How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review

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Objective This article aims to analyze the metrics proposed in the literature for evaluating entrepreneurship ecosystems. Methods The PRISMA protocol was followed, enabling a systematic and transparent review. A total of 288 records were obtained from the Scopus and Web of Science databases, and after a thorough screening and detailed content review, a final selection of 39 relevant articles was made. Results The main findings identified key thematic lines related to regional entrepreneurship development, the measurement of global entrepreneurship, networks, benchmarking of entrepreneurial ecosystem policies, and metrics on the economic impact of entrepreneurship. The following main methodologies for measuring these ecosystems were identified: composite indices, network analysis, multicriteria analysis, qualitative methods, and mixed-method approaches. Finally, it is proposed that the five categories of metrics most used to measure the performance of entrepreneurship ecosystems are: outcome metrics, ecosystem condition metrics, composite indices, subjective and perception-based metrics, and other metrics. Conclusions This review provides a useful conceptual foundation for decision-makers, serving as rigorous input for future research and the design of public entrepreneurship policies. 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F1000Research 2025, 14 :1307 ( https://doi.org/10.12688/f1000research.172389.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Systematic Review How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review [version 1; peer review: 1 approved with reservations, 2 not approved] Rodrigo Chaves-Ladino https://orcid.org/0000-0001-7103-8696 1 , Claudia Nelcy Jiménez-Hernández https://orcid.org/0000-0002-3097-6624 2 Rodrigo Chaves-Ladino https://orcid.org/0000-0001-7103-8696 1 , Claudia Nelcy Jiménez-Hernández https://orcid.org/0000-0002-3097-6624 2 PUBLISHED 25 Nov 2025 Author details Author details 1 Faculty of Economic Sciences, Universidad Nacional de Colombia, Bogotá, Colombia 2 Faculty of Agricultural Sciences, Universidad Nacional de Colombia, Bogotá, Colombia Rodrigo Chaves-Ladino Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Visualization, Writing – Original Draft Preparation Claudia Nelcy Jiménez-Hernández Roles: Data Curation, Methodology, Project Administration, Supervision, Validation, Visualization, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS Abstract Background Entrepreneurial ecosystems are becoming increasingly relevant due to their crucial role in boosting economies through business development, although this concept and the measurement of its performance are still subjects of academic debate. Objective This article aims to analyze the metrics proposed in the literature for evaluating entrepreneurship ecosystems. Methods The PRISMA protocol was followed, enabling a systematic and transparent review. A total of 288 records were obtained from the Scopus and Web of Science databases, and after a thorough screening and detailed content review, a final selection of 39 relevant articles was made. Results The main findings identified key thematic lines related to regional entrepreneurship development, the measurement of global entrepreneurship, networks, benchmarking of entrepreneurial ecosystem policies, and metrics on the economic impact of entrepreneurship. The following main methodologies for measuring these ecosystems were identified: composite indices, network analysis, multicriteria analysis, qualitative methods, and mixed-method approaches. Finally, it is proposed that the five categories of metrics most used to measure the performance of entrepreneurship ecosystems are: outcome metrics, ecosystem condition metrics, composite indices, subjective and perception-based metrics, and other metrics. Conclusions This review provides a useful conceptual foundation for decision-makers, serving as rigorous input for future research and the design of public entrepreneurship policies. READ ALL READ LESS Keywords Performance, entrepreneur, entrepreneurship, metrics, entrepreneurial ecosystems Corresponding Author(s) Rodrigo Chaves-Ladino ( [email protected] ) Close Corresponding author: Rodrigo Chaves-Ladino Competing interests: No competing interests were disclosed. Grant information: This research was funded by the “Convocatoria para la Formación de Capital Humano de Alto Nivel para los Departamentos de Amazonas, Arauca, Boyacá, Caquetá, Casanare, Guaviare, Nariño, Putumayo, San Andrés y Vichada”, under the framework of Convocatoria 15 del Sistema General de Regalías (SGR), for the development of doctoral studies. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2025 Chaves-Ladino R and Jiménez-Hernández CN. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Chaves-Ladino R and Jiménez-Hernández CN. How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review [version 1; peer review: 1 approved with reservations, 2 not approved] . F1000Research 2025, 14 :1307 ( https://doi.org/10.12688/f1000research.172389.1 ) First published: 25 Nov 2025, 14 :1307 ( https://doi.org/10.12688/f1000research.172389.1 ) Latest published: 25 Nov 2025, 14 :1307 ( https://doi.org/10.12688/f1000research.172389.1 ) Introduction The concept of entrepreneurial ecosystems (EEs) has emerged in response to the need to give greater prominence to the entrepreneur, complementing earlier studies on the clustering of economic activity and socio-territorial entities ( Maroufkhani et al., 2018 ). This concept differs from other approaches in that the entrepreneur is considered the fundamental unit, rather than the firm, as previously assumed, underscoring the importance of the social and economic context in which entrepreneurship is embedded, as well as the policy agenda that promotes entrepreneurial processes ( De Brito & Leitão, 2021 ; Maroufkhani et al., 2018 ; Mukiza et al., 2020 ). By placing the entrepreneur at the center, the role of other actors shifts—for instance, the role of government changes from being a leader and coordinator to that of a guarantor of a favorable socioeconomic environment for sustainable entrepreneurial activities. With regard to the environment, Alam and Bhowmick (2023) emphasize that a genuinely entrepreneurial context emerges through the everyday interaction of society and entrepreneurial activities over time—for example, successful entrepreneurs can act as mentors and role models for emerging and growing entrepreneurs ( Mukiza et al., 2020 ). For this reason, several authors ( Isenberg, 2010 ; Meshram & Rawani, 2018 ; Qian, 2018 ) view EEs as evolutionary entities that develop in different ways depending on their context, meaning no two EEs are alike. Research on entrepreneurial ecosystems remains scarce and fragmented ( Guimarães et al., 2023 ; Meshram & Rawani, 2018 ; Ribeiro et al., 2024 ), and there is still no generalized consensus on what constitutes an entrepreneurial ecosystem, the challenges of its conceptualization, or its research agenda ( Carayannis et al., 2022 ; Fernandes & Ferreira, 2022 ; Mukiza et al., 2020 ). Entrepreneurial ecosystems have emerged as a key conceptual framework for understanding the dynamics that facilitate the emergence, development, and consolidation of new ventures within a given territory ( Stam, 2015 ). This approach acknowledges that the success of entrepreneurial initiatives depends not only on the individual characteristics of entrepreneurs, but also on the interaction among multiple actors and institutions that constitute the environment in which they operate ( Spigel, 2017 ). Despite growing academic and policy interest in strengthening these ecosystems, a fundamental challenge persists: the lack of consensus on how to objectively and comparably measure their performance ( Corrente et al., 2019 ; Huang-Saad et al., 2017 ). The development of metrics to assess the performance of entrepreneurial ecosystems is crucial for several reasons: (1) it enables the identification of factors that contribute to value generation within the ecosystem and how these influence entrepreneurial activity ( Corrente et al., 2019 ); (2) it supports decision-making by policymakers, investors, and other stakeholders interested in designing intervention strategies to foster more dynamic and sustainable ecosystems ( Leendertse et al., 2022 ); and (3) it provides an empirical basis for comparing different ecosystems at regional, national, and international levels, thereby advancing the understanding of their functioning and evolution ( Acs et al., 2017 ; Lafuente et al., 2022 ). Given the heterogeneity of approaches and the lack of a clear consensus on such metrics ( Guimarães et al., 2023 ; Meshram & Rawani, 2018 ), this research proposes a systematic literature review aimed at identifying and analyzing existing metrics related to the performance of entrepreneurial ecosystems. This study focuses on general-purpose EEs applicable in diverse contexts, a delimitation that enables the analysis to concentrate on indicators that reflect the functioning of ecosystems based on entrepreneurial, institutional, and governmental interactions within a specific territory. To ensure the coherence and relevance of the analysis, digital and university entrepreneurial ecosystems were excluded due to their characteristics, which significantly differentiate them from traditional and territorially rooted entrepreneurial ecosystems. In the former case, digital ecosystems exhibit distinct dynamics characterized by globalization, digital scalability, and the predominance