Introduction

Scientific knowledge appropriation (KA) or the ability to generate rents or value from scientific knowledge is a big challenge for countries when trying to recover investment in research and development (R&D). It is not only a problem for emerging economies (Dedrick & Kraemer, 2015) robust R&D systems. Nevertheless, knowledge leakages or spillovers are common because national innovation systems do not have the strength to retain this knowledge.

AC has been demonstrated as a critical element of appropriation and vice-versa (Cuéllar et al., 2022; Cuéllar et al., 2023a). AC has been defined as the ability to acquire external knowledge, transform, and exploit it (Cohen & Levinthal, 1990). AC seminal authors have shown the relevance of AC in the KA process and the importance of both AC and KA in generating competitive advantages and innovation performance (Cuéllar et al., 2022; Cuéllar et al., 2023a). Nevertheless, to the best of our knowledge, the relationship between AC and KA at a country level has not been studied or even partially analyzed. For instance, some studies have investigated AC and KA in subsidiaries (Volvo Group), and they were able to identify the relevance of AC and KA to emerging economies (Cenamor et al., 2019). Researchers were also able to demonstrate the relevance of AC over KA but only for specific technologies (Dedrick & Kraemer, 2015). In addition, as Fig. 1 shows, the number of studies conducted either on AC or KA individually in emerging economies and especially in Latin America has been few.

Fig. 1
figure 1

Studies of AC or KA in a country level. Legend: Red color is the country with the most studies, followed by light blue, orange, and dark blue

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This study seeks to increase knowledge of AC and KA at a country level using scientific papers and patents, designed to provide a more complete perspective of players, networks, and knowledge flows. In our business case study, we analyzed the Colombian innovation ecosystem. We used text mining, bibliometrics, and patent analysis methods to recognize local KA and KS.

Our research is divided into the following sections: Firstly, we analyze the state of knowledge of AC and KA measurement methods to identify the different strategies used in the academic community showing the main approaches and identifying the best options to analyze AC and KA at a country level. Secondly, we propose our new methodology, which blends text mining and bibliometric indicators to analyze AC and KA at a country level. Finally, we show our case of study of Colombia (Fig. 2).

Fig. 2
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AC dimensions based on Cohen and Levinthal (1990) and Zahra and George (2002)

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The following research questions were proposed in our study:

RQ1 seeks to understand which indicators are best for measuring the AC and KA at a country level.

RQ2–RQ4 were created to show our tool for AC and KA measurement.

The specific questions were:

RQ2 How has the KA of Colombian scientific knowledge evolved, and who has conducted KA, Colombian organizations or foreign organizations?

RQ3 What is the cycle of KA and AC at country level, and what have been the knowledge flows?

RQ4 Who is appropriating Colombian scientific knowledge, native or foreign organizations, and which type of organization are done this KA?

Background in the Art

Absorptive Capacity Measuring Based on AC Dimensions

We reviewed AC and KA measurement literature to answer RQ1, asking which indicators are best at measuring AC and KA at a country level. We started analyzing AC. As Cuéllar et al. (2022; 2023a) showed, AC was built as a multidimensional concept, and many authors have created methods to measure AC based on its dimensions.

The acquisition stage has been measured by scanning the microeconomic and macroeconomic environment to obtain market knowledge from suppliers, customers, competitors, consultancies, universities, technological centers, conferences, digital networks, and fairs (Alves & Galina, 2020; Heeley, 1997; Jiménez-Castillo & Sánchez-Pérez, 2013; Popadiuk & Nunes, 2018; Yang & Tsai, 2019; Zhang et al., 2018).

The assimilation stage has been measured using different indicators, such as knowledge reactivation, demand analysis, and new opportunities identified by customers (Zhang et al., 2018); the human resources with high learning capabilities and employees capacity for recognizing market changes, new opportunities to help customers, and skills to understand demand change (Jiménez-Castillo & Sánchez-Pérez, 2013; Pérez et al., 2019).

Lau and Lo (2015) measured transformation based on the employees skill to store knowledge information for future development and to conduct periodic meetings to identify market trends, the company’s skills to understand the demand of changing markets. The last indicator was used also by Jiménez-Castillo and Sánchez-Pérez (2013).

