Introduction

Innovation has been widely recognized as driving economic growth, firm competitiveness, and sustainable development (Antikainen and Valkokari, 2016). As technology advances and customer expectations rise, innovation becomes more crucial than ever (Waqas et al., 2021). Therefore, it is crucial for a business to keep up with the latest market trends to achieve success. To stay ahead of the competition, companies need to prioritize innovation in their products to meet the changing needs of their customers (Guerola-Navarro et al., 2022). Consequently, researchers, practitioners, and policymakers are interested in comprehending the dynamic interplay between innovation and organizational performance (Neely et al., 2001). Researchers have invested significant effort in understanding the complexities of this relationship. Meanwhile, professionals and policy-makers are working on creating successful innovation strategies that can positively affect industrial performance (Nigam and Boughanmi, 2017). Therefore, research on the innovation and industrial performance nexus is significant from a professional standpoint and merits consideration from a scholarly perspective.

Despite extensive research, the innovation-industrial performance nexus is still somewhat fragmented (Husin et al., 2020). This is because there is a wide variety of theoretical frameworks, methodologies, and empirical findings (Ismail and Abdmajid, 2007). Therefore, to obtain big-picture research on the innovation and industrial performance nexus, conducting a scientific study encompassing all related aspects is necessary. Several theoretical and empirical frameworks have been proposed to examine the relationship between innovation and industrial performance. Due to the dynamic changes in the environment, research on innovation and industrial performance is also evolving continuously (Makkonen et al., 2014). However, there is still a lack of scientific information concerning the evolution of innovation research in terms of industrial performance (Fiorentino et al., 2021). Consequently, the relationship between innovation and industrial performance in the past, present, and future has not yet been fully understood. Therefore, it is essential to map the research landscape to understand future research’s evolution, trends, and direction.

Existing research on innovation and industrial performance mainly focuses on empirical analysis. However, descriptive and network analysis of innovation research evolution associated with industrial performance received less attention. To fill the existing research gap, the current study employs a bibliometric approach to map the landscape of the innovation-industrial performance nexus. A bibliometric study is a quantitative analysis method used to assess academic publications’ impact, characteristics, and patterns using various metrics and statistics (Ninkov et al., 2022). Bibliometric methods are helpful, especially in capturing study areas’ intellectual structure and growth, detecting research trends and new subjects, and exposing academic collaboration patterns (Ding et al., 2016). In addition, it can help define the core themes and their relationships (Kasperiuniene and Faiella, 2023), which ultimately results in a more in-depth comprehension of the innovation-industrial performance nexus.

This study aims to comprehensively explore the relationship between innovation and industrial performance by identifying prevailing global research trends, thematic evolution, and knowledge gaps within the scholarly literature. Through a quantitative analysis, it will uncover key themes and connections among different studies. The research will shed light on how discourse has evolved over time. Additionally, it will propose directions for future studies by identifying gaps in the research related to innovation and industrial performance. This effort is not merely academic; it holds practical value for industry professionals, policymakers, and researchers. By demonstrating how innovation can be utilized to improve industrial performance, the study offers a framework for future research that aims to enhance both theoretical knowledge and practical implementations in the domain.

The originality of this study lies in its comprehensive bibliometric analysis designed to systematically map and analyze the global research landscape regarding innovation and industrial performance. Unlike previous investigations, which have typically been restricted to specific empirical contexts or isolated theoretical frameworks, this study adopts a holistic bibliometric methodology encompassing various advanced analytical techniques. These include word frequency analysis, co-occurrence network analysis, and thematic evolution mapping. Such methods enable the identification of broader thematic patterns and shifts in scholarly discourse, providing a clearer, more integrated understanding of how innovation strategies have evolved. This systematic approach helps bridge existing knowledge gaps by offering a coherent narrative that aligns innovation practices with contemporary global economic, technological, and environmental imperatives.

Furthermore, the research’s significance is heightened by its focused examination of contemporary themes, such as sustainability, green innovation, and Industry 4.0 topics that directly address some of the most pressing global challenges and opportunities facing modern industries today. As businesses increasingly grapple with sustainability demands and the transformative potential of digital technologies, understanding these emerging themes becomes crucial. By explicitly highlighting the transition toward sustainable and digitally integrated innovation practices, the study significantly enriches theoretical understandings and provides practical, actionable insights. These insights guide industry stakeholders, including business leaders and policymakers, enabling them to strategically adapt to complex market dynamics and evolving sustainability requirements.

This study contributes substantially to the existing knowledge base through its innovative methodological approach and focused exploration of timely thematic areas. By establishing a comprehensive analytical framework, the research offers significant theoretical contributions and practical implications. It underscores the importance of innovation in driving industrial performance and resilience, emphasizing the necessity for strategic alignment between innovation activities and evolving global challenges and opportunities. As such, it serves as a critical resource for both academia and industry, enhancing understanding and guiding strategic decision-making in innovation management amidst a rapidly changing global landscape.

Literature review

The nexus between innovation and industrial performance has been extensively studied across various national and regional contexts, revealing diverse insights into how innovation drives competitiveness and productivity. Despite the breadth of research, the literature remains fragmented, often focusing on localized empirical settings that limit comprehensive generalizations. In North America and Europe, studies frequently underscore the pivotal role of innovation in fostering competitive advantage and enhancing productivity. For instance, Neely et al. (2001) illustrated how innovation functions as a catalyst for organizational competitiveness, establishing a direct correlation with productivity and profitability within European manufacturing sectors. Complementing this, Makkonen et al. (2014) examined the influence of dynamic capabilities shaped by innovation, demonstrating their critical role in enabling North American firms to adeptly navigate economic crises. These dynamic capabilities not only mitigate adverse economic impacts but also reinforce firms’ competitive positions through sustained innovative practices. Collectively, these studies highlight the multifaceted ways in which innovation acts as a cornerstone for industrial success, although the fragmented nature of research indicates a need for more integrative analyses across diverse global contexts.