of technological platforms as core elements of their operation ( Bejjani et al., 2023 ). As such, digital ecosystems are not strictly dependent on a specific geographic context but operate in virtual environments and are often based on transnational networks ( Bejjani et al., 2023 ; Pigola et al., 2024 ; Wibisono, 2023 ). The metrics used to evaluate them typically focus on factors such as user traction, technological scalability, and digital venture capital investment, which do not necessarily reflect the performance of more territorially grounded entrepreneurial ecosystems ( Bejjani et al., 2023 ; Pigola et al., 2024 ; Wibisono, 2023 ). On the other hand, university-based entrepreneurial ecosystems are closely tied to academic institutions, research centers, and incubation programs managed by universities. Their development and performance are measured using specific indicators, such as the number of university spin-offs and patents generated, the research funds obtained, and the levels of technology transfer. These metrics follow an institutional logic that is not representative of broader entrepreneurial ecosystems not exclusively linked to the academic sphere ( Ayala-Gaytán et al., 2024 ; Kobylińska & Lavios, 2020 ; Wang et al., 2024 ). Based on this review, the aim is to offer a structured synthesis of the main indicators used to evaluate EEs. In doing so, the study seeks to contribute to the development of more robust analytical frameworks and to the generation of knowledge that is useful to researchers, policymakers, and other stakeholders interested in measuring and improving entrepreneurial ecosystems. Methods This systematic literature review was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology ( Page et al., 2021 ). Information sources The literature search was carried out using the Scopus and Web of Science (WOS) databases, due to their recognition as leading sources for indexing high-quality scientific publications. Both databases offer broad and multidisciplinary coverage, ensuring access to relevant and up-to-date research across various academic fields; moreover, they provide robust tools for bibliometric analysis, such as impact indicators, citation metrics, and tracking of research trends. Their ability to filter documents according to rigorous quality criteria and their advanced search functionalities enable the identification of studies that meet the methodological standards required for a reliable and replicable systematic review. Therefore, these databases ensure the inclusion of high-impact scientific literature, thereby strengthening the validity and relevance of the findings obtained. Selection of keywords for the systematic literature review To structure the search equations, a keyword adherence test was conducted. According to Ruthes and da Silva (2015) this strategy is used to assess the relevance of the keywords employed in the research and to quantitatively evaluate the pertinence of each term, the objective being to eliminate nonadherent keywords—that is, those that are not representative of the research area. Accordingly, to identify combinations that generate a greater number of relevant results in scientific databases, a comparison was made between the terms “entrepreneurial ecosystem” and “entrepreneurship ecosystem,” which revealed that the former is more commonly used in the academic literature, suggesting that it is preferred as the standard term within the discipline ( Table 1 ). Table 1. Keyword adherence test for the structuring of search equations. Keywords groups Number of results obtained per database Group 1 Group 2 Scopus Web of science Entrepreneurial ecosystem Index 9,183 82 Indicator 3,171 78 Metrics 1,003 21 Performance 10,688 479 Entrepreneurship ecosystem Index 2,667 22 Indicator 883 22 Metrics 320 4 Performance 3,003 89 In addition, several complementary terms were evaluated within the second group of keywords—specifically “index,” “indicator,” “metrics,” and “performance”—as these concepts are directly related to the performance of entrepreneurial ecosystems. The results showed that the combination of “entrepreneurial ecosystem” with these terms yielded a greater number of indexed articles in both Scopus and Web of Science (WOS), compared to “entrepreneurship ecosystem.” Therefore, to ensure a robust search framework aligned with research trends in the field, the combination of “entrepreneurial ecosystems” with the terms “index,” “indicator,” “metrics,” and “performance” was used. This decision optimizes the retrieval of relevant literature while maintaining the methodological rigor of the study. The search process for relevant publications was carried out without restrictions regarding the year of publication in order to include the largest possible number of documents collected up to January 25, 2025. However, only open-access and full-text articles were considered, with abstracts and conference papers being excluded. Table 2 presents the search equations used in each of the consulted databases. Table 2. Search equations and number of results obtained. Database Search equations Documents found Search date Scopus (TITLE ( (“entrepreneurial ecosystem*”)) AND TITLE-ABS-KEY ((index OR performance OR metric* OR indicator*))) AND (LIMIT-TO (OA, “all”)) 155 January 25, 2025 Web of Science Entrepreneurial ecosystem* (Title) and index OR performance OR metric* OR indicator* (Topic) 133 January 25, 2025 Eligibility criteria The inclusion criteria for this review were as follows: (1) the article develops or proposes metrics for the performance of entrepreneurial ecosystems; and (2) articles written in English with full-text availability. Studies were excluded if: (1) they focused on metrics related to digital or university-based entrepreneurial ecosystems, as these are not aligned with the objective of the present research; or (2) they were literature review articles, since this study seeks to directly analyze articles that propose or adapt metrics. Data extraction Records from the Scopus and WOS databases were downloaded in RIS (Research Information Systems) format and then uploaded into the Rayyan software for duplicate removal and the selection of relevant documents based on title and abstract. Data processing The following information was extracted from the included articles: title, author name(s), year of publication, article objective, and the list of proposed or used metrics. This information was used to compile a RIS file containing the final set of documents, which was then uploaded into the VosViewer software to perform a cluster analysis based on the co-occurrence of keywords. Results The results of the process for selecting relevant literature are presented in Figure 1 . Figure 1. Stages of the PRISMA systematic review process. Legend: This figure illustrates the sequential stages of the PRISMA protocol applied in the study, including identification, screening, eligibility, and inclusion of the final set of articles used to analyze the metrics for entrepreneurial ecosystems. Source: Authors’ elaboration. Figure 2 shows the distribution of publications selected for this literature review over the years. Although publications on metrics in entrepreneurial ecosystems are still limited in number, there has been a modest increase, with 2022 being the year with the highest number of publications on the topic. It is also worth noting that the topic has only begun to develop over the past ten years. Figure 2. Publications per year on entrepreneurial ecosystem metrics. Legend: This figure shows the temporal distribution of the selected publications, evidencing an increasing research trend over the last decade and identifying 2022 as the year with the highest number of studies on ecosystem performance metrics. Source: Authors’ elaboration. Concept of entrepreneurial ecosystem Most of the articles that formed the corpus for this research were based on the definitions provided by Acs et al. (2017) , Spigel (2017) and Stam and Van de Ven (2021) . A common feature across multiple definitions is the existence of interrelated actors (including entrepreneurs, institutions, and organizations) that interact within a specific environment to facilitate the emergence and development of productive ventures. Similarly, entrepreneurial ecosystems are characterized by interactive dynamics, in which institutional, social, and economic aspects influence the entrepreneurial capacity of a given territory ( Acs et al., 2017 ; Audretsch & Belitski, 2017 ). Accordingly, it can be affirmed that there is a consensus in recognizing these ecosystems as interdependent sets of actors, factors, and coordinated processes that support entrepreneurial activity. However, there are differences in the specific components included in each definition. Some authors emphasize elements such as leadership, entrepreneurial culture, capital markets, and receptive customers as being essential for the effective functioning of an EE ( Andrews et al., 2022 ; Cowell et al., 2018 ; Kansheba et al., 2023 ; Komlósi et al., 2024 ), while other studies focus on more simplified aspects, such as the presence of skilled individuals, business opportunities, and available resources ( Fomishyna et al., 2023 ; Kshetri, 2014 ; Shen et al., 2023 ; Zhang et al., 2024 ). From another perspective, Sternberg et al. (2019) emphasize that an EE comprises actors, organizations, and factors that specifically enable productive entrepreneurship within a given territory. Furthermore, authors such as Stam and Van de Ven (2021) argue that the EE concept has evolved beyond earlier notions such as industrial clusters, broadening the scope of relevant actors