The Impact of Knowledge Spillovers on Economic Growth from a National Perspective: A Comprehensive Analysis

Abstract

Knowledge spillovers, driven by development and research projects, are crucial in generating new companies and services. They enhance innovation, improve competitiveness, and sustain the economic growth of nations. Hence, this paper aims to examine the relationship between knowledge spillovers and economic growth. It offers a comprehensive review of the scientific literature on the relationship between knowledge spillovers and economic growth, investigating the impact of economic cycles on knowledge spillover. Doing this provides valuable insights into how to leverage them at the different stages of the economic cycle. Hence, a PRIMA systematic review was conducted. Articles from the last 15 years were analyzed from repositories and scientific databases with a Cohen’s kappa coefficient of 0.8902. This review identifies and presents a systematic analysis of the impacts of favoring and hindering knowledge spillovers in the economic growth of a nation. These effects offer greater resilience to a nation after periods of recession. In addition, the case study of three countries is presented to illustrate the findings from the review. The results show that better utilizing knowledge spillovers to enhance economic growth depends on a functional compromise between the university, industry, and governments to understand and commit to knowledge-based economic development. Our study has implications for policymakers who aim to boost economic growth by promoting knowledge spillovers.

1. Introduction

Nowadays, in a globalized and technology-driven economy, knowledge spillovers play a significant role in the economic growth and innovation of a country [1,2,3]. Its financial and technological strength, competitiveness, and international reach depend on its ability to adapt, develop, and implement inventions through effective strategies and mechanisms [4]. Moreover, innovation (included in the ninth sustainable goal of the United Nations Development Programme) is a crucial driver of economic growth by promoting technological progress, scientific research, and sustainable industries. This, in turn, stimulates the search for lasting and sustainable solutions to environmental and economic challenges while facilitating sustainable development [5]. Hence, “the need to evaluate the effectiveness of the innovation transfer is increasing” [4]. Over the few last decades, the study of the relationship between economy and innovation has emerged as a distinctive area of examination, covering regional economics, the economics of growth, firm theory, and industrial organization. It has evolved into a particular area of competence in economics specialized in exploring the effects of technological transformation as an endogenous process [6,7]. In the study of multiple domains of economic theory, “innovation is viewed as a complex, path-dependent process characterized by the interdependence and interaction of a variety of heterogeneous agents, able to learn and react creatively with subjective and procedural rationality” [7]. Therefore, examining the relationship between knowledge spillovers and economic growth is relevant to improving strategies and policies that support research and development (R&D) efforts and the overall growth of nations.

The sharing of knowledge has become an effective driver of economic growth and development in an increasingly interconnected world [8]. The generation and diffusion of knowledge promote the design of new products and services, improve the existing ones, and facilitate the engineering of new production processes, ultimately creating new jobs and increasing economic activity [8,9]. This process, coined as knowledge spillover, involves transferring information, ideas, and technologies between diverse economic actors [10]. Patent registration, technology transfer, scientific publications, university–industry collaborations, and networking, among others, are examples of knowledge spillovers [11,12,13]. Efficient spillovers of knowledge and innovation have a positive impact on economic performance and policy outcomes [4]. For example, patent registrations and their dissemination enhance the quality of patented technologies, leading to increased innovation, productivity, and entrepreneurship [14,15]. Moreover, the quality of patents, environmental innovation, and intellectual property rights contribute to improving industrialized economies [16,17]. This emphasizes the importance of innovation as a critical driver for sustainable development and economic growth.

To effectively promote the transmission of innovation requires a thorough analysis and assessment of local, national, and regional economies [4]. This analysis supports the design of initiatives and policies to promote an innovative environment for knowledge spillovers, creating opportunities to sustain growth and development. R&D activities promote economic growth, motivating the new generations to flourish in a globalized world through knowledge. The geographical proximity between university faculties may foster informal sharing of knowledge, thus increasing the potential for technology transfer and knowledge commercialization through entrepreneurship [18,19]. Nevertheless, economic cycles have positive and negative effects on knowledge spillovers [20]. The allocation of budgets for R&D projects impacts university–industry collaboration as well as the generation and promotion of new patents. Hence, the allocation of these funds may be altered depending on the stage of the economic cycle.

Based on the given scenario, the main research question of this work arises: What is the relationship between the spillover of knowledge and the economic growth of countries?

To further investigate this topic, three complementary research questions have been raised:

• How does the economic cycle affect the knowledge spillovers?
• How do knowledge spillovers affect economic growth?
• What are the prospects for economic growth based on the knowledge spillovers?

Answering these questions is crucial for understanding the impact of various forms of knowledge spillovers on the economic development of regions and countries. Furthermore, the findings of this study provide practical implications to design comprehensive policies, revealing the positive effects of knowledge spillovers on economic growth.

Therefore, the purpose of this review article is to analyze the effects of the link between knowledge spillovers and economic growth. This analysis sheds light on the dynamics between knowledge spillovers and economic cycles to further identify strategic opportunities in changing business environments.

As a result of this research, this study presents two main contributions to the literature on knowledge transfer and economic cycle with both theoretical and practical implications. First, it provides a systematic overview of the relationship between knowledge spillover and economic growth by presenting underlying theory in this field. As a novelty, this study frames the positive and negative impacts of economic cycles on knowledge spillovers and the effects of favoring or hindering knowledge transfer on economic growth. This theoretical contribution is fundamental for developing proper public and private policies to leverage its outcomes, designing more effective spillover initiatives, and allocating innovation funds and investments. Second, this study analyzes the relationship between four variables related to economic cycles and knowledge spillover in the case of Germany, France, and Spain to exemplify the relationship between the areas under study.