Research from Asia, particularly China, increasingly highlights the integration of sustainability and green innovation as pivotal components within the broader discourse of industrial growth. This focus is reflective of a growing recognition of the necessity to balance economic development with environmental stewardship. Guo and Xu (2021) underscored that digital transformation, coupled with sustainable innovation, plays a crucial role in enhancing firm performance in China’s manufacturing sector, suggesting that technological advancements can be harmoniously aligned with eco-friendly objectives. Furthermore, Khan et al. (2022) emphasized green innovation not merely as a supplementary approach but as an essential strategy to achieve energy efficiency and promote environmental sustainability. Their findings highlight the strategic importance of adopting eco-friendly technologies and practices, positioning them as key drivers for sustainable industrial growth across various Asian contexts. This body of research collectively illustrates how Asian economies are progressively embedding sustainability into the core of their industrial development agendas, reflecting a paradigm shift toward more responsible and resilient growth models.

In Latin America and Africa, the literature extensively highlights both the challenges and opportunities tied to innovation policy and entrepreneurial ecosystems, reflecting the regions’ diverse socioeconomic landscapes. Nigam and Boughanmi (2017) delved into innovative practices aimed at addressing financial distress within emerging economies, underlining how entrepreneurial policy frameworks can significantly enhance resilience and foster economic stability. Complementing this, Fiorentino et al. (2021) examined the pivotal role of innovation during the early growth stages of startups in Italy, presenting insights that are highly relevant to Latin American contexts due to shared entrepreneurial dynamics and economic hurdles. These studies collectively shed light on how tailored innovation strategies and supportive policies can drive sustainable growth and adaptability in varying economic environments.

The geographical variability inherent in innovation practices underscores the necessity of adopting an integrated global perspective that considers the dynamic interplay between local conditions and overarching global trends. Although existing studies extensively cover various aspects of innovation, they often fall short in synthesizing these diverse contexts into a cohesive framework, leaving a notable gap in comprehensive understanding. Our study seeks to bridge this gap through a holistic bibliometric analysis approach, systematically examining and synthesizing literature from a broad spectrum of geographical contexts. This methodology not only unifies disparate regional insights but also elucidates the global landscape of innovation and industrial performance. By doing so, it enhances our understanding of regional trends and provides valuable insights that can guide strategic decisions with global relevance, ultimately fostering more informed and effective innovation strategies worldwide.

Methodology

Data sources and collection

Figure 1 illustrates the sequential process that has been done in order to collect data. The first step is to search for relevant documents in the Scopus database. Scopus was selected as it is one of the most comprehensive and recognized academic databases in business, management, accounting, economics, and finance disciplines. Its extensive coverage, rigorous indexing standards, and wide acceptance among bibliometric researchers ensure a high degree of reliability and representativeness of the collected data (Baas et al., 2020, Vila et al., 2020, Pranckute, 2021). The study used specific words to find the sources of the documents needed. Since the study looked into the relationship between innovation and industrial performance, the keywords “innovation,” “industrial,” and “performance” were used in the document searching process. The document search results in step 1 yielded a total of 8,615 documents. The document produced in Step 1 is a compilation of various publications from different fields of study, including journals, proceedings, and books. As a result, the document must be filtered to ensure that it meets certain source and field of study requirements.

Fig. 1
figure 1

Stages of data collection.

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In the second stage of the process, document filtering was conducted to ensure that only publications meeting specific criteria were included. This step is essential to prevent an overly broad discussion of the topic. The study has limited its focus to documents pertaining exclusively to business, management, accounting, economics, econometrics, and finance, as these fields are directly relevant to the research question being addressed. Following the application of the filtering process, a total of 3,905 documents were retained in step 2. These documents possess a high degree of relevance to the research question.

The third step is determining the source of documents and the language. The documents that have been provided are restricted to journal sources written exclusively in the English language. This study only included journal sources because they were selected through the peer-review process. The peer review process ensures that the document meets journal publication quality standards. English was chosen as the preferred language due to its widespread use in scientific communication on a global scale. After considering the sources of documents (journals only) and language (English), the final document for analysis is 2712.

Data analysis

The study utilized the RStudio software and the Bibliometrix R package to perform bibliometric analysis. RStudio is an integrated development environment (IDE) for the R programming language, which is widely used for statistical computing and data analysis (Racine, 2012). Meanwhile, Bibliometrix is an R package specifically designed for quantitative research in bibliometrics and scientometrics. Bibliometrix allows users to comprehensively analyze scientific literature data, such as citation and co-citation analysis, collaboration networks, and thematic analysis (Aria and Cuccurullo, 2017). It supports importing bibliographic data from various sources and offers descriptive analysis as well as network analysis. A description of the bibliometric analysis and aspects of each analysis are presented in Table 1.

Table 1 Description of bibliometric analysis.
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Results and discussion

Trend topics analysis

The field of innovation and industrial performance studies is constantly evolving, as illustrated in Fig. 2. In this analysis, we identify the trend of the topics for the last 16 years (2008–2024). During the initial period (2008–2010), the research community’s attention was largely focused on foundational elements of business strategy. Terms like ‘learning,’ ‘knowledge management,’ and ‘competitiveness’ began to surface, reflecting an early emphasis on the intrinsic capabilities that enable businesses to perform and sustain in a competitive environment. This period can be considered one where the groundwork for understanding the essential drivers of business performance was being laid down, with a particular focus on the cultivation of internal knowledge and competencies as critical resources.

Fig. 2
figure 2

Trend topics over time.

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The Rise of Innovation and Entrepreneurship presents during 2011–2015. This phase marks a significant expansion in the scope of research with a pronounced emphasis on ‘innovation’ and ‘entrepreneurship.’ The surge in these terms corresponds with a global increase in technological advancements and a burgeoning startup culture, emphasizing the role of innovation as a key driver of economic growth and entrepreneurship as a mechanism for commercializing innovative ideas. During this time, the literature starts to reflect an understanding of innovation not just as a product or a process but as a systemic phenomenon that encompasses a wide range of business activities.