to include intermediaries and political institutions. While most definitions align in identifying interdependent elements that benefit entrepreneurial dynamics, they differ in the breadth and specificity with which they address factors such as leadership, culture, types of entrepreneurships, and the complexity of actor interactions. Key thematic areas Figure 3 , which was generated using VosViewer software, illustrates the relationships between key terms that co-occur across the analyzed document set. The colors identify groups or clusters of terms that tend to be thematically related. • Cluster 1 (Red): Regional Development of Entrepreneurship Figure 3. Keyword co-occurrence network of entrepreneurial ecosystem metrics. Legend: The figure displays a network map generated in VosViewer based on co-occurrence analysis of keywords from Scopus and Web of Science. Clusters represent thematic areas of research—such as regional development, global measurement, and policy analysis—indicated by different colors. Source: Analysis based on data from Scopus and Web of Science processed in Rayyan and VosViewer. Search date: January 25, 2025. This cluster groups terms related to access to financial, human, and social capital in the context of entrepreneurship and its impact on regional development. The inclusion of terms such as “regional development” and “regional planning” suggests a focus on the territorial planning of entrepreneurship, highlighting the importance of public policies and infrastructure in strengthening the ecosystem ( González-Serrano et al., 2021 ; Sternberg et al., 2019 ; Szerb et al., 2019 ). The presence of the keyword fsQCA (Fuzzy-set Qualitative Comparative Analysis) indicates the use of comparative methodologies to analyze the factors that determine the success of entrepreneurial ecosystems, recognizing them as complex systems requiring both qualitative and quantitative approaches. fsQCA is useful for studying EEs because multiple factors interact nonlinearly and may lead to different pathways to ecosystem success or failure ( González-Serrano et al., 2021 ; Komlósi et al., 2022 ; Zhang et al., 2024 ). In the reviewed literature, studies such as those by Komlósi et al. (2024) and Szerb et al. (2019) emphasize the importance of financing and regional policies in enhancing the competitiveness of entrepreneurial ecosystems in Europe. • Cluster 2 (Green): Global Measurement of Entrepreneurship This cluster groups studies focused on measuring entrepreneurial ecosystems at a global level, with emphasis on the relationship between innovation, social networks, and startups. The presence of the term “Global Entrepreneurship Monitor” (GEM) indicates the use of international indicators to assess the quality of entrepreneurship across different countries. The combination with the term “social media” reflects a focus on digital platforms as facilitators of visibility, funding, and growth for new ventures. Studies such as those by Kshetri (2014) , Sitaridis & Kitsios (2020) and Yan and Guan (2019) highlight the role of the GEM as a key tool for analyzing the dynamics of entrepreneurial ecosystems and their impact on the economy. Similarly, Kshetri (2014) and Sitaridis and Kitsios (2020) emphasize the influence of innovation and digital connectivity on the performance of startups, showing that more developed ecosystems exhibit strong interactions among entrepreneurs, investors, and support networks. • Cluster 3 (Blue): Networks, Policies, and Regional Dynamics of Entrepreneurship This grouping of terms focuses on the role of collaborative networks and public policies in shaping and influencing the performance of entrepreneurial ecosystems. The presence of the keywords “networks” and “policy” reflects researchers’ interest in explaining how interactions among entrepreneurs, governments, and organizations impact entrepreneurial activity in different regions ( Auerswald & Dani, 2017 ; Iacobucci & Perugini, 2021 ; Rocha et al., 2022 ). Studies by González-Serrano et al. (2021) and Sternberg et al. (2019) underscore the importance of networks as facilitators of knowledge, investment, and resource flows within the ecosystem. On the other hand, Sitaridis and Kitsios (2020) argue that public policies play a critical role in fostering dynamic entrepreneurial environments, noting that poorly designed incentives can hinder business growth rather than support it. • Cluster 4 (Yellow): Benchmarking and Policy Analysis of Entrepreneurial Ecosystems This cluster focuses on the comparative evaluation of entrepreneurial ecosystems through benchmarking and systems analysis. Its main objective is to measure and compare the impact of public policies on entrepreneurial development, identifying best practices at national and regional levels Balawi and Ayoub (2022) and Stam and Van de Ven (2021) . The study by Balawi and Ayoub (2022) proposes a methodology for assessing the effectiveness of entrepreneurial ecosystems using a systems-based approach, highlighting benchmarking as a powerful tool for identifying strengths and weaknesses across Nordic countries. • Cluster 5 (Purple): Metrics on the Economic Impact of Entrepreneurship This cluster centers on measuring the economic impact of entrepreneurial ecosystems, including financial, market, and business growth metrics. The combination of the terms “economics” and “metrics” indicates that these studies analyze how entrepreneurship contributes to economic development through quantifiable indicators. Research by Leendertse et al. (2022) , for example, has developed models to evaluate EE performance in terms of job creation, R&D investment, and GDP growth. Similarly, Balawi and Ayoub (2022) propose the Global Entrepreneurship Index as a key metric for comparing the quality of entrepreneurial ecosystems internationally, emphasizing the importance of factors such as access to finance, education, and digital infrastructure in business success. Discussion Methodologies for measuring entrepreneurial ecosystems Several methodologies have been employed to measure entrepreneurial ecosystems, using both quantitative and qualitative approaches ( Sternberg et al., 2019 ), and these methodologies are aimed at capturing the complexity of ecosystems and their impact on entrepreneurship ( Rocha et al., 2022 ). For instance, composite indexes use various variables and methods to evaluate entrepreneurial ecosystems, often drawing from multiple data sources to generate a single index ( Corrente et al., 2019 ), and some of these indexes also incorporate data on the quality of entrepreneurs ( Andrews et al., 2022 ). Composite indexes A significant portion of the studies analyzed in this review employed the Global Entrepreneurship Index (GEI) (e.g., Balawi & Ayoub, 2022 ; Calispa-Aguilar, 2021 ; Lafuente et al., 2022 ), which considers both individual and institutional aspects of entrepreneurship in assessing the state of an entrepreneurial ecosystem within a given country ( Balawi & Ayoub, 2022 ; Calispa-Aguilar, 2021 ). The GEI relies on expert surveys and national statistics to measure entrepreneurial attitudes, skills, aspirations, and contextual conditions ( Calispa-Aguilar, 2021 ; Sitaridis & Kitsios, 2020 ); however, composite indexes are often criticized for oversimplifying ecosystem complexity, difficulties in variable selection and weighting, and their limited guidance on how to improve specific ecosystem components ( Corrente et al., 2019 ; Rocha et al., 2022 ). Network analysis Another increasingly adopted approach is network analysis, which uses social network metrics to analyze the relationships and structure of entrepreneurial ecosystems in order to quantify structural elements ( Ancona et al., 2023 ). Network analysis enables the evaluation of strength and collaboration among actors and is argued to be a more suitable method for capturing the complexity of entrepreneurial ecosystems than traditional metrics ( Auerswald & Dani, 2017 ; Huang-Saad et al., 2017 ). Multicriteria analysis This method is used to compare entrepreneurial ecosystems while considering the variability of weights that can be assigned to different factors, producing a more reliable probabilistic ranking than single-score classifications. For example, stochastic multicriteria acceptability analysis (SMAA) is a derived methodology that identifies relationships between ecosystem factors and growth-oriented startups ( Corrente et al., 2019 ). Nonparametric methods such as the “benefit of the doubt” approach have also been applied to assess the relative efficiency of entrepreneurial ecosystems and determine which components should be prioritized for improvement ( Lafuente et al., 2022 ). Qualitative methods These studies provide detailed descriptions of specific entrepreneurial ecosystems and enable a deep understanding of ecosystem dynamics. Qualitative methods may include interviews with key actors and document analysis ( Stam & Van de Ven, 2021 ). Qualitative comparative analysis (QCA) explores combinations of factors leading to a specific outcome and can uncover the causal complexity of these phenomena ( Komlósi et al., 2024 ; Zhang et al., 2024 ). Mixed methods The combination of quantitative and qualitative methods can offer a more comprehensive understanding of entrepreneurial ecosystems ( Sternberg et al., 2019 ). This approach allows quantitative data to measure outcomes and qualitative data to uncover the underlying processes ( Cowell et al., 2018 ). Several authors ( Aliabadi et al., 2022 ; Corrente et al., 2019 ; Sternberg et al., 2019 ) argue that measuring entrepreneurial ecosystems requires a mix of methods to capture the complexity of