From rigidity to responsiveness: A holistic analysis of the key pillars of strategic agility in modern enterprises

From rigidity to responsiveness: A holistic analysis of the key pillars of strategic agility in modern enterprises | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article From rigidity to responsiveness: A holistic analysis of the key pillars of strategic agility in modern enterprises Denisa Malá, Martina Minárová, Mariana Sedliačiková, Hussam Musa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9481289/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract The paper aims to investigate how strategic agility enables organizational adaptation in evolving business environments, focusing on European enterprises. While extant agility research often focuses on isolated organizational aspects, comprehensive strategic agility requires coordinated development across dimensions, challenging conventional structures and prompting organization wide transformations in organizational responses to the market. Drawing on quantitative research of EU enterprises (n = 456) conducted between 2023 and 2024, six interconnected dimensions are examined: agile values, collaborative workforce, technological flexibility, agile management practices, adaptive organizational structures, and innovation capacity. The findings reveal that only 23% of organizations achieve a high level of strategic agility, with critical drivers including digital technology investments, decentralized decision-making, and employee involvement in innovation. Management agility shows the strongest cross-dimensional interconnectedness, while demographic factors show no significant influence on perceived agility. The study advances a holistic framework linking capabilities, structural adaptations, and agility outcomes. Managerial development and cultural change emerge as practical levers, suggesting that an agile mindset should be cultivated across hierarchical levels. The study contributes to understanding the multidimensional nature of strategic agility and its role in enhancing organizational competitiveness and resilience. strategic agility agile management innovation digital technologies decision-making Figures Figure 1 INTRODUCTION People currently live in a time of constant changes and uncertainty. Disruption has become the norm, and digital progress has transformed the world. Recent global events have highlighted unpredictability of the life. These shifts and rapid developments are altering various aspects of society. Educated, tech-savvy generations have been reshaping employer-employee relationships and business processes. Numerous books, seminars, and conferences discuss the implications of these changes on strategic management, organizational structures, teamwork, and innovation. Amidst this, there's a search for solutions to address these complex challenges. Strategic Agility (SA) emerges as a key concept, offering enterprises the flexibility and resilience needed to reduce uncertainty and seize new opportunities in this dynamic environment. After analyzing various scientific sources, multiple frameworks describing SA concepts and measurement methods were identified. Drawing from Wendler's (2014) research and comparing it with other SA concepts (Yang & Liu, 2012; Teece et al., 2016; Alahyari et al., 2017; Tallon & Pinsonneault, 2011), six fundamental pillars of SA were characterized: values, technologies, workforce, management, collaboration, and structures. These six dimensions of SA have been selected based on a synthesis of relevant scientific framework; they represent a comprehensive set of key factors (from cultural and technological to managerial and structural) that integrate all aspects of strategic agility. This model, which is suitable for SMEs, forms the basis of the research into agility in business enterprises of the European Union. Each of these pillars represents a critical dimension of SA in an organization, as detailed below. Agile values and technologies are prerequisites for SA in an enterprise. Agile values create a culture embracing proactivity, quick response, trust, and change management. Agile technologies enable efficient communication, information sharing, and appropriate tech use. An agile workforce possesses multiple skills to respond to changes, learns continuously, communicates reliably, and takes responsibility. Their thinking and actions align with quality and market requirements. Agile management involves leaders handling changes swiftly, informing and inspiring employees, following long-term visions, and strategically managing investments in advanced technologies. Agile collaboration focuses on activities between departments and external partners, emphasizing quality, feedback, and information sharing. Flexible structures allow quick adaptation of organizational processes to implement changes and ensure competitiveness, enabling rapid decision-making and responsibility shifts. To implement SA, enterprises need people with appropriate skills and knowledge. Managers must handle changes in customer requirements, new markets, and innovations. Flexible structures supporting SA describe the enterprise's ability to flexibly adapt and foster a collaborative culture. The strategic gap addressed by this paper lies in the fact that SA, as a key prerequisite for business success in a dynamic and unpredictable environment, has not yet been sufficiently explored. There is a lack of a comprehensive approach that integrates various aspects of SA, from values and technologies to management, collaboration, and organizational structures, into an integrated framework for assessing and developing SA in enterprises. Critical gaps include limited longitudinal studies of agile transformation sustainability, insufficient attention to industry-specific implementation factors, enterprise size, and underdeveloped measurement frameworks. Future research should examine these together with the documented benefits. LITERATURE REVIEW Based on a comprehensive secondary analysis of scientific literature and a critical examination of existing definitions, differences reveal how strategic agility (SA) is defined across different theoretical perspectives. While there is a broad agreement on SA as a dynamic organizational capability, theoretical approaches differ in their emphasis on specific dimensions and underlying mechanisms. Early formulations by Abshire (1996), who coined the term, emphasized agile strategies in unpredictable environments. Ganguly et al. (2009) advanced this discourse by integrating responsiveness and knowledge management for efficient adaptation, while Conboy (2009) encompassed environmental perception, decision-making, and strategic direction maintenance. Yang and Liu (2012) identify four core attributes: flexibility, responsiveness, innovation, and resilience, and argue that these attributes enable survival amid complexity. This multi-dimensional approach contrasts with Tallon and Pinsonneault's (2011) more focused on rapid response and risk management. Teece et al. (2016) use "enterprise agility" synonymously, focusing on resource reallocation for value creation, which shifts attention from external responsiveness to internal resource allocation. Alahyari et al. (2017) offer another perspective, positioning SA as a strategic tool for market positioning. These definitional variations reflect theoretical tensions regarding whether SA is primarily an external adaptation mechanism or an internal capability development process (Peterman & Zacher, 2021). For the purposes of this research, these various approaches have been integrated to define strategic agility as an enterprise's capability to rapidly recognize changes in its environment and accurately interpret them, and flexibly respond through strategic and operational process modifications while preserving its core identity and long-term objectives. This definition addresses the limitations of single-dimension approaches while recognizing the dual nature of SA as both an external adaptation and an internal capability development process. Agile Values Agile values underpin rapid response and adaptability to changing business environments, emphasizing innovation over maintaining the status quo (Huck-Fries et al., 2025). Huck-Fries et al. (2025) demonstrate how agile organizations reframe failure as learning opportunities, encouraging risk-taking and innovation. It is argued that open communication, personal responsibility, and continuous improvement are hallmarks of agile organizations, particularly when driven by top management commitment. The alignment of organizational and employee values is critical. Meister et al. (2022) report that over 80% of employees prioritize value alignment, with many willing to leave positions misaligned with their values. Research indicates agile values influence risk perception and learning, forming the foundation of adaptive, innovative cultures (Goncalves et al., 2020; Rizi et al., 2024). Thus, it is contended that embedding agile values strategically is essential for enterprise growth. Agile Technologies Agile technologies encompass tools and methods facilitating flexible development, collaboration, and business responsiveness (Beck, 2001). The work of Dybå & Dingsøyr (2009) established that agile software