The determinants of the concentration of superstar firms: Cluster analysis and its relationship with economic development and artificial intelligence

Gracia Bustelo, José Luis; Miró Pérez, Albert; Meruvia Torrez, Harold Article The determinants of the concentration of superstar firms: Cluster analysis and its relationship with economic development and artificial intelligence Economies Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Gracia Bustelo, José Luis; Miró Pérez, Albert; Meruvia Torrez, Harold (2025) : The determinants of the concentration of superstar firms: Cluster analysis and its relationship with economic development and artificial intelligence, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 13, Iss. 2, pp. 1-20, https://doi.org/10.3390/economies13020052 This Version is available at: https://hdl.handle.net/10419/329332 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Academic Editor: Tsutomu Harada Received: 14 January 2025 Revised: 6 February 2025 Accepted: 11 February 2025 Published: 14 February 2025 Citation: Bustelo, J. L. G., Pérez, A. M., & Torrez, H. M. (2025). The Determinants of the Concentration of Superstar Firms: Cluster Analysis and Its Relationship with Economic Development and Artificial Intelligence. Economies,13(2), 52. https://doi.org/10.3390/ economies13020052 Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). Article The Determinants of the Concentration of Superstar Firms: Cluster Analysis and Its Relationship with Economic Development and Artificial Intelligence José Luis Gracia Bustelo 1,* , Albert Miró Pérez 2and Harold Meruvia Torrez 3 1 Department of Economics and Business, ESERP Business and Law School, Universitat Central de Catalunya, 08010 Barcelona, Spain 2Department of Economics and Business, Universitat Oberta de Catalunya, 08018 Barcelona, Spain; amiroper[email protected] 3Marketing, Communication and Sales Department, EAE Business School, 08015 Barcelona, Spain; harold.torr[email protected] *Correspondence: [email protected] Abstract: This study analysed the determining factors of the concentration of “superstar firms” in specific economies, with a focus on the interaction between technological innovation, economic development, and market structures. Using global data from Statista on superstar firms for the year 2022, statistical methods such as correlation analysis, an ANOVA, and cluster analysis were applied to identify patterns and relationships between variables like the GDP, market capitalization, and the development of artificial intelligence (AI). The analysis in this paper revealed significant positive correlations between the number of superstar firms and key economic indicators such as the GDP and market capitalization, suggesting that these firms drive economic growth and technological advancement. The cluster analysis identified groupings of countries based on their technological capabilities and economic performance, highlighting that a great number of these firms are concentrated in advanced economies. This work emphasizes the importance of technological infrastructure, innovation policies, and regulatory frameworks in promoting competitive environments for superstar firms. Additionally, it addresses the socioeconomic implications, including challenges related to wealth concentration, inequality, and the transformation of the labour market. Public policies are recommended to foster inclusive innovation, STEM education, and international governance to balance global competitiveness with equitable economic growth. Keywords: superstar firms; technological innovation; economic development; artificial intelligence; regulatory policies 1. Introduction Superstar firms have become dominant in the global economy, reshaping industries and concentrating wealth (Amiti et al.,2024). With high productivity, innovation, and market leadership, they use global value chains (GVCs) and Global Wealth Chains (GWCs) to optimize production and consolidate influence (Bair et al.,2023). Their dominance has grown with digitalization, especially post-COVID-19 (Yoon,2020). This phenomenon is analyzed through theories and case studies across industries like entertainment and logistics (Guan,2023). The rise in superstar firms has drawn academic interest, focusing on their concentration and expansion. Key factors include market power, consumer behaviour, technology, Economies 2025,13, 52 https://doi.org/10.3390/economies13020052 Economies 2025,13, 52 2 of 20 and human capital (Eeckhout,2022), which have widened income disparities, highlighting the need for structural analysis (Autor et al.,2020). Countries that promote technological innovation attract and foster leading firms (Bloom et al.,2017). The literature highlights the impact of national contexts on superstar firms’ success. In Europe, these firms capture larger market shares while reducing labour participation by spreading fixed costs efficiently (Stiel & Schiersch,2020). Policies, technological infrastructure, and R&D funding are crucial for fostering innovation (Carrera Mora et al.,2021). The AI Readiness Index developed by the IMF measures a country’s capacity for technological advancement (Oxford Insights,2023). Recently, governments have aimed to attract tech firms through investments in data infrastructure, trade liberalization, and