these systems, although the choice of methodology depends on the specific goals of the research. Metrics for evaluating entrepreneurial ecosystems No single metric is capable of fully capturing the complexity of an entrepreneurial ecosystem ( La Rovere et al., 2021 ; Rocha et al., 2022 ). The metrics used to evaluate ecosystem performance identified in this systematic review can be grouped into several categories, each with a specific focus that captures different aspects of these environments ( Table 3 ). Table 3. Classification of metrics for entrepreneurial ecosystems. Type of metric Metric description Output Metrics Number of Startups or Emerging Enterprises: This is a fundamental metric that measures the number of new businesses created in a specific area ( Huang-Saad et al., 2017 ; Iacobucci & Perugini, 2021 ; Rocha et al., 2022 ). It is often used as a key indicator of entrepreneurial activity in a region ( Corrente et al., 2019 ; Rocha et al., 2022 ). Total Early-Stage Entrepreneurial Activity (TEA): This metric, used by the Global Entrepreneurship Monitor (GEM), measures the percentage of the adult population involved in starting new businesses ( Calispa-Aguilar, 2021 ; Szerb et al., 2019 ; Yan & Guan, 2019 ). It is widely used to compare levels of entrepreneurial activity across regions and countries ( Yan & Guan, 2019 ). Business Survival Rate: Indicates the proportion of businesses that remain operational after a specific period, reflecting the ecosystem’s resilience ( Iacobucci & Perugini, 2021 ; Leendertse et al., 2022 ; Nicotra et al., 2018 ). High-Growth Firms: This metric identifies the number of firms experiencing rapid growth in terms of revenue or employment ( Corrente et al., 2019 ; Iacobucci & Perugini, 2021 ). These companies are considered key drivers of job creation and wealth ( Iacobucci & Perugini, 2021 ). Ecosystem Condition Metrics (Inputs) Financing: The availability of funding is crucial for the development of new ventures. Common metrics include access to venture capital, business loans, and entrepreneurship subsidies ( Corrente et al., 2019 ; Huang-Saad et al., 2017 ; Iacobucci & Perugini, 2021 ; Rocha et al., 2022 ). Human Capital and Knowledge: These metrics assess the availability and quality of talent and knowledge within the ecosystem. They include R&D expenditure, the quality of human capital, higher education attainment, and the number of researchers ( Guerrero & Siegel, 2024 ; Huang-Saad et al., 2017 ; Iacobucci & Perugini, 2021 ; Leendertse et al., 2022 ). Infrastructure: The availability and quality of physical (transport, communications) and technological infrastructure are critical. Metrics include access to physical infrastructure, hardware and software facilities, and R&D centers ( Guerrero & Siegel, 2024 ; Huang-Saad et al., 2017 ; Iacobucci & Perugini, 2021 ; Leendertse et al., 2022 ). Institutions: These evaluate the regulatory framework and institutional support for entrepreneurship, including government programs, institutional transparency, institutional quality, and entrepreneurship policy support ( Corrente et al., 2019 ; Fomishyna et al., 2023 ; Iacobucci & Perugini, 2021 ; La Rovere et al., 2021 ; Yan & Guan, 2019 ). Education: Assesses the availability and quality of entrepreneurship education programs at all levels ( Huang-Saad et al., 2017 ; Sharma et al., 2024 ). Culture: The presence of social and cultural norms that promote entrepreneurship is essential. This can be measured through expert surveys evaluating social and cultural support for entrepreneurship ( Corrente et al., 2019 ; Huang-Saad et al., 2017 ; Sharma et al., 2024 ). Networks: Entrepreneurial connectivity and network density are crucial for collaboration, knowledge exchange, and access to resources. Metrics include the number of connections between entrepreneurs and other ecosystem actors ( Balawi & Ayoub, 2022 ; Corrente et al., 2019 ). Market: Metrics include market dynamism, sophistication, and scale. A dynamic and competitive market is important for the development of new businesses and openness to new ideas and technologies ( Corrente et al., 2019 ; Nicotra et al., 2018 ; Riaz et al., 2022 ; Yan & Guan, 2019 ). Composite Indexes Entrepreneurial Ecosystem Index (EE): This index combines multiple variables to assess the overall quality of the ecosystem, allowing comparisons across regions ( Iacobucci & Perugini, 2021 ; Leendertse et al., 2022 ; Riaz et al., 2022 ; Sharma et al., 2024 ; Stam & Van de Ven, 2021 ). Global Entrepreneurship Index (GEI): The GEI evaluates the state of an entrepreneurial ecosystem using 14 pillars ( Lafuente et al., 2022 ). Regional Entrepreneurship and Development Index (REDI): This index assesses regional development and entrepreneurship by combining various ecosystem-related factors ( Komlósi et al., 2024 ). Subjective and Perceptual Metrics Perception of the Environment: Surveys are used to capture how entrepreneurs perceive the supportiveness of their environment and its contribution to the region ( Fomishyna et al., 2023 ; Guerrero & Siegel, 2024 ; Iacobucci & Perugini, 2021 ). Entrepreneurial Attitude: Scales and surveys are used to measure the attitudes and perceptions of entrepreneurs ( Sethar et al., 2022 ). Other Metrics Online Attention: Measures the level of attention entrepreneurship receives online, particularly on social media, and can reflect public interest and the ecosystem’s dynamism ( Yan & Guan, 2019 ). First, output metrics include indicators such as the number of startups created in a region, the total early-stage entrepreneurial activity (TEA) rate, business survival rates, and the number of high-growth firms. These metrics assess the direct impact of the ecosystem on the creation and sustainability of new ventures and are commonly used in studies evaluating the effectiveness of public policies and entrepreneurship support programs. In contrast, input metrics focus on the conditions that foster venture creation and growth. Within this category, access to financing is a key element, as assessed through indicators like venture capital investment and startup loans. Human capital and knowledge are measured via variables such as R&D expenditure, the educational level of the population, and the presence of researchers in the region. Infrastructure—both physical and technological—is another crucial component, including access to transportation networks, digital connectivity, and the availability of innovation hubs. Institutions also play a critical role in the ecosystem, as their regulations and support can either facilitate or hinder entrepreneurial activity. This includes evaluating the quality of government policies and entrepreneurship programs. Lastly, entrepreneurial culture and collaboration networks are also considered under this category, as they promote knowledge exchange and opportunity creation for new entrepreneurs. Another group of metrics relates to dynamic capabilities, which are focused on the ability of the ecosystem to adapt and respond to environmental changes. Indicators here include knowledge absorption capacity, flexibility in adopting innovations, and entrepreneurs’ responsiveness to economic and technological challenges. Also included in the classification are composite indexes, whose aim is to provide an integrated view of the entrepreneurial ecosystem by combining multiple variables into a single metric. Widely used examples include the Entrepreneurial Ecosystem Index (EE), the Global Entrepreneurship Index (GEI), and the Regional Entrepreneurship and Development Index (REDI). These indexes facilitate comparisons across regions or countries and support the design of policies aimed at strengthening entrepreneurial ecosystems. In addition to quantitative metrics, subjective and perceptual metrics rely on surveys and perception studies to capture entrepreneurs’ impressions of their operating environment. These include assessments of the entrepreneurial climate and entrepreneurial attitudes, often measured through scales gauging confidence in business opportunities and the willingness to take risks. Finally, some emerging metrics have appeared in recent years, such as online attention, which measures the visibility of entrepreneurial ecosystems on social media and digital platforms. These metrics reflect the ecosystem’s dynamism and its ability to attract investors and talent. Collectively, these metrics allow for a multifaceted analysis of entrepreneurial ecosystems, offering valuable tools for researchers and policymakers interested in fostering more conducive environments for innovation and business development. Using a combination of these metrics—rather than relying on a single indicator—enables a more complete and accurate assessment of ecosystem performance. Conclusion This systematic review of the metrics used to assess entrepreneurial ecosystems reveals the existing conceptual and methodological fragmentation in the literature. The diversity of approaches, both quantitative and qualitative, highlights the inherent complexity of these systems, where multiple factors interact in a nonlinear manner to influence entrepreneurial dynamics. The analysis made it possible to identify five major categories of metrics: (i) output metrics, which measure the ecosystem’s impact on the creation and consolidation of firms; (ii) ecosystem condition metrics, which assess the availability of essential resources such as financing, human capital, infrastructure, and institutions; (iii) composite indexes, which integrate multiple dimensions to allow comparisons among ecosystems at regional, national, and international levels; (iv) subjective and perceptual