Post-2015, between 2015 and 2019, the academic narrative began to consolidate around the operationalization of innovation. Research terms, such as ‘innovative performance,’ ‘productivity,’ ‘business performance,’ and ‘financial performance’ gain traction, indicating a shift toward measuring the outcomes of innovation activities. This period reflects an increased scholarly interest in understanding how innovation impacts firm-level performance metrics, productivity, and financial results and how businesses can harness the power of innovation to achieve tangible results.

The period between 2020–2023 is the emergence of sustainability and Industry 4.0. In this period, the focus of research has evolved to encompass emerging trends, such as ‘sustainability,’ ‘green innovation,’’ ‘environmental performance,’’ and ‘industry 4.0’. This shift is indicative of the growing importance of integrating environmental considerations into business strategy and the transformative impact of the fourth industrial revolution. Research in this period reflects an acute awareness of the critical need for businesses to adapt to sustainability challenges while leveraging the advancements in digital technologies characteristic of Industry 4.0.

This section aims to explore how the field of innovation and industrial performance has evolved based on trending topics. The analysis shows that this field is constantly changing, driven by global economic, technological, and environmental trends. The study divides the development of the field into different phases, each characterized by a shift in research focus. Initially, researchers focused on understanding the fundamentals of successful business strategies that could help companies stay competitive in their respective industries. However, as time progressed, researchers became more concerned about sustainability and the adoption of eco-friendly practices. This shift in focus was due to the growing recognition that businesses have a responsibility to protect the environment and reduce their impact on the planet (Khan et al., 2022).

In recent years, the field has seen another significant shift in research focus toward the adoption of advanced digital technologies. This shift is due to the increasing importance of technology in business operations, as well as the recognition that digital innovations can significantly impact a company’s performance and success (Guo and Xu, 2021). Taken together, the study highlights the dynamic and responsive nature of academic inquiry in the innovation and industrial performance field. Researchers are continually adapting their focus to reflect the changing needs and priorities of businesses, as well as the broader economic, technological, and environmental trends shaping the world today.

Network analysis

Co-occurrence network

Co-occurrence networks are visual representations of the connections between different elements in a dataset (Ozek et al., 2023). These elements could be anything from keywords to authors or institutions. The main purpose of co-occurrence networks is to analyze the relationships between large datasets (Radhakrishnan et al., 2017). In the context of bibliometric analysis, a co-occurrence network is created by identifying pairs of elements that appear together frequently in documents (Qiu et al., 2014). This helps to build the network. Co-occurrence happens when two or more elements are found in the same document more often than would be expected by chance (Su and Lee, 2010). Figure 3 shows the results obtained from the co-occurrence networks. According to these results, there are four distinct clusters of nodes (Red, Blue, Green, and Purple).

Fig. 3
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Co-occurrence network.

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The Co-Word network cluster in Table 2 provides a quantitative description of the Co-occurrence network shown in Fig. 3. A node’s betweenness is a measure of how much it lies on the shortest paths connecting it to other network nodes. Nodes with high betweenness scores represent significant research themes or authors that connect different fields or sub-disciplines (Diallo et al., 2016). A node’s closeness is a measure of the average distance that separates it from all other nodes in the network. High Closeness nodes indicate research topics or authors that are closely related to a wide range of other research topics, which suggests their interdisciplinarity and significance in the field (Thurner et al., 2020). PageRank is a ranking algorithm that assigns a value to each web page based on its importance (Sharma et al., 2020). In a co-occurrence network, PageRank can be used to evaluate the influence of research themes, authors, or publications. When determining a node’s importance, PageRank considers its connections’ quantity and quality. This ensures that nodes with connections to influential nodes receive higher importance scores.

Table 2 CoWord Network Cluster.
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Cluster 1 (Red node) encapsulates the core concepts of innovation and its direct impact on firm performance. ‘Innovation’ stands out with the highest betweenness centrality, underscoring its crucial role as a linchpin within the network. It is pivotal in the literature because it likely connects disparate topics, indicating that discussions around innovation often serve as a bridge to discussions around other related concepts. Other nodes in this cluster, although having a closeness and PageRank that suggest relevance, do not serve as central connection points in the literature, possibly because they are often discussed within the context of innovation rather than as standalone topics, or they might be emerging topics that are yet to establish strong linkages within the existing literature.

Cluster 2 (Blue node) delves into the mechanisms and processes of innovation within SMEs. The relatively higher values of betweenness for nodes, such as ‘Innovation Performance’ and ‘Absorptive Capacity’ suggest that these concepts are crucial in connecting research on SMEs with broader innovation discussions. The presence of ‘Knowledge Management’ with no betweenness but some closeness and PageRank implies that while it is an important topic, it may not be central to the current scholarly dialog on innovation within SMEs, but is nonetheless closely related to other key concepts within the cluster.

Cluster 3 (Green) reflects the outcomes of innovation processes. The node ‘Performance’ has a significant betweenness score, illustrating its centrality and indicating that discussions on performance are often situated at the intersection of various research themes within this domain. It is conceivable that ‘Performance’ serves as a common outcome measure for various types of innovation (product, process, etc.), thus its central position. The presence of ‘Dynamic Capabilities’ and ‘Market Orientation’ with lower betweenness but notable closeness and PageRank suggests these are emerging areas of interest that are becoming more central to the discourse on innovation outcomes.

Cluster 4 (Purple) points to a geographic and environmental dimension within the innovation literature, particularly focusing on the context of China and the incorporation of sustainability and environmental considerations in innovation. The high betweenness for ‘China’ indicates that China is a significant case study or context through which scholarly discussions on innovation are being channeled. Similarly, ‘Sustainability’ and ‘Green Innovation’ with high betweenness signify the growing centrality of environmental considerations in innovation research. The zero betweenness for ‘Environmental Performance’ and ‘Eco-Innovation,’ despite having closeness and PageRank, could suggest that these are specialized topics that have not yet become central connectors in the literature but are nonetheless recognized for their importance in the field.