Overall, this article constitutes a valuable tool for scholars, decision-makers, and professionals with an interest in innovation dynamics and economic sustainability by providing upgrades on the state-of-the-art and practical implications of the effects of economic growth and knowledge spillovers.

This paper is structured as follows: Section 2 provides a theoretical background for this study, while Section 3 elaborates on the methodology used for this review. Section 4 presents the relationship and effects of knowledge spillovers and economic growth identified from the literature review. In Section 5, the case studies of Germany, France, and Spain are explored by comparing the values of gross domestic product (GDP), gross domestic expenditure on R&D (GERD), the number of patent applications counted by filing office and applicant’s origin, and the total number of scientific publications. The data from 2000 to 2018 are examined to contrast the results from the review. Section 6 synthesizes and discusses the findings and prospects of harnessing knowledge spillovers for economic growth. Finally, Section 7 presents the conclusions and limitations of this study.

2. Theoretical Background

2.1. Knowledge Spillovers

Knowledge spillover refers to transferring, exchanging, and disseminating information, ideas, experience, and technology among individuals, academic institutions, research institutes, and organizations [10]. The main objective of this exchange is to utilize the accumulated knowledge and innovations developed in a specific area to apply them in other contexts, ultimately improving competitiveness and promoting innovation in a national economy [21].

Knowledge is transmitted through various channels and mechanisms, including R&D activities, collaborations between universities and industries, technology transfer, networks, and associations. These channels enable knowledge sharing generated in one place or sector to be applied in others, driving the creation of new products, services, processes, and business models [21]. This process is not limited to sharing information and knowledge. It also includes effectively adapting and applying that knowledge in new contexts. It has a positive impact on innovation, productivity, and economic efficiency by allowing organizations and individuals to access new ideas and approaches, learn from best practices, and collaborate to develop creative solutions to face financial and technological challenges [22,23].

Nevertheless, there are some obstacles hindering the spread of knowledge. These obstacles include differences in mindset between academia and industry, unequal expectations, and technological and cultural barriers [24]. Therefore, overcoming these challenges requires effective governance, active collaboration, and innovative strategies that foster the successful transfer of knowledge and technology among different stakeholders [25].

Knowledge spillover mechanisms involve the structures that enable and promote information and technology transmission between different economic actors. These mechanisms play a significant role in sustaining economic development and enhancing competitiveness in a national economy [7,10,14]. By facilitating the circulation and application of knowledge and technology, they create a conducive environment for innovation, entrepreneurship, and adaptability to economic and technological changes [7,21].

These mechanisms are essential for economic development and competitiveness, since they effectively disseminate knowledge from one scenario to another, encouraging innovation and adaptation to economic and technological changes. Collaboration between academia and industry is also a fundamental mechanism, as it enables the direct transfer of knowledge from the academic environment to practical application in industry [26,27].

2.2. Economic Growth

Economic growth is a multifaceted phenomenon that drives the progress and prosperity of nations. It has been studied in several academic fields and has profound implications for a country’s development. Many studies have supported its importance, exhibiting the key factors causing economic growth.

Efficiency in human resource management and productivity are among the essential factors for sustainable economic growth [28]. Effective management practices might act as a driving force for economic growth, leading to reduced poverty and increased employment opportunities [29].

Investing in human capital is another crucial pillar for economic development and social progress. Becker [30] stressed the importance of education and training for long-term economic growth. Moreover, innovation and technology play a significant role in influencing economic growth [31]. Bénabou and Tirole [32] found that innovation and incentives are relevant factors in promoting economic growth and development, as observed in a representative sample of countries.

Economic growth is also intrinsically linked to a country’s ability to adapt to technological changes and shifting consumer demands. Investment in education, R&D, and promoting a culture of continuous learning are factors driving the accumulation of knowledge [21].

From a macroeconomic standpoint, the relationship between economic growth and knowledge spillover can be defined from a resilience perspective. Countries that invest in generating knowledge through research and education tend to be better equipped to handle economic fluctuations and global challenges. Investing in the creation, transmission, and application of knowledge is a fundamental strategy for promoting innovation, increasing competitiveness, and achieving sustainable economic growth [33]. Therefore, to gain a better understanding of the relationship between knowledge spillover and the economic growth of nations, an analysis of the state of the art was conducted.

3. Methodology

This systematic review was conducted through PRISMA methodology [34] to tackle the research questions. A systematic literature review is defined as “a specific methodology that locates existing studies, selects and evaluates contributions, analyses and synthesizes data, and reports the evidence in such a way that allows reasonably clear conclusions to be reached about what is and is not known” [35] (p. 671). This research methodology emerged from medicine but has gained attention in managerial studies [36,37,38,39,40] and business research [41,42]. PRISMA methodology, in particular, uses a comprehensive guideline that sets high standards for a detailed and rigorous process, allowing for extensive data collection, reliability of the findings, and minimizing bias in the frame of qualitative research.

Figure 1 shows the workflow for selecting information from scientific articles from journals and conferences related to the following terms: knowledge, spillovers, and economic growth.

This review was carried out in three stages: (1) formulating the research questions, (2) delimitating the scope, and (3) creating a comprehensive search strategy to retrieve all relevant documents [34]. This search began by examining the key terms in the titles and abstracts of articles indexed to the specific scientific databases. Scientific documents published in the last fifteen years were analyzed from repositories and scientific databases such as SCOPUS, Web of Science, Science Direct, Taylor & Francis, and IEEE. Furthermore, each article was analyzed to identify its pertinence, coding the documents that fit the classification structure.