Finally, exploitation phase was measured by identifying the knowledge used on new products (Jiménez-Castillo & Sánchez-Pérez, 2013; Zhang et al., 2018). Other investigators have used the quality and variety of products, the production and flexibility capability, cost reduction, labor cost reduction, and raw material cost reduction to measure the exploitation phase (Alves & Galina, 2020). Finally, Lau and Lo (2015) analyzed exploitation by identifying whether companies seek to exploit the new knowledge, and whether employees have a common language related to new products.

Measuring Based on Potential AC and Realized AC

Other researchers have measured AC based on Zahra and George (2002) who put together acquisition and assimilation in a new phase named Potential AC and transformation and exploitation in Realized AC.

Potential AC is measured by scanning skills of the organization and employees to undestand new opportunities for customers (Flor et al., 2018) to search for information inside and outside the organization (Kim et al., 2016; Vicente-Oliva et al., 2015), and it is used for industrial structure analysis and technological trend analysis (Aliasghar et al., 2019) and knowledge storage (Aliasghar et al., 2019; Flor et al., 2018; Kuek et al., 2013).

Realized AC was analyzed based on new product or service development (Liu et al., 2021), capabilities to use external knowledge, grab opportunities of external knowledge, periodical meetings to conduct market analysis, development of new products, employee’s consciousness regarding innovations, evaluation of the best form for exploiting knowledge, and to share a common language to talk about products and services (Flor et al., 2018).

AC Measurement Using a Non-Dimensional Approach

R&D has been one of the main proxies used to measure AC through a non-dimensional approach based on human resources (Luo, 1997; Veugelers, 1997), R&D intensity (Behera, 2015; Cruz-González et al., 2015; Jiménez-Castillo & Sánchez-Pérez, 2013; Mowery & Oxley, 1995; Tsai, 2001), R&D investment based on the scientific literature (Mangematin & Nesta, 1999), patents (George et al., 2001), and strategic alliances (Cherbib et al., 2021; Gilsing et al., 2008; Mangematin & Nesta, 1999; Mowery et al., 1996).

Patent Analysis and Bibliometrics Methods for Measuring AC and KA

Some authors have analyzed AC based on backward citations (BC) (Sears, 2018), for instance, non-self-BC to measure AC (Appio et al., 2019; Rothaermel & Thursby, 2005), self BC (Shin & Jalajas, 2010), and the ratio between own BC compared to BC of patents and non-patent literature (Basse Mama, 2018). Another approach has used cross patent citations (Kim & Inkpen, 2005).

Miguélez and Moreno (2015) analyzed regional AC using mobility and network variables. They took patent information and analyzed inventors’ mobility and networks based on the countries of the inventors (Gilsing et al., 2008). Other authors have applied social network analysis indicators to measure AC (Enkel & Heil, 2014; Gilsing et al., 2008; Zhang et al., 2007).

Other authors have used other indicators based on patent data to measure AC. These approaches include firm stock patents (Dushnitsky & Lenox, 2005), patents per capita in 101 countries (Malik et al., 2021), prior cumulative patents (Nooteboom et al., 2007), the share of patents among all the players in an industry and pioneer technology identified by patents that do not have patent prior art (Srivastava et al., 2015; Srivastava & Shainesh, 2015), and by analyzing the interaction between universities and industry measure by patents (Bishop et al., 2011).

Figure 3 shows the different approaches that were studied in this research paper. The different methods applied are shown by the measuring done (non-dimensional, multiple dimensions, potential, and realized). The best approaches for country analysis to have relevant samples are national surveys and bibliometrics (where we included social network analysis patent analysis). The Figure also shows that non-dimensional methods and potential and realized analysis have been more commonly applied than multiple dimensional analysis.

Fig. 3
figure 3

Absorptive capacity measurement approaches explored in this study. Legend: The square size indicates the size of the analyzed sample. (https://public.flourish.studio/visualisation/14079619/)

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Patent classification has been used by numerous authors to compare organizations based on their patent classification (Ruth et al., 2013; vom Stein et al., 2015), for instance, the WIPO international patent classification IPC (Ruth et al., 2013).

The Fig. 4 summarizes AC measurement methods. The size in the pie indicates the number of scientific papers identified in our analysis used to measure AC. R&D analysis, R&D employees, social network analysis, and citation analysis have been the preferred methods for one dimension measurement. For the acquisition stage and Potencial AC, environmental scanning has been the most popular. For the assimilation stage, the most popular methods have been customer analysis and human resource analysis. For transformation measurement, demand and market changes have been the most popular form of measurement. For exploitation, development of new product and services is the most studied. For realized AC, human resources and new products and services have been the most common measurement methods.