development, characterized by iterative cycles and frequent customer feedback, enables rapid innovation. Frameworks like Scrum and Kanban help teams prioritize and adapt swiftly (Weflen et al., 2022), while collaboration and open communication are central, enhancing problem-solving and productivity (Dybå et al., 2014; 2025; Malik et al., 2025). Agility extends beyond IT, supporting project management in diverse sectors such as marketing and manufacturing. However, Santos and Carvalho (2021) identify cultural resistance and process misalignment as primary barriers in large enterprises. It is contended that despite adoption, many organizations implement agile technologies superficially, adopting the terminology and tools while failing to embrace the fundamental cultural transformation required, ultimately undermining their potential for genuine strategic advantage. Agile technologies streamline administration and recruitment, enabling faster hiring and freeing resources for strategic initiatives (Kude et al., 2023). They support customer relations (Mohamed & Darwish, 2019) and enhance supply chain flexibility through improved planning and inventory management (Zielske et al., 2022). Overall, agile technologies enhance flexibility, collaboration, customer focus, and competitiveness (Runping et al., 2025). Agile Workforce Aghina et al. (2020) demonstrate that agile HR processes incorporating continuous employee feedback boost engagement by up to 20% and accelerate recruitment by 75%. Employees increasingly demand meaningful, accessible, and engaging work experiences, which is supported by agile organizational design (Xiangsheng & Fizz, 2024; Moh'd et al., 2024). Truss (1999) and Šikýř (2014) highlight that shifting from traditional roles to teamwork increases the need for self-control, responsibility, and continuous learning, despite associated psychological pressures. Based on the presented findings, it is supposed that this theoretical framework challenges the conventional understanding of hierarchical control and reframes psychological pressure not as a disadvantage but as a driver for organizational transformation. Teams with shared mindsets and proactivity, emphasizing soft skills, strong communication, and continuous development, excel in agility (McMackin & Heffernan, 2020; Ranasinghe & Sangarandeniya, 2021, Jooss, et al., 2024). Yet challenges remain in overcoming resistance and inconsistent processes, with culture being key to innovation management (State of Agile Report, knowledgehut.com; Abdala et al., 2025). Agile HR fosters environments of collaboration, self-reflection, and human connection, critical for employee motivation and enterprise success (Moh'd et al., 2024; Mollet & Kaudela-Baum, 2023). Agile Management Modern business demands creativity, courage, and flexibility (Suntinger, 2010). Tas (2022) conceptualizes agile leadership as integral to strategic agility, managing change in competitive environments through adaptability and team empowerment. It contrasts with traditional hierarchies by promoting autonomous, cross-functional teams, transparent communication, and accountability (Tandon et al., 2024). This transformation generates positive outcomes, including improved productivity, satisfaction, and competitiveness (Vaszkun & Sziráki, 2023). Effective agile leaders facilitate knowledge sharing and trust rather than exercising control (Tandon et al., 2024). Emotional intelligence and ethical behavior underpin effective agile leadership, creating supportive environments that facilitate change acceptance (Tas, 2022). It is suggested that many organizations adopt agile frameworks superficially, maintaining traditional hierarchical structures under new terminology, which ultimately constrains genuine employee independence and strategic innovation. Porkodi (2024) emphasizes that agile leadership directs team composition aligned with products and customer needs, a prerequisite for agility and innovation. Leaders 4.0 embody adaptability and innovation, critical for meeting the demands of today's agile enterprises (Awodiji, 2024, Lanteri, 2025). Agile Collaboration Agile collaboration features flexibility, iteration, transparency, and collective accountability (Nold & Michel, 2016), enabling rapid feedback and adaptation (Crocitto & Youssef, 2003). Gligor et al. (2013) demonstrate that agile collaboration enables swift responses to environmental changes, crucial for competitiveness in dynamic markets. While Chakravarty et al. (2013) confirm that IT capabilities enhance organizational agility, expenditure alone is insufficient without strategic investments. Collaborative agreements expand resource access and knowledge sharing, supporting sustainable competitive advantages in turbulent environments (Mueller & Jungwirth, 2020; Tufan & Mert, 2023). Cultural and procedural shifts pose challenges, but successful agile collaboration improves team efficiency, innovation, and adaptability to new challenges (Nold & Michel, 2016; Mancuso et al., 2024). It is aligned with the perspective that agile collaboration's effectiveness depends critically on cultural readiness and strategic implementation rather than mere adoption of collaborative frameworks, as superficial integration may yield limited competitive benefits. Agile Structures Flexible organizational structures enable rapid adaptation of processes and decision-making, supporting agility and innovation (Lichtenthaler, 2020). By decentralizing authority and fostering employee autonomy, enterprises can enhance responsiveness and competitiveness. Continuous learning and agile methodologies embed the resilience necessary for sustained success in dynamic environments. It is aligned with the view that structural flexibility alone is insufficient without corresponding cultural transformation, as rigid organizational mindsets can weaken even the well-designed agile frameworks. The literature review highlights SA as a vital capability for enterprises to rapidly adapt to market changes through flexible values, technologies, workforce, leadership, collaboration, and structures. Agile management fosters innovation, resilience, and competitive advantage by promoting open communication, empowering teams, and continuous learning. However, comprehensive integration frameworks remain underdeveloped. Successful agility requires a cultural shift supported by agile leadership and integrated practices across the enterprise to navigate uncertainty and sustain long-term growth. METHODOLOGY AND HYPOTHESES Research Design The study employs a two-phase mixed-methods approach combining primary quantitative research and systematic literature review. Phase 1. The primary quantitative research, conducted between September 2023 and January 2024, focused on assessing the development level of individual pillars of strategic agility in European Union enterprises. The objectives were to identify the most and least developed agility dimensions, explore their interconnections, and examine the influence of organizational age on agility. Phase 2. The second phase employed a systematic literature review (SLR) following PRISMA guidelines (Page et al., 2021) to synthesize prior research on strategic agility and to identify theoretical gaps. A structured search was conducted in Scopus (1996–2025) and the Web of Science Core Collection (1996–2025). Google Scholar was used as a supplementary source to capture additional records that may not be indexed in Scopus/WoS. The search string combined agility-related terms with conceptual terms using Boolean operators: ("strategic agility" OR "enterprise agility" OR "organizational agility" OR "business agility" OR "organizational adaptability") AND ("framework" OR "model" OR "adaptation" OR "responsiveness" OR "flexibility"). Backward citation searching complemented the database search. Eligible studies were peer-reviewed, English-language journal articles and conference proceedings published between 1996 and 2025 that addressed strategic agility concepts, frameworks, or applications. Records were exported, duplicates were removed, and titles/abstracts were independently screened by two reviewers. Full texts were then assessed for eligibility. The initial search yielded a large pool of records (with Google Scholar providing approximate hit counts rather than exact database records). Following screening and full-text assessment, 126 articles were reviewed in full, and 77 studies were retained for synthesis. Sample The research focused on enterprises operating in the European Union. EU member states share common regulatory frameworks and economic integration while demonstrating sufficient regional diversity to provide comprehensive insights into strategic agility implementation across varying organizational contexts. Following Louangrath (2017) and Faeron (2017), the minimum sample size was calculated using the standard formula, considering a confidence interval (at 95% reliability level, z = 1.96), margin of error 5%, proportion of the sign (p = 0.5 for unknown value), and population size of approximately 24 million EU enterprises. The minimum sample size was set at 380 enterprises. An electronic survey was distributed to 2,560 enterprises using email contacts sourced from a European business database. Out of 2,560 questionnaires sent, 742 responses were received (28.98 % response rate). After discarding 286 incomplete or non-representative responses, the final sample included 456 enterprises. Missing or partially completed data within valid questionnaires were handled using mean substitution to maintain consistency across variables. Sample representativeness was verified using Pearson's Chi-square goodness-of-fit test, comparing enterprise size distribution against reference data from Statista. The test confirmed sample representativeness, with p = 0.570 exceeding the significance level of α = 0.05. Data Collection An anonymous electronic questionnaire was developed to ensure objective responses without concerns about potential consequences. The identification section collected data on enterprise size (micro: 1-9, small: 10-49, medium: 50-249 employees) to verify sample representativeness. The research section contained 24 questions divided into six categories according to agility dimensions: (1) organizational values, (2) implementation of new technologies and innovations, (3) employees, (4) management and leadership, (5) cooperation within and outside the enterprise, and (6) organizational structure and hierarchy. The structure reflects theoretically grounded pillars of agility and allows for statistical analysis of interrelationships between dimensions. Each dimension was assessed using four Likert-type items (where 1 indicates high agility, 2 moderate agility, 3 low agility, and 4 no agility). To verify internal consistency and reliability of the questionnaire, a pilot test was conducted on a sample of 50 respondents. Cronbach's alpha coefficient was used to assess internal consistency (Cronbach, 1951). Analysis demonstrated Cronbach's alpha value of α = 0.913, indicating reliability and exceeding the minimum recommended threshold of 0.7 for exploratory research. The questionnaire was therefore used in the main research without modifications. Data Analysis Data analysis included descriptive statistics (arithmetic mean, mode, and median) to compare agility across dimensions, rated on a 1 to 4 scale (1 = high agility; 4 = absence of agility). The Friedman test was used to confirm significant differences in agility across dimensions (p = 0.0). Wilcoxon signed-rank tests identified which dimensions differed significantly. Pearson correlation analysis revealed interdependence among all six agility dimensions, particularly between management and employees, management and collaboration, management and structures, and collaboration and structures. Spearman's correlation assessed the impact of demographics (gender, education, job position, tenure, company size, sector, and company age) on agility dimensions, showing only weak but significant correlations with employment length and enterprise age. One-way ANOVA and the ETA coefficient (η) were used to analyze differences in agility dimensions across industries. Hypotheses Based on the literature review and empirical evidence, four hypotheses were formulated to be tested in the context of EU enterprises: H1: Collaboration and organizational values will show a mean score ≤ 2.20 on a 4-point agility scale and will be significantly different from the least agile dimension (p < 0.05) in EU enterprises. Research by Camarinha-Matos (2019) has shown that globalization and digitalization have significantly increased the need for effective collaboration in today's business environment. Holbeche (2018) highlights that investments in tools and training that support collaboration directly contribute to increasing agility in this area. Shams et al. (2021) point out that the development of agile values requires an emphasis on corporate values, ethics, and social responsibility, which form the basis of an agile culture. These findings support the assumption that it is collaboration and agile values that are among the most developed dimensions of agility in EU enterprises. H2: Management will exhibit a mean score ≥ 2.25 on a 4-point agility scale and will be significantly less agile than the most agile dimension (p < 0.05) in EU enterprises. Research by Yang and Liu (2012) points out that traditional hierarchical structures in enterprises often hinder managerial agility by slowing down decision-making processes and reducing the ability to respond flexibly to dynamic market changes. In such systems, managers tend to be less inclined to take risks and innovate, which weakens overall management agility. At the same time, Zitkus (2011) points to the cultural specificities of the European management approach, which emphasizes consensus and long-term stability, factors that can hinder fast and flexible decision-making. These findings suggest that management, as a pillar of agility, remains the least developed in European enterprises. H3: Strategic agility represents an integrated system where all dimensions show significant positive correlations (p < 0.01), confirming the interdependence between the different pillars of agility. Seo et al. (2025) point out that enterprises function as integrated systems in which the parts are interconnected and interact with each other. Therefore, improving one area of agility often requires or naturally leads to changes in other pillars. For example, the implementation of agile methodologies in product development inevitably affects organizational structure, internal communication, and collaborative culture. Interdependence is also reflected in the fact that neglecting one dimension can hinder progress in other areas. If an enterprise focuses solely on technology but neglects human capital or corporate values, its ability to achieve higher levels of agility may be limited. This complex nature of agility is supported by the empirical findings of authors such as Wise (2015), Rigby et al. (2020) and Hoda et al. (2020), whose studies suggest that successful agile transformations require simultaneous changes across multiple pillars. Based on these findings, it is assumed that agility in organizations is a complex and interconnected system in which progress in one dimension supports the development of the others. It is important to note, however, that while this hypothesis has strong theoretical and empirical underpinnings, the exact nature and strength of the relationships between the different dimensions of agility may depend on the specific enterprise, its size, industry, and other factors. H4: There is a negative relationship between the age of the enterprise and the level of managerial agility. Newly established enterprises are typically required to respond swiftly and flexibly to rapidly changing market conditions to survive and grow. Unlike long-standing enterprises, younger enterprises often operate without entrenched hierarchical structures and rigid bureaucratic procedures, enabling faster decision-making and more agile implementation of innovations. Furthermore, these enterprises tend to be built on modern technologies and progressive business models from the outset, which enhances their capacity to adapt to emerging trends and competitive pressures (Hsueh, Tu, 2004). Their organizational culture is often characterized by openness to experimentation, continuous learning, and a readiness to embrace change—attributes that collectively support higher agility in management (Govuzela, Mafini, 2019). These characteristics suggest that organizational youth can foster a more flexible, dynamic approach to leadership and operations, which forms the basis for the hypothesis that more recently established enterprises tend to demonstrate greater management agility. RESULTS AND DISCUSSION This part presents the key findings of the research, followed by their interpretation in the context of existing literature. The analysis focuses on evaluating the level of development across six dimensions of strategic agility in European Union enterprises, identifying the most and least developed pillars, and exploring their interrelationships. Firstly, the research results were evaluated by simple statistical tools: mean, mode, and median, which enabled comparison of the six dimensions and the degree of agility achieved in each of them. The highest agility was observed in the collaboration dimension, where the mean on a scale of 1 to 4 (where 1 indicates high agility, 2 moderate agility, 3 moderate deviation from agility, and 4 no agility) was 2.13, followed by the value dimension, which achieved the mean value of 2.15. The management (mean of 2.28) and the workforce (mean of 2.23) dimensions ranked as the least agile. It should be noted that the differences in obtained mean values are rather small, and all dimensions show signs of moderate agility, as the mean values are close to the value of 2. However, despite the small differences, the dimensions can be ranked from the least to most agile, as viewed in Figure 1. It is interesting to find out that the management and workforce were identified by respondents as the least agile dimensions within the overall sample of EU enterprises. On the other hand, collaboration was identified as the most agile dimension, which may slightly contradict. This apparent contradiction may be explained by the finding, confirmed by Soda and Zaher (2012), that effective collaboration often occurs horizontally among colleagues rather than within formal management structures. Theoretical framework