Thematic evolution

Figure 4 provides a bibliometric analysis detailing the thematic evolution of topics within the realm of innovation and industrial performance from 1969 to 2024. The analysis is divided into five periods of time. The period between 1969 and 2007 is the foundational period. During this formative era in the study of business and management, the literature focused primarily on foundational concepts. Competitiveness was often scrutinized, with an emphasis on how businesses could establish and maintain a competitive edge through innovation performance. Knowledge management began to be recognized as a pivotal element, with studies exploring how effectively managing knowledge resources could drive innovation and improve overall productivity. This period laid the groundwork for understanding the intrinsic elements that contribute to a firm’s performance and its ability to innovate.

Fig. 4
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Thematic Evolution.

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Expansion and diversification are identified in the period between 2008–2014. In these years, the academic dialog expanded beyond the internal dynamics of firms to include the impact of broader entrepreneurial activities and the systemic aspects of supply chain management. The concept of technology transfer gained attention, highlighting the importance of transferring knowledge from research to practical applications in business. Open innovation emerged as a new paradigm, signaling a shift toward leveraging external sources of innovation and collaborating beyond traditional corporate boundaries. This period marked a transition toward embracing a more holistic view of innovation as an interconnected process.

Periode between 2015–2018 is characterized by integration and collaboration. This interval saw the integration of sustainability into the innovation conversation, indicating a pivot toward long-term, responsible business practices. The focus on service innovation revealed a broadening of the innovation scope, moving past tangible products to include intangible services. Open innovation continued to be a major theme, emphasizing the significance of collaborative efforts and partnerships in driving innovation. The discourse during this period underscored the necessity of blending innovation with strategic partnerships and sustainable practices.

The literature from 2019 to 2021 underscored the application of innovation in more targeted ways. Innovation policy and management became central topics, reflecting a concern with how policies can foster innovation ecosystems and how innovation can be managed to maintain competitiveness. Attention to SMEs highlighted the role of smaller firms in innovation, suggesting a democratization of the innovation process. Productivity remained a concern, now discussed in conjunction with R&D and policy, to elucidate how innovation could be harnessed to drive economic and industrial efficiency.

Looking to the most recent (2022–2024) and upcoming years, green innovation and the principles of Industry 4.0 are projected to take center stage. This focus suggests a dual agenda: driving innovation while maintaining a commitment to environmental stewardship. The inclusion of SMEs indicates continued interest in understanding how smaller businesses adapt to and instigate innovation. Policy discussions are expected to revolve around how to create conducive environments for sustainable innovation and how to leverage technological advancements for sustainable development.

The thematic evolution in the innovation-industrial performance nexus, as highlighted in the bibliometric analysis, marks a significant paradigm shift from an internal, firm-centric view to a broader, more holistic, and sustainable approach. This transition mirrors underlying transformations in global socio-economic and technological landscapes, necessitating a corresponding evolution in business, management, and accounting practices. Initially, the focus within this nexus was predominantly on internal firm dynamics, emphasizing competitiveness and knowledge management. This approach was aligned with the traditional view of business as an isolated entity competing in a market. However, over time, the scope widened, acknowledging that innovation and performance extend beyond the confines of a firm and are influenced by a myriad of external factors, such as supply chains, technological developments, and broader economic trends (Cricelli et al., 2022).

The literature also shows an increasing emphasis on collaboration and open innovation, reflecting an understanding that innovation often results from the cross-pollination of ideas and technologies across different entities (Vivona et al., 2023). This includes competitors, academia, and research institutions, leading to more robust and creative solutions and driving industry and sector-wide advancements. Furthermore, recent trends emphasize sustainability and responsible innovation, aligning with global concerns about environmental impact and the necessity for long-term viability. This integration of sustainability into business practices indicates a recognition that long-term industrial performance depends on environmental stewardship and social responsibility, in addition to economic success (Gallardo-Vázquez et al., 2023).

Thematic map

Figure 5 presents a detailed thematic map that vividly illustrates the intricate research landscape exploring the dynamic connection between innovation and industrial performance. This meticulously crafted map is segmented into distinct clusters, each symbolizing a unique area of focus within this evolving field. Themes depicted on the map are categorized based on their centrality and level of development, leading to the formation of four distinct categories: niche, basic, motor, and emerging or declining. Each category reveals valuable insights into how different themes interact and evolve over time, providing a comprehensive overview of the current state of research in this field.

Fig. 5
figure 5

Thematic map.

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Motor themes are well-established research topics with a vast body of literature and significant cross-disciplinary connections (Chen et al., 2019). These themes are well-established and drive research in the field, influencing many other areas. Niche themes are specific research areas with limited interaction with other themes, characterized by high density but low centrality (Ho et al., 2021). These themes may indicate specialized topics or emerging areas that have not yet gained widespread influence.

Emerging or declining themes are characterized by lower density but higher centrality. Such themes can either be new areas that are beginning to gain attention and engage with established themes or older areas that are losing their significance but still maintain connections to other themes (Sadatmoosavi et al., 2021). Basic themes are characterized by having low density and low centrality. The research areas are not well-developed and lack significant interconnections with other areas in the field (Rejeb et al., 2023). These themes may represent either emerging areas or peripheral topics that have yet to gain traction.

Table 3 provides a quantitative description of the prevailing themes presented in Fig. 5. At the forefront of this analysis is the term ‘Innovation,’ which appears with the highest frequency, indicating its undoubted centrality in the discourse. The term serves as a nucleus around which other thematic elements revolve, illustrating its foundational role in the nexus under study. The occurrence of ‘Firm Performance’ as the second most prevalent term suggests a strong scholarly focus on the outcomes and impacts of innovation. The significance of ‘China’ as a frequently occurring term may point to the country being a case study or a significant player in the innovation discourse, possibly due to its rapid industrial growth and focus on innovation as a national strategy.