AI promotion (McKinsey Global Institute,2022). The concentration of superstar firms in certain economies can heighten inequality by concentrating profits and market power (Philippon,2019). Digitalization has provided advanced tools for data analysis and market segmentation, driving global expansion (Morillo-Aguilar,2022). Beyond innovation, economic sustainability—measured by the per capita GDP, labour productivity, and data infrastructure—also influences their growth. High-productivity economies with strong domestic markets facilitate expansion by lowering costs and increasing efficiency (Autor et al.,2020). This study introduces the Innovation Capabilities Index and the Economic Sustainability Index to analyze factors driving the concentration of superstar firms across different national contexts. Despite their global relevance, gaps remain in the understanding of the conditions that enable their emergence and sustainability, with limited research integrating innovation, economic development, and the role of national policies and market structures. This research aimed to address the question of what factors determine the concentration of superstar firms in specific economies, with three main objectives: analyzing the impact of these firms on economic growth and market capitalization, particularly regarding AI development; exploring their sectoral distribution in technology, finance, industry, and energy; and offering policy recommendations to help governments foster environments that support firm growth while tackling inequality and wealth concentration. By integrating technological, economic, and policy aspects, this study contributes to the ongoing debate on the role of superstar firms in global economic dynamics. As these firms reshape industries, regulatory frameworks must evolve to balance innovation-driven growth with sustainable development. Additionally, research has shown that corporate sustainability initiatives play a role in the expansion of superstar firms, as they adopt green supply chains, energy-efficient products, and renewable energy projects. However, challenges like “greenwashing”, where firms exaggerate their environmental efforts without meaningful change, have also been noted (Paluš et al.,2024;Lyon & Montgomery,2015). In global economic governance, there is a growing call for a cohesive, multilateral regulatory framework to address the transnational challenges posed by superstar firms (Mazur,2023). Additionally, a new research field is emerging on how these firms are reshaping labour markets, driving a transition toward highly digitized and specialized employment, and altering global skill demands (Biondo et al.,2024). In contrast to previous studies examining the impact of superstar firms on income distribution (Piketty,2014) or the labour market structure (Biondo et al.,2024), our research enhances understanding by introducing two key indices: the Innovation Capabilities Index and the Economic Sustainability Index. These indices assess the presence of superstar firms based on a country’s technological and economic environment and allow for the segmentation of economies into homogeneous groups according to their development and competitiveness. Economies 2025,13, 52 3 of 20 Our findings support previous studies on the role of AI and technological infrastructure in the concentration of these firms (Acemoglu & Restrepo,2018) but challenge the conventional view by showing that the correlation between superstar firms and AI development is moderate, suggesting other structural factors are involved. This study contributes to the literature by offering an innovative methodology to segment economies based on the superstar firm presence and providing an analytical framework to evaluate the conditions favouring their concentration. It also presents public policy recommendations supported by empirical data, offering tools to design strategies that enhance competitiveness while addressing economic inequality. Building on existing research on the impact of superstar firms on economic development and innovation (Autor et al.,2020;Brynjolfsson et al.,2019), our study took a novel approach by applying quantitative methods, including cluster analysis, correlations, and statistical models, using recent data from Statista for the year 2022. The article is organized as follows: Section 2reviews the literature on superstar firms, examining their definition, characteristics, and global economic impact, along with the factors promoting their concentration in specific countries and sectors and the implications for inequality and competitiveness. Section 3outlines the methodology, including the Statista dataset and statistical methods used to identify patterns and significant relationships. Section 4presents the analysis results, while Section 5discusses the findings in relation to the existing literature. Finally, Sections 6–8offer conclusions and public policy recommendations, highlighting the need for a supportive environment for these firms while addressing the challenges of their economic concentration. 