As depicted in Figure 1, from a total of 912 selected articles, 118 duplicates were removed, resulting in a set of 794 documents. The inclusion criteria were based on the articles’ ability to provide comprehensive answers to the research questions related to the relationship between knowledge spillovers and economic growth, its effects, and related factors. After further screening, 695 studies were excluded as they were unrelated to the research topic. Of the remaining 99 articles, 43 were dismissed as they met the exclusion criteria from the full-text review process. This excluding criteria were set as follows: (1) articles addressing the indirect effects of knowledge and knowledge spillover related to knowledge capital, the links with the price of highly important products such as oil, and related articles with the indirect effects of technology; and (2) articles focusing on the role of relational proximity, competitiveness and growth derived from entrepreneurship, and absorption capacity and effects of foreign direct investments (FDIs). Finally, 56 articles were selected for data extraction and review procedures to obtain the desired results. Thus, this systematic review was carried out, achieving a Cohen’s kappa coefficient of 0.8902, indicating “almost perfect agreement” between the observers [43]. The results of each stage of the review are published as a public dataset [44].

Table 1. Quality assessment questions for papers.

Quality Assessment Questions Answer	Answer
Does the paper describe the positive and negative effects on the countries’ economies due to the influence of knowledge spillovers?	(+1) Yes/(+0) No
Does the paper describe how the economic cycle impacts knowledge spillovers?	(+1) Yes/(+0) No
Does the paper describe how knowledge spillovers affect economic growth?	(+1) Yes/(+0) No
Is the paper published in a journal or conference indexed in SJR?	(+1) if it is ranked Q1, (+0.75) if it is ranked Q2, (+0.50) if it is ranked Q3, (+0.25) if it is ranked Q4, (+0.0) if it is not ranked

describes the quality questions applied as the criteria for evaluating the scientific articles.

The Reporting Items for Systematic Reviews and Meta-Analysis (

Table A1. The Reporting Items for Systematic Reviews and Meta-Analysis.

Section and Topic	Item #	Checklist Item	Location Where Item Is Reported
TITLE
Title	1	Identify the report as a systematic review.	1
ABSTRACT
Abstract	2	See the PRISMA 2020 for Abstracts checklist.	1
INTRODUCTION
Rationale	3	Describe the rationale for the review in the context of existing knowledge.	2
Objectives	4	Provide an explicit statement of the objective(s) or question(s) the review addresses.	2
METHODS
Eligibility criteria	5	Specify the inclusion and exclusion criteria for the review and how studies were grouped for the syntheses.	3
Information sources	6	Specify all databases, registers, websites, organizations, reference lists and other sources searched or consulted to identify studies. Specify the date when each source was last searched or consulted.	3
Search strategy	7	Present the full search strategies for all databases, registers and websites, including any filters and limits used.	3
Selection process	8	Specify the methods used to decide whether a study met the inclusion criteria of the review, including how many reviewers screened each record and each report retrieved, whether they worked independently, and if applicable, details of automation tools used in the process.	3
Data collection process	9	Specify the methods used to collect data from reports, including how many reviewers collected data from each report, whether they worked independently, any processes for obtaining or confirming data from study investigators, and if applicable, details of the automation tools used in the process.	3
Data items	10a	List and define all outcomes for which data were sought. Specify whether all results that were compatible with each outcome domain in each study were sought (e.g., for all measures, time points, analyses), and if not, the methods used to decide which results to collect.	2
	10b	List and define all other variables for which data were sought (e.g., participant and intervention characteristics, funding sources). Describe any assumptions made about any missing or unclear information.	3
Study risk of bias assessment	11	Specify the methods used to assess risk of bias in the included studies, including details of the tool(s) used, how many reviewers assessed each study and whether they worked independently, and if applicable, details of automation tools used in the process.	-
Effect measures	12	Specify for each outcome the effect measure(s) (e.g., risk ratio, mean difference) used in the synthesis or presentation of results.	-
Synthesis methods	13a	Describe the processes used to decide which studies were eligible for each synthesis (e.g., tabulating the study intervention characteristics and comparing against the planned groups for each synthesis (item #5)).	3
	13b	Describe any methods required to prepare the data for presentation or synthesis, such as handling of missing summary statistics, or data conversions.	3
	13c	Describe any methods used to tabulate or visually display results of individual studies and syntheses.	2
	13d	Describe any methods used to synthesize results and provide a rationale for the choice(s). If meta-analysis was performed, describe the model(s), method(s) to identify the presence and extent of statistical heterogeneity, and software package(s) used.	-
	13e	Describe any methods used to explore possible causes of heterogeneity among study results (e.g., subgroup analysis, meta-regression).	-
	13f	Describe any sensitivity analyses conducted to assess robustness of the synthesized results.	-
Reporting bias assessment	14	Describe any methods used to assess risk of bias due to missing results in a synthesis (arising from reporting biases).	-
Certainty assessment	15	Describe any methods used to assess certainty (or confidence) in the body of evidence for an outcome.	1
RESULTS
Study selection	16a	Describe the results of the search and selection process, from the number of records identified in the search to the number of studies included in the review, ideally using a flow diagram.	3
	16b	Cite studies that might appear to meet the inclusion criteria, but which were excluded, and explain why they were excluded.	3
Study characteristics	17	Cite each included study and present its characteristics.	3
Risk of bias in studies	18	Present assessments of risk of bias for each included study.	-
Results of individual studies	19	For all outcomes, present, for each study: (a) summary statistics for each group (where appropriate) and (b) an effect estimate and its precision (e.g., confidence/credible interval), ideally using structured tables or plots.	-
Results of syntheses	20a	For each synthesis, briefly summarize the characteristics and risk of bias among contributing studies.	-
	20b	Present results of all statistical syntheses conducted. If meta-analysis was conducted, present for each the summary estimate and its precision (e.g., confidence/credible interval) and measures of statistical heterogeneity. If comparing groups, describe the direction of the effect.	-
	20c	Present results of all investigations of possible causes of heterogeneity among study results.	-
	20d	Present results of all sensitivity analyses conducted to assess the robustness of the synthesized results.	-
Reporting biases	21	Present assessments of risk of bias due to missing results (arising from reporting biases) for each synthesis assessed.	-
Certainty of evidence	22	Present assessments of certainty (or confidence) in the body of evidence for each outcome assessed.	-
DISCUSSION
Discussion	23a	Provide a general interpretation of the results in the context of other evidence.	13
	23b	Discuss any limitations of the evidence included in the review.	13
	23c	Discuss any limitations of the review processes used.	-
	23d	Discuss implications of the results for practice, policy, and future research.	-
OTHER INFORMATION
Registration and protocol	24a	Provide registration information for the review, including register name and registration number, or state that the review was not registered.	2
	24b	Indicate where the review protocol can be accessed, or state that a protocol was not prepared.	2
	24c	Describe and explain any amendments to information provided at registration or in the protocol.	2,3
Support	25	Describe sources of financial or non-financial support for the review and the role of the funders or sponsors in the review.	15
Competing interests	26	Declare any competing interests of review authors.	15
Availability of data, code and other materials	27	Report which of the following are publicly available and where they can be found: template data collection forms; data extracted from included studies; data used for all analyses; analytic code; any other materials used in the review.	2