on strategic agility in business (Beck et al., 2001; Huck-Fries, 2025; Meister et al., 2022; Gligor et al., 2013) emphasizes the importance of collaboration, as well as the essential role of corporate values for sustaining agility. Higher agility in both of these dimensions (2.13 and 2.15) may be the result of better employee engagement and effective adoption of shared values. In practice, higher agility in these dimensions indicates that the enterprise has well-established mechanisms to support teamwork and value sharing, which can be key to swift and successful adaptation to change. Enterprises that emphasize collaboration and incorporate agility in their value system may naturally exhibit higher agility in these areas (Chakravarty et al., 2013). Management and the workforce, on the other hand, may still have different approaches and perspectives on agility, which could explain lower scores in both of these dimensions. Although the enterprise possesses a clear system of agile values and has implemented agile principles, their manifestation through the actual behavior of the enterprise’s management and workforce may lag behind. To summarize the above reasoning and provide clear arguments, high agility in the collaboration dimension indicates that enterprises have a strong culture of teamwork, which is enhanced by effective communication among employees. This environment then promotes rapid information exchange, collective decision-making, and the ability to respond quickly to change (Vaszkun, Sziráki, 2023). The second place for the value dimension could be explained by enterprises placing an emphasis on shared values and principles that guide their activities and processes. This approach tends to promote consistent behavior and decision-making across the enterprise, increasing its ability to adapt to new challenges and environments (Satell, Windschitl, 2021). On the other hand, lower agility in management may signal that executives may have difficulty in adapting to agile methods or supporting agile processes across the enterprise or may be unwilling to do so. This may include their conscious or unconscious resistance to change, lack of flexibility in management structures, or a lack of skills necessary to effectively manage independent agile teams. Lower levels of agility among the workforce may indicate problems such as a lack of training in agile methods, low levels of engagement and intrinsic motivation, resistance to changing work processes, or, potentially, fear of taking responsibility for such action. The findings align with those of Sherehiy and Karwowsky (2014), who observed that enterprises with effective collaboration and clearly defined values may be able to swiftly respond to market changes and innovate their processes. However, deficiencies in management and employee agility can limit the full potential of the enterprise, which can have a negative impact on its overall performance and competitiveness. The research has been approached from the perspective of comparing the agility scores in all six dimensions. Friedman’s test confirmed that the six dimensions of agility in targeted enterprises are not equally important, since p-value < 0.001, proving that not all agility dimensions have the same impact or are equally implemented. Wilcoxon signed rank test (Table 1) was applied to determine which dimensions are more significant than the others. Table 1 Wilcoxon signed rank test for agility dimensions Test Statistics a V-C S-V T-S Z -1.078 b -2.361 b -.274 b Asymp. Sig. (2-tailed) 0.281 0.018 0.784 W-T M-W Z -1.149 b -2.203 b Asymp. Sig. (2-tailed) 0.251 0.028 a. Wilcoxon Signed Ranks Test b. Based on negative ranks. Dimensions: V – values, T – technologies, W – workforce, M – management, C – collaboration, S – structures Source: authors As can be deduced from Figure 1, the value and collaboration dimensions achieved the lowest values (ranging from 1 to 4), and are thus the most agile . High agility in the value dimension indicates that enterprises have a strong foundation in an agile culture. In the collaboration dimension, high agility indicates effective teamwork and communication. This foundation is crucial as Abdala et al. (2025) emphasize that fostering a corporate culture that prioritizes continuous learning, encourages experimentation, and supports strategic pivots when necessary allows managers to align business direction with evolving market demands, regulatory requirements, and consumer preferences, creating a proactive mindset that enables enterprises to remain competitive and responsive to both opportunities and threats in the ever-changing business landscape. The achieved values were highest in management ; therefore, it proves to be the least agile dimension. This suggests that management may be the biggest barrier to the implementation of agility in European enterprises. This may reflect traditional hierarchical structures or rigid management processes that are rather difficult to transform, and means that this area requires the most attention in agile transformation (Waardenburg, Vliet, 2013; Boehm, Turner, 2002). The other dimensions – technology, workforce, and structures, ranked in between, indicating that in agility, enterprises perform on average in these areas. In structures, this may reflect a partial adaptation to more agile organizational forms. In technology, average scores suggest some degree of adoption of agile technology solutions, while there is undoubtedly room for improvement. As to the workforce dimension, the scores prove that employees are partially ready for agile working practices; nevertheless, there is still potential for development. This aligns with the findings by Mancuso et al. (2024), who demonstrate that by allowing enterprises to access innovative products and services from startups, they provide a swift and flexible means of reconfiguring the competencies and resources of an enterprise, suggesting that workforce agility can be enhanced through external partnerships that bring fresh perspectives and innovative approaches to internal teams. It is advisable for the EU enterprises to build on their strength in the values and collaboration dimensions by using the corporate culture in spreading the agile values, as well as the collaboration of teams to develop creativity and innovation in their operations. On the other hand, attention should be paid to the transformation of management towards agile practices (Lichtenthaler, 2020). Since enterprises prove to have agile values, it is likely that the problem of implementing them into management’s behavior and actions. Therefore, since there are differences between dimensions, a holistic approach appears to be appropriate for the agile transformation of EU enterprises. Improvement in one dimension can positively impact other dimensions, and the valuable insight into the relative strengths and weaknesses of different aspects of agility allows EU enterprises to prioritize their efforts in implementing agile practices, while on one hand strengthening their strengths and on the other, addressing the areas that need attention. As part of the research, the Pearson correlation analysis was used to investigate the correlation between the six agility dimensions. The test confirmed a direct dependence among all dimensions (Table 2), while a strong direct correlation between management and employees (rs = 0.730), management and collaboration (rs = 0.746), management and structures (rs = 0.742), and collaboration and structures (rs = 0.702) were discovered. These findings mean that the more agile the management of an enterprise is, the more agile are the employees. Furthermore, with more agile collaboration, the agility in structures increases, and higher agility in collaboration brings more agile structures. Table 2 Correlations between agility dimensions Correlations V T W M C S V Pearson Correlation 1 .681 ** .693 ** .680 ** .649 ** .664 ** Sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000 N 456 456 456 456 456 456 T Pearson Correlation .681 ** 1 .633 ** .687 ** .679 ** .673 ** Sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000 N 456 456 456 456 456 456 W Pearson Correlation .693 ** .633 ** 1 .730 ** .686 ** .658 ** Sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000 N 456 456 456 456 456 456 M Pearson Correlation .680 ** .687 ** .730 ** 1 .746 ** .742 ** Sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000 N 456 456 456 456 456 456 C Pearson Correlation .649 ** .679 ** .686 ** .746 ** 1 .702 ** Sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000 N 456 456 456 456 456 456 S Pearson Correlation .664 ** .673 ** .658 ** .742 ** .702 ** 1 Sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000 N 456 456 456 456 456 456 **. Correlation is significant at the 0.01 level (2-tailed). Source: authors The fact that a direct dependence between all dimensions was confirmed suggests that agility is a complex and interrelated concept, and should be approached as such. The interdependence between all six dimensions indicates that improvement in one single dimension positively influences the other five dimensions, which supports the suggestion for a holistic approach to implementing agility. Strong correlation between management and employees (r = 0.730) highlights the key role of people