2. Theoretical Framework The concentration of superstar firms in certain economies has captured the interest of academics and investment groups due to their significant impact on the global economy and the structure of local markets (Yoon,2020). These firms, characterized by their leadership in innovation, high market capitalization, and competitive advantages in terms of profitability and productivity, represent a distinctive phenomenon in the contemporary economy (Autor et al.,2020). However, the emergence and prevalence of superstar firms are not uniform across all contexts; instead, they are heavily influenced by the specific structural characteristics of each country, such as the innovation environment, competitiveness in attracting foreign direct investment (FDI), and economic sustainability (Brynjolfsson et al.,2019). The phenomenon of superstar firms not only redefines competitive dynamics at a global level but also has direct implications for the economic structure, such as the market concentration and income distribution (De Loecker et al.,2020). These firms often consolidate in specific sectors where their competitive advantages allow them to capture disproportionate market shares, contributing to increased income inequality and a decline in the labour’s share of the GDP (Autor et al.,2020;Abraham & Bormans,2020). This phenomenon is exacerbated by the growing digitalization of the economy and the effects of markets concentrating success in a few highly innovative and productive firms (Schulz & Mayerhoffer,2021). On the other hand, superstar firms also generate spillover effects in local and global markets. Recent research has suggested that these firms, by integrating with local firms through global value chains or foreign direct investment, significantly boost the productivity of linked firms, although these benefits are often accompanied by higher levels of concentration and unequal competition (Vrolijk,2021;Amiti et al.,2024). However, their high capacity for capital accumulation and low dependence on external financing can re- Economies 2025,13, 52 4 of 20 duce the resource allocation efficiency in global markets, exacerbating economic inequality (Xu et al.,2020). For this reason, the impact of superstar firms extends beyond the economic sphere to decision-making in education and employment (Choi et al.,2021). The visibility and success of these firms have influenced the choice of university careers, which, in the long term, can create imbalances between the supply and demand for certain types of human capital, negatively affecting initial wages in some sectors. As noted in Schumpeter’s seminal work, the development of innovation capabilities is highlighted as a fundamental element for creating leading firms, as innovative economies tend to generate favourable conditions for product and service differentiation, which is crucial to competing in highly dynamic markets (Aghion et al.,2019;Endzejczyk & Schmitka,2020). Similarly, a country’s capacity to attract investment and the stability of government support are decisive factors in the location of superstar firms, as a competitive investment environment allows these firms to access financial resources and achieve longterm stability (Globerman & Shapiro,2021). Thus, political stability plays a crucial role in attracting foreign direct investment (FDI), as it creates a predictable environment, improves investor confidence, and ensures property rights protection, fostering long-term stability for firms in competitive investment climates (Jansen,2024). Moreover, economic sustainability, reflected in labour market stability and high productivity, is essential for superstar firms to operate efficiently and project sustained growth (McKinsey Global Institute,2022). Consequently, economic sustainability, characterized by a stable labour market and high productivity, is crucial for firms to thrive. Increased labour productivity enhances economic growth and safeguards against external challenges by supporting operational efficiency and sustained growth for superstar firms (Fedulova et al.,2019). The relationship between the number of superstar firms—firms noted for their market influence and leadership—and a country’s economic and technological development has been extensively explored in the economic and business literature. Superstar firms, typically characterized by a high market capitalization and innovative capacity, not only lead in their respective sectors but also have a notable impact on the economies of their home countries. They also play a crucial role in generating productivity within their ecosystems, with positive spillover effects on other firms through their supply chains. These interactions not only improve the performance of collaborating firms but also encourage the adoption of advanced technologies and better business practices across industries (Amiti et al.,2024). Thus, superstar firms act as catalysts for economic and technological growth, promoting competitiveness in an increasingly dynamic global environment. Hence, it is suggested that the growth of these firms is associated with market concentration and productivity increases, which in turn reinforce their role in developing more robust and competitive economies globally (Autor et al.,2020). The literature shows that the presence of superstar firms is correlated with key economic variables such as the Gross Domestic Product (GDP) and corporate market capitalization. It has been confirmed that economies with higher market capitalization