Fig. 4
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Main indicators use to AC measurement. Legend: https://public.flourish.studio/visualisation/7313787/

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Knowledge Appropriation Measurement

We analyzed different KA measurement methods. Milesi et al. (2013) measured KA in Argentina based on patent, brands, secrecy, first-mover company strategy, participation, and control of supply distribution networks. Colombelli et al. (2020) used a similar approach but aggregated the lead time of products or services. Other authors have used similar approaches based on IP (Arbussà & Coenders, 2007; Bahl et al., 2021; Barros, 2021; Spithoven & Teirlinck, 2015). These authors either mixed IP with informal mechanisms (Leiponen & Byma, 2009), collaboration between organizations (Benedicto et al., 2014; Rubira-García et al., 2018), or examined the complexity of product design, employees contracts, lead time advantage, complementary manufacturing, marketing, and service capabilities (Torres de Oliveira et al., 2021). Other approaches have measured the impact that research studies have had in the news (Uribe-Tirado et al., 2020), patent citations (Wang & Chen, 2010), or the triple helix interaction in small-scale fisheries (Fig. 5).

Fig. 5
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Framework of analysis of AC and KA

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A Methodology to Measure AC and KA in a Macro and Meso Level

The last chapter showed that surveys and bibliometric methods are the best methodologies for analyzing AC and KA at a country level. In order to explore the AC and KA of Colombian scientific knowledge, we used bibliometrics and patent analysis to analyze the entire landscape (Fig. 6).

Fig. 6
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Toolbox generated to measure AC and KA at the macro and meso level

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Data Recovery

We analyzed the scientific papers published by Colombians that generated KA, which was measured by patent FC. We decided to use the Patent Lens database and Scopus to link scientific and technological (patent) literature using scientific and technological citations. Our main objective was to show the KA of scientific knowledge appropriation at a macro and meso level and the relevance of AC in this process. Therefore, we analyzed the origin of the publications and patents by country. We focused on Colombia as a business case study because, in innovation rankings, this country is not known as a generator of innovation. However, Colombia has historically produced more scientific literature than other emerging countries in the region (Incites, 2022).

We searched the patent lens database by using the following query: author.affiliation.grid.address.country_code: “CO.” This search strategy produced 227,922 results. Due to not every scientific publication has been cited by patent literature, we filtered our search to only look for scientific literature that is cited by patents. Through this method, the number of results decreased considerably to 1680 results. These final results were named scientific key literature (SKL) due to its importance to generate technological developments. Afterward, we analyzed the knowledge exchange process to understand the AC process of the scientific papers and the generation of patents, which we associated with KA and AC transformation and exploitation stages. Therefore, we did a BC analysis of the scientific literature that the SKL cited. BC was found using the “Patent Lens database,” and 50,697 BCs were recovered through this process. In addition, we were able to identify the world patents that have exploited SKL. These were used as an indicator of KA and realized AC. In order to recover this data, the Patent Lens database was also used. A complete dataset of 3066 patent families was obtained.

Data Cleaning

A specific Knime workflow was designed to normalize duplicate data and to link the three main blocks of information-scientific key literature, backward citations and patents (Cuellar et al. 2023b; Tursi & Silipo, 2019; Urbina-Cardona et al. 2023). In addition, we used Tableau Desktop and WinPure clean and match community edition to normalize country information.

Data Analysis

Our research was conducted on two levels: macro and meso. Macro analysis was done based on countries, and meso analyses used authors’ affiliations and correspondence author affiliation.

The knowledge flows between countries were created using BC and FC, which were analyzed by using social network analysis methodologies. We analyzed KA, the type of organizations, and the influence of AC based on network centrality to generate appropriation.

The framework summarizes the methodology and indicators that were used in our analysis.

Case of Study “Knowledge Appropriation of Colombian Scientific Key Knowledge and the Influence of Absorptive Capacity over the Appropriation”

Based on the framework showed in the methodology, we conducted a case study of KA by examining scientific key literature and the influence of AC.

RQ2 seeks to recognize how KA evolved at the local and foreign level. By basing KA evolution on the FC, we were able to track the evolution of KA. The life cycle showed that this appropriation began in 1975 with an emerging phase characterized by low KA. The rising number of patents began in 1998 with a new phase called the growth stage characterized by an exponential increase in appropriation. This period has not ended. This analysis shows that KA has increased over time (Fig. 7).

