatia, and Slovenia. These trends occur due to the fact that the CEE region has relatively low position in terms of the interaction within the knowledge triangle between research, education, and innovation. Comparing achievements of the CEE countries in research, innovation, and education, we noticed that the CEE countries have a relatively good position against the EU average in terms of education performance. This conclusion is confirmed by high and growing tertiary education attainment levels and higher than the EU average employment rates of recent graduates in seven out of eleven studied CEE countries. Unfortunately, it does not translate sufficiently to abilities to learn through all life; CEE universities do not shape the necessity of lifelong learning strongly enough when educating students. Low lifelong learning participation rate is the weakest element of higher education systems in the CEE region; again Estonia and Slovenia are the only exceptions in this respect. Nevertheless, the CEE countries have relatively good performance in educational activities, but do not link it enough to research and innovation. This is also proved by Gajdzik and Wolniak (2022), who studied technical university programs in Poland and concluded that only some of them and only indirectly are linked to topics related to innovation and creativity. This conclusion confirms that the use of educational potential is the missing link between research and innovation in the CEE countries. In order to build educational competences of the twenty-first century, universities should offer study programs and curricula, which enable students to test their competences in a real environment and learn from projects developed together with different stakeholders, such as companies or local communities (Carayannis & Morawska-Jancelewicz, 2022).

Both the comparative analysis of knowledge triangle data and hierarchical cluster analysis show that the CEE countries are a heterogeneous group in terms of knowledge triangle performance. Five country clusters can be distinguished in the CEE region. The structure of clusters can be explained as follows. The first cluster comprises Estonia and Slovenia that are the CEE countries with high percentage of population with tertiary education. Lifelong learning is most prevalent here as well. Furthermore, both countries belong to the leaders in the CEE region in areas such as digitalization and ICT adoption (European Commission, 2018).

Lithuania forms a separate cluster. This is mainly due to the specifics of the Lithuanian state, which is among the torchbearers in area of education reforms. First, Lithuania introduced new management methods in higher education, which brought a steady flow of incoming international exchange students (Bileviciute et al., 2019). Second, Lithuania has the highest percentage of people who completed tertiary education in the analyzed set of countries and relatively strong position in terms of the availability of R&D personnel and researchers in higher education sector. Bulgaria and Poland are the third splinter group. The countries perform poorly in many indicators and on average in some. Poland spends quite high percentage of its GDP on higher education compared to other analyzed CEE countries and overall performs better than Bulgaria across nearly all indicators, which explains another early split. However, even though there are relevant supporting instruments, this does not translate into open innovation capacity of the Polish universities (Baron, 2021). On the other hand, both countries have the same strengths in intellectual property protection lying in high and growing design applications. This conclusion is also supported by the extended research on the creativity and innovation in Polish universities (Marczewska & Weresa, 2022). The remaining countries are in the middle of the pack and can be treated as one large cluster, but it very quickly splits in two. Croatia, Latvia, and Slovakia form one trio, whereas Czechia, Hungary, and Romania the second. Slovakia and Hungary separate immediately from their respective trios, indicating significant differences. For example, Romania, with 0.05% expenditure on R&D carried out by higher education sector, ranks an order of magnitude lower than other countries in its trio. Meanwhile, Romania files very little patents and overall performs worse than Czechia and Hungary. Both Czechia and Hungary have many similarities in their innovation systems. In particular, they are similar to each other in institutional structure of R&D system as not only universities, but also research institutes are quite important in these countries in conducting research activity. The other remaining pair, Croatia and Latvia, has also many similarities. First, they are similar in size and population. Second, they have similar endowment in human resources for R&D and innovation. Last, but not least, the interactions within the knowledge triangle measured by research and development activities carried out by higher education institutions and financed by business in relation to GDP are also similar in both countries. Interestingly, recent research focused on university autonomy and commercialization of research in Latvia proves that universities could build a friendly environment for commercialization and develop entrepreneurial culture thanks to greater flexibility and experimentation with funding allocation (Muizniece, 2021).