host more leading firms in strategic sectors, indicating a symbiotic relationship between GDP growth and the expansion of standout firms (Freund & Sidhu,2017). Recent studies have reinforced this connection, highlighting that a developed capital market not only drives economic growth but also fosters the expansion of key firms in strategic sectors. This is because superstar firms, by leading in market capitalization, contribute to sustainable economic growth while facilitating the adoption of advanced technologies and attracting capital. Consequently, the strengthening of financial markets Economies 2025,13, 52 5 of 20 and their interaction with the GDP is positioned as a key driver of economic development (Bekhti et al.,2022). Similarly, economic growth and market capitalization often accompany the emergence of these firms in advanced economies, suggesting a reciprocal relationship: while economic development drives the growth of superstar firms, these firms in turn contribute to GDP growth (Cabral,2021). Beyond traditional economic variables, the growth of superstar firms has been linked to the development and adoption of emerging technologies, particularly in AI. Investments in AI reflect nations’ commitment to incorporating cutting-edge technologies into their productive and governmental sectors. For this reason, leading firms tend to allocate significant resources to AI development and data management (DataAI), leveraging their financial capacity to remain at the technological forefront (Agrawal et al.,2018). The adoption of AI by the most influential firms in an economy can have a multiplier effect, contributing to the country’s technological advancement and strengthening the overall economic ecosystem (Acemoglu & Restrepo,2018). This leads to the formulation of the first hypothesis, which outlines whether the existence of superstar firms positively impacts their country of origin. The hypothesis to be addressed is as follows: Hypothesis 1. The number of superstar firms in a country is positively associated with higher market capitalization, GDP, and AI development. Classifying firms by their sector allows for a better understanding of how superstar firms are distributed and specialized across different sectors, which in turn can impact the economies in which they operate. In the literature, superstar firms are typically those firms that, due to their size, innovation, and market capitalization, exert disproportionate influence over the market and, at times, the regulatory framework of their sectors (Autor et al.,2020). The sectors in which these firms operate can determine their ability to innovate, attract significant capital, and develop and implement specific types of technologies. According to recent studies, the types of predominant firms in a country can significantly influence the presence of superstar firms, suggesting that these leading firms tend to be concentrated in certain sectors like technology and finance (Bessen,2019). Superstar firms in technological and financial sectors demonstrate a notable ability to attract capital and dominate in terms of the market share, while other sectors like industry and energy also hold considerable weight, albeit with different growth and competition dynamics (Bessen,2019). In line with this approach, the typology of a firm can be understood as a relevant variable for comprehending the distribution patterns of superstar firms across different countries. Based on the theoretical review, the following hypothesis was proposed: Hypothesis 2. The presence of superstar firms varies significantly according to the type of firm, being higher in technology and finance sectors compared to industrial and energy sectors. The segmentation of countries into groups or clusters based on their economic and technological characteristics is a common methodology in international economics studies to understand patterns of development and competitiveness. An approach that integrates the number of superstar firms—leading firms dominating the market in terms of capitalization and their innovation capacity—along with economic and technological development variables allows for the creation of country groupings with similar characteristics, facilitating comparisons of their development levels (Rodrik,2016). Thus, the presence of standout firms in an economy reflects not only a high level of competitiveness but also a robust Economies 2025,13, 52 6 of 20 technological infrastructure and an economic policy that fosters innovation and business growth (López-Rubio et al.,2024). Using cluster analysis in this context helps group countries according to the number of superstar firms and key economic variables such as the GDP and market capitalization, as well as AI development indicators. Previous studies have demonstrated that the number of superstar firms is often associated with economies that exhibit greater technological sophistication and highly competitive business ecosystems (Freund & Sidhu,2017). Particularly, more superstar firms tend to be concentrated in countries with a higher adoption of advanced technologies, especially AI, fostering clusters of innovation and sustained economic growth (Acemoglu & Restrepo,2018). Aligned with this, cluster analysis has been applied to identify patterns and similarities