Fig. 7
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Knowledge appropriation life cycle and percentage of appropriation by national applicants and foreign applicants

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Regarding local KA, we found a negative outcome of only 1.76%. This result shows that the primary phenomenon with SKL has been a KS. In other words, SKL has been appropriated, transformed, and exploited by foreigners and not by Colombians.

Figure 8 focuses on local KA. Although our research shows an increase in Colombian filed patents, the amount of patents filed is so low as to be considered irrelevant (in the peak year of 2013, only nine patents were filed). This analysis shows that the KA process by local patent applicants is a rare phenomenon, and the technology transformation and exploitation associated with realized AC are rarely undertaken by local organizations.

Fig. 8
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Knowledge appropriation process by Colombian applicants based on patent FC

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In RQ3, we identified the critical countries in BC, SKL, FC, and the knowledge flows. Our goal in this analysis was to show the KA cycle at a country level to see the link between AC and KA. We followed the framework proposed in Fig. 5. To understand the knowledge flows, we recognized the countries of origin of BC. We identified the USA, the UK, Germany, and Japan as major BC countries in the emergent and growth stage. Spain and France were two other major countries considered to be in the growth stage. In the emergent stage, only 2.10% were acquired from Colombian sources, and in the growth stage, this number doubled but was still such a low number as to be considered irrelevant when compared to other countries (Fig. 9).

Fig. 9
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Key countries identified by developed backward citations, forward citations, and SKL

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We started analyzing main countries by coauthorship with Colombian organizations regarding the assimilation stage. We found that the USA was the main collaborator, followed by the UK, Spain, Germany, and Brasil. This analysis showed that the assimilation process carried out by SKL has been developed mainly through collaboration with countries with strong R&D and not with neighboring countries such as Ecuador, Venezuela, or Peru (Table 1).

Table 1 Country coautorships statitistics
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Finally, we analyze transformation and exploitation of knowledge based on the countries of origin of the patent applicants (FC), which also reflects KA (Fig. 10).

Fig. 10
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Country scientific coauthorship in SKL in the emergent stage

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The USA has been the most active country for KA, followed by Japan in the emerging stage, and Germany and China in the growth stage. The FC analysis shows that the KA process has been carried out mainly by developed countries.

This analysis also shows that Latin American KA has been irrelevant, and African countries have been isolated from these knowledge flows.

Assimilation AC and its Relevance in KA and KS and Exploitation

RQ3 aimed to understand the AC assimilation process based on country collaboration. Five communities were found in the emergent stage using the VOS viewer community detection tool shown in Fig. 10 with the different colors (van Eck & Waltman, 2010). The major countries in each subgroup were identified. The USA was the most visible in the violet color cluster, while Spain was a key country in the red cluster, the UK in the yellow, and Switzerland in the green. The major countries that were involved in social network analysis were the USA, Sweden, Brazil, and UK. Another relevant indicator that came to light through social network analysis is the betweenness centrality. This indicator identifies the countries that are bridges between the different communities. We found that the USA, Spain, Sweden, Brasil, and the UK had the biggest betweenness centrality.

In the growth stage, we found the USA as a key country. A major scientific partners of the USA were Spain and Germany, which can be seen by the number of records and the number of coauthorships by country. Subgroups between countries such as Sweden, Australia, and Norway were identified through SNA analysis. A strong cohesion between Europe, Asia, and North America was found to be evident in this stage. Using the betweenness centrality indicator, we found that the main bridges of countries in the growth stage were between France, Spain, the USA, and Brazil.

Social network analysis indicators show the evolution that has occurred in the network over time. Some critical insights can be obtained based on this analysis. For instance, half of SKL was developed by Colombians without international collaboration. In addition, the growth stage shows an increase of 32% in the collaboration between Colombians and international organizations. An increase in collaboration between 2 or 3 countries can also be seen in the emerging and growth stage. This analysis shows that increased collaboration is related to growth in KA. Network diameter shows that the network is more compact in the growth stage than in the emergent stage, and density analysis shows that the growth stage has increased the strength of collaboration between countries (Fig. 11).

Fig. 11
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Country scientific coauthorship in SKL in the growth stage

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Going Deeply Among Knowledge Acquisition, Knowledge Assimilation, Knowledge Exploitation and Appropriation

To understand knowledge flows and the dynamics of knowledge acquisition, assimilation, realized AC, and KA, we analyzed the relationship between BC countries, SKL countries, and FC countries by citations.

