Inequality in Funding and Productivity in the South Korean Academic System

For the past fifty years, South Korea has been recognized as a country that has built a national economy based on significant investments in R and D (Research and Development) activities. In the late 1960s, the Korean government established public research institutes and provided research funding, beginning its R and D endeavors. The 1980s saw the rise and development of private R and D efforts by major global companies like Samsung and LG. Universities became a new R and D player in the 1990s. The importance of Korean universities in the national innovation system has increased as the country’s economy moves closer to the stage of creative innovation.

Along with this development of the Korean research system, the institutionalization of the funding system has evolved. The Korean research system is highly dependent on competition rather than on general support based on a formula consisting of various indicators (e.g., the number of academic staff). In doing so, the National Research Foundation (Hereafter NRF) is the main public agency responsible for providing research funding to academia. Some research programs follow a top-down approach based on RFPs (Request for Proposals) given by NRF, while the others are bottom-up competitions based on research proposals submitted by academics themselves.

Research funding, along with research personnel and equipment, are among the main factors in the function of scientific production. Research funding has steadily increased not only in Korea but also globally over the past few decades. For instance, OECD countries spent $497 billion on research funding in 2020, double the amount from 15 years ago.^[1] This reflects the policy efforts of many countries to support new industries and technologies in a new environment and to increase employment opportunities.

In the realm of R and D communities, the issue of research funding inequality has become increasingly important. Particularly in science policy, the conflict between excellence-based research support and egalitarian resource distribution has been a longstanding issue.^[2] An unequal distribution of research funding influences the possibility of individual researchers’ acquisition of research resources. This may result in an overall decrease in research productivity, although a few brilliant scientists are more likely to produce outstanding research outputs comparing other ordinary colleagues. Moreover, at the individual level, this has a strong relationship with factors such as career stage, gender, and institutional reputation or prestige. Various countries are evolving their research funding support policies to strike a balance between excellence and equality.

In Korea, which has been advancing its university research system over the past 30 years, the questions of how research funding is allocated and its impacts on research productivity have become crucial. In particular, within university research systems responsible for creative basic research, there is little research on how unequal distribution of research funding affects research productivity. Moreover, it is imperative that university research funding policies are grounded in quantitative data analysis. Therefore, this study aims to explore the relationship between the concentration of research funding in the Korean university system and research productivity, addressing these academic and policy requirements.

There has been considerable research on research funding and inequality in research funding. Research funding inequality is known to be increasing globally. This can be attributed to the increasing number of large research projects. The logic behind this phenomenon is that the best researchers should receive the most funding due to economies of scale.^[3] Bloch and Sørensen have found several signs of increasing grant size.^[4] They measured an increase in average grant size in several countries, including Denmark, Switzerland, and the United Kingdom, as well as increased support for research centers. On the other hand, Sörlin argues that project-based funding, tax breaks, and the commercialization of university research have led to the creation of superstar researchers, which in turn has led to a ‘winner-take- all’ structure.^[5]

In particular, the focus on research excellence has led to an increase in the size of research funding at the global level. This allows researchers to maximize research productivity, including publications, increase scientific impact, and provide an optimal environment for new discoveries.^[6] Some scholars also argue that larger research centers can provide long-term stable funding for researchers, which is associated with increased grant size.^[7] However, this logic has the potential to marginalize researchers further who have not traditionally had access to funding, which could eventually undermine system-wide excellence. On the other hand, Bonaccorsi and Daraio argue that research funding inequality increases as large-scale funding is used to maximize socioeconomic impact.^[8] They sought to empirically measure whether large research organizations in France increase scientific productivity. They found no empirical support for the notion that concentrated institutions increase scientific productivity by generating spillover effects, increasing face-to-face contacts, and facilitating tacit knowledge exchange.