among economies with a high degree of AI development and concentration of high-performing firms. This suggests that clusters based on AI indicators and the concentration of leading technology firms allow for a better understanding of national innovation strategies and investment policies. According to the literature, certain groups of countries may share distinctive characteristics in terms of the number of superstar firms and levels of AI development, resulting in clusters defined by a combination of economic power and advanced technological capabilities (Agrawal et al.,2019). AI is therefore seen to play a key role in transforming the global business landscape and in the concentrationof superstar firms, as it enables processautomation, valuechain optimization, and the mass customization of products and services (Brynjolfsson & McAfee,2023) . In this study, AI was conceptualized as an indicator of technological development that influences the competitiveness and growth of market-leading companies. To measure this variable, data from Oxford Insights’ AI Readiness Index 2023 (Oxford Insights,2023), which assesses the ability of governments and private sectors to adopt AI, as well as information from Statista (2022) on AI investment in different economies, were used. Recent research has indicated that the presence of superstar firms is correlated with high levels of AI adoption, as these companies have the infrastructure, capital, and organizational capacity to lead the implementation of advanced technologies (Howard,2019). However, this study challenges the traditional view that directly associates AI development with the concentration of these firms, finding that the correlation between both variables is moderate, suggesting that there are other structural factors, such as market regulation and economic infrastructure, which also play a key role in shaping the global business ecosystem. Based on the theoretical review, the following hypothesis was proposed: Hypothesis 3. Countries group into homogeneous clusters based on their number of superstar firms, economic development, and AI advancement, with more superstar firms and AI advancements concentrated in the most competitive and developed countries. 3. Methodology 3.1. Variables and Methodology The analysis incorporated a set of key variables essential for understanding the impact of superstar firms across various economic sectors. Below is an outline of these variables, along with their descriptive statistical characteristics, summarized in Table 1. Additionally, for insights into the distribution of superstar firms by country, refer to Table A1 (Appendix A). To evaluate this relationship, firms were classified into categories or typologies based on their predominant sector, represented by dichotomous variables: T1 for energy firms (including oil, natural gas, and petrochemicals), T2 for technology firms, T3 for industrial Economies 2025,13, 52 7 of 20 and pharmaceutical firms, and T4 for the financial and investment sector. Each of these categories is associated with different business models, growth expectations, and sectoral regulations—factors that can impact each sector’s capacity to produce superstar firms (Koller et al.,2020). Table 1. Definition and description of key variables in analysis of superstar firms. Dep. Variable Nomenclature Total Superstar Firms Superstar Firms 100 Indep. Variable Nomenclature Mean Std. Des. Kurtosis Skewness Gross Domestic Product GDP 3994.987 7040.427 7.779 2.838 Market Capitalization MC 2751.748 8961.095 17.847 4.217 Total Artificial Intelligence 1Total IA 72.618 5.026 0.792 0.299 Energy Firms (Including Oil, Natural Gas, Petrochemicals) T1 0.441 0.5111 −2.199 0.244 Technology Firms T2 0.444 0.615 0.387 1.085 Industry and Pharmaceuticals T3 0.667 0.485 −1.594 −0.773 Financial and Investment Sector T4 0.388 0.501 1.987 0.498 1 where STATISTA defines AI as the following: “AI refers to the ability of a computer or machine to mimic the competencies of the human mind, which often learns from previous experiences to understand and respond to language, decisions, and problems”. Additionally, it was noted that the technology sector (T2) has exhibited exponential growth in the concentration of superstar firms, while the financial sector (T4) maintains a significant presence due to its ability to mobilize large volumes of capital (Freund & Sidhu,2017). In comparison, the industrial (T3) and energy (T1) sectors may have a lower concentration of superstar firms but remain relevant in emerging economies and nations with abundant natural resources. 3.2. Methodology The present study employed a combination of statistical analyses to explore the relationships between the number of superstar firms (leading firms) and various economic and technological variables. The methodology was divided into the following subsections: correlation analysis, a T-test for independent samples, an analysis of variance (ANOVA), and cluster analysis. The analyses were conducted using SPSS software, version 29. 