Multivariate dynamics of Ecuadorian public universities and their research trends, according to Web of Science (pre-COVID period) Open Access

https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/qss_a_00336

In the era of knowledge, the role of public universities as engines of research and development is essential for the progress of nations (Arroyo, Vaca et al., 2023; Balladares-Burgos, García-Naranjo, & Granda-Villamar, 2020). Ecuador, immersed in this context, has experienced significant growth in its scientific production during the prepandemic period (2011–2018). This study dives into the complex web of interactions between public higher education institutions and priority research areas, seeking to decipher patterns and correlations that define their contribution to scientific knowledge (Barandiaran, 2012; Marín & Zawacki-Richter, 2019).

The main objective is to analyze the trends of scientific production in Ecuador in the pre-COVID-19 period (2015–2018) This analysis, enriched by the graphical representation of a PCA biplot, emerges as a powerful tool to visualize the complexity of these multivariate relationships (Ruiz, Ruff, & Galindo, 2021).

The methodology used involved the selection of 1,826 publications, based on a rigorous consultation in Web of Science (WoS), to characterize the scientific production of public universities in the country. The choice of the biplot as an instrument of analysis is justified by its capacity to represent in a two-dimensional space both the position of the universities and the variability of the research areas (Hutahayan, Nainggolan, & Tobing, 2023; López-Medina, Mendoza-Ávila et al., 2022).

The importance of this study lies in its contribution to the understanding of how Ecuadorian public universities are inserted in the global scientific panorama, particularly in the areas of “education,” “social sciences,” “engineering,” and “chemistry,” which emerge as fundamental axes of scientific production. This analysis not only offers a detailed X-ray of research activity but also lays the groundwork for future strategies for academic and scientific strengthening in the country (Ascencio Jordán, García Viteri et al., 2020; Wang & He, 2022).

It is noteworthy that, after an exhaustive documentary investigation in two of the world’s leading scientific information databases, Scopus and WoS, no document addressing or analyzing the topic in the period considered, either before or after, was found. Therefore, this study positions itself as a pioneer in the application of multivariate statistical tools in bibliometric analyses within emerging countries, such as Ecuador, that analyze their scientific production to improve decision-making. This uniqueness further highlights its relevance, especially in a context where budget constraints in public universities are high, thus justifying the urgent need for this type of crucial information to improve decision-making and the efficient allocation of resources.

This study focuses on analyzing the research trends of Ecuadorian public universities during the prepandemic period (2015–2018). This period provides an essential baseline for understanding research trends under normal conditions and allows for a precise comparative evaluation in future studies on the impact of the COVID-19 pandemic on research priorities and strategies.

Castillo and Powell (2019) conducted a comprehensive analysis of the historical development of research in Ecuadorian universities. Their study reveals a remarkable growth in publications and research projects in recent decades, with a special emphasis on how educational policies and socioeconomic changes have influenced these trends. They highlight the role of globalization and technology in promoting scientific research, as well as the regional particularities that characterize the Ecuadorian educational system.

Torres-Salinas, Robinson-Garcia et al. (2013) discuss in depth how biplot techniques, especially HJ-biplot analysis, have been adopted in the educational sector to analyze and visualize complex data. Their work highlights the relevance of these statistical tools in mapping research trends and identifying key areas for academic development. They underline how this methodology allows a clearer understanding of the interrelationship between different disciplines and their impact on scientific production.

Zhimnay Valverde, Fernandez et al. (2019) examine disciplinary trends in Ecuadorian universities, highlighting a notable prevalence in fields such as Social Sciences and Education in certain areas, while, in other regions, Science and Engineering disciplines are more dominant. This study provides detailed insight into how academic and research priorities may be influenced by social needs, labor market demands, and government policies.

Gil Alvarez, Morales Cruz, and Nieto Almeida (2021) address the significant impact of the COVID-19 pandemic on university research trends in Ecuador. They analyze how the health crisis has changed research priorities, prompting a greater focus on areas such as public health, distance education, and technology. They also highlight the shift towards international and multidisciplinary collaboration, as well as the adaptation of universities to new modes of research and teaching.

The influence of globalization on university research in Ecuador has been a topic of interest in recent years. Researchers such as Aldás-Onofre and Cordero (2023) have explored how global integration affects research decisions and international collaborations, pointing to an increase in scientific production in areas of global relevance.

Funding is a critical factor in university research. According to studies by Espinoza, González-Fiegehen, and Granda (2019), resource allocation and governmental support have a direct impact on the research areas prioritized by Ecuadorian universities.