From: [34] Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71.

in Appendix A) were used to specify the page numbers where relevant information was found in the selected documents’ title, abstract, introduction, methods, results, discussion, and financing sections.

To enrich the results from this review, trends within economic growth are presented, relating them to the number of patent registrations corresponding to Germany, France, and Spain as exploratory case studies.

4. Results of Systematic Literature Review

4.1. VOSviewer^® Bibliometric Analysis

To analyze the literature review, VOSviewer^® was used to construct and visualize bibliometric networks [45]. Figure 2 depicts the five clusters identified within the reviewed documents.

These clusters show the close relationship between the flow of knowledge as a promoter of the economic growth of nations. First, a link between economic growth and R&D is identified. R&D is crucial in driving innovation and productivity and therefore plays a critical role in economic growth. By investing in R&D, companies can create knowledge and introduce innovations; investment has a positive impact through the creation of knowledge and the introduction of innovations, leading to positive effects. This investment might lead to significant improvements in productivity and competitiveness, which in turn contributes to overall economic growth [28,46].

The second cluster identified the connection between technological changes and entrepreneurship. Technological changes have a significant impact on entrepreneurship by creating new business opportunities and transforming existing models. The introduction of innovative products and services to the market through technology might stimulate the creation of new companies [47]. Likewise, adopting disruptive technologies might boost entrepreneurial activity by opening new market niches and generating competitive advantages for start-ups [48]. A third cluster is established between human capital and knowledge spillover. Human capital is a crucial factor in generating and disseminating knowledge within the economy. Highly skilled human capital is a significant driver in exchanging skills and experiences among individuals and organizations, thus becoming a key facilitator in knowledge flows [49]. Moreover, investing in human capital through education and training might enhance the capacity to absorb and apply knowledge, leading to innovation and economic growth [30].

The fourth cluster points to environmental policies in studies related to Europe and Japan. The implementation of environmental policies in Europe and Japan has proven to encourage innovation in sustainable technologies and cross-sector collaboration, leading to the flow of knowledge [50,51,52,53,54]. These policies promote the transfer of technology and knowledge between companies and sectors, contributing to the adoption of more environmentally friendly practices and fostering economic growth [46]. Additionally, effective communication within organizations might facilitate the dissemination of knowledge about sustainable environmental practices, promoting the adoption of eco-efficient measures [54].

Finally, the fifth cluster encompasses economic integration and knowledge spillovers. Economic integration promotes the exchange of knowledge and information between countries and regions. Economic integration enables knowledge transfer by reducing trade barriers and facilitating the mobility of people and resources between different markets [22]. Also, face-to-face communication in organizations might strengthen ties between companies from various countries, promoting the circulation of knowledge and experiences in a globalized context [55].

4.2. Effects of Economic Cycles on Knowledge Spillovers

Economic cycles might affect knowledge spillovers in several ways. On the one hand, during periods of economic growth, funding and resources available for R&D increase, conducting advances in knowledge and its spillovers [13,33,56]. On the other hand, during recessions, investments in R&D may decrease, thereby slowing down the flow of knowledge and technologies [57,58,59]. Additionally, economic uncertainty makes companies reluctant to share their body of knowledge with other actors, thus reducing knowledge spillover [7].

As the economy grows, nations and firms may expand their investment in R&D, having a positive impact on the transfer of new knowledge and technology. The increase in funding and resources available for R&D stimulates research efforts and knowledge dissemination through publications and university–industry collaboration, among others [2,25,60]. Furthermore, cooperation between universities and industries is essential to facilitate knowledge spillover. Formal partnership and informal knowledge transfer benefit companies, improving their innovative performance and closing technological gaps [61]. Universities play a significant role in transmitting knowledge and technologies through the creation of academic spin-off companies [62,63,64]. Their success depends on factors such as strategic entrepreneurial orientation and the effective management of local and internal resources [47,62,65].