Table 3 Thematic map terms.
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The clustering of terms into themes reveals a structured and multifaceted research landscape. Each cluster encapsulates a specific aspect of the broader theme, with Cluster 1 centered around the core concept of ‘Innovation’ and Cluster 2 delving into ‘Innovation Performance.’ This progression from basic innovation concepts to their performance implications suggests a logical flow of research interests and inquiries. Cluster 3, with ‘Performance’ at its core, expands the discussion to the determinants of performance, including entrepreneurship and research and development activities. The emergence of ‘Technological Innovation’ alongside ‘Sustainability’ and ‘Green Innovation’ in Cluster 6 highlights a significant pivot toward environmental considerations, reflecting the increasing integration of sustainability goals in innovation strategies.

The network metrics, Betweenness, Closeness, and Page Rank, bring additional depth to the analysis. High betweenness for ‘Innovation’ and ‘China’ highlights their role as pivotal themes that connect disparate strands of research, suggesting that these terms are integral in the flow of ideas within the network. Closeness underscores the accessibility of a term within the network, with ‘Innovation’ and ‘Firm Performance’ being central and thus likely to appear across a wide range of research sub-fields. The Page Rank scores align with these findings, indicating the overarching influence and authority these terms have in the literature.

The thematic map serves as a visual synthesis of the data, charting the terms based on their centrality and density. The map showcases ‘Innovation Performance,’ ‘SMEs,’ and ‘Product Innovation’ as both central and dense, indicative of their status as ‘Motor Themes,’ well-established and pivotal in driving the field’s research agenda. On the other hand, ‘Business Performance’ and ‘Knowledge Management’ are categorized as ‘Niche Themes’, suggesting that while they are developed themes, their influence is more specialized within the field. ‘Basic Themes’, such as ‘Innovation,’ ‘Firm Performance,’ and ‘R&D,’ are foundational and ubiquitous throughout the research network, underscoring their importance in the literature.

This comprehensive bibliometric analysis uncovered a dynamic and vibrant research ecosystem that stands out for its unwavering emphasis on innovation as a pivotal determinant of industrial performance. The data intricately delineates a scholarly landscape that concentrates on foundational principles and actively branches into emerging areas of interest, such as sustainability. This shift reflects a broader and increasingly significant trend toward integrating environmental concerns within the strategic framework of innovation, highlighting the necessity for industries to adapt to evolving ecological imperatives.

The clusters and network metrics offer a strategic guide for academia and industry, signaling well-established domains and highlighting potential avenues for future research and exploration. Zhu et al. (2023) suggest that future research should explore the implementation path to stimulate innovation vitality and sustainable development potential. The study maps out a dynamically evolving domain, deepening its engagement with established knowledge while extending its reach into new thematic areas. The transition toward topics, such as ‘Green Innovation,’ signals a responsive shift in the academic and industrial communities, aligning with global sustainability imperatives (Oduro et al., 2022).

Discussion

This study comprehensively explores the nexus between innovation and industrial performance, uncovering clear thematic evolutions and global research trends within the scholarly literature. Our findings indicate a significant transformation of research focus over time, initially emphasizing foundational competitive strategies and internal organizational competencies. This early phase highlighted the importance of leveraging internal knowledge and capabilities to secure competitive advantages. Subsequently, research attention has progressively shifted toward sustainability-oriented innovation and the integration of Industry 4.0 technologies. This contemporary shift aligns with broader global economic, technological, and environmental dynamics, underscoring innovation’s critical role as a catalyst for sustainable competitiveness and industrial resilience amid rapidly changing market conditions.

The bibliometric analysis reveals substantial geographical variability in innovation practices and emphases across different regions. Research originating from North America and Europe primarily links innovation to competitive advantage, productivity enhancement, and resilience during periods of economic crises (Neely et al., 2001, Makkonen et al., 2014). These studies typically examine how innovation-driven practices enable firms to sustain performance and navigate economic challenges effectively. In contrast, studies from Asian contexts, notably China, prominently emphasize sustainability and green innovation as central strategies for achieving balanced industrial growth (Guo and Xu, 2021, Khan et al., 2022). This regional focus illustrates the increasing recognition of the necessity for industries to harmonize economic objectives with environmental responsibilities. Meanwhile, literature from Latin America and Africa underscores the critical role of innovation policy frameworks and entrepreneurial ecosystems in addressing unique economic constraints and fostering resilience (Nigam and Boughanmi, 2017, Fiorentino et al., 2021). These findings collectively indicate that innovation strategies are context-dependent, deeply influenced by distinct regional economic conditions and institutional frameworks. Our findings stress the necessity for integrated, globally informed innovation strategies that acknowledge and leverage these regional distinctions effectively.

Notably, the analysis identifies sustainability and Industry 4.0 as emergent dominant themes within the innovation literature, reflecting contemporary socio-economic and technological imperatives. The increased emphasis on sustainability indicates a profound alignment of innovation practices with global environmental goals, underscoring the imperative for firms to adopt sustainable business models actively. Concurrently, the prominence of Industry 4.0 underscores the transformative potential of digital technologies in enhancing operational efficiency, productivity, and global competitiveness. This dual emphasis highlights that innovation strategies must now comprehensively integrate sustainability principles alongside digital transformation initiatives, marking a critical strategic shift necessary for firms seeking long-term viability and success.

Furthermore, the thematic evolution mapping clearly underscores the growing integration of interdisciplinary perspectives within innovation research. The noticeable move toward collaborative and open innovation paradigms illustrates an expanded understanding of innovation as a collaborative, systemic phenomenon, transcending traditional, firm-centric frameworks (Vivona et al., 2023). This trend demonstrates the practical necessity for industry stakeholders to cultivate multi-stakeholder partnerships and cross-sectoral collaborations actively. Such collaborative frameworks are increasingly recognized as essential for generating robust, innovative solutions to complex industrial and environmental challenges. This aligns with findings by Cricelli et al. (2022), who emphasize the strategic value of collaborative innovation ecosystems, indicating that broader stakeholder involvement can significantly enhance innovative outcomes and sustainable performance.