3.2.1. Correlation Analysis Between Superstar Firms and Continuous Variables The purpose of this analysis was to determine whether there was a significant association between the number of superstar firms in a country and key continuous variables such as market capitalization (MC), the Gross Domestic Product (GDP), and the Artificial Intelligence Development Indicator (Total AI). Pearson’s correlation coefficient was used for this purpose, a statistical method that quantifies the strength and direction of linear relationships between variables. This is why we investigated part of the relationship between the market concentration and the decline in labour participation in the GDP (Autor et al.,2020). The calculation was performed using the following equation: r=∑Xi−XYi−Y q∑Xi−X2∑Yi−Y2(1) where X i and Y i represent the scores of each country in terms of the number of superstar firms and the selected continuous variables (market capitalization, GDP, Total AI), respectively. X and Y are the means of the corresponding variables. Economies 2025,13, 52 8 of 20 3.2.2. T-Test for Independent Samples: Superstar Firms and Firm Typology The purpose of this analysis was to understand the relationship between the number of superstar firms and the firm typology, represented by dichotomous variables (T1, T2, T3, T4), as outlined in Table 1. We evaluated both the differences in the average number of superstar firms based on the presence of each firm type and the impact of each typology on the likelihood of having a high number of leading firms (Church & Ware,2000). Here, the dichotomous variables (T1, T2, T3, T4) were configured as grouping variables to analyze whether significant differences existed in the number of superstar firms. For this purpose, a T-test for two independent samples was defined as follows: t=X1−X2 rs2 1 n1+s2 2 n2 (2) where X1 and X2 are the means of the superstar firms for each firm typology group. Thus, s2 1 and s2 2 are the variances for each group. Finally, n1 and n2 are the sample sizes for each group. 3.2.3. Analysis of Variance (ANOVA) Between Superstar Firms and Industry Types To further investigate the impact of superstar firms, the goal was to examine whether there were significant differences in the number of superstar firms across different industry types and if these differences were associated with variations in economic indicators such as market capitalization or the GDP. The analysis sought to identify which sectors, represented by categories such as T1, T2, T3, and T4, exhibited higher levels of market capitalization or the GDP based on the number of superstar firms present, shedding light on the sectorial impact of these leading firms on the studied economies. The methodological procedure was based on an analysis of variance using an ANOVA table, where industries were set as the categorical independent variable and the number of superstar firms as the dependent variable. This approach allowed for the modelling of the average differences in the number of superstar firms across industry types, with the equation used describing the relationship between the industrial categories and the dependent variable to assess the statistical significance of the observed variations (Ližbetinová et al.,2019). The equation was as follows: F=Between −group variation Within −group variation =∑K k=1nkXk−X2 ∑K k=!∑nk i=1Xik −Xk2(3) where K is the number of groups (industries), nk is the sample size of the group k, Xk e is the mean of group k, and X is the overall mean. 3.2.4. Cluster Analysis: Grouping Countries Based on Superstar Firms and Economic and Technological Development Variables The cluster analysis aimed to group countries based on their level of economic, technological, and business development, considering the number of superstar firms and other key variables such as AI development, the GDP, and market capitalization. This methodology allowed for the identification of similarities in development profiles between countries, revealing patterns that link the number of leading firms with economic and technological indicators and facilitating the classification of economies into homogeneous groups. To perform the analysis, a hierarchical clustering method was used, which allowed for the observation of how groups of countries formed at different levels of similarity. This approach used hierarchical cluster analysis, which typically measures the similarity Economies 2025,13, 52 15 of 20 Table 10. ANOVA. Cluster Error Root Mean Square gl Root Mean Square gl F Sig. Superstar firms 1067.676 3 1.670 14 636.278 0.000 Total AI 119.394 3 5.096 14 23.430 0.000 MC 16.788 3 0.567 14 11.972 0.000 GDP 15.515 3 0.508 14 10.856 0.001 1are worked in logarithms. 5. Discussion The results obtained in this study provide an interesting insight into the relationship between superstar firms and economic and technological variables, as well as the grouping patterns of countries. First, the findings indicate a strong correlation between superstar firms and other key variables, such as market capitalization (MC), the Gross Domestic Product (GDP), and artificial intelligence development (Total AI). Additionally, the cluster analysis and ANOVA tests revealed significant differences between groups of countries based on their performance on these variables. In the following, we will discuss these results in relation to the specialized literature. 