Ramírez-Montoya, Andrade-Vargas et al. (2021) have highlighted the growing importance of innovation and technology in university research in Ecuador. Their analysis suggests a trend towards the incorporation of new technologies and innovative methods in academic research.

Barrera-Rodríguez, Echeverri-Gutiérrez et al. (2023) analyze how research in Ecuadorian universities contributes to the social and economic development of the country, with special attention to research projects aimed at solving local problems.

The study by Betancur (2023) on neurosciences reveals significant differences in global scientific production, with North America leading, and developing regions, such as Latin America, lagging. This finding contrasts with the predominant focus of Ecuadorian universities in areas such as education and social sciences, highlighting a divergence in research priorities. Asia’s notable contribution to neuroscience suggests a changing global dynamic, which could influence trends in Ecuador. International collaboration, an aspect highlighted in Betancur and Restrepo’s study, offers a valuable model for improving the global visibility of Ecuadorian research in advanced fields such as neurosciences.

The research of Mejia, Valladares-Garrido et al. (2019) on the impact of student scientific societies on the scientific production of medical students in Latin America offers an interesting parallel to the study of research trends in Ecuadorian universities. The finding that participation in the Scientific Society of Medical Students stimulates scientific production suggests that similar initiatives could enhance research in other disciplines in Ecuador. This approach emphasizes the importance of support structures for student research, an element that could be crucial in promoting diversified and robust academic research in Ecuadorian universities.

The research of Segura-Robles, Parra-González, and Gallardo-Vigil (2020) on active methodologies in education has gained significant interest, as evidenced in the bibliometric and collaborative network study that analyzes publications between 2009 and 2019. This approach highlights a sustained growth in publications and a predominance of English as the main language, an emerging and growing trend in this field, with a focus on specific topics that are likely to gain more relevance in the coming years.

The objective of the present research is to analyze the trends of scientific production in Ecuador in the pre-COVID period (2015–2018).

The prepandemic period provides an essential baseline for understanding research trends under normal conditions. This is crucial to evaluate any significant changes that may have occurred due to the COVID-19 pandemic. Without a clear baseline, it would be difficult to discern whether the observed changes in research trends are direct results of the pandemic or part of a long-term evolution. Understanding research trends before the pandemic is vital for the formulation of informed research policies. Findings on prepandemic trends can serve as a reference for policymakers, helping them design strategies that not only address the current needs arising from the pandemic but also build on the strengths and weaknesses that existed before the crisis.

The analysis is based on all articles published in scientific journals indexed in WoS, considering all its collections such as SCIE, SSCI, AHCI, ESCI, CPCI, and BKC. The participation of 27 public universities was found, and for a more detailed study the universities were classified according to the geographic region of the country: 13 universities in the Coast, 13 in the Highlands, and one in the East.

The focus on public universities in this study is intentional and driven by several key factors. Public universities in Ecuador play a crucial role in the national research landscape due to their significant contributions to scientific knowledge and their considerable public funding. These institutions are often at the forefront of research and development efforts, aligning closely with national priorities and policies.

Furthermore, public universities typically have larger student populations and more diverse research programs compared to private institutions. This makes them representative of broader research trends and priorities within the country. By concentrating on public universities, we aim to provide insights that are directly relevant to policymakers and can inform strategic decision-making at a national level.

To ensure the accuracy and reliability of our analysis, we implemented a thorough data-cleaning process. This involved several key steps, including the removal of duplicate records and the correct identification of institutional affiliations. For example, publications from the Technical University of Machala appeared under various names, such as “Tech Univ Machala,” and those from the Polytechnic School of Litoral were listed as “Higher School Polytechnic of Litoral.” These variations were standardized to ensure consistency in our data set. By addressing these discrepancies, we ensured that each institution’s contributions were accurately represented, providing a clearer and more reliable picture of the research landscape in Ecuador. When the data was cleaned with the help of the R-Studio software, 1,826 publications were obtained in the four most popular research areas (Education, Social Sciences, Engineering, and Chemistry) by researchers from public universities in Ecuador. The analysis was performed in R with the dynBiplotGUI package, created by Egido Miguélez (2015). There are different applications of the dynamic biplot in economics; however, there is no application that analyzes universities in terms of their performance in knowledge production.

A biplot is a graph that represents two sets of data simultaneously in a single two-plane or two-dimensional plot. This technique is used in multivariate data analysis to visualize the relationship between variables and observations (Yan & Kang, 2002).