Some researchers understand the issue of funding allocation as a question of equity, suggesting that funding concentration undermines equity among researcher groups.^[2] This equity can be increased by encouraging more diverse and broad participation in research funding. A criticism of this is that science is an inherently unequal game, so equity cannot go hand in hand with it. It has also been pointed out that if funding is distributed equally, research that requires critical mass cannot be conducted. In the case of Korean research, there is a study by Cho on the inequality of research funding.^[9] Cho’s study empirically proves that there exists inequality and cumulative advantages in the Korean research community in terms of a number of papers, citations, and research grants. However, the study was conducted 16 years ago with a survey-sample size of 437 researchers in three scientific disciplines and is not comparable to the scope and scale of our research.

Against this backdrop, we put forward three research questions at the individual and organizational level. To begin with, how unevenly is funding allocated in South Korean academic system? Has it gotten worse over the past five years? Second, how are the research outputs are created differently during the last five years? Third, how have the last five years’ research output, funding and inequality related to each other?

We utilize integrated data on publications and academic research grants subsidized by governments, including information about recipients, institutions, grant amounts, and research periods from 2017 to 2021. We carry out descriptive statistics, including an analysis of variance and an analysis of inequalities as measured by Gini coefficients, to present trends and an overview of publication production and research grant distributions.

First, we investigate whether there has been an intensification of research funding concentration in Korean universities from a system-level perspective. We utilize the Gini coefficient, the most commonly used measure of societal inequality, which can be calculated using the Lorenz curve.

Second, we examine the research funding concentration over a period of five years based on the personal and environmental attributes of university researchers. For example, we can analyze how the Gini coefficient has changed for different groups such as men and women, junior faculty and senior faculty, universities in local areas versus those in capital areas, and faculty in science and engineering disciplines compared to those in humanities and social sciences. Through this analysis, we can diagnose how the distribution of research funding has evolved at the system level over the past five years.

Third, we analyze the relationship between research funding, research productivity, and concentration at the individual and organizational levels. Research productivity is the most significant idea in measuring the results of scientific operations. It is affected by a number of variables, including environmental factors like the attributes of associated institutions, such as size, reputation, location, and mission, as well as personal aspects such as gender, age, and research area. Using this, we examine the relationship between research productivity and funding disparity.

We apply the Gini coefficient to measure the inequality of research funding. To construct the Lorenz curve, we arrange the entire population of researchers in ascending order of their research funding amounts. We set the total number of researchers as 100, with the horizontal axis representing the cumulative percentage and the vertical axis representing the cumulative percentage of total research funding accumulated by each researcher, normalized to 100. The Lorenz curve can be defined as the line connecting these cumulative population percentages and corresponding cumulative research funding percentages. The Gini coefficient is then calculated as the ratio of the area between the diagonal line and the Lorenz curve to the total area of the triangle under the diagonal line.

Tables 1 and 2 show descriptive statistics of our data at individual and organizational level. According to Table 1, the number of researchers in engineering is the biggest, followed by social science. In terms of average funding, researchers in engineering rank top, followed by those in maritime and agricultural science. Regarding productivity, medical and pharmaceutical science and maritime and agricultural science have the most productive scientists. Moreover, male researchers get more funding in total and on average, produce more papers efficiently. Senior researchers get more funding and produce more papers efficiently.

According to Table 2, the number of universities in social science is the biggest, followed by humanities. In terms of average funding, universities in engineering rank top, followed by those in medical and pharmaceutical science. Regarding productivity, universities with medical and pharmaceutical science and engineering areas are most productive. Moreover, capital universities get more funding in total and on average, produce more papers efficiently. Private universities get more funding and produce more papers less efficiently.

Table 3 below shows the recent trend in funding size and distribution. Over the last five years, the number of projects, funding, and average project size have all increased. Furthermore, we see that the success rate, as assessed by the number of principal investigators divided by the total number of researchers, remains consistent, except for a minor drop in 2020. This could indicate that the funding situation has improved as research funding for a comparable number of researchers increases yearly. However, the median value (i.e., the 50% quartile) of financing has stayed steady over the same period, but the standard deviation has progressively increased. This suggests that the increase in funding has been centered more on the ‘richer’ group, whereas funding for the ‘poorer’ group did not increase.