Nevertheless, our bibliometric approach has inherent limitations, particularly related to potential regional biases resulting from the overrepresentation of studies from specific countries, notably China. This concentration raises legitimate concerns about the risks of over-interpretation and challenges to the generalizability of the findings across diverse contexts. In response, we advocate for future research explicitly targeting underrepresented regions or undertaking comparative analyses across diverse geographic contexts to ensure broader representativeness. Additional methodological limitations include the study’s reliance exclusively on publications in English, potentially excluding significant research contributions available in other languages. Consequently, future bibliometric analyses could significantly benefit from adopting multilingual approaches and broader data sources, such as industry reports and gray literature, enhancing the comprehensiveness, depth, and diversity of the analytical foundation.

This research offers several significant strategic implications for academia, policymakers, and industry practitioners. For academia, our study explicitly identifies critical future research trajectories, emphasizing areas, such as eco-innovation, interdisciplinary collaborations, and sector-specific analyses related to the adoption and impact of Industry 4.0 technologies. Policymakers gain actionable insights on developing supportive regulatory frameworks and incentive structures designed to stimulate sustainable and digitally driven industrial transformation, crucial for addressing contemporary global challenges. For industry practitioners, the study underscores essential strategic priorities, including the imperative to embed sustainability practices deeply within corporate strategy, adopt digital technologies proactively, invest in workforce skill development, and drive organizational culture transformations toward innovation-centric and sustainable practices. Collectively, these comprehensive insights support more informed strategic decision-making, empowering diverse stakeholders to foster innovation that effectively addresses global challenges while promoting sustainable and resilient industrial growth.

Conclusions

The analysis of innovation and industrial performance has illustrated significant transformations over time, reflecting intricate interactions among global economic, technological, and environmental dynamics. Initially, research predominantly focused on foundational competitive strategies, emphasizing internal knowledge acquisition and the development of core competencies as critical elements necessary for firm competitiveness. These foundational approaches largely prioritized understanding how internal organizational capabilities could be leveraged to gain a competitive advantage in the marketplace. As research progressed, attention expanded to incorporate entrepreneurship and productivity considerations. This broader perspective recognized the critical role entrepreneurial activities and productivity improvements play in driving economic growth and enhancing competitive positions, thereby extending both the theoretical and practical dimensions of innovation studies.

More recently, scholarly discourse distinctly emphasizes sustainability and Industry 4.0, reflecting a clear alignment with contemporary socio-economic imperatives and global environmental concerns. Emerging themes, such as sustainability, green innovation, and the incorporation of advanced digital technologies into industrial practices, have emerged as focal points within innovation literature. These themes indicate a significant shift toward integrating ecological and technological considerations into strategic frameworks. This shift is critical because it underscores the necessity for firms to adapt to environmental challenges, utilize sustainable resources effectively, and leverage technological advancements strategically. Incorporating sustainability practices and Industry 4.0 technologies is not merely advantageous but essential for ensuring long-term viability and competitive success within increasingly complex and demanding global market environments.

Furthermore, the present study explicitly aligns historical developments and thematic evolutions within the innovation literature with the central research objectives, providing a robust analytical framework that offers clear insights into effective innovation strategies in contemporary industrial contexts. The findings reveal a pressing need for organizations to integrate sustainability-oriented practices alongside advanced Industry 4.0 technologies strategically. Such integration serves not only to sustain competitive advantages but also to equip firms with the resilience and agility necessary to navigate rapidly changing market conditions and evolving global challenges. The insights derived from this study carry substantial practical implications for industry stakeholders, policymakers, and the academic community. Specifically, it highlights priority areas requiring focused strategic attention, interdisciplinary research initiatives, and collaborative efforts across various sectors to foster sustainable industrial growth and innovation.

Implications

Implications for knowledge and future research agenda

The study contributes to the academic understanding of innovation and industrial performance. It provides a comprehensive analysis of the field’s current research trends and geographic contributions. The study highlights the growing emphasis on sustainability and technological advancements in innovation, which is vital in the current global scenario. It also identifies areas with limited existing literature, providing a valuable guide for researchers looking to explore new avenues of research. The insights from this study are of great value to academic institutions, as they can leverage this knowledge to refine their research agendas and educational offerings. This will help align their academic pursuits with the changing global demands and trends, making their scholarly endeavors in business, management, and accounting more relevant and impactful.

Advocating for an interdisciplinary approach to modern industrial challenges showcases the complexity of today’s innovation. This perspective integrates fields like business, technology, environmental science, and public policy for more effective problem-solving. It acknowledges that contemporary issues require collaboration beyond single disciplines, fostering a holistic research environment. By dismantling traditional academic barriers, interdisciplinary research results in comprehensive studies that capture real-world complexities. This approach generates more profound insights and practical solutions tailored to the interconnectedness of various industries, enriching academic discourse and enhancing research applications for complex industrial problems and challenges.

The study maps global trends in innovation and industrial performance research. It identifies underexplored regions and topics, suggesting avenues for future investigation and funding. It also highlights the evolution of research priorities over time. This overview is essential for academic institutions and researchers in business, management, and accounting, informing strategic decisions about increased focus or investment. Fostering a balanced global research landscape addresses emerging trends and regional disparities in innovation and performance work.

Future research in eco-innovation should focus on the implementation and impacts of strategies across various industries. This agenda requires examining how new legislation for environmental sustainability integrates into corporate operations and culture. A key part of this study is evaluating the effectiveness of these laws and policies. Additionally, comparative analyses are necessary to explore how eco-innovation strategies differ and produce varying results across regions and industries. Such studies will provide insights into regional and sector-specific challenges and opportunities in eco-innovation, contributing to a clearer understanding of how different environments affect the adoption and success of these strategies.