The economic cycles have a significant impact on knowledge spillovers between academia and industry. Collaboration between university and industry, investment in R&D, and academic research approaches are necessary factors enabling positive effects of knowledge spillover on the economic development of a country [66]. However, it is necessary to adapt collaborative strategies according to regional and cultural conditions to achieve successful co-creation in the university–industry environment [57]. This collaboration is enhanced during the stage of economic growth since universities have access to a budget for the proposal of research projects. From these undertakings, new services and products are often generated jointly with academic linkage projects, benefiting stakeholders in regional systems [48].

The third mission of academia is to transfer knowledge and technologies to society to foster entrepreneurship and economic growth [18]. University specialization and interdisciplinarity play a significant role in triggering this collaboration, facilitating an understanding of complex problems and the development of industry-relevant skills [64,67]. However, as framed by [48,68], there are limitations to the university–industry collaboration and technology transfer, since the actors adjusted their actions for redistributing smaller economic resources. Furthermore, partnership between universities and industry is crucial for knowledge transfer, but differences in values and cognitive styles need to be overcome [26].

Economic cycles impact the spillover of knowledge and technologies between academia and industry and the generation of patents and inventions [69]. Patent generation often begins with the execution of R&D projects [68]. The budget allocated by governments for R&D and the number of patents are significant factors in labor productivity and economic growth. Nevertheless, it requires a long run to fully profit from these processes [54].

When the economic output grows, universities may access budget lines for developing academic projects, increasing the number of patent registrations [48]. This may even result in more complex patents, as economic resources can be leverage to improve innovation [70]. Hence, legislation in some countries, such as the United States and most European countries, promotes technology transfer and the generation of patents through incentives and initial financing [47]. However, the relationship between the economic cycle and the creation of patents and inventions is complex and involves various factors, including organizational practices, intellectual property, and partnership between several stakeholders [18,71,72].

Furthermore, universities hold support programs for entrepreneurship, but the success of these initiatives depends heavily on funding from the government and private entities. Without the seed capital destined to promote these ventures, it is challenging to create knowledge, gain experience, and transfer technology [62].

Figure 3 summarizes the effects of the stages of growth and decline in economic cycles on knowledge spillover, as identified from the literature. During the expansion of the economy, there is an increase in support, investment, and execution of projects. This may be attributed to the availability of budget lines for R&D initiatives during this stage of the cycle. In contrast, during a recession, there is a decrease in R&D activities due to uncertainties.

4.3. Effects of the Spillover of Knowledge on the Economic Growth of a Nation

In the same fashion that scholars have identified how economic cycles influence knowledge spillover, they also have discussed the effects of knowledge transference on economic growth. The economy of a nation is influenced by sharing and transferring knowledge [13,61,73,74]. Developing new knowledge and innovation is one of the critical factors with a high impact on economic growth. It can improve the productivity, sustainability, and competitiveness of organizations and countries [10]. In a world driven by information and technology, knowledge is a valuable asset that stimulates economic development and improves competitiveness in global markets. Therefore, knowledge and economic growth evidence a close interdependence that impacts the sustained progress of a nation. Furthermore, opportunities arise when new ideas and discoveries are shared to create advanced products and services and to streamline existing processes [33].

Table 2. Favorable effects of the spillover of knowledge on economic growth.

Favorable Effects	Reference
Stimulate innovation and entrepreneurship to create new products, services, and processes that drive economic growth.	[10,21,66]
Enhance the productivity and efficiency of the economy by promoting the adoption of best practices and optimize organizational resources.
Promote long-term competitiveness and economic development contributing to economic growth.
Facilitate access to new ideas, information, and experience, thus promoting the development and implementation of new technologies.	[33]
Develop a skilled workforce as people acquire new knowledge and capabilities to improve productivity.	[62,75]
Foster collaboration between different economic actors, such as universities, research institutions, companies, and entrepreneurs to join efforts for growth and development.	[21]
Enable companies to increase competitiveness through efficient practices and develop innovative products.	[10,33]
Stimulate the transfer of technology and the commercialization of academic knowledge, generating income and promoting local economic growth.	[76]
Generate spin-off firms promoting innovation, employment, and economic growth.	[62]
Promote collaboration between natural sciences and business schools to enhance innovation and develop advanced technologies in the industry, thus benefiting economic growth.	[18]
Patent citation analysis helps to understand the transmission of information and innovation between different entities, e.g., countries, laboratories, companies, and universities.	[68]
Technology transfer and innovation have a positive impact on the economic cycles and growth of a country.	[26,27]
Promote creative organizational learning to enhance knowledge management processes and, in turn, improve organizational performance.	[23]

outlines the references describing the relevant positive effects of the spillover of knowledge on the economic growth of a nation, understanding economic growth as expansions in indicators such as gross domestic product (GDP), gross national income, and R&D expenditure, among others [64,66,73].

In contrast,

Table 3. Hindering effects of limiting the spillover of knowledge on economic growth.

Hindering Effects	Reference
Economic inequality may increase due to unequal access to knowledge, resulting in disparities between technologically advanced companies and regions with limited access to information and knowledge.	[21]
Introducing advanced and more efficient technologies may initially result in job losses and economic instability in outdated fields.
Inadequate protection of intellectual property rights may trigger the unauthorized appropriation of knowledge and technologies, discouraging investment in R&D.	[77]
The concentration of knowledge among a select few economic players may result in the creation of monopolies or dominant market positions market, limiting competition and innovation.	[78]
Due to rapid technological obsolescence, inefficient investment in technologies that soon become outdated will negatively affect companies’ profitability and sustainability.	[26]
The dissemination of incorrect or inadequate information may lead to incorrect decisions about the implementation of new technologies or practices, resulting in economic losses.	[79]
Lack of collaboration and partnership among economic actors may hinder knowledge flow and synergies driving innovation and economic growth.	[10]
Establishing solid links between individuals may be challenging when there are divergences in ideas and expectations, making knowledge transfer difficult.	[22]
Distinguish knowledge between investment in academic research and its transfer to the market.	[56]
Combining formal and informal knowledge spillover channels increases technology management’s complexity and slows its economic benefits.	[60]
Delays in patent examinations may impact the return on the investment. Factors such as the technical complexity of the invention and the number of claims filed may influence the span of the process and slow profiting from the patent.	[67]
Technology clusters may not benefit from assumed knowledge spillovers, and the complexities of these spillovers may not be immediately apparent.	[80]

describes effects that, under certain conditions, may generate uncertainty and knowledge gaps that could become an advantage taken by opportunistic firms or sectors, leading to monopolies and hindering economic growth.