in the enterprise in promoting agility at all levels of the hierarchy. This finding aligns with the research by Xiangsheng & Fizz (2024), which similarly confirmed a positive correlation between human resources and strategic agility. Although management’s agility scores are the lowest, it is the managers who set the tone and communicate the benefits of agility and its principles across the whole enterprise. Managers also create an environment of autonomy, flexibility, and innovation among employees (Clayton, 2021). Conversely, agile employees may require and encourage more agile approaches from their management, which, as proved by the results, may be a way to build up the overall enterprise agility. Strong correlation between management and collaboration (r = 0.746) suggests that the more agile management is, the more it contributes to effective collaboration in an enterprise. Managers who adopt agile practices promote open communication, teamwork and knowledge sharing, which reflects in developing innovation and creativity among cooperating employees (Ivari, Ivari, 2011). This aligns with findings by Runping et al. (2025), who discovered that ventures should establish an efficient system for distributing, interpreting, and implementing strategic knowledge through cross-departmental meetings, information-sharing platforms, and collaboration mechanisms that enhance the dissemination and application of strategic knowledge. It works vice versa as well, the more cooperative and collaborative the workforce is, the more agile approach from the managers is required. Another strong correlation was found between management and structures (r = 0.742), which indicates that agile management is closely linked to the creation and maintenance of agile corporate structures. This also applies in terms of hierarchy, which means that an organizational structure that is flatter, more open, and more flexible can easily affect the way an enterprise is managed. Flatter hierarchies mean fewer decision-making levels, and smoother, faster communication of information, roles, or tasks, as well as a less complex system of authorities and their delegation (Bueechl et al., 2021). The strong correlation between collaboration and structures (r = 0.702) suggests that agile organizational structures significantly promote effective collaboration. This is further supported by Mukherjee et al. (2015), who found that flexible, less hierarchical enterprises are likely to facilitate better, faster, and easier communication and collaboration between different parts of the enterprise. From the above, it can be concluded that management appears to be a key factor in agile transformation as it correlates strongly with several other dimensions. These strong correlations enable authors to claim that agile transformation should be a comprehensive process and should not be implemented as isolated initiatives. Improvements in one dimension, especially in management, will lead to improvements in other dimensions, creating a virtuous cycle of agile transformation. This perspective is reinforced by Lanteri (2025), who argues that since organizations need to constantly transform themselves and continuous innovation is key to survival, they should be designed and led for constant transformation. With this in mind, a conclusion can be made that the focus in adopting and/or improving agile practices should be primarily on management as a potential catalyst for overall agile transformation. Besides searching for correlations among the individual dimensions, the relationship between each agility dimension and the demographic data of respondents were also investigated. To determine the relations, the Spearman’s correlation coefficient test was used, measuring the strength and direction of monotonic association between two variables (Table 3). Table 3 Spearman's correlation coefficient of the relationship between agility dimensions and respondents’ demographics Spearman's rho O25 O26 O27 O28 O29 O31 V Correlation Coefficient 0.038 -0.035 -0.042 .106* -0.010 0.052 Sig. (2-tailed) 0.419 0.454 0.368 0.024 0.828 0.266 N 456 456 456 456 456 456 T Correlation Coefficient 0.082 -0.022 -0.011 0.070 0.059 0.001 Sig. (2-tailed) 0.079 0.633 0.822 0.136 0.210 0.981 N 456 456 456 456 456 456 W Correlation Coefficient 0.009 -0.026 0.049 .132** -0.042 0.087 Sig. (2-tailed) 0.843 0.575 0.292 0.005 0.376 0.063 N 456 456 456 456 456 456 M Correlation Coefficient 0.091 -0.067 -0.053 .105* -0.014 .112* Sig. (2-tailed) 0.053 0.154 0.254 0.025 0.769 0.017 N 456 456 456 456 456 456 C Correlation Coefficient 0.072 -0.056 -0.048 0.080 0.001 0.062 Sig. (2-tailed) 0.123 0.230 0.308 0.089 0.984 0.189 N 456 456 456 456 456 456 S Correlation Coefficient 0.041 0.005 -0.037 .121** 0.025 0.058 Sig. (2-tailed) 0.382 0.911 0.431 0.010 0.592 0.213 N 456 456 456 456 456 456 *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed). O25 – respondent’s gender O26 – respondent’s education O27 – respondent’s position in the enterprise O28 – respondent’s length of service in the enterprise O29 – size of the enterprise O30 – sector in which the enterprise operates O31 – length of time the enterprise has been in the market Source: authors Regarding gender, education level, respondent’s position in the enterprise, and the size of the enterprise, the research results confirmed no correlation, as all p-values are greater than 0.05. This means that it cannot be certainly claimed that these factors influence agility in enterprises. The lack of correlation in terms of gender suggests that men and women perceive the status of agility similarly, which indicates that agile practices and principles are universally applicable regardless of gender. The lack of correlation in education suggests that the perception of agility implementation is not influenced by the highest achieved level of formal education. According to Tripathi et al. (2020), this likely suggests that agile principles are a matter of practice and culture rather than formal education. For the respondent’s position in the enterprise, there has also been noted a lack of correlation, indicating that the perception of agility implementation is similar across different levels of the corporate hierarchy. This may suggest that agile principles are sufficiently embedded across the organization and that communication and training efforts related to agility are reaching employees regardless of their formal position. The uniform perception also implies that agile practices may be integrated into day-to-day operations across departments and management layers. The lack of correlation for the size of enterprise suggests that agility is not necessarily dependent on the size, and agile practices are applicable across enterprises of different sizes. These results support the idea that agility is a universal concept that is not dependent on demographic or business characteristics. Instead of focusing on demographic or structural factors, enterprises may decide to pay attention to building an overall agile culture and implementing agile practices. The lack of correlation in gender, education, and employee position suggests that agility provides equal opportunities for all employees. Lack of correlation in size of enterprise supports the idea that agile principles can be adapted to serve different types of enterprises. In the question about how long the respondents have been working in their enterprise, a weak direct relationship in the value (rs = 0.106), workforce (rs = 0.132), management (rs = 0.105), and structures (rs = 0.121) dimensions were confirmed. While these correlations are statistically significant, their strength is very low, indicating minimal practical impact. This means that although there is a tendency for shortly employed employees to perceive greater agility, the differences are not strong enough to suggest a substantive behavioral or structural distinction within the organization. This finding supports the research of Jooss et al. (2024), who, by unpacking both initial and dynamic skills-matching mechanisms, adopt a processual view on human resource management and respond to the call for more dynamic approaches to managing talent, suggesting that tenure alone may not be the primary determinant of agile perception, but rather the dynamic adaptation and skills development throughout employment. The weak positive correlations in the values dimension may indicate that employees employed for a shorter time have a slightly better understanding and identification with the agile values of the enterprise. These employees tend to rate themselves and their co-workers as more adaptable, flexible, and open to change. This could also suggest that newer employees are already hired with greater emphasis on agile skills and thinking and are thus somewhat naturally more open to new methods and approaches. Employees working in their enterprise for a longer time may be assumed to have ingrained older work habits, which are less compatible with agile values. The strongest, although still weak, correlation in the workforce dimension may indicate that short-term employers may also perceive themselves and their colleagues as slightly more agile, as they have less embedded work habits, and this makes employees more open to new, innovative approaches. Aghina et