In a biplot, points represent the rows (observations) and the columns (variables) are represented by vectors, where the position of each point on the plane reflects its relationships with the other observations and with the variables. In addition, the arrows on the graph indicate the direction and magnitude of the original variables in two-dimensional space (Guo, Geng et al., 2022).

The biplot is useful for the following reasons:

• to visualize relationships between variables and observations;

• to identify the contribution of the variables; and

• to simplify the understanding of multivariate models.

The HJ-biplot, developed by Villardón (1986), is an extension of the traditional biplot that allows a richer and more precise interpretation of the relationships between observations and variables.

• Observations: The position of a point (observation) in the graph indicates its relationship with other observations. Close points represent similar observations.

• Variables: The direction and length of a vector (variable) indicate the direction of the greatest variability of that variable and its relative importance.

• Angles between vectors: The cosine of the angle between two variable vectors indicates their correlation. A small angle (close to 0°) indicates a high positive correlation, while an angle close to 180° indicates a high negative correlation.

• it allows a joint visualization of observations and variables, facilitating the interpretation of complex data;

• it provides a more balanced representation of variability in the data by adjusting the scales of observations and variables; and

• it is particularly useful for identifying patterns and relationships in multivariate data, allowing insights into the underlying structure of the data.

• universities for the ranks;

• research areas for columns; and

• situations throughout the period studied (2015–2018).

• biplot analysis of the two-way data matrix for the reference year; and

• projection on the biplot graph obtained in the previous stage of the rest of the situations to be studied, generating their trajectories along different contexts.

The four research areas with the most scientific articles published by Ecuadorian public universities in WoS in the pre-COVID period are shown in Figure 1.

In the HJ-biplot graphs, the research areas are represented by vectors, while dots identify the public universities; the acronyms of each university were used for the labels. Table 1 shows the classification of universities for the different types of geographic regions.

Table 2 shows the number of publications of public universities located in the Coast-East region for the prepandemic period (2015–2018) and the average number of publications per year.

According to Table 2, the University of Guayaquil had the highest average in three research areas, Education (42.25), Social Sciences (40.5), and Engineering (3.25), and in Chemistry the highest average was that of the Technical University of Machala (2.25). The information captured in the HJ-biplot is shown in Table 3. The cumulative variance explained by the first two axes amounts to 94.89%. This indicates that two axes are sufficient to characterize the position of the public universities of the Coast-East region in the four research areas most frequented by the institutions’ researchers.

Table 4 shows the contribution of each axis to the variability of publications in the different research areas. All variables have a high contribution and can be interpreted in planes 1 and 2. Education, Social Sciences and Engineering received high contributions from Axis 1 and Chemistry receives a high contribution from Axis 2.

Figure 2 shows the HJ-biplot for the 2018 data matrix, which provides the highest number of scientific publications in the research areas. A strong and direct association is observed between Social Sciences and Education and a less strong but direct correlation between Social Sciences and Education with Engineering. The only correlation independence is observed between Chemistry and Education.

As for the universities of the Coast-East region, of the 14 universities analyzed, only two did not obtain a good quality of representation (ULEAM and UTEQ); therefore they are not observed on the map. The University of Guayaquil, located in the fourth quadrant, showed high values in Education and Social Sciences, while UTMACH presented high values in Engineering, and ESPOL and UTM were better represented in Chemistry. The universities located to the left of the map did not show high values in any of the four areas.

Figure 3 shows the dynamic HJ-biplot, which made it possible to project the universities in each year and analyze their trajectories over time. The University of Guayaquil obtained its highest increase in the variables of Social Sciences and Education in 2018. The Technical University of Machala was the one that changed its trajectory the most regarding the research areas, as in 2015 and 2016 it was best represented by the Chemistry area, then in 2017 it was characterized by the Education variable, and in 2018 it obtained its highest increase in Engineering. The Technical University of Manabí obtained its highest increase in variable Chemistry in 2018; in the same way, the Polytechnic Superior School of Litoral increased its production in Chemistry, although moderately. The rest of the universities showed general trajectories with slight approximations to the research areas, placing themselves in a plane far from them.

Table 5 shows the number of publications of public universities located in the Highlands region for the prepandemic period (2015–2018) and the average number of publications per year.

According to Table 5, the National University of Chimborazo had the highest average in Education (14), the Higher Polytechnic School of Chimborazo in Social Sciences (6.5), the Higher Polytechnic School of the Army and the National Polytechnic School obtained the highest average in Engineering (both 18) and in Chemistry the highest average was that of the National Polytechnic School (11.25).