5. Case Studies: Knowledge Spillovers and Economic Cycles in Germany, France, and Spain

To complement the findings of the preceding sections, this section provides an exploratory analysis of the economic growth of Germany, France, and Spain. These countries are active members of the European Union (EU), which is recognized as the largest regional group with the highest level of economic integration [81]. Thus, these countries share similar policies and initiatives frameworks and use the Euro as the common currency [82]. Furthermore, Germany, France, and Spain are among the top 30 countries in the Global Innovation Index and with three or more top 100 science and technology clusters [83]. These countries have faced similar economic cycles of expiation and recession. This allows an initial comparative analysis of their national economies and innovative systems within a similar context.

This analysis compares GDP and GERD values (economic variables) with the number of patent applications and scientific publications (knowledge spillover variables). GDP measures the monetary value of merchandise and services manufactured by an economy in each period. It is a macroeconomic indicator broadly used to monitor the economic growth of a nation. Although it does not capture the full picture of the economic well-being of a country, a high GDP rate generally indicates a stronger economy and the potential for increased living standards [84,85]. GERD encompasses the domestic expenditure on R&D activities, including the systematic undertaking of creative work and the application of knowledge to raise knowledge stock and potentially influence innovation [66]. Total patent applications are a measure of the knowledge stock and innovative capacity of a nation [83]. In addition, previous studies shown a positive impact of the total number of patent on economic growth [86,87]. Accordingly, this variable is used as a reference for this analysis. Finally, scientific and technical journal articles are related to the transmission of knowledge among several entities and economic actors [73]. This indicator is used to measure innovation capability performance in a wide variety of contexts [75,83,88]. Although scientific and technical journal articles serve as valuable sources of knowledge transmission, they also have limitations related to access, bias, and complexity. It is essential to consider these factors when relying on journal articles for information or when assessing the broader impact of research in scientific and technical fields.

Data from 2000 to 2018 were collected and published as a Mendeley dataset [89], given the disruption at the end of 2019 due to the COVID-19 pandemic, modifying the dynamics of the economy with different impacts in the countries from that point in time.

Figure 4 depicts the evolution of economic cycles regarding the GDP annual rate growth of Germany, France, and Spain [90,91,92].

As shown in Figure 4, Spain experienced a slight decrease in its growth rate from 2001 to 2002, which was followed by consistent growth from 2003 to 2007. Germany showed a negative growth rate in 2002 and 2003, while from 2004, it recorded a positive albeit variable growth until 2007. In contrast, France reported a positive growth rate from 2000 to 2007.

In December of 2007, the economy of the United States of America entered the period known as the “Great Recession” that roughly lasted from 2007 to 2009 [93]. This phenomenon harmed these three European economies, particularly during 2008 and 2009. Germany experienced its lowest point in 2009 with a growth rate of −5.69%, whereas Spain and France recorded growth rates of −3.76% and −2.87%, respectively. The year after, Germany reported the highest recovery with a 4.18% growth rate, followed by France with 1.95%, while Spain’s rate was only 0.16%. Although Germany and France displayed a significant recovery in the following years, it took Spain longer to stabilize.

Figure 5 depicts the annual GDP value in current USD billion of Germany, France, and Spain from 2000 to 2018 [89].

The GDPs of Germany, France and Spain showed a general trend of economic growth between 2000 and 2018. Germany and France had significantly larger GDPs compared to Spain throughout this period. However, the financial crisis of 2007–2009 caused a decrease in the GDP of all three countries. Despite this setback, they managed to recover in the following years. In terms of stability, Germany exhibited sustained growth with smoother fluctuations compared to Spain and France. Spain showed greater volatility but achieved a solid recovery after the crisis. France maintains a constant expansion in general with some variations in its growth rate. Despite the differences, the three countries managed to maintain positive economic development trends.

Figure 6 presents the annual GERD in current USD millions of Germany, France, and Spain from 2000 to 2018 [89].

The expenditure on R&D activities is associated with the nation’s capacity to generate innovative and knowledge stock [14,94,95]. In the last two decades, most countries in the European Union have increased their R&D spending [94]. Germany has consistently increased its domestic R&D spending, while France and Spain have maintained stable expenditure levels. It is worth noting that France increased its R&D investment in 2009, while Germany and Spain slightly decreased their spending during the same period.

Figure 7 shows the total number of patent registrations in Germany, France, and Spain from 2000 to 2018 [89].

Tracking patent applications provides insight into potential innovation trends by identifying the trending technologies investigated by different countries [96] and knowledge spillover [72,97]. From Figure 8, the number of patent registrations in Germany remained constant during the first half of the period, which was followed by a decrease. Meanwhile, Spain and France have exhibited a trend of continuous growth in the number of patents, indicating their commitment to innovation. Although the total numbers of patents granted varies among these countries, the data suggest that they have implemented measures to promote and protect R&D+i activities. The sustained increase in registered patents in Spain and France may indicate a focus on R&D and a recognition of the importance of intellectual property, while Germany displayed a stable and declining trend. This contrast may be attributed to the different approaches and strategies toward innovation and intellectual property protection, which reflect the unique economic and research environment in each country.