Future research should explore collaboration and open innovation in addressing global sustainability challenges. The goal is to analyze international partnerships’ and cross-sector collaborations’ roles and impacts on sustainable business practices. Understanding how diverse stakeholders, including governments, private entities, and NGOs, interact toward common sustainability goals is essential. Additionally, examining models of open innovation will assess their effectiveness in promoting inclusivity within the innovation process. Such studies will show how open innovation can enhance participation and knowledge sharing, resulting in more equitable outcomes. This research is critical for understanding collaborative innovation’s role in fostering sustainable, inclusive industrial development practices.

The evolution of Industry 4.0 requires extensive research on how businesses adapt their models to leverage new technologies. This research should explore integrating digital technologies, AI, and automation in various sectors to assess their impacts on business performance, operational efficiency, and sustainability. Studies will reveal these technologies’ challenges and opportunities, particularly in enhancing productivity, fostering innovation, and promoting sustainable practices. Understanding the implications for workforce dynamics, skill needs, and organizational structures is also crucial. This analysis helps businesses and policymakers navigate Industry 4.0 complexities, aligning tech adoption with broader economic, social, and environmental goals.

Implications for business practice

The study emphasizes the importance of integrating sustainability into companies’ basic strategies. This goes beyond simply following environmental regulations and requires a shift toward sustainable business models. This transformation necessitates the development of environmentally friendly products and processes. The strategic realignment serves a dual purpose: meeting the growing consumer demand for sustainable products and positioning businesses to navigate impending regulatory changes and market fluctuations. This approach is not only an ethical imperative but also a strategic maneuver to maintain relevance and competitive advantage in a rapidly evolving global market where sustainability is increasingly becoming a key determinant of the success of business organizations.

Companies must adapt to maintain a competitive edge in today’s fast-evolving business landscape. The rise of Industry 4.0 includes advanced technologies like artificial intelligence (AI), the Internet of Things (IoT), and big data analytics, necessitating a transformation that integrates these tools into core processes. Employee training is crucial to equip the workforce with the skills needed for effective tool utilization. Additionally, businesses must update their models to leverage technology’s potential fully. This multifaceted approach enables businesses to thrive in the digital and technological revolution, securing a sustainable competitive advantage.

Business organizations must prioritize innovation and sustainability through cultural transformation, requiring a significant shift in values and practices. Strong leadership commitment is essential for setting the organization’s tone and direction. Leaders must actively embody innovation and sustainability principles. Employee engagement is crucial; all levels of staff should be empowered to contribute ideas and participate in innovative processes. Organizations must foster an environment where experimentation is encouraged and sustainable practices are rewarded. This involves embracing failures as learning opportunities and fostering a culture that drives continuous innovation and sustainability for long-term success in a competitive landscape.

This study offers significant implications for industrial practice, particularly emphasizing the strategic integration of sustainability and Industry 4.0 technologies into business operations. Firms should leverage insights derived from this research to align their innovation strategies effectively with contemporary competitive requirements. The findings underscore actionable strategic directions, highlighting sustainability integration and advanced digital transformation as pivotal for maintaining competitive advantage amidst global challenges. Additionally, the study identifies the necessity of fostering interdisciplinary and cross-sectoral collaborations, further reinforcing practical pathways for enhancing industrial performance. By embracing these strategic insights, industrial stakeholders can not only navigate the complexities of modern innovation ecosystems but also proactively shape sustainable and technologically adaptive business practices essential for long-term viability and competitiveness

The findings underscore the critical need for firms to strategically realign their innovation approaches to explicitly integrate sustainability objectives alongside advanced technological adoption. This involves not just superficial adjustments but a comprehensive overhaul wherein companies invest strategically in green innovations and robust digital infrastructures. Emphasis should be placed on cultivating a workforce adept in these new paradigms through continuous employee training, securing unwavering leadership commitment, and nurturing organizational cultures that prioritize and reward innovative thinking. Simultaneously, industry stakeholders are urged to collaborate with policymakers to develop incentive structures and regulatory frameworks that support sustainable, technology-driven industrial transformations. Such policies would not only promote compliance with evolving global sustainability standards but also enhance competitiveness in dynamic market environments seeking eco-friendly and digitally advanced solutions.

Limitations

The bibliometric approach relies on the available publications, citations, and other related data to analyze the innovation-industrial performance nexus. One of the limitations of this approach is its limited scope, as it may not capture the entire landscape of innovation, especially if some relevant information is not documented in the form of publications, patents, or conference proceedings. Additionally, there is often a time lag between the occurrence of innovation and its publication or citation in the bibliometric data. Consequently, the study might not be able to capture the most recent developments in the innovation-industrial performance nexus, leading to outdated or incomplete findings. Another concern is the language bias present in the bibliometric approach, which often focuses on publications in a specific language, usually English. This bias may exclude potentially significant research and innovations reported in other languages, thus limiting the comprehensiveness of the study. Furthermore, biases in citation practices could influence the study’s findings, such as the preference for citing well-established researchers or prominent institutions. This may lead to an overemphasis on certain studies or innovations while underrepresenting others.

The bibliometric approach also faces challenges in capturing the multifaceted nature of innovation. By focusing on quantifiable indicators, such as the number of publications and citations, the approach may not encompass the complexity of innovation, leading to potential inaccuracies in the study’s findings. Moreover, this method is primarily based on formal research outputs and may not capture informal innovation networks or collaborations that significantly contribute to the innovation-industrial performance nexus. This limitation can lead to an incomplete understanding of the landscape. Relying on bibliometric data also poses a risk of oversimplifying the complex relationships between innovation and industrial performance. This could result in an inadequate representation of the nexus, hindering the ability to generate comprehensive and actionable insights. Additionally, the bibliometric approach relies on publication databases, which may contain inaccuracies, inconsistencies, or errors that could impact the validity of the study’s findings.