Our first analysis (see Fig. 12), as seen on the left side of the figure, shows the cited countries and where knowledge was acquired by Colombian organizations. In the center of the figure, you can see the SKL countries that assimilated knowledge from BC. On the right side of the figure, the countries that made KA and knowledge transformation and exploitation by patents are shown.

Fig. 12
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Country by BC, SKL, and FC in the emergent stage

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This analysis shows that the USA was the primary knowledge source in the emergent stage, and the knowledge from this country has been acquired mainly by US organizations and appropriated by them. The assimilation process was done by Colombian organizations in collaboration with Spain, Venezuela, France, Mexico, and the UK, as shown in Fig. 12. Germany, Brazil, and China were other prominent countries in the appropriation and exploitation process.

The growth stage shows an increase in the number of countries where knowledge was acquired and assimilated. The growth stage had almost twice the number of countries where knowledge was acquired as the emergent stage, and the number of SKL countries moved from 35 to 95 countries. FC analysis shows that the number of countries moved from 13 to 53, demonstrating a significant increase in countries that appropriated and exploited this knowledge (Fig. 13).

Fig. 13
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Country by BC, SKL, and FC in growth stage

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We built a bibliographical coupling analysis to further explore the link between countries where knowledge was acquired (BC) and countries that were involved in knowledge appropriation (FC). We did not filter for different stages to have a holistic perspective for this analysis (Fig. 14).

Fig. 14
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Bibliographical coupling analysis between BC and FC countries. https://public.flourish.studio/visualisation/7601018/

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A relevant pattern in our analysis was recognized. The major BC countries were the USA and the UK. They can be considered building blocks in the generation of scientific development that is later appropriated by other countries. Other major countries that had considerable BC were Germany, Canada, and France. When KA was performed by Colombian applicants, Colombian BC was shown to be an important building block.

What Happens when a Country is the Main Owner of the SKL Knowledge?

In this research, we wanted to understand what happened when a country was the primary developer of the SKL. To answer this question, we used the corresponding author (CA) which is defined as the author who is the leader in the development of the SKL. Among the roles of a CA are to be in agreement with the journal to make the payments and to make any required corrections in the manuscript (Cambridge University, 2022) (Fig. 15).

Fig. 15
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Countries CA in emergent and growth stages

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We found that Colombia made up 35% of SKL CA in the emergent stage and 43% of SKL CA in the growth stage. On the other hand, Venezuela had a 22% of CA in the emergent stage. In addition, the USA had a 15% of CA, and Spain had 11% of CA in the growth stage. This analysis shows the leading role that Colombian organizations played in SKL.

To understand knowledge flows when a country was a CA, we identify the networks between CA countries in SKL and FC countries. When Colombia was CA, the main outcome was a knowledge spillover where knowledge was transformed, exploited, and appropriated mainly by the USA (41%), China (12%), and Colombia but by a lesser proportion than by other countries (8%). On the other hand, this outcome shows that local KA improved from 1.76 to 8% when Colombia was the CA. In addition, this analysis showed that the USA has been the only country that has been able to transform its own knowledge with 57% of its academic articles being appropriated by themselves when they were the CA. Other countries that have achieved KA when they were the CA were Germany, Chile, and Canada. These outcomes show that most developed economies have developed better mechanisms to do KA.

Understanding KA at an Organizational Level

RQ5 seeks to understand when appropriation happens by local applicants, by partners, or by other organizations unrelated to scientific development. In order to understand this process, we analyzed all the organizations involved in the SKL and KA processes (Fig. 16).

Fig. 16
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Relationship between SKL correspondence author country and KA country. https://public.flourish.studio/visualisation/7979624/

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Firstly, we identified whether KA was done by some of the players that were in the SKL, or whether it was done by external organization KS. KS happens when none of the organizations that worked on the scientific paper was an applicant in the patent. We defined owner appropriation when the CA of SKL was also part of the appropriation and exploitation. We understand that the CA organization gives more knowledge to SKL development; for this reason, we defined CA as an SKL owner. Partner appropriation happens when the owner does not conduct KA, but when an SKL partner does this.

Our analysis showed that the most common type of outcome is a KS of 95%. Furthermore, 5% of KA is represented by 39% of foreign KA, 38% of local KA, and 20% by partner KA (Fig. 17).