Figure 8 shows the total scientific and technical journal articles published by Germany, France, and Spain from 2000 to 2018 [89].

Scientific publications point to effective knowledge transfer and the communication of scientific advancement achieved through collaborative research. This implies Germany’s commitment to collaborative R&D efforts and their spillover impact. Spain also displayed consistent growth with a slight decline in 2013 and 2015. Meanwhile, France raised its publications between 2000 and 2013 but experienced a decrease in publications since 2014.

Based on Figure 6, Figure 7, Figure 8 and Figure 9, Germany showed larger differences compared with France and Spain, particularly in the expenditure on R&D and the number of patents. This country had an increasing slope in its economic cycle between 2000 and 2008 with a significant value. Nevertheless, after 2008, the economic cycles remained constant with cyclical rises and falls. During the same period, Germany registered a high number of patents, which may be associated with this GDP slope from 2000 to 2008. From 2008 onwards, the number of patent registrations declined slightly, corresponding to an almost horizontal behavior of its economic cycle.

France increased the number of patent registrations between 2000 and 2008, which was similar to Germany. There was a considerable slope for the GDP value. However, after 2008, the economic cycle remained relatively stable with annual patent registrations remaining constant. In the case of Spain, there was a peak in patent registration in 2008, which corresponded to a period of high GDP. Prior to this peak, there was a slight increase in the number of patents in line with a slight increase in GDP. Following this peak, GDP increased while the number of patents decreased slightly.

This initial analysis of the trends between these variables points to an apparent correspondence between the increase in the number of patents and the growth of GDP values for the three countries. To explore this further, linear regression was performed to investigate the relationship between GDP—GERD, GDP—patent applications, GDP—scientific articles, GERD—patent applications, and GERD—scientific articles. GERD—scientific articles linear regression showed higher consistency among the three countries with the following results: (a) Germany: r2 = 0.86 (Figure 9a), (b) France: r2 = 0.79 (Figure 9b), and (c) Spain: r2 = 0.73 (Figure 9c). The regression analysis is available in the Mendeley dataset [89].

These results suggest a more extensive study to identify the behavior of economic and knowledge spillover variables and the relationship among them.

6. Discussion

The relationship between the economic cycle and the generation of knowledge and inventions is complex and multifaceted, involving organizational factors, intellectual property, and university–industry collaboration [18,72,98]. Studies have shown that countries with high knowledge spillover experience higher economic growth rates [21]. The transfer of knowledge and technology and collaboration between the academia and business sectors encourage innovation and technology development, increasing companies’ productivity and competitiveness in the market [18,20,21,33,48,99].

This collaboration endows R&D activities and the transfer of technology and information through policies encouraging cross-border partnership and knowledge spillover [95,100]. Instead of focusing primarily on short-term performance indicators, a systemic evaluation of formal and informal knowledge transfer activities is suggested to optimize assessing academic research. In this context, support organizations such as technology transfer offices are critical to manage and coordinate knowledge transmission activities [60,99]. Despite the economic benefits of technology transfer between universities and companies, it has been pointed out that the expansion of patenting in scientific research may create obstacles to the advancement of fundamental research [101].

The economy is constantly evolving with traditional and emerging sectors changing in balance. This has resulted in a shift in the sectoral structure of the economy toward the growth of high-tech industries as a sign of the economy’s transformation. In addition, analyzing and evaluating innovation transmission have become particularly relevant. Thus, it is necessary to develop a system of indicators for accurately assessing knowledge diffusion at different regional levels [4].

Knowledge is crucial for generating industrialized economies. The extent of knowledge spillover in economic growth depends on the ability of developed countries to absorb and apply the knowledge gained from highly industrialized countries. Knowledge transmitted from highly industrialized nations, such as OECD and G7 members, is considered a key determinant of productivity growth for developing economies. FDI and imports are potential channels for transferring knowledge from these highly industrialized countries to developing countries [102]. However, it requires a minimal absorptive capacity to acquire knowledge from technologically intensive imports or FDI [20].

Regarding endogenous growth theory, policies aimed at promoting innovation may lead to economic growth in the long run [103]. Governments often try to increase the stock of knowledge and spillovers through R&D subsidies. The EU has launched initiatives to encourage R&D investment and collaboration among research teams from different countries and disciplines. Government policies are expected to support R&D investment and international cooperation, as knowledge spillover is a significant factor in economic growth [96,100].

By harnessing tools such as patent analysis and the early identification of emerging technologies, companies and governments may make informed decisions about R&D investment, catalyzing a positive impact on the economic growth of their nations [96,104]. Knowledge spillover between universities and industry contributes to economic growth by boosting innovation and generating new technologies and products. However, “knowledge filters” (e.g., illogical government regulations and bureaucratic red tape) hinder the commercialization of innovations and their impact on the market [69].

Economic cycles significantly impact knowledge spillover. During an economic upswing, financing and resources for R&D increase, leading to a surge in academic knowledge generation. In contrast, during a recession, companies and countries often decrease their R&D investments, resulting in a reduction in the spillover of new knowledge and technologies [57,58]. Additionally, economic uncertainty may restrict companies’ willingness to share knowledge and technology with other players, thereby reducing the flow of knowledge [7].

The formal and informal spillover of knowledge benefits firms, improving their innovative performance and closing technology gaps [61,62]. However, this collaboration is also affected by economic cycles. When the economy expands, investment in R&D efforts increases, stimulating the transmission of knowledge through scientific publications and collaborative programs in R&D. However, limitations were identified in technology transfer between these two actors, especially in times of resource redistribution [68].