The information captured in the HJ-biplot is shown in Table 6. The cumulative explained variance captured by the first three axes amounts to 95.08%. This indicates that three axes are sufficient to explain the position of the public universities in the Highlands region in the four research areas most frequented by researchers in the institutions.

Table 7 shows the contribution of each axis to the variability of publications in the different research areas. All variables have a high contribution and can be interpreted in planes 1 and 2; Social Sciences, Engineering, and Chemistry received a high contribution from Axis 1 and Education received a high contribution from Axis 2.

Figures 4 and 5 show the HJ-biplots for the 2018 data matrix for the Highlands region. A moderate and direct association is observed between Chemistry and Engineering and the latter presented a less strong but direct correlation with Social Sciences. The only correlation independence is observed between Chemistry and Education.

Five of the 13 universities in the Highlands region did not show a good quality of representation; the Higher Polytechnic School of the Army showed high values in Chemistry, the Polytechnic School Nacional showed high values in Engineering and Chemistry, the Higher Polytechnic School of Chimborazo showed high values in Education, and the Cuenca State University was characterized by the area of Engineering. The rest of the universities did not show high values in any of the four areas.

Figure 6 shows the dynamic biplot of the universities in the Highlands region, which made it possible to project the situation of the universities in each of the years, obtaining their trajectories.

The Higher Polytechnic School of Chimborazo has a defined trajectory: In the years 2015 and 2018 it is best represented by Education, and in the years 2016 and 2017, it is best represented by Social Sciences. The Higher Polytechnic School of the Army is the one that changed its trajectory the most: In 2015 and 2016, it was best represented by Engineering, in 2017, it changed its trajectory to Social Sciences, and in 2018, it obtained its highest score in Chemistry. The National Polytechnic School obtains the highest values in Chemistry and Engineering in 2018.

Research has demonstrated the practical utility of the dynamic biplot of Egido Miguélez (2015) for the study of the concentration of publications of Ecuadorian universities across research areas, as well as for the inspection of their trajectories. The HJ-biplot technique (Gómez-Marcos, Ruiz-Toledo et al., 2021) allows a graphical representation in which universities and areas can be superimposed in the same reference system with maximum quality of representation.

In the present study, Ecuadorian universities were studied by region, broken down by Coast-East and Highlands, and in both cases the accumulated inertia was very high. The research areas showed different covariances in each region.

In the Coast-East region, the strongest correlation was between Social Sciences and Education. These results are consistent with the research by Zhimnay Valverde et al. (2019). In the Highlands region, the strongest correlations were between Engineering and Social Sciences and between Chemistry and Education; for both groups, Chemistry and Education were independent.

Universities in the Coast-East region doubled those in the Highlands in Education and Social Sciences, while those in the Highlands doubled those in the Coast-East region in Engineering and Chemistry.

We can conclude that the public universities of the Highlands are focused on research in STEM (Chemistry and Engineering); in general, this trend is pushed by ESPE and EPN. The public universities of the Coast-East region are focused on research in Social Sciences and Education, and this trend is pushed by the University of Guayaquil.

Focusing on education research might occur because, according to Diaz-Kovalenko, Barros-Naranjo et al. (2023), in a developing country such as Ecuador, education is perceived as a key driver for social and economic progress. On the other hand, it is essential to address social sciences studies in a country for several important reasons. Research in social sciences plays a vital role in advancing humanity and in the socioeconomic development of communities and nations. And by offering multiple perspectives on everyday reality, it helps interpret and explain the processes of change and development, as well as deepening the understanding of human relationships and their roots, consequences, and effects (Thuy, 2022). Additionally, focusing on engineering studies in a developing country is crucial for several significant reasons. First, it can help ensure a high educational standard in engineering programs, even in nations with limited resources for laboratory facilities and equipment, as noted by Murad, Vanfretti et al. (2017). Second, evaluating the impact of research in developing countries is essential to justify investment in research and align it with national needs and circumstances, as highlighted by Zarog (2022). Third, a multidisciplinary approach and practical training, supported by the use of the Internet, open-source tools, and e-learning platforms, can enhance engineering education in developing countries and ensure the continued relevance of engineering graduates, as suggested by Onime and Uhomoibhi (2012). Last, the implementation of educational models and curricular innovations in postgraduate programs, focused on the industrial sector, can foster research and development in developing countries, as proposed by Forcael, Ávila, and Tenreiro (2022).