al. (2020) similarly conclude that it is effective for an enterprise to emphasize recruiting such employees who manifest an agile mindset and appear more flexible and open to change. Another benefit of these employees is that they may tend to see things more positively and idealistically, having a limited view of the barriers to agility in the enterprise, which are more visible to employees with longer work tenure. The weak positive correlation in management may indicate that with shorter tenure, employees tend to view management as slightly more agile, rating the enterprise leaders as more flexible. adaptable and open to change. Newer employees may, undoubtedly, have less bias against management and may be more open to perceiving their efforts to be more agile. Koutsikouri et al. (2020) found that these employees have not yet had the opportunity to experience situations where management might exhibit less agile behavior. Thus, they tend to see management in a more positive light during their first months or years in the enterprise. The weak positive correlation in the structure s dimension may indicate that employees working in the enterprise for a shorter time tend to perceive organizational structures, hierarchies, processes, and systems as slightly more agile. Newer employees may not yet have had sufficient time to encounter the rigid aspects of corporate structures, if there are any, and may have less understanding about how traditional corporate structures work. Another aspect worth considering is the new employees’ optimistic expectations about the flexibility and adaptability of corporate structures and processes. This perspective is supported by empirical findings of Malik et al. (2025), who emphasize the importance of digital orientation as an antecedent that requires intermediate steps of information governance and digital transformation to influence digitally enabled strategic agility, suggesting that newer employees may better recognize and appreciate digitally enhanced structural elements that contribute to organizational agility. On the other hand, as Gregory et al. (2022) found, established employees have most likely experienced attempts by the enterprise to reorganize or any unsuccessful change efforts, which have affected their perceptions of the agility of structures. Newer employees would also typically compare current structures to previous employers. while employees working in an enterprise for a longer period tend to compare them to the past structures within the same enterprise. When searching into the enterprise’s length on the market, a weak direct relationship was found in the management dimension (rs = 0.112), meaning that the shorter the enterprise has been operating on the market, the more agile the management is. Spearman’s rank coefficient proved a weak direct dependence between the enterprise’s time in the market and management agility. This finding provides an interesting insight into the relationship between the age of an enterprise and the agility of its management. The result suggests that younger enterprises tend to have more agile management, which can be explained by newer enterprises being established with modern management practices and philosophies that place more emphasis on agility. Organizational structures and corporate processes of these enterprises are less rigid, allowing for greater flexibility in management. Newer enterprises have also emerged in a more dynamic market environment, which itself requires a more agile approach to management. Moreover, they often employ young managers who are more open to agile methods. Similar conclusions were reached by Permatasari and Abadi (2024), whose research suggests that newer employees, still acclimating to the company's environment and less resistant to adopting agile methodologies, exhibit the highest levels of agility and adaptability in project execution. These enterprises face more pressure to innovate and adapt quickly in order to maintain their position in the market, which is reflected in more agile management. What aligns with the previous findings is that new enterprises have not had time to build complex bureaucratic structures that can hinder agility. A one-way analysis of variance (ANOVA) using the ETA coefficient (η) was applied to investigate the potential relationship between the level of each agility dimension and the industry in which the enterprises operate (Table 4). Table 4 ANOVA analysis of the effect of industry on enterprise agility dimensions ANOVA Sum of Squares df Mean square F Sig. ETA V between groups 6.932 7 0.990 2.272 0.028 0.185142 within groups 195.294 448 0.436 total 202.226 455 T between groups 7.448 7 1.064 2.442 0.018 0.1917 within groups 195.218 448 0.436 total 202.666 455 W between groups 6.203 7 0.886 2.636 0.011 0.198885 within groups 150.619 448 0.336 total 156.822 455 M between groups 7.548 7 1.078 3.015 0.004 0.212093 within groups 160.241 448 0.358 total 167.789 455 C between groups 6.249 7 0.893 2.329 0.024 0.187368 within groups 171.746 448 0.383 total 177.995 455 S between groups 3.569 7 0.510 1.175 0.315 within groups 194.341 448 0.434 total 197.910 455 Source: authors The results of the analysis revealed statistically significant differences between industries in all agility dimensions, with the exception of structures. The ETA coefficient indicates a weak to moderate dependence between industry and five agility dimensions. The strongest association was observed in management (η = 0.212), followed by the workforce (η = 0.1988), technology (η = 0.1917), collaboration (η = 0.1874), and values (η = 0.185) dimensions. In structures, no statistically significant relationship relevant to industry was proved. These findings mean that the industry has some, although not dominant, influence on various aspects of corporate agility. The most pronounced relationship appears to be in management, which may imply that management practices vary across most industries. The absence of a significant relationship in structures suggests that organizational structures may be similarly agile (or non-agile) across industries. Based on the research results, it can be concluded that the industry has some influence on the agility of EU enterprises, but is not a major factor. Other factors, e.g. corporate culture, enterprise size, or strategy, may have a greater impact on agility than the industry itself. Khan et al. (2022) also emphasize that enterprises should consider the specific aspects of their industry when implementing agile practices, especially in the management dimension. The more unstable and faster the industry changes, the harder it is for enterprises to be flexible and high-performing. This is further supported by research findings of Tufan & Mert (2023), who reveal the journey of transforming knowledge into performance, showing that in the manufacturing industry, which is affected by rapid change and environmental uncertainties, the absorptive capacity for the success of SMEs is transformed into an advantage in competitive environments through strategic agility, becoming one of the main drivers of sustainable business performance. HYPOTHESES EVALUATION This section presents a detailed evaluation of the four key hypotheses that formed the study on SA in EU enterprises. Using a combination of quantitative analysis and qualitative insights, the development and interrelations of agility pillars were assessed. The findings shed light on strengths and weaknesses within enterprises, offering a comprehensive understanding of agility dynamics and areas for improvement. H1: Collaboration and organizational values will show a mean score ≤ 2.20 on a 4-point agility scale and will be significantly different from the least agile dimension (p < 0.05) in EU enterprises. Analysis of mean scores shows that collaboration (2.13) and agile values (2.15) are the two most agile dimensions, with lower scores indicating higher agility. This finding is statistically reinforced by the Wilcoxon signed-rank test, where both dimensions show significantly higher agility than others (p < 0.05). From a theoretical perspective, this aligns with expectations—strong teamwork and shared values are widely recognized as core enablers of agility. The data provides robust support for Hypothesis 1, confirming that collaboration and values are the strongest pillars of agility within EU enterprises. H2: Management will exhibit a mean score ≥ 2.25 on a 4-point agility scale and will be significantly less agile than the most agile dimension (p < 0.05) in EU enterprises. Management exhibits the highest mean score (2.28), indicating it is perceived as the least agile dimension. Wilcoxon test results confirm this, showing statistically significant differences—e.g., management is less agile than the workforce (p = 0.028). Qualitative insights support this view, highlighting resistance to change, hierarchical inertia, and slower adoption of agile practices within management structures. The evidence firmly supports Hypothesis 2, establishing management as the weakest link in agility among EU enterprises. H3: Strategic agility represents an integrated system where all dimensions show significant positive correlations (p < 0.01), confirming the interdependence between the different pillars of agility. Pearson correlations reveal