5.1. Correlation Between Superstar Firms and Economic Variables The correlation analysis showed that superstar firms are closely linked with the GDP and market capitalization, supporting the idea that these firms are key players in national economies and their development. This relationship aligns with previous studies that have highlighted the impact of large firms on economic growth. Therefore, a significant portion of the economic output tends to be concentrated in superstar firms, as they not only generate a substantial share of employment and wealth but also lead technological innovations that drive economic growth (Autor et al.,2019). Additionally, the positive correlation with AI variables, especially the Total AI, suggests that the presence of superstar firms is linked to the technological development of countries. These findings align with what the literature suggests: large technological firms are not only drivers of economic growth but also catalysts for the advancement in the adoption of emerging technologies such as AI (Brynjolfsson & McAfee,2014). 5.2. Cluster Analysis: Grouping Countries Based on Economic and Technological Characteristics The cluster analysis revealed that countries were grouped into four distinct categories based on their performance on variables such as superstar firms, market capitalization, the GDP, and the Total AI. Cluster 1, which included the United States, stood out for its high concentration of superstar firms and significant development in AI, reinforcing the notion that countries with advanced technological sectors tend to have a higher concentration of prominent firms. This pattern aligns with the literature suggesting that countries with a competitive business environment and a robust technological sector are more likely to have a high number of outstanding firms (Cunningham et al.,2020). Cluster 2, which included China, showed a similar economic profile, although with fewer superstar firms. This could reflect the phenomenon of economic power being concentrated in a small number of technological firms, such as the large tech firms in China, which, despite their size, have not yet reached the concentration of firms like those in the United States. Thus, China has experienced explosive growth in technology and superstar firms, but the business concentration is still somewhat lower than in more developed countries, like the U.S. (Xu et al.,2020). Economies 2025,13, 52 16 of 20 As for Clusters 3 and 4, which grouped European and emerging countries, the lower presence of superstar firms and the reduced development in AI and market capitalization suggest a different economic structure, more distributed among medium and small enterprises. This observation allows us to see that in countries with more diversified and less concentrated economies, growth is more balanced, and the impact of superstar firms is smaller (Acemoglu et al.,2020). The results of the ANOVA tests show significant differences between the clusters in the variables of superstar firms, the Total AI, market capitalization, and the GDP, further reinforcing the idea that countries are grouped according to distinctive characteristics. This supports the notion that the concentration of wealth (in this case, represented by superstar firms) is strongly linked to economic development and the market structure (Piketty,2014). The difference in the means of superstar firms between the clusters underscores the central role of large firms in dominant economies, while the greater heterogeneity in the countries in Clusters 3 and 4 reflects less concentrated economies. The fact that superstar firms are associated with a higher GDP and market capitalization in Clusters 1 and 2 is also consistent with theories on the “economy of the few” (Gabaix,2016), which argues that a small number of large firms have a disproportionate impact on key economic variables in a country. The differences in the variability of market capitalization and the GDP across the clusters highlight the relevance of these firms in the global economic and financial structure. 6. Policy Implications It is essential that public policies promote a competitive environment through antitrust regulations that limit the excessive concentration of market power and encourage inclusive innovation through tax incentives and subsidies for emerging sectors and small businesses that have not yet reached a robust level of global competition. Additionally, it is recommended to invest in advanced technological infrastructure and human capital development, particularly in areas such as artificial intelligence and digital technology, to help less developed economies close technological gaps between them and leading countries. Public policies should also consider the creation of international governance frameworks to address tax evasion and harmonize regulations between countries to avoid regulatory arbitrage and ensure fair competition conditions. Furthermore, it is crucial to develop educational and continuous training programmes focused on STEM skills to prepare the workforce for the demands of digitized economies and minimize the adverse effects of labour displacement caused by automation and advanced technologies. In this context, sustainability should be integrated as a strategic axis through policies that encourage responsible and transparent business practices, avoiding phenomena like greenwashing and promoting business models that balance profitability with environmental and social responsibility. Finally, a balanced approach is required that prioritizes both global competitiveness and economic inclusion, ensuring that the benefits generated by superstar firms are distributed equitably and contribute to sustainable development. 