Fig. 17
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(Left) Ks and type of KA (right) type of local KA

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When Appropriation Happens by Local Applicants

Based on our data, our last analysis showed that KA done by local applicants in emerging countries can be considered atypical, local applicants developed only 1.76% (50) of patents. We decided to delve into these cases and segment the KA local cases into different categories:

  • KA done by all organizations that are involved in SKL

  • KA done by local organizations where foreign organizations are not in the patent

  • KA done by a local organization that is the unique organization in SKL

  • KA done by a new local organization that is not involved in SKL

  • KA done by a SKL organization and a new local organization

  • KA done by local organizations that are involved in SKL

  • KA done by some of the local and foreign in SKL organizations

We identified that the most common type of local KA was participation by all organizations that were in SKL in the patent development (30.51%). Another common scenario has been that only the local organizations filed a patent without the aid of foreign organizations; however, in SKL, they had coauthorship with international organizations (22%). In addition, another relevant scenario has been the patent application by only the local organization (13%) and the patent application done by a different local organization that was not a coauthor in the SKL (10%) (Fig. 18).

Fig. 18
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Comparison between SKL and appropriator organizations

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Regarding the organization type that was done in this KA, we found that it was done mainly for universities (70%), companies (22%), and inventors (6.67%).

Our outcome indicates that appropriation is done mainly for the same type of organizations that produce the SKL.

The following figure demonstrates which kinds of local patent applicants have participated in KA. Applicants were segmented using R&D activity and FC. The principal organizations for R&D were the most recognized universities in the country for R&D (Incites, 2022). These universities are Universidad Nacional, Pontificia Universidad Javeriana, Universidad de Antioquia, and Universidad de los Andes. FC analysis showed the main leaders to be Google, Augura, and Universidad Eafit. The last analysis confirms the relevance of Colombian universities in the KA of the SKL that they have produced.

On the other hand, we tried to understand the relevance of AC in appropriation at an organizational level. We analyzed the SKL collaboration network to see if the local organizations that have appropriated and exploited knowledge were prominent in the SKl community. We found that critical organizations shown in our last analysis were part of the main scientific communities in SKL and although they did not have the most substantial cohesion with other SKL organization, they have been part of these communities (Fig. 19).

Fig. 19
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Type of triple helix organizations that has appropriated and exploited the knowledge

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RQ4 shows than in emerging economies, the main outcome is a KS were SKL is not absorbed or appropriated by the country, and when it is apppropriated, it is by the same SKL organization. A weak link between quintuple helix ecosystem players (Carayannis & Campbell, 2010) can be seen in Colombia where knowledge is not transferred to companies or government, and it stays stagnant in universities.

Discussion and Limitations

Our study shows a novel approach to measuring AC and KA at macro and meso levels that can be used to understand the relationship between AC and KA. Our tool does this by analyzing the SKL that patents have cited. We took all the SKL from Colombian organizations that have been cited by patents (FC) throughout the world. One of the advantages of this methodology is that it can be replicated by other countries. Therefore, this process can be used to help evaluate and compare different regional innovation systems between different countries.

We opted to utilize bibliometric methods to examine KA and AC in countries. Bibliometric techniques, with their quantitative orientation, enable the systematic collection of scientific and patent data. Furthermore, such methodologies offer a comprehensive view that encompasses thematic analysis, participant analysis, and more (Florêncio et al., 2020). In addition, bibliometric methods facilitate the measurement of productivity and impact related to scientific and technological outputs (Soares et al., 2019).

On the other hand, bibliometrics allow for the analysis of large data sets that may not be feasible with surveys and interviews. Bibliometrics enable the collection, processing, and analysis of information, providing a comprehensive and representative landscape of scientific and technological production (Ribeiro et al., 2023). Additionally, bibliometric methods offer a historical perspective of the data, effectively illustrating trends, patterns, and connections within the information (Huang et al., 2021).

Our methodology starts by analyzing appropriation grade, comparing foreign and local KA from an S curve analysis (Ernst, 1997), which allows us to identify the different stages of KA. Other authors have used this approach in different countries to measure the role of the technological regime and technological catch-up and the link with life cycle and KA (Park & Lee, 2006) (Fig. 20).