metrics, which capture actors’ perceptions of the ecosystem and its conditions; and (v) emerging metrics, which are focused on currently relevant factors such as the visibility of ecosystems on social media platforms. The findings of this study highlight the adoption of mixed methodologies to evaluate the performance of entrepreneurial ecosystems, combining quantitative and qualitative approaches in order to capture their complexity. While composite indexes such as the Global Entrepreneurship Index (GEI) and the Regional Entrepreneurship and Development Index (REDI) have enabled standardized comparisons, their applicability in specific contexts remains a challenge due to the heterogeneity of entrepreneurial ecosystems and the difficulty of capturing emerging dynamics. One of the main gaps identified in the literature is the lack of metrics that measure the temporal evolution of ecosystems and their ability to adapt to technological, economic, or regulatory changes. Most of the reviewed studies have adopted static approaches, without accounting for the dynamic nature of entrepreneurial ecosystems. In this regard, further efforts are needed to develop tools that enable longitudinal analysis and the identification of evolutionary patterns in these systems. The limitations of this study are related to the selection of only two databases, Scopus and WOS, and articles published in English and with full text only, which could exclude relevant papers and contribute to a potential methodological bias. Therefore, broader and more inclusive research is needed in future studies. In theoretical terms, this study contributes to the consolidation of the research field of entrepreneurial ecosystems by providing a structured classification of the metrics used in the academic literature. It also underscores the need to move toward integrative approaches that combine structural, systemic, and outcome-based measurements for a more accurate evaluation of ecosystem performance. From a practical perspective, the review offers a useful reference framework for policymakers and other stakeholders interested in measuring the performance of entrepreneurial ecosystems. Identifying key metrics and their applicability in various contexts will support the formulation of more effective strategies aimed at fostering innovation and competitiveness within these environments. Ethical considerations Not applicable. Data availability No data are associated with this article. Supplementary Data Availability Statement in Zenodo repository: “How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review”. https://doi.org/10.5281/zenodo.17387472 . ( Chaves-Ladino & Jiménez-Hernández, 2025 ). This project contains following extended data: • 1. PRISMA 2020 Checklist Complete vf.pdf • 2. Database review.xlsx Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). Reporting guidelines Not applicable. Acknowledgements Not applicable. References Acs ZJ, Stam E, Audretsch DB, et al. : The lineages of the entrepreneurial ecosystem approach. Small Bus. Econ. 2017; 49 (1): 1–10. 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Sustainability (Switzerland). 2022; 14 (9). Publisher Full Text Sharma A, Das N, Singh SP, et al. : Association Between Entrepreneurship Ecosystem and Entrepreneurial Behavior & Attitudes. J. Glob. Inf. Manag. 2024; 32 (1): 1–26. Publisher Full Text Shen R, Guo H, Ma H: How do entrepreneurs’ cross-cultural experiences contribute to entrepreneurial ecosystem performance? J. World Bus. 2023; 58 (2): 101398. Publisher Full Text Sitaridis I, Kitsios F: Competitiveness analysis and evaluation of entrepreneurial ecosystems: A multi-criteria approach. Ann. Oper. Res. 2020; 294 (1–2): 377–399. Publisher Full Text Spigel B: The Relational Organization of Entrepreneurial Ecosystems. Entrep. Theory Pract. 2017; 41 (1): 49–72. Publisher Full Text Stam E: Entrepreneurial Ecosystems and Regional Policy: A Sympathetic Critique. Eur. Plan. Stud. 2015; 23 (9): 1759–1769. Publisher Full Text Stam E, Van de Ven A: Entrepreneurial ecosystem elements. Small Bus. Econ. 2021; 56 (2): 809–832. Publisher Full Text Sternberg R, von Bloh J , Coduras A: A new framework to measure entrepreneurial ecosystems at the regional level. Zeitschrift fur Wirtschaftsgeographie. 2019; 63 (2–4): 103–117. Publisher Full Text Szerb L, Lafuente E, Horváth K, et al. : The relevance of quantity and quality entrepreneurship for regional performance: The moderating role of the entrepreneurial ecosystem. Reg. Stud. 2019; 53 (9): 1308–1320. Publisher Full Text Wang Q, Li Y, Yang Y, et al. : University-Led Entrepreneurship Ecosystem Building in underserved communities: From a network perspective. Geogr. Rev. 2024; 114 (3): 353–377. Publisher Full Text Wibisono E: The digital entrepreneurial ecosystem in the European Union: Evidence from the digital platform economy index. Eur. Plan. Stud. 2023; 31 (6): 1270–1292. Publisher Full Text Yan Y, Guan J: Entrepreneurial ecosystem, entrepreneurial rate and innovation: The moderating role of internet attention. Int. Entrep. Manag. J. 2019; 15 (2): 625–650. Publisher Full Text Zhang X, Hu H, Zhou C, et al. : Is a Rural Entrepreneurial Ecosystem Conducive to the Improvement of Entrepreneurial Performance? Evidence from Typical Counties of Rural Entrepreneurship and Innovation in China. Land. 2024; 13 (11). Publisher Full Text Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 25 Nov 2025 ADD YOUR COMMENT Comment Author details Author details 1 Faculty of Economic Sciences, Universidad Nacional de Colombia, Bogotá, Colombia 2 Faculty of Agricultural Sciences, Universidad Nacional de Colombia, Bogotá, Colombia Rodrigo Chaves-Ladino Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Visualization, Writing – Original Draft Preparation Claudia Nelcy Jiménez-Hernández Roles: Data Curation, Methodology, Project Administration, Supervision, Validation, Visualization, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information This research was funded by the “Convocatoria para la Formación de Capital Humano de Alto Nivel para los Departamentos de Amazonas, Arauca, Boyacá, Caquetá, Casanare, Guaviare, Nariño, Putumayo, San Andrés y Vichada”, under the framework of Convocatoria 15 del Sistema General de Regalías (SGR), for the development of doctoral studies. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Article Versions (1) version 1 Published: 25 Nov 2025, 14:1307 https://doi.org/10.12688/f1000research.172389.1 Copyright © 2025 Chaves-Ladino R and Jiménez-Hernández CN. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Chaves-Ladino R and Jiménez-Hernández CN. How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review [version 1; peer review: 1 approved with reservations, 2 not approved] . F1000Research 2025, 14 :1307 ( https://doi.org/10.12688/f1000research.172389.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 1 VERSION 1 PUBLISHED 25 Nov 2025 Views 0 Cite How to cite this report: Nguyen P. Reviewer Report For: How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review [version 1; peer review: 1 approved with reservations, 2 not approved] . F1000Research 2025, 14 :1307 ( https://doi.org/10.5256/f1000research.190110.r443060 ) The direct URL for this report is: https://f1000research.com/articles/14-1307/v1#referee-response-443060 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 22 Jan 2026 Phung Nguyen , University of Vaasa, Wolffintie, Finland Not Approved VIEWS 0 https://doi.org/10.5256/f1000research.190110.r443060 Thank you for your review. The research topic you explored is essential to the field, and the research has yielded some valuable insights. However, the research has major problems that need to be addressed to make it a reliable, rigorous, ... Continue reading READ ALL Thank you for your review. The research topic you explored is essential to the field, and the research has yielded some valuable insights. However, the research has major problems that need to be addressed to make it a reliable, rigorous, and, more importantly, replicable academic paper. Research background and objective You stated that this research aims to analyze existing metrics of entrepreneurial ecosystem performance. Still, you then said to include only general-purpose entrepreneurial ecosystems and exclude digital and university entrepreneurial ecosystems because of the different metrics used. With this in mind, the research objective and title should clearly indicate the type of entrepreneurial ecosystem intended to be reviewed to avoid misinterpretation. Methods You justified the significance of the Scopus and Web of Science databases, as well as the complementary terms used, without citing any sources, which, to a certain extent, reduced the reliability of the methods. Any confirmations like “Their ability to filter documents according to rigorous quality criteria and their advanced search functionalities enable the identification of studies that meet the methodological standards required for a reliable and replicable systematic review”, or “as these concepts are directly related to the performance of entrepreneurial ecosystems” need a strong source to persuade the readers. The introduction of Rayyan software, VOSViewer, and PRISMA, as applied in the research, also lacked sources, i.e., what they are and why they were considered for use. You did not justify how you mitigated bias or ensured the reliability of including the articles for review and of the data analysis. This information is essential for a systematic review as it tells the readers how reliable your review is. Results and Discussion The PRISMA flow diagram (Figure 1) should be moved to the methods