We examine research funding, publications, and Gini coefficients to comprehend the individual-level inequality in the Korean academic system. The overall research funding and average values according to each research area (i.e., eight fields), gender (i.e., male or female), and age periods (i.e., under 30s, 40s, 50s, and above 60s) are shown in Tables 4 and 5 below regarding the funding for academics from NRF during the last five years. According to the trend in the two tables, both the average and total funding will rise by 2021. Nonetheless, up until 2021, total and average funding in three fields, natural science, engineering, and maritime and agricultural science, showed a consistent rise. Specifically, it is evident that the trade conflicts between Korea and Japan and COVID-19 have made a tremendous increase conceivable in the engineering and medical and pharmaceutical fields. When comparing disciplines, funding for academics in science and engineering is higher than for those in other fields. Furthermore, older or male academics are given more funding than junior or female academics, except for academics above the 60s.

The Gini coefficients show the disparity in funding between academics. Figure 1 displays the Gini coefficient values over a 5-year period for each research discipline (natural sciences, for example), gender (male or female), and age periods by 10 years. We note that the coefficients of non-science disciplines, such as the humanities and social sciences, are bigger than those of scientific and engineering disciplines, contradicting the previous results above (i.e., total and average amount of funding).

Additionally, compared to male academics, female academics had a higher coefficient. When the findings from the earlier analysis above are taken into account together, academics with relatively lower average funding per principal researcher and total research funding tend to have more funding inequality or funding concentration. In fields and groups with limited funding size, funding is more likely to be focused on a smaller number of researchers.

Tables 6 and 7 display the total and average number of publications Korean academics have produced during the past five years, broken down by eight fields (such as the humanities), gender, and career periods. The number of publications and their average values show a consistent upward trend, with a minor decline in 2018 and 2019. As seen by the rise in research funding over the same time period (see Tables 4 and 5), the engineering and medical and pharmaceutical fields have seen a particularly notable increase in publications. Within the disciplines, there are about twice as many publications in the fields of engineering and medical and pharmaceuticals than there are in the natural sciences and social sciences together. The productivity of the medical and pharmaceutical fields, or the number of publications produced by each researcher, also held the top spot. Compared to their female counterparts, male academics published a greater number of articles and were more productive. A similar pattern is seen with senior professors.

The production disparities among Korean academics by personal attributes, including gender, career time, and discipline, are depicted in Figure 2 below. In general, across the period, the productivity gap has widened. More inequality is shown in non-scientific fields like the arts and physical education and humanities than in fields of sciences like the natural sciences and engineering. This could imply that the structure of inequality is greater in productive areas than in less productive areas. Male academics are more unequal than female academics in terms of production, and group inequality for male groups has been increasing over time while it temporarily decreased for female groups in 2018. Senior academics in the 50s and 60s groups also exhibit a similar pattern, while junior groups in the 30s and 40s show a slight decrease in 2018 and 2019.

Figure 1:
Inequality of funding for academics according to personal characteristics.

In summary, at the individual level, analysis reveals disparities in funding allocation and productivity across disciplines, genders, and career stages during the last five years. Funding tends to concentrate on academics in science and engineering disciplines such as engineering and medical and pharmaceutical science, with male and senior academics in the 50s receiving more funding support. Research productivity also correlates with funding levels, with engineering and science fields exhibiting higher publication rates. However, academics in medical and pharmaceutical science and maritime and agricultural science have produced more papers than those in engineering on average. In addition, academics in their 40s publish, on average, more than those in their 50s.