Fig. 20
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Local appropriators

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Knowledge flows is a topic that has been studied few in KA literature, for instance, the role of KA in knowledge flows between multinationals and their subsidiaries in Portugal, Germany (Faria & Sofka, 2008) and China (Wu et al., 2005), or the role of KA over knowledge flows and KS in Japan and the USA (Cohen et al., 2002). The relationship between AC and knowledge flows has been analyzed using patent data and a citation analysis from USPTO patent database. Other authors have analyzed the influence of AC over the knowledge flows in incubators firms (Rothaermel & Thursby, 2005) and the role of AC in capturing US business models of three Australian companies (Bailey, 2017). Our novel approach uses backward—BC—and forward—FC—citation using visual analytics (Ebert et al., 2021) that permit researchers to analyze and clarify knowledge flows between the countries of origin of BC, SKL, and FC. This methodology allows researchers to measure AC of the countries involved in the generation of SKL literature and recognize the countries scanned in the environment (BC countries) to generate SKL. Furthermore, the methodology measures knowledge assimilation by analyzing country collaboration networks and their influence over KA and knowledge exploitation from the patents generated from SKL. The relationship between knowledge acquisition and KA was done by using bibliographic coupling analysis showing the influence of BC countries over FC countries. Finally, we made a zoom to recognize the appropriation process when a country was the primary developer of the SKL that was identified using the correspondence author (CA). The last two approaches are novel in the literature of KA and AC and could make a significant contribution to both fields (Fig. 21).

Fig. 21
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SKL coaffilliation network

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Regarding the measurement of AC and KA at a meso level, our tool can analyze a whole country or region. For instance, our methodology allows for the understanding of specific cases of KS, KA done by the corresponding authors, KA done by a partner in SKL, or KA done by SKL organizations that were not the CA.

KA and KS are topics that have been studied but not at a whole country level as we did in our research. Other authors have analyzed other perspectives from KA and KS. For instance, the relevance of both in product innovation in Belgium, Germany, and Spain (Spithoven, 2013), the relevance of KA and alliances to product innovation in Colombia (Caldas et al., 2021), or the relevance of KA in KS from Germany and Portugal multinational companies. Our paper complements this literature showing the relevance of AC for KA and the positive effect of a low AC in KS.

In addition, we analyzed the local KA deeply and analyzed whether the KA was done by the CA organization or if KA was done by all the organizations that were in the SKL. Our tool also measures the types of organization that have participated in appropriation (company, university, governmental) to understand the role of the innovation ecosystem players (Carayannis & Campbell, 2010) and the influence of AC over KA based on the organizational co-authorship network, identifying the importance of local organizations in these networks. Other authors have analyzed the influence of AC in regional innovation system; for instance, in China (Li et al., 2018), the impact of foreign direct investment over regional innovation at a city level can identify the positive impact of AC (Jiang et al., 2021) and the relevance of AC in the interaction between companies and universities in the Spanish regional Andalucia innovation system (Pinto et al., 2013).

Our main contribution to this topic was the segmentation done by a type of player segmenting it by local or foreign organizations and by identifying the roles they played in SKL.

Regarding our case of study, to the best of our knowledge, no former studies have analyzed AC and KA at the country level based on the whole R&D landscape, although both topics exhibit a significant relationship and considerable convergence (Cuéllar et al., 2022; Cuéllar et al., 2023a). For instance, Barros (2021) studied only a sample of 505 companies in the Brazilian ecosystem, as well as Andreeva et al. (2021) who analyzed the link between intellectual capital and appropriability in Finland, Spain, and Russia based on 649 firms, or Arvanitis and Bolli (2013) who identified the relevance of AC and KA in Belgium, Germany, Norway, Portugal, and Switzerland with a sample level of 4570 companies.

In addition, our business case also fills a large gap in the Colombian knowledge management and innovation literature where there are only a few studies as Caldas et al. (2021), who studied AC and KA in 913 manufacturing firms.

Other studies have used similar approaches to us to understand KA. For instance, Huang (2016) used scientific and technology knowledge flows in the genomic industry. Nevertheless, the scope was different. Our study opens different possibilities to do research associated to this field, for instance, to use the same approach to understand a country’s KA and AC relationship and to compare regional innovation systems. In addition, other indicators can be adhered to our methodology as the measurement of novelty or originality (Harrigan et al., 2017) indicators required to identify innovation or to use granted patents that would be a better proxy for KA.

Our outcome can be used as measurements to recognize the weaknesses of emerging countries to retain and exploit their own knowledge.

Our analysis showed that KA is not common in these types of economies. In addition, this local KA is done mainly by universities showing that the cohesion between the triple helix is an important task that should be done by governments to improve KA.