Some critical linkages were found from the comparative analysis of economic growth trends, R&D expenditure, the number of patent registrations, and scientific articles between Germany, France, and Spain from 2000 to 2018. We found a positive relationship between the number of scientific publications and the evolution of GERD. Patent applications provide a relevant overview of innovation. Whereas Germany has remained stable in its number of patents and has increased its journal publications, Spain and France have shown constant patent registration growth, indicating their continued commitment to promoting innovation and protecting intellectual property [105,106,107]. This relationship between economic growth and innovation highlights the importance of R&D investment in maintaining a favorable innovative and economic environment [105,106,108].

Challenges and risks associated with the spillover of unregulated knowledge have been evidenced as well as challenges related to technological obsolescence, R&D efforts, investment, and lack of collaboration. When knowledge is concentrated in a small group of economic actors, monopolies and dominant positions in the market may arise [78]. Nevertheless, an inadequate protection of intellectual property rights may lead to the unauthorized appropriation of knowledge and technologies [77], reducing the interest in promoting R&D investment. Additionally, knowledge spillovers in technology clusters may be more complex than assumed, making it difficult to identify the real benefits [80,109]. The challenge for developing countries lies in absorbing and applying knowledge acquired from industrialized nations. Knowledge transmitted from highly industrialized countries is an important driver of productivity growth in developing economies [20].

Understanding the relationship between knowledge and economic growth is crucial for developing practical strategies. Investment in education, R&D, and promoting a continuous learning culture are vital strategies for accumulating knowledge [20]. Academic entrepreneurship and start-ups are fundamental forms of knowledge spillover [2,7,110]. Interdependent factors influence knowledge-based entrepreneurship at the national, regional, and industry levels [15,111]. International collaboration for joint-patent investigation, such as German initiatives, can be particularly effective when choosing suitable university partners [67]. Another strategy to consider is initiatives to strengthen the development of patents and start-ups between industry and universities, where researchers and institutions benefit [62,112]. Implementing academic spin-off programs, such as the Knowledge Intensive Business Services from Spain, positively impacts regional innovation systems and economic growth [63].

Finally, government policies promote innovation through R&D investments, supporting endogenous growth theory [103,113]. Hence, it is also critical for the interaction and participation of industry, academia, and government to develop proper policies for enhancing a nation’s innovation system and define appropriate metrics to assess the success of knowledge spillover activities and their impact on economic growth [26]. Countries investing in knowledge generation are more resilient to economic fluctuations and are better prepared to face global challenges [32].

7. Conclusions and Limitations

Through this review, we found that the literature broadly agrees on the key role of knowledge spillovers in dynamizing national economies. We also provide a framework for leveraging the relationship between knowledge spillovers and economic growth. Sharing knowledge is fundamental for economic development, as it facilitates the transfer of information and technology between various economic actors of a nation or region. The review also found that a significant portion of knowledge spillover is carried out by university–industry collaboration, which includes joint patenting, technological development, and spin-offs. Collaboration between these actors, such as universities, research institutions, and companies, is necessary to catalyze innovation and prompt economic growth. However, there are obstacles to commercializing university innovations, and they need to be identified and characterized to propose further solutions. Therefore, it is necessary to put in place a policy and infrastructure framework that benefits researchers, institutions, and other stakeholders to stimulate the development of new knowledge. The role of government in generating such a framework is vital to enable the implementation of incentives for R&D investments leading to employment generation and economic growth.

Although this study conducted extensive research, it has some limitations. The primary perspective of this work was from a national standpoint, particularly from developed countries. The impact of knowledge spillover on economic growth depends on several factors such as the quality and the quantity of patents and scientific articles, the number of start-ups, cluster integration, and geographical proximity, among others. We limited this analysis to GDP, GERD, total patents, and scientific and technical journal articles (identified from the literature review) as the studied variables for comparative and exploratory purposes within the context of three EU countries. However, countries with higher GERD, like Israel and Korea, or a larger total number of patents such as China, Japan, and the United States were excluded, which may affect the generalization of the findings. Therefore, a regional study contrasting various integration groups with different levels of economic integration may provide a more comprehensive view, including a regional perspective on the matter under study. Additionally, it is essential to identify the dynamics of the relationship between knowledge spillovers and economic growth from the standpoint of developing countries and compare the effectiveness of strategies applied in different economic contexts. Other economic and spillover knowledge variables should also be explored, including the analysis of the quality of patents and scientific and technical journal articles. Likewise, natural events or disruptions, such as earthquakes, floods, or economic crises, should be investigated. Thus, it is necessary to delve deeper into the linkages between the economic and knowledge variables to understand the relationship between knowledge spillovers and economic cycles.

Future studies may be conducted in further research fields to deepen the findings of this study. Exploring the applications and scope of innovative digital ventures and the business ecosystem is crucial to fostering the spillover of knowledge and digital entrepreneurship. One aspect demanding in-depth research is the impact of new technologies on the growth of innovative digital start-ups and the requirement of digital skills for the labor force. Additionally, it is necessary to examine the political measures needed to equip the labor market with the digital skills required to promote the creation and growth of these start-ups. It is also important to further research the interdependent national, regional, and industry factors influencing knowledge-based entrepreneurship to foster entrepreneurship.

Finally, an in-depth and comparative examination of the linkages between the variables related to economic cycles and knowledge spillover is necessary to understand their relationship and develop effective policies to foster national innovative systems. In addition, the relationship between the ability to absorb knowledge from foreign countries and domestic spending on R&D should be studied.