Regarding funding inequality, disparity of non-science disciplines, such as the humanities and social sciences, are stronger than those of science and engineering disciplines (e.g. medical and pharmaceutical science). Moreover, female or senior academics in the 50s or 60s are experiencing stronger inequality. With regard to publication inequality, non-science disciplines such as arts and physical education, as well as humanities, show higher levels of disparity than science and engineering disciplines such as maritime and agricultural science. Furthermore, we see a stronger inequality for male and senior professors in the 50s and 60s. Overall, we observe an increasing trend of inequality regarding both funding and publication except 2021.

In order to understand the inequality of the Korean academic system at the organization level, we investigate research funding, publications, and Gini coefficients. Tables 8 and 9 show an overall consistent increase in the total and average funding received by universities. Engineering is the discipline that has had the biggest increase in both average and total terms. In terms of average funding increases, capital and public universities outperform non-capital and private universities; nevertheless, the overall increase in funding amounts is comparable because each group of universities (i.e. public and private) comprises a different number of universities. In particular, there is a steady increase in the average funding difference between the two categories (i.e. legal status and locations).

The following Figure 3 illustrates the disparity in funding amongst Korean universities based on organizational attributes such as research focus, location, and legal status. Multi-disciplinary science has the greatest Gini coefficient, or inequality, followed by pharmaceutical and medical science. Compared to non-science fields like the humanities and social sciences, there is a greater funding disparity between universities in science and engineering fields like medicine and pharmaceutical science. Compared to their peer groups, there is a greater and growing disparity in both non-capital and private university groups. Nonetheless, during the last five years, the overall level of inequality has remained stable.

Figure 2:
Inequality of publications from academics according to personal characteristics.

The total and average numbers of publications produced by Korean universities over the previous five years are displayed in Tables 10 and 11. In terms of total and average numbers, we see consistent growth through 2021, following a modest decline in 2018 and 2019. Universities in the fields of medical and pharmaceutical science and engineering produced the greatest and second-largest numbers of publications overall and in terms of productivity (i.e., number of publications per university). Up until 2020, universities outside of capital areas generated more papers than those inside. However, starting in 2021, universities inside of capital areas began to produce more papers. This may be due to the fact that the average number of publications of capital universities has increased remarkably. Public universities display a higher productivity (i.e. number of publications per a university), although private universities have produced more papers overall.

The productivity disparity among Korean universities is depicted in Figure 4 below based on organizational attributes such as research focus, locations, and legal status. Over the past five years, there has been little change in the productivity gap compared to the funding gap. Compared to non-science fields like the humanities and social sciences, there is a greater production gap across universities in science and engineering fields like medical and pharmaceutical science. Higher levels of inequality have been observed in capital-area universities compared to non-capitalarea universities, and both groups’ levels of inequality have been rising over time. Furthermore, compared to public institutions, private universities exhibit greater inequality. Interestingly, public universities have seen a decline in inequality, despite private universities experiencing an increase in it. This indicates that for the past five years, competition among private institutions has gotten more intense.

In summary, at the university level, analysis reveals disparities in funding allocation and productivity across research focus, locations, and legal status during the last five years. Research funding concentrates on universities in science and engineering in both total and average terms. Capital universities show remarkable funding increases, while peer groups show a modest increase relatively. Public universities get two times more funding than private universities. Research productivity shows a similar pattern to funding allocation in average terms except for medical and pharmaceutical science.

Regarding funding inequality, non-science disciplines, such as the humanities and social sciences, are weaker than those of science and engineering disciplines. Moreover, disparities persist, with capital and private universities receiving more funding and producing more publications than their counterparts. However, the inequality coefficient for capital universities has increased, while that for private universities is in a reverse trend. Moreover, the study finds that funding inequality levels remain relatively stable over the years. Regarding publication inequality in disciplines, a similar pattern has observed to funding inequality.

Figure 3:
Inequality of funding for universities according to organizational characteristics.

Figure 4:
Inequality of publications from universities according to organizational characteristics.

Interestingly, funding inequality for universities also shows a similar trend to publication inequality except that of capital-area universities in 2021.