section and should show clearly the reasons for excluding the articles including the number of articles, for example, foreign language, research topic, etc. You should also use the standard PRISMA flow diagram, available at this link https://www.prisma-statement.org/prisma-2020-flow-diagram . The results and discussion are really problematic and rambling. The discussion should present research findings, but in your research, it did not reflect the results; it even introduced new ideas. The main focus of your study is the metrics; therefore, the results and discussion should be structured around them. What was the connection between the clusters and the metrics mentioned in Table 3? Also, what was the connection between the methodologies and the metrics? You provided many pieces of information, but they looked scattered and did not address what the research was actually seeking to answer. Moreover, there needs to be elaboration on the use of VOSViewer to generate a co-occurrence map to increase the replicability of your research. Did you use a keyword thesaurus? How did you set the thresholds? Were the clusters generated automatically, or were they generated manually? Conclusion There needs to be a mention of future research directions or an agenda based on the results and research gaps identified; otherwise, a review looks like a summary of what has been researched. Paper structure In addition to the structural problems mentioned, you had too many small paragraphs in your manuscript, which scattered the information and reduced the flow and consistency of the research. I recommend you restructure your manuscript, at least by linking the ideas into longer paragraphs. Are the rationale for, and objectives of, the Systematic Review clearly stated? Partly Are sufficient details of the methods and analysis provided to allow replication by others? Partly Is the statistical analysis and its interpretation appropriate? Partly Are the conclusions drawn adequately supported by the results presented in the review? Partly If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Not applicable Competing Interests: No competing interests were disclosed. Reviewer Expertise: Entrepreneurship, Innovation, Management, Sustainability I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Nguyen P. Reviewer Report For: How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review [version 1; peer review: 1 approved with reservations, 2 not approved] . F1000Research 2025, 14 :1307 ( https://doi.org/10.5256/f1000research.190110.r443060 ) The direct URL for this report is: https://f1000research.com/articles/14-1307/v1#referee-response-443060 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Ahmed SW. Reviewer Report For: How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review [version 1; peer review: 1 approved with reservations, 2 not approved] . F1000Research 2025, 14 :1307 ( https://doi.org/10.5256/f1000research.190110.r443058 ) The direct URL for this report is: https://f1000research.com/articles/14-1307/v1#referee-response-443058 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 16 Jan 2026 Sardar Wasi Ahmed , Norwegian University of Science and Technology (NTNU), Aalesund, Norway Not Approved VIEWS 0 https://doi.org/10.5256/f1000research.190110.r443058 Overall assessment The manuscript, titled “How to measure the performance of Entrepreneurial Ecosystems: A Systematic Literature Review” presents a systematic literature review (SLR) of metrics used to evaluate entrepreneurial ecosystem (EE) performance. While the topic is relevant and ... Continue reading READ ALL Overall assessment The manuscript, titled “How to measure the performance of Entrepreneurial Ecosystems: A Systematic Literature Review” presents a systematic literature review (SLR) of metrics used to evaluate entrepreneurial ecosystem (EE) performance. While the topic is relevant and the review process is competently documented, the manuscript remains largely superficial in its analysis and contribution. The study primarily catalogs existing metrics without offering substantive theoretical integration, methodological advancement, or novel analytical insight. As such, the study falls short of the standards expected for a systematic review intended to meaningfully advance understanding in this field. Although the review follows formal procedural steps (e.g., PRISMA), compliance with protocol alone does not compensate for the lack of analytical depth. The manuscript consolidates what is already well known in the literature and does so in a largely descriptive manner. In its current form, the work does not provide sufficient scholarly value to justify as a indexable scientific work. Conceptual framing and positioning The introduction reiterates familiar arguments regarding the importance of EEs and the lack of consensus on their measurement. These points are extensively documented in prior literature and are not problematized or extended in a meaningful way. The manuscript does not clearly articulate how it advances beyond existing reviews, nor does it identify a precise conceptual or theoretical gap that this study resolves. The exclusion of digital and university-based ecosystems is asserted rather than analytically justified. While such exclusions may be defensible, the authors do not engage with the conceptual implications of this decision or reflect on how it limits the scope and interpretability of their findings. As a result, the framing appears selective rather than theoretically grounded. Methods The methodological section is procedurally sound and transparently reported. The use of PRISMA, Scopus, Web of Science, Rayyan, and VOSviewer reflects adherence to standard review practices. However, methodological correctness should not be conflated with methodological rigor in analysis. The search strategy is narrow and conservative, relying heavily on title-based keyword filtering. This design choice likely excludes a substantial body of relevant work that addresses ecosystem performance using adjacent or alternative terminology. The manuscript does not critically reflect on this limitation or explore its consequences, which undermines the comprehensiveness expected of a SLR. Analysis and results The results section is predominantly descriptive. Bibliometric outputs such as publication trends and keyword co-occurrence maps are presented, but they are not analytically exploited. The identification of thematic clusters does not lead to deeper theoretical insight, comparative evaluation, or critical synthesis. Also, the cluster analysis remains a mapping exercise rather than an interpretive one. Relationships between clusters, underlying theoretical assumptions, and methodological tensions are not examined. As a result, bibliometric analysis adds little beyond visual organization of literature. Metrics classification The classification of metrics into inputs, outputs, composite indices, subjective measures, and emerging indicators is intuitive but analytically shallow. Similar classifications already exist in the literature, and the manuscript does not convincingly demonstrate how its framework differs from or improves upon them. Crucially, the paper fails to grapple with core conceptual issues such as causal ambiguity, temporal sequencing, and endogeneity among ecosystem variables. Metrics that function simultaneously as conditions and outcomes are treated as discrete categories without sufficient theoretical justification. This oversimplification weakens the analytical credibility of the classification. Discussion and research agenda The discussion reiterates well-established critiques of ecosystem measurement, such as fragmentation and the dominance of static indicators. However, these observations are neither novel nor developed into a coherent analytical argument. The proposed future research agenda is generic and lacks specificity. Calls for longitudinal studies, dynamic metrics, or mixed methods are commonplace in the field and do not provide actionable guidance. The manuscript does not articulate concrete methodological pathways, data strategies, or analytical frameworks that could realistically advance research on entrepreneurial ecosystem performance. Recommendation Despite procedural correctness, the manuscript lacks the analytical depth, conceptual originality, and critical synthesis required of a SLR. Addressing these shortcomings would require substantial reconceptualization and reanalysis, rather than incremental revision. Approval Status : Not Approved Thanking with, Sardar Wasi Ahmed, Ph.D. Associate professor, NTNU School of International Business, Norway ** This review includes language refinement support using ChatGPT by OpenAI. The AI tool was employed to enhance the clarity, tone, and structure of the review text Are the rationale for, and objectives of, the Systematic Review clearly stated? No Are sufficient details of the methods and analysis provided to allow replication by others? Partly Is the statistical analysis and its interpretation appropriate? Partly Are the conclusions drawn adequately supported by the results presented in the review? Partly If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Partly Competing Interests: No competing interests were disclosed. Reviewer Expertise: Entrepreneurship I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Ahmed SW. Reviewer Report For: How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review [version 1; peer review: 1 approved with reservations, 2 not approved] . F1000Research 2025, 14 :1307 ( https://doi.org/10.5256/f1000research.190110.r443058 ) The direct URL for this report is: https://f1000research.com/articles/14-1307/v1#referee-response-443058 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Batista-Canino RM. Reviewer Report For: How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review [version 1; peer review: 1 approved with reservations, 2 not approved] . F1000Research 2025, 14 :1307 ( https://doi.org/10.5256/f1000research.190110.r439424 ) The direct URL for this report is: https://f1000research.com/articles/14-1307/v1#referee-response-439424 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 06 Jan 2026 Rosa M. Batista-Canino , University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.190110.r439424 I appreciate the opportunity to read this interesting work and congratulate the authors on the choice of topic. It is a current and increasingly relevant subject in the field. The paper also has a clear purpose, which the authors pursue ... Continue reading READ ALL I appreciate the opportunity to read this interesting work and congratulate the authors on the choice of topic. It is a current and increasingly relevant subject in the field. The paper also has a clear purpose, which the authors pursue consistently throughout the manuscript. Below are some suggestions that could help enhance the clarity, comprehensibility, and relevance of the work: Paragraph structure: It would be desirable for the paragraphs to have greater substance, bringing together all the key information. Very short paragraphs (two or three lines) tend to reduce the quality of exposition and make the article feel somewhat telegraphic. Introduction of the concept: Since the literature review focuses on how entrepreneurial ecosystems are being measured, the article would benefit from starting with a discussion of the concept itself, rather than presenting it as an outcome of the review. I would suggest moving the section that debates the concept before the methodology and concluding it with a summary table of the concepts found in the literature. Methodological details: In the methodology section, the authors mention using Vosviewer, but it is important to specify the parameters applied to obtain those results. This is particularly useful to allow other researchers to replicate the process or extend the review in future publications, making the results comparable. Scientific background: It would also be interesting to include a table summarizing the scientific background of the field to further strengthen the exposition. An example article is attached for reference. Future research avenues: In the discussion, it would be expected that the authors not only describe the results but also propose potential directions for future research. For instance: Which metrics seem most promising? Which could offer better results based on their knowledge and review? Overall, I believe the paper only requires some improvements to be ready for indexing in this promising journal. Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Partly Is the statistical analysis and its interpretation appropriate? Yes Are the conclusions drawn adequately supported by the results presented in the review? Partly If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Not applicable References 1. Batista-Canino R, Santana-Hernández L, Medina-Brito P: A holistic literature review on entrepreneurial Intention: A scientometric approach. Journal of Business Research . 2024; 174 . Publisher Full Text Competing Interests: No competing interests were disclosed. Reviewer Expertise: Entrepreneurship, Employability, Innovation I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Batista-Canino RM. Reviewer Report For: How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review [version 1; peer review: 1 approved with reservations, 2 not approved] . F1000Research 2025, 14 :1307 ( https://doi.org/10.5256/f1000research.190110.r439424 ) The direct URL for this report is: https://f1000research.com/articles/14-1307/v1#referee-response-439424 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 25 Nov 2025 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 3 Version 1 25 Nov 25 read read read Rosa M. Batista-Canino , University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain Sardar Wasi Ahmed , Norwegian University of Science and Technology (NTNU), Aalesund, Norway Phung Nguyen , University of Vaasa, Wolffintie, Finland Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Nguyen P. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 22 Jan 2026 | for Version 1 Phung Nguyen , University of Vaasa, Wolffintie, Finland 0 Views copyright © 2026 Nguyen P. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Not Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Thank you for your review. The research topic you explored is essential to the field, and the research has yielded some valuable insights. However, the research has major problems that need to be addressed to make it a reliable, rigorous, and, more importantly, replicable academic paper. Research background and objective You stated that this research aims to analyze existing metrics of entrepreneurial ecosystem performance. Still, you then said to include only general-purpose entrepreneurial ecosystems and exclude digital and university entrepreneurial ecosystems because of the different metrics used. With this in mind, the research objective and title should clearly indicate the type of entrepreneurial ecosystem intended to be reviewed to avoid misinterpretation. Methods You justified the significance of the Scopus and Web of Science databases, as well as the complementary terms used, without citing any sources, which, to a certain extent, reduced the reliability of the methods. Any confirmations like “Their ability to filter documents according to rigorous quality criteria and their advanced search functionalities enable the identification of studies that meet the methodological standards required for a reliable and replicable systematic review”, or “as these concepts are directly related to the performance of entrepreneurial ecosystems” need a strong source to persuade the readers. The introduction of Rayyan software, VOSViewer, and PRISMA, as applied in the research, also lacked sources, i.e., what they are and why they were considered for use. You did not justify how you mitigated bias or ensured the reliability of including the articles for review and of the data analysis. This information is essential for a systematic review as it tells the readers how reliable your review is. Results and Discussion The PRISMA flow diagram (Figure 1) should be moved to the methods section and should show clearly the reasons for excluding the articles including the number of articles, for example, foreign language, research topic, etc. You should also use the standard PRISMA flow diagram, available at this link https://www.prisma-statement.org/prisma-2020-flow-diagram . The results and discussion are really problematic and rambling. The discussion should present research findings, but in your research, it did not reflect the results; it even introduced new ideas. The main focus of your study is the metrics; therefore, the results and discussion should be structured around them. What was the connection between the clusters and the metrics mentioned in Table 3? Also, what was the connection between the methodologies and the metrics? You provided many pieces of information, but they looked scattered and did not address what the research was actually seeking to answer. Moreover, there needs to be elaboration on the use of VOSViewer to generate a co-occurrence map to increase the replicability of your research. Did you use a keyword thesaurus? How did you set the thresholds? Were the clusters generated automatically, or were they generated manually? Conclusion There needs to be a mention of future research directions or an agenda based on the results and research gaps identified; otherwise, a review looks like a summary of what has been researched. Paper structure In addition to the structural problems mentioned, you had too many small paragraphs in your manuscript, which scattered the information and reduced the flow and consistency of the research. I recommend you restructure your manuscript, at least by linking the ideas into longer paragraphs. Are the rationale for, and objectives of, the Systematic Review clearly stated? Partly Are sufficient details of the methods and analysis provided to allow replication by others? Partly Is the statistical analysis and its interpretation appropriate? Partly Are the conclusions drawn adequately supported by the results presented in the review? Partly If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Not applicable Competing Interests No competing interests were disclosed. Reviewer Expertise Entrepreneurship, Innovation, Management, Sustainability I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. reply Respond to this report Responses (0) Nguyen P. Peer Review Report For: How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review [version 1; peer review: 1 approved with reservations, 2 not approved] . F1000Research 2025, 14 :1307 ( https://doi.org/10.5256/f1000research.190110.r443060) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-1307/v1#referee-response-443060 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Ahmed S. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 16 Jan 2026 | for Version 1 Sardar Wasi Ahmed , Norwegian University of Science and Technology (NTNU), Aalesund, Norway 0 Views copyright © 2026 Ahmed S. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Not Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Overall assessment The manuscript, titled “How to measure the performance of Entrepreneurial Ecosystems: A Systematic Literature Review” presents a systematic literature review (SLR) of metrics used to evaluate entrepreneurial ecosystem (EE) performance. While the topic is relevant and the review process is competently documented, the manuscript remains largely superficial in its analysis and contribution. The study primarily catalogs existing metrics without offering substantive theoretical integration, methodological advancement, or novel analytical insight. As such, the study falls short of the standards expected for a systematic review intended to meaningfully advance understanding in this field. Although the review follows formal procedural steps (e.g., PRISMA), compliance with protocol alone does not compensate for the lack of analytical depth. The manuscript consolidates what is already well known in the literature and does so in a largely descriptive manner. In its current form, the work does not provide sufficient scholarly value to justify as a indexable scientific work. Conceptual framing and positioning The introduction reiterates familiar arguments regarding the importance of EEs and the lack of consensus on their measurement. These points are extensively documented in prior literature and are not problematized or extended in a meaningful way. The manuscript does not clearly articulate how it advances beyond existing reviews, nor does it identify a precise conceptual or theoretical gap that this study resolves. The exclusion of digital and university-based ecosystems is asserted rather than analytically justified. While such exclusions may be defensible, the authors do not engage with the conceptual implications of this decision or reflect on how it limits the scope and interpretability of their findings. As a result, the framing appears selective rather than theoretically grounded. Methods The methodological section is procedurally sound and transparently reported. The use of PRISMA, Scopus, Web of Science, Rayyan, and VOSviewer reflects adherence to standard review practices. However, methodological correctness should not be conflated with methodological rigor in analysis. The search strategy is narrow and conservative, relying heavily on title-based keyword filtering. This design choice likely excludes a substantial body of relevant work that addresses ecosystem performance using adjacent or alternative terminology. The manuscript does not critically reflect on this limitation or explore its consequences, which undermines the comprehensiveness expected of a SLR. Analysis and results The results section is predominantly descriptive. Bibliometric outputs such as publication trends and keyword co-occurrence maps are presented, but they are not analytically exploited. The identification of thematic clusters does not lead to deeper theoretical insight, comparative evaluation, or critical synthesis. Also, the cluster analysis remains a mapping exercise rather than an interpretive one. Relationships between clusters, underlying theoretical assumptions, and methodological tensions are not examined. As a result, bibliometric analysis adds little beyond visual organization of literature. Metrics classification The classification of metrics into inputs, outputs, composite indices, subjective measures, and emerging indicators is intuitive but analytically shallow. Similar classifications already exist in the literature, and the manuscript does not convincingly demonstrate how its framework differs from or improves upon them. Crucially, the paper fails to grapple with core conceptual issues such as causal ambiguity, temporal sequencing, and endogeneity among ecosystem variables. Metrics that function simultaneously as conditions and outcomes are treated as discrete categories without sufficient theoretical justification. This oversimplification weakens the analytical credibility of the classification. Discussion and research agenda The discussion reiterates well-established critiques of ecosystem measurement, such as fragmentation and the dominance of static indicators. However, these observations are neither novel nor developed into a coherent analytical argument. The proposed future research agenda is generic and lacks specificity. Calls for longitudinal studies, dynamic metrics, or mixed methods are commonplace in the field and do not provide actionable guidance. The manuscript does not articulate concrete methodological pathways, data strategies, or analytical frameworks that could realistically advance research on entrepreneurial ecosystem performance. Recommendation Despite procedural correctness, the manuscript lacks the analytical depth, conceptual originality, and critical synthesis required of a SLR. Addressing these shortcomings would require substantial reconceptualization and reanalysis, rather than incremental revision. Approval Status : Not Approved Thanking with, Sardar Wasi Ahmed, Ph.D. Associate professor, NTNU School of International Business, Norway ** This review includes language refinement support using ChatGPT by OpenAI. The AI tool was employed to enhance the clarity, tone, and structure of the review text Are the rationale for, and objectives of, the Systematic Review clearly stated? No Are sufficient details of the methods and analysis provided to allow replication by others? Partly Is the statistical analysis and its interpretation appropriate? Partly Are the conclusions drawn adequately supported by the results presented in the review? Partly If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Partly Competing Interests No competing interests were disclosed. Reviewer Expertise Entrepreneurship I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. reply Respond to this report Responses (0) Ahmed SW. Peer Review Report For: How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review [version 1; peer review: 1 approved with reservations, 2 not approved] . F1000Research 2025, 14 :1307 ( https://doi.org/10.5256/f1000research.190110.r443058) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-1307/v1#referee-response-443058 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Batista-Canino R. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 06 Jan 2026 | for Version 1 Rosa M. Batista-Canino , University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain 0 Views copyright © 2026 Batista-Canino R. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions I appreciate the opportunity to read this interesting work and congratulate the authors on the choice of topic. It is a current and increasingly relevant subject in the field. The paper also has a clear purpose, which the authors pursue consistently throughout the manuscript. Below are some suggestions that could help enhance the clarity, comprehensibility, and relevance of the work: Paragraph structure: It would be desirable for the paragraphs to have greater substance, bringing together all the key information. Very short paragraphs (two or three lines) tend to reduce the quality of exposition and make the article feel somewhat telegraphic. Introduction of the concept: Since the literature review focuses on how entrepreneurial ecosystems are being measured, the article would benefit from starting with a discussion of the concept itself, rather than presenting it as an outcome of the review. I would suggest moving the section that debates the concept before the methodology and concluding it with a summary table of the concepts found in the literature. Methodological details: In the methodology section, the authors mention using Vosviewer, but it is important to specify the parameters applied to obtain those results. This is particularly useful to allow other researchers to replicate the process or extend the review in future publications, making the results comparable. Scientific background: It would also be interesting to include a table summarizing the scientific background of the field to further strengthen the exposition. An example article is attached for reference. Future research avenues: In the discussion, it would be expected that the authors not only describe the results but also propose potential directions for future research. For instance: Which metrics seem most promising? Which could offer better results based on their knowledge and review? Overall, I believe the paper only requires some improvements to be ready for indexing in this promising journal. Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Partly Is the statistical analysis and its interpretation appropriate? Yes Are the conclusions drawn adequately supported by the results presented in the review? Partly If this is a Living Systematic Review, is the ‘living’ method appropriate and is the search schedule clearly defined and justified? (‘Living Systematic Review’ or a variation of this term should be included in the title.) Not applicable References 1. Batista-Canino R, Santana-Hernández L, Medina-Brito P: A holistic literature review on entrepreneurial Intention: A scientometric approach. Journal of Business Research . 2024; 174 . Publisher Full Text Competing Interests No competing interests were disclosed. Reviewer Expertise Entrepreneurship, Employability, Innovation I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Batista-Canino RM. Peer Review Report For: How to Measure the Performance of Entrepreneurial Ecosystems: A Systematic Literature Review [version 1; peer review: 1 approved with reservations, 2 not approved] . F1000Research 2025, 14 :1307 ( https://doi.org/10.5256/f1000research.190110.r439424) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. 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