Conclusions and Policy Implications

Theoretical Implications

The novelty of this study is threefold. First, our contribution to the concept of the knowledge triangle lies in stressing creativity, which links three vertices of the triangle—research, education, and innovation—and is highly important for interactions between them. Second, this paper adds to previous strand of research on the knowledge triangle pointing out the key elements of the three vertices, which should accompany financial and human resources. We recognized that education vertex needs to build its strengths in particular on shaping students’ ability to learn. The key element of research vertex is excellence and impact, while the most important success factor of universities regarding innovation vertex is collaboration. Third, empirical part of the paper contributes to better understanding of the CEE universities performance indicating the heterogeneity of this region.

Furthermore, the knowledge triangle concept seems to be an interesting framework for studying universities’ ecosystem as it encompasses R&D, innovation, and educational activity of universities and goes beyond commercialization. However, it only partly includes the connection between academia and citizens, which limits the discussion about the role of universities in finding solutions to societal challenges. Our review of the latest literature allows pointing out that a citizens’ perspective to the knowledge triangle framework could be added to broaden the research in this topic.

However, in interpreting the results, one should take into account an important research context. It should be pointed out that the CEE economies still transform their innovation systems (Radosevic, 2022; Stojčić, 2021); therefore, indicators used in the analysis might not fully reflect their creativity potential. For example, although patents as a proxy for creativity and innovation are well established in the literature (e.g., Veugelers & Wang, 2019), there are many papers on patents’ drawbacks, such as costs or long patenting procedures, which may discourage the CEE inventors from patenting. Therefore, we need to interpret the results with caution and more empirical research is needed to further develop the knowledge triangle concept.

Policy and Managerial Implications

The results of this peace of research have some policy implications and managerial implications. As the interactions between education and research and its transformation to innovation seems to be the missing element of the knowledge triangle in all CEE countries, common approach that integrates higher education policy with research policy is a way to overcome this barrier. Taking into account the diversity of the CEE countries in knowledge triangle performance, tailored innovation policy measures are required for each cluster of countries to address their weaknesses in the functioning of education-research-innovation triad. In the clusters that are leaders in the CEE regions (clusters 1 and 2), a stronger support to university excellence in research seems to be important in order to push them to advance in the world university ranking list. In clusters that lag behind in the CEE region (cluster 3), policy should focus on “third mission” of universities with strong support to the involvement of universities in cooperation with enterprises. In all clusters, strengthening interactions between education and research seem to be indispensable.

In order to activate the creativity potential of CEE universities a support for strengthening interactions within the knowledge triangle, both locally and internationally is indispensable. It seems that education is the missing link between research and innovation. Investment in education and research conducted by universities may speed up the process of transforming knowledge into practice. Thus, universities should invest in developing entrepreneurial culture and adjust their study programs in order to promote innovativeness and entrepreneurship.

When designing the innovation policy, at both global and organizational level, it should be taken into account that research, education, and innovation activities have been globalized along with the globalization of production processes. Nowadays, countries compete first of all for talents, although the competition for physical capital is still important. And again, without investment in education, talent development is not possible. Thus, universities should focus on attracting talents and helping them to grow thanks to creativity- and innovation-oriented teaching and training. Furthermore, it should be pointed out that cooperation in research, science, education, and production processes facilitates the flow of ideas and boosts creativity. Such cooperation in all its dimensions (national, international, intersectoral, interorganizational) is an inspiration for creativity and is a way to better use local resources to create innovation, although the forms of this cooperation will be shifting from physical interactions towards strengthening of virtual networking.

Limitations and Future Research Directions

In spite of the merits of this study, there are several limitations that call for future research. The first limitation of our research is related to the period of our analysis. Due to the changes in the International Standard Classification of Education in 2011 (UNESCO, 2012), our analysis is limited to the period of 2012–2020 in order to keep consistency regarding indicators and data, so it shows a medium-time perspective. Repeating similar study in the future when longer data series will be available might also be an interesting research direction. Furthermore, the dataset encompasses only entire countries, not regions within these countries. Thus, it might be interesting to perform similar clustering of the analyzed countries’ NUTS 2 regions.

Additional studies might also examine the institutional environment for universities’ functioning in different countries and its evolution over time, including the impact of various policy instruments on creativity, R&D, innovation, and entrepreneurial education.

As empirical research on the role of universities in the knowledge triangle shows that there is no single model that describes interactions included in the knowledge triangle framework, some case studies of the best universities and the interactions between research, innovation and education might be also valuable. Such case studies could complement our research by providing an insight to processes occurring inside universities in different countries, and they can also serve as best practices in this respect.