In this study, we examine the disparities in funding, publications, and the academic system in Korea from both an individual and an organizational perspective. This study, which draws support for its conclusions from methodological rigor and empirical data, offers a thorough picture of the research funding landscape in South Korea and its consequences for scientific performances.

First, a resource concentration on science and engineering fields, such as engineering and medical and pharmaceutical sciences, is evident in the overall features of the Korean academic system, as outlined in Section 4.1. This is seen in the number of academics, funding, and publications in these fields. In terms of personal traits, research funding and publications are dominated by senior male professors in their 50s. Furthermore, compared to their peer universities, on average, public and capital-area universities generate twice as much funding and publish twice as many articles. The quantity and scope of projects have grown substantially over the past five years, while the number and percentage of supported scholars have stayed constant. Nonetheless, there has been a notable increase in the standard deviation of financing amounts. This indicates that financial inequality has worsened even if financing opportunities have improved over the past five years.

Second, our analysis shows differences in funding distribution and productivity during the past five years between fields, genders, and career stages at the individual level. Academics in scientific and engineering fields often receive the majority of funding. Funding levels and research productivity are usually correlated. Disparities in funding across non-science fields (e.g. the humanities and social sciences) are more pronounced than those between science and engineering fields. Science and engineering disciplines exhibit lower levels of discrepancy regarding publishing inequality than non-science subjects. Except for 2021, we see an overall rising trend in funding and publication inequality.

Thirdly, the analysis conducted at the university level has shown differences in funding distribution and productivity among research areas, geographical regions, and legal status during the past five years. The average term pattern of research productivity and budget allocation is comparable, except for medical and pharmaceutical science. In terms of funding inequality, the differences in levels have remained mostly constant throughout time. A comparable pattern regarding funding inequality has been noted with regard to publishing inequality across disciplines. Fascinatingly, university funding inequality has a pattern that is comparable to that of publishing inequality, apart from capital-area universities in 2021.

These analysis results shed light on the complex dynamics of research funding and productivity in South Korean academia, emphasizing the need for policies that balance excellence and equity in resource allocation. In this vein, we put forward some policy implications.

First, despite an increase in financing and publications overall and on average over the past five years, we have discovered that inequality, as determined by the Gini coefficient and standard deviation, has worsened. Thus, inequality is located in a distinct policy dimension of science and technology than that of publications and funding. Because this feature is a sensitive predictor of superior research systems, careful and persistent regulation of this policy variable is necessary.

Second, when it comes to funding disparities between disciplines, scientific and engineering fields receive significantly higher overall and average funding than non-science fields. Remarkably, disciplines indicate that organizational inequality exhibits a different tendency than individual inequality. Put differently, scientists and engineers exhibit lower levels of inequality at the individual level and higher levels of inequality at the organizational. On the other hand, universities in non-science fields have weaker organizational inequality, while their academics in those fields exhibit larger individual inequality. This implies that there should be a distinction made between the funding policies for individuals and universities.

Thirdly, certain groups, such as private universities, require greater policy action. However, we also need to consider organizational factors like location and legal status in order to support the scientific and engineering disciplines. Particularly, more attention needs to be paid to capital-area and private universities.

Lastly, we suggest some limitations of this study and upcoming future studies. First, in terms of the definition of inequality in policy practices, what happens when a research group grows because of a pressing need for policy? Is it detrimental to a nation’s scientific system or other groups? There could be a ‘good’ inequality for the overall academic system. Secondly, we need an econometric model that uses inequality as a predictor of research productivity to perform a more sophisticated statistical analysis. By comprehending the impact of inequality, we may improve the efficient distribution of funds throughout the academic research system.

This research was supported by the research fund of Hanbat National University in 2023. Only Ki-Seok Kwon, among all the authors, is the beneficiary of this grant. All authors much appreciate the anonymous reviewers’ insights that improved this paper.