Although there are more than 29 public universities in Ecuador, only the oldest universities are focused on the development of hard sciences. This analysis lays the groundwork for future research that could deepen the understanding of the motivations behind universities’ research choices, as well as the evaluation of the impacts of this research on Ecuadorian society. In addition, the continuity of this type of analysis in postpandemic periods could reveal changes in research priorities and strategies in response to emerging dynamics.

We acknowledge several limitations in this study. First, the exclusive reliance on WoS-indexed publications may overlook significant research contributions not indexed in WoS. Second, the focus on the pre-COVID period means that the findings may not fully capture the current research landscape. Future studies could expand the scope to include non-WoS-indexed publications and post-COVID data to provide a more comprehensive understanding of research trends.

An important consideration in this study is the potential biases introduced by relying solely on the WoS database for data collection. WoS, while comprehensive and respected, has known limitations that can affect the visibility of scientific production, especially from regions such as Latin America and other parts of the Global South (Muñoz-Uribe, 2023). One of the main criticisms of WoS is its tendency to favor journals published in English and those with higher international recognition, often at the expense of locally significant research published in other languages and regional journals (Castro, 2023).

This linguistic and publication bias can lead to an underrepresentation of the full spectrum of scientific contributions from non-English-speaking countries. Consequently, our analysis might not fully capture all relevant research outputs from Ecuadorian public universities, potentially skewing the results towards more internationally visible publications.

Future research could explore several avenues to build on the findings of this study. For instance, post-COVID research trends present a unique opportunity to examine how the pandemic has reshaped research priorities and methodologies in Ecuadorian public universities. Specific questions that future studies could address include the following:

• How have research priorities shifted in response to the COVID-19 pandemic?

• What new research areas have emerged as a result of the pandemic?

• How has the pandemic affected the collaboration patterns among researchers and institutions?

• What are the long-term impacts of COVID-19 on research funding and infrastructure in Ecuadorian universities?

• How have digital tools and remote research methodologies been integrated into the research practices of these universities?

The findings of this study have several practical implications for policymakers and academic institutions in Ecuador. First, the identified regional differences in research focus suggest the need for region-specific research policies. Policymakers should consider developing tailored research strategies that leverage the strengths of each region, such as promoting Social Sciences and Education research in the Coast-East region and Engineering and Chemistry research in the Highlands region.

Second, academic institutions can use these insights to align their research agendas with regional needs and strengths, potentially enhancing their impact and visibility. For example, universities in the Coast-East region could focus on developing programs and collaborations that address social and educational challenges, while those in the Highlands region might prioritize technological and scientific innovations.

Third, understanding the pre-COVID research landscape provides a baseline for assessing the impact of the pandemic on research activities. This can help in designing recovery and support measures that ensure the continuity and resilience of research efforts during and after health crises. By fostering regional specialization and collaboration, Ecuador can improve its overall research output and relevance on the global stage.

The present study effectively demonstrates the applicability of the dynamic biplot to analyze the distribution and evolution of scientific publications of Ecuadorian public universities in various research areas. By implementing the HJ-biplot approach, a detailed and high-quality visualization was achieved, facilitating the superimposition of universities and areas of study in a unified frame of reference. Notable differences in research trends were identified between the regions of Ecuador, with a bias towards Social Sciences and Education in the Coast-East region, and a preference for Engineering and Chemistry in the Highlands region. This pattern points to a concentration on applied sciences by the older institutions in the Highlands, led by ESPE and EPN, in contrast to a focus on social sciences and education in the Coast-East region, driven mainly by the University of Guayaquil.

This analysis not only highlights the diversity of approaches to university research in Ecuador but also raises relevant questions about the driving forces behind these trends. Future exploration of these motivations and the impact of research on Ecuadorian society is an essential step in understanding the evolution of the academic landscape in the country. Furthermore, it is anticipated that the continuation of these analyses in the postpandemic context will provide valuable insight into the adaptive shifts in research priorities and strategies, reflecting the new dynamics and challenges facing Ecuadorian public universities.

Dennis Peralta: Conceptualization, Formal analysis, Methodology, Software, Visualization, Writing—original draft, Writing—review & editing. Patricio Álvarez: Conceptualization, Methodology, Writing—original draft, Writing—review & editing. Fernando Pacheco: Conceptualization, Methodology, Writing—original draft. Angelo Aviles: Validation, Writing—original draft.

The authors have no competing interests.

This research received no external funding.

The data supporting the findings of this study were retrieved from the Web of Science database using the following search query: ‘CU = (ECUADOR) AND PY = (2015-2018) AND DT = (Article)’. Access to these data requires a subscription to the Web of Science platform, and the data set can be accessed by authorized users through institutional or personal subscriptions.