7. Limitations and Future Directions While this study offers a significant contribution to the analysis of the concentration of superstar firms and its impact on economic development and technological innovation, it presents some limitations that should be considered. Economies 2025,13, 52 17 of 20 First, although the study employed recent data from Statista (2022) and applied rigorous statistical methodologies such as cluster analysis and a correlation analysis of economic variables, data availability remained a challenge. The research relied on a limited set of macroeconomic and technological indicators, which may not capture all dimensions that influence the concentration of these firms, such as fiscal policies, investment in education, or institutional stability. Second, this study focused on a country-level analysis, which allowed for the identification of general patterns in the distribution of superstar firms but did not address sectoral or regional dynamics within countries. Future research could delve deeper into the role of specific industrial clusters or the relationship between these firms and smalland medium-sized enterprises (SMEs) in different economic environments. Third, the methodology used allowed for the establishment of associations between variables, but not causality. Although we found strong correlations between the presence of superstar firms, the development of artificial intelligence, and GDP growth, we cannot claim that the existence of these firms is the direct cause of economic or technological development. Future studies could employ more advanced approaches, such as panel econometric models or causality analysis, to refine this relationship. Finally, this study integrated the impact of superstar firms on the global economy into academic debates, aligning itself with previous research highlighting their role in capital concentration and innovation (Autor et al.,2020;Bessen,2019), but also challenging certain traditional approaches by showing that the relationship with artificial intelligence is more complex than has been suggested. By proposing an analytical framework based on indices of innovation and economic sustainability, this article opens new lines of research on the interaction between public policy, technology, and the business concentration in the global economy. 8. Conclusions Superstar firms are emerging as key players in global economic dynamics, and their ability to concentrate wealth and generate technological innovation represents a major phenomenon. This study highlights that the concentration of these firms is not only linked to their size and market power, but also to their fundamental role in the adoption and development of advanced technologies, especially artificial intelligence. AI acts as a driver of transformation, allowing superstar firms to optimize processes, reduce costs, and improve the quality of their products and services. Significant investments in AI by these firms not only increase their competitiveness but also consolidate their dominant position in the market. This translates into a virtuous cycle where technological superiority fuels market growth and, in turn, allows superstars to explore new business opportunities through radical innovations. Furthermore, the presence of superstar firms in technology-intensive sectors, such as artificial intelligence, has profound implications for the structure of the labour market and income distribution. On the one hand, these firms generate high-quality jobs, but they can also contribute to growing inequality, as access to the skills needed to thrive in an AI-driven environment may be limited to a narrow portion of the population. Finally, it is crucial to consider that the dominance of superstar firms and their influence on the AI ecosystem pose significant challenges in terms of regulation and public policy. Policymakers must strike a balance between fostering innovation and ensuring that the benefits of economic growth are distributed more equitably. This includes considering strategies that promote effective competition and regulations that mitigate the risk of market power becoming even more concentrated in the hands of a few entities. Economies 2025,13, 52 18 of 20 Author Contributions: Conceptualization, J.L.G.B. and H.M.T.; methodology, A.M.P.; software, A.M.P.; validation, J.L.G.B., A.M.P. and H.M.T.; formal analysis, A.M.P.; investigation, J.L.G.B.; resources, H.M.T.; data curation, H.M.T.; writing—original draft preparation, A.M.P.; writing—review and editing, J.L.G.B.; visualization, J.L.G.B.; supervision, A.M.P.; project administration, J.L.G.B.; funding acquisition, J.L.G.B. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Informed Consent Statement: Not applicable. Data Availability Statement: The source of the data for Statista (www.statista.com (accessed on 4 February 2024)). Conflicts of Interest: The authors declare no conflict of interest. Appendix A Table A1. Relationship between countries and superstar firms. 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