The current bibliometric analysis does not extensively consider the geographical origin of publications, potentially leading to regional biases, particularly when certain countries dominate thematic clusters. For example, the prominence of China within one thematic cluster underscores the possibility of overinterpretation skewed toward a single national perspective. While this study systematically explores global trends and diverse thematic clusters to provide balanced interpretations, the influence of region-specific research dynamics cannot be completely excluded. To address this, we explicitly acknowledge that regional trends may exert nuanced effects on innovation and industrial performance. Consequently, we recommend further region-specific bibliometric investigations to deepen understanding and ensure that interpretations remain broadly representative and geographically balanced

The bibliometric approach, while valuable for analyzing scholarly output and citation patterns, has inherent limitations that may affect the robustness and applicability of a study’s findings. One key concern is its inability to fully capture the nuanced differences in innovation practices, industrial structures, and policy environments that vary significantly across countries and sectors. Such variations are critical as they influence how innovation unfolds and interacts with industrial performance in different contexts. Consequently, relying solely on bibliometric data may result in conclusions that lack generalizability, rendering them less applicable to specific regions or industries with unique characteristics. Moreover, the scope and depth of the analysis are often restricted by the availability and accessibility of bibliometric data, which can vary widely depending on the source and coverage of databases. These data limitations may lead to gaps in analysis, potentially causing partial or biased interpretations of the innovation-industrial performance nexus. Therefore, while bibliometric methods provide valuable insights, they should be complemented with other qualitative and quantitative approaches to achieve a more comprehensive understanding.

Suggestions

Expanding the scope of data sources is essential for capturing a more comprehensive landscape of innovation. This may involve incorporating additional data sources beyond publications and citations. Gray literature, such as technical reports, policy documents, working papers, and data from social media, industry surveys, and expert interviews, can be integrated to provide a more nuanced understanding of the innovation-industrial performance nexus. The challenge of capturing informal innovation networks can be addressed by incorporating data from various sources, such as industry reports, organizational websites, and databases. This will provide a more holistic view of the innovation ecosystem and its impact on industrial performance.

In addition to traditional bibliometric data, which often suffers from a time lag that can affect the relevance and accuracy of research findings, researchers should actively incorporate real-time data sources to enhance their analysis. These real-time sources include news articles, which provide immediate updates on industry trends and significant events; industry reports that offer in-depth insights and analyses of current market dynamics; and web-based repositories that house the latest research outputs, datasets, and technological advancements. By integrating these dynamic and up-to-date sources, researchers can capture the most recent developments in innovation and industrial performance, thereby ensuring that their findings are not only current but also reflective of the rapidly evolving landscape. This multifaceted approach enables a more comprehensive and nuanced understanding of the subject matter, bridging the gap between historical bibliometric data and present-day realities, ultimately making the research more robust, timely, and applicable to contemporary contexts.

To address the issue of language bias effectively, it is imperative to implement a multilingual approach in both data collection and analysis. This strategy involves researchers collaborating closely with experts who are proficient in multiple languages, enabling the identification and incorporation of significant research and innovations that are published in non-English sources. By broadening the linguistic scope, the study can encompass a diverse range of perspectives and findings, thereby enhancing its representativeness and comprehensiveness. Such an inclusive methodology ensures that valuable insights from different linguistic and cultural backgrounds are not overlooked, ultimately contributing to a more holistic and accurate understanding of the research topic.

To avoid oversimplification, researchers should adopt a more comprehensive analytical framework that incorporates various dimensions of innovation and industrial performance. This framework should encompass a multifaceted approach that not only considers traditional metrics of innovation, such as R&D expenditures and patent outputs, but also delves into the qualitative aspects, including organizational capabilities, knowledge spillovers, and the dynamic interactions between firms and industries. Additionally, it is crucial to examine the role of contextual factors, such as policy environments, which influence regulatory landscapes; institutional frameworks that determine governance structures and operational norms; and cultural aspects that shape organizational behaviors and innovation mindsets. By integrating these dimensions, researchers can better understand the complex, interdependent relationships that drive the innovation-industrial performance nexus, offering insights that are both nuanced and reflective of real-world dynamics.

To minimize the risk of measurement errors in bibliometric studies, researchers must undertake a meticulous process of data validation and cross-checking. This process involves not only verifying the accuracy of the bibliometric data but also ensuring its overall reliability through rigorous methodological approaches. One effective strategy is triangulation, which entails comparing and contrasting findings obtained from multiple, independent data sources. By doing so, researchers can identify inconsistencies, corroborate results, and strengthen the credibility of their study. Triangulation helps in uncovering potential biases or anomalies that may arise from relying on a single source, thus enhancing the robustness and validity of the research outcomes. Additionally, implementing standardized data collection protocols, employing advanced analytical tools, and continuously reviewing data against established benchmarks further contribute to minimizing errors and maintaining the integrity of the research process.

Future research should prioritize comprehensive comparative analyses across diverse geographic contexts to deepen our understanding of how both local and regional factors influence the effectiveness of sustainability initiatives and digital strategies. By examining these variations, researchers can uncover nuanced insights into the socio-economic, cultural, and environmental determinants that shape the success of such strategies. Additionally, systematic exploration of cross-sectoral variations in the adoption of Industry 4.0 technologies is crucial, with a focus on addressing the unique challenges and opportunities inherent within specific sectors. This approach will illuminate sector-specific barriers and enablers, providing a more tailored understanding of technology integration. Furthermore, expanding investigations into interdisciplinary and cross-sectoral collaborations can offer vital insights into how multi-stakeholder partnerships foster comprehensive, inclusive, and effective innovation ecosystems. Such collaborations can reveal the dynamics of knowledge exchange, resource sharing, and coordinated governance that are essential for driving sustainable and technologically advanced development across multiple sectors and regions.