strong, statistically significant relationships (p < 0.01) among all six agility dimensions, illustrating the systemic nature of agility. Particularly strong correlations include management & workforce: r = 0.730, management & collaboration: r = 0.746, management & structures: r = 0.742, collaboration & structures: r = 0.702. These results underscore the interdependence between dimensions; improving one area, especially management, can have a ripple effect across others. Hypothesis 3 has been accepted, as Pearson correlations reveal strong, statistically significant relationships (p < 0.01) across all six agility dimensions (highlighting their systemic interdependence), where improvements in one area, particularly management, can positively influence others. H4: There is a negative relationship between the age of the enterprise and the level of managerial agility. The Spearman correlation between management agility and enterprise age is positive and significant (r = 0.112, p = 0.017), suggesting younger enterprises may perceive their management as more agile. However, the correlation is weak, and interpretation should be cautious, this could reflect generational attitudes or limited exposure rather than structural differences. The hypothesis 4 has been preliminary accepted, recognizing that while the relationship is statistically significant, its weakness highlights the need for further research, ideally through long-term studies. The findings confirm the prominence of collaboration and values, highlight management as the weakest pillar, demonstrate agility’s systemic nature, and suggest a preliminary link between younger enterprises and higher management agility, pointing to directions for future research. CONCLUSION The research findings confirm that agility in European enterprises is a multidimensional concept, with varying levels of agility observed across the six dimensions studied. Collaboration and values emerged as the most agile dimensions, likely due to strong interpersonal trust and established value systems that support teamwork and adaptability. Conversely, management and workforce scores were perceived as the least agile, suggesting the need for greater emphasis on leadership development and employee empowerment in agile transformations. Statistical tests confirmed significant differences among the dimensions, supporting the importance of a targeted yet holistic approach to agility enhancement. Strong interdependencies among dimensions, especially involving management, highlight its central role in enabling or constraining overall enterprise agility. Interestingly, demographic factors such as gender, education, or enterprise size had no significant influence on perceived agility, emphasizing that agility is rooted more in culture and practices than structural characteristics. Overall, the findings suggest that strengthening management agility may serve as a strategic lever, amplifying agility across the organization due to its strong interconnectivity with other dimensions. Enterprises should therefore prioritize cultivating an agile mindset during recruitment and onboarding, ensure consistency of agile practices across all hierarchical levels, and tailor agility efforts to industry volatility and innovation demands based on the pace and nature of change in their industry. Fostering adaptability, openness to innovation, and continuous feedback mechanisms will help embed agility more deeply across departments. The limitations of the research were mainly due to the geographic focus, potential subjectivity of responses, and a short timeframe. While the quantitative findings provide useful statistical insight, future studies should consider incorporating qualitative methods, such as interviews or focus groups. These would help uncover the reasons behind the observed perceptions of agility, especially in the areas where correlations were weak or absent and where quantitative measures alone may not capture deeper organizational dynamics. A qualitative approach could also explore how organizational culture, leadership behavior, or internal communication influence employees’ views on agility. Declarations Funding: This work was supported by the VEGA Grant Agency under project No. 1/0120/25. Author Contribution Malá Denisa was responsible for methodological design and data processing. She developed the empirical part of the article, performed analytical procedures, and ensured the validity and reliability of the applied methods. She also contributed to interpretation of the empirical results and their managerial implications.Minárová Martina contributed to the conceptual framing of strategic agility, developed the theoretical background, and designed the research model. She carried out extensive literature research focused on defining key constructs and differentiating agility from related concepts. She also prepared the introductory sections and formulated the research gaps.Sedliačiková Mariana worked on the development of the practical perspective of the study, especially regarding strategic agility and business sustainability. She synthesized theoretical findings with current trends and designed the discussion section. 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Expert Systems with Applications , 187, 115866. https://doi.org/10.1016/j.eswa.2021.115866 Wendler, R. (2014). Development of the organizational agility maturity model. In Proceedings of the 2014 Federated Conference on Computer Science and Information Systems (pp. 1197-1206). IEEE. https://doi.org/10.15439/2014F79 Wise, T. P., & Reuben, D. (2015). Agile readiness: Four spheres of lean and agile transformation. Routledge. Xiangsheng, D., & Fizza, I. (2024). Enterprise’s Strategic Agility and Resource Allocation Choice: A Case of SMEs in China. Journal of Knowledge economy , 16, 2229-2248. https://doi.org/10.1007/s13132-024-02046-0 Yang, C., & Liu, H. M. (2012). Boosting firm performance via enterprise agility and network structure. Management Decision , 50(6), 1022-1044. https://doi.org/10.1108/00251741211238319 Zielske, M., Held, T., & Kourouklis, A. (2022). A framework on the use of agile methods in logistics startups. Logistics , 6(1), 19. https://doi.org/10.3390/logistics6010019 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 19 May, 2026 Reviews received at journal 18 May, 2026 Reviewers agreed at journal 08 May, 2026 Reviews received at journal 08 May, 2026 Reviewers agreed at journal 30 Apr, 2026 Reviewers invited by journal 29 Apr, 2026 Editor assigned by journal 28 Apr, 2026 Submission checks completed at journal 28 Apr, 2026 First submitted to journal 21 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9481289","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":633100540,"identity":"8cce6729-e03a-4a81-89a2-2dcaf8d0b02f","order_by":0,"name":"Denisa Malá","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYDCCA2AEBOwMjA/AbB6itTAzMBsQrYUBqoVNgigtfMd7Dx78UcMQzd/M/KyaN+cOg3zPAfxaJM+cSzjMc4whd8ZhNrPbvNueMRicbcCvxeBGjsFhBjaG3IbDDCAthxkM+Ak4zOD+G4ODP/4x5M4/zP6tGKRFvp+Qlhs8Bgd42xhyNxzmMWMGaWEg5DDJM0CH8fZJ5G48zFMsOXfbMx6DMwfwa+E7fsb4449vNrnzjrdv/PB22x05+Z4EAi6DAAk4i2BEjoJRMApGwSggAgAAJh1Jd7HFIYoAAAAASUVORK5CYII=","orcid":"","institution":"Matej Bel University","correspondingAuthor":true,"prefix":"","firstName":"Denisa","middleName":"","lastName":"Malá","suffix":""},{"id":633100541,"identity":"9e9dbe1d-cc22-483b-999c-a1fa258836a9","order_by":1,"name":"Martina Minárová","email":"","orcid":"","institution":"Matej Bel University","correspondingAuthor":false,"prefix":"","firstName":"Martina","middleName":"","lastName":"Minárová","suffix":""},{"id":633100542,"identity":"8744c3a2-eb68-4751-9ca5-8bdbc3a2fc6f","order_by":2,"name":"Mariana Sedliačiková","email":"","orcid":"","institution":"Technical University of Zvolen","correspondingAuthor":false,"prefix":"","firstName":"Mariana","middleName":"","lastName":"Sedliačiková","suffix":""},{"id":633100545,"identity":"764a6f96-e888-4620-bae4-226617becc90","order_by":3,"name":"Hussam Musa","email":"","orcid":"","institution":"Matej Bel University","correspondingAuthor":false,"prefix":"","firstName":"Hussam","middleName":"","lastName":"Musa","suffix":""}],"badges":[],"createdAt":"2026-04-21 08:39:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9481289/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9481289/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108724066,"identity":"ca545686-40c5-42b4-883c-1b7a1c8985df","added_by":"auto","created_at":"2026-05-07 16:40:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":56907,"visible":true,"origin":"","legend":"\u003cp\u003eMean values achieved in six agility dimensions\u003c/p\u003e\n\u003cp\u003eSource: authors\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9481289/v1/e6f1e6181daf8bee3cbb22e5.png"},{"id":108806714,"identity":"713d2555-3a70-422c-85b5-67e8fdcd6a29","added_by":"auto","created_at":"2026-05-08 15:29:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":622155,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9481289/v1/e9c24397-2fc1-44e7-a542-281ad29381f3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"From rigidity to responsiveness: A holistic analysis of the key pillars of strategic agility in modern enterprises","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003ePeople currently live in a time of constant changes and uncertainty. Disruption has become the norm, and digital progress has transformed the world. Recent global events have highlighted unpredictability of the life. These shifts and rapid developments are altering various aspects of society. Educated, tech-savvy generations have been reshaping employer-employee relationships and business processes. Numerous books, seminars, and conferences discuss the implications of these changes on strategic management, organizational structures, teamwork, and innovation. Amidst this, there\u0026apos;s a search for solutions to address these complex challenges. Strategic Agility (SA) emerges as a key concept, offering enterprises the flexibility and resilience needed to reduce uncertainty and seize new opportunities in this dynamic environment.\u003c/p\u003e\n\u003cp\u003eAfter analyzing various scientific sources, multiple frameworks describing SA concepts and measurement methods were identified. Drawing from Wendler\u0026apos;s (2014) research and comparing it with other SA concepts (Yang \u0026amp; Liu, 2012; Teece et al., 2016; Alahyari et al., 2017; Tallon \u0026amp; Pinsonneault, 2011), six fundamental pillars of SA were characterized: values, technologies, workforce, management, collaboration, and structures. These six dimensions of SA have been selected based on a synthesis of relevant scientific framework; they represent a comprehensive set of key factors (from cultural and technological to managerial and structural) that integrate all aspects of strategic agility. This model, which is suitable for SMEs, forms the basis of the research into agility in business enterprises of the European Union. Each of these pillars represents a critical dimension of SA in an organization, as detailed below.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAgile values\u003c/strong\u003e and \u003cstrong\u003etechnologies\u003c/strong\u003e are prerequisites for SA in an enterprise. Agile values create a culture embracing proactivity, quick response, trust, and change management. Agile technologies enable efficient communication, information sharing, and appropriate tech use. An agile \u003cstrong\u003eworkforce\u003c/strong\u003e possesses multiple skills to respond to changes, learns continuously, communicates reliably, and takes responsibility. Their thinking and actions align with quality and market requirements. Agile \u003cstrong\u003emanagement\u003c/strong\u003e involves leaders handling changes swiftly, informing and inspiring employees, following long-term visions, and strategically managing investments in advanced technologies. Agile \u003cstrong\u003ecollaboration\u003c/strong\u003e focuses on activities between departments and external partners, emphasizing quality, feedback, and information sharing. Flexible \u003cstrong\u003estructures\u003c/strong\u003e allow quick adaptation of organizational processes to implement changes and ensure competitiveness, enabling rapid decision-making and responsibility shifts. To implement SA, enterprises need people with appropriate skills and knowledge. Managers must handle changes in customer requirements, new markets, and innovations. Flexible structures supporting SA describe the enterprise\u0026apos;s ability to flexibly adapt and foster a collaborative culture.\u003c/p\u003e\n\u003cp\u003eThe strategic gap addressed by this paper lies in the fact that SA, as a key prerequisite for business success in a dynamic and unpredictable environment, has not yet been sufficiently explored. There is a lack of a comprehensive approach that integrates various aspects of SA, from values and technologies to management, collaboration, and organizational structures, into an integrated framework for assessing and developing SA in enterprises. Critical gaps include limited longitudinal studies of agile transformation sustainability, insufficient attention to industry-specific implementation factors, enterprise size, and underdeveloped measurement frameworks. Future research should examine these together with the documented benefits.\u003c/p\u003e"},{"header":"LITERATURE REVIEW","content":"\u003cp\u003eBased on a comprehensive secondary analysis of scientific literature and a critical examination of existing definitions, differences reveal how strategic agility (SA) is defined across different theoretical perspectives. While there is a broad agreement on SA as a dynamic organizational capability, theoretical approaches differ in their emphasis on specific dimensions and underlying mechanisms.\u003c/p\u003e\n\u003cp\u003eEarly formulations by Abshire (1996), who coined the term, emphasized agile strategies in unpredictable environments. Ganguly et al. (2009) advanced this discourse by integrating responsiveness and knowledge management for efficient adaptation, while Conboy (2009) encompassed environmental perception, decision-making, and strategic direction maintenance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYang and Liu (2012) identify four core attributes: flexibility, responsiveness, innovation, and resilience, and argue that these attributes enable survival amid complexity. This multi-dimensional approach contrasts with Tallon and Pinsonneault\u0026apos;s (2011) more focused on rapid response and risk management. Teece et al. (2016) use \u0026quot;enterprise agility\u0026quot; synonymously, focusing on resource reallocation for value creation, which shifts attention from external responsiveness to internal resource allocation. Alahyari et al. (2017) offer another perspective, positioning SA as a strategic tool for market positioning. These definitional variations reflect theoretical tensions regarding whether SA is primarily an external adaptation mechanism or an internal capability development process (Peterman \u0026amp; Zacher, 2021).\u003c/p\u003e\n\u003cp\u003eFor the purposes of this research, these various approaches have been integrated to define strategic agility as an enterprise\u0026apos;s capability to rapidly recognize changes in its environment and accurately interpret them, and flexibly respond through strategic and operational process modifications while preserving its core identity and long-term objectives. This definition addresses the limitations of single-dimension approaches while recognizing the dual nature of SA as both an external adaptation and an internal capability development process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAgile Values\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAgile values underpin rapid response and adaptability to changing business environments, emphasizing innovation over maintaining the status quo (Huck-Fries et al., 2025). Huck-Fries et al. (2025) demonstrate how agile organizations reframe failure as learning opportunities, encouraging risk-taking and innovation. It is argued that open communication, personal responsibility, and continuous improvement are hallmarks of agile organizations, particularly when driven by top management commitment.\u003c/p\u003e\n\u003cp\u003eThe alignment of organizational and employee values is critical. Meister et al. (2022) report that over 80% of employees prioritize value alignment, with many willing to leave positions misaligned with their values. Research indicates agile values influence risk perception and learning, forming the foundation of adaptive, innovative cultures (Goncalves et al., 2020; Rizi et al., 2024). Thus, it is contended that embedding agile values strategically is essential for enterprise growth.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAgile Technologies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAgile technologies encompass tools and methods facilitating flexible development, collaboration, and business responsiveness (Beck, 2001). The work of Dyb\u0026aring; \u0026amp; Dings\u0026oslash;yr (2009) established that agile software development, characterized by iterative cycles and frequent customer feedback, enables rapid innovation. Frameworks like Scrum and Kanban help teams prioritize and adapt swiftly (Weflen et al., 2022), while collaboration and open communication are central, enhancing problem-solving and productivity (Dyb\u0026aring; et al., 2014; 2025; Malik et al., 2025). Agility extends beyond IT, supporting project management in diverse sectors such as marketing and manufacturing. However, Santos and Carvalho (2021) identify cultural resistance and process misalignment as primary barriers in large enterprises. It is contended that despite adoption, many organizations implement agile technologies superficially, adopting the terminology and tools while failing to embrace the fundamental cultural transformation required, ultimately undermining their potential for genuine strategic advantage.\u003c/p\u003e\n\u003cp\u003eAgile technologies streamline administration and recruitment, enabling faster hiring and freeing resources for strategic initiatives (Kude et al., 2023). They support customer relations (Mohamed \u0026amp; Darwish, 2019) and enhance supply chain flexibility through improved planning and inventory management (Zielske et al., 2022). Overall, agile technologies enhance flexibility, collaboration, customer focus, and competitiveness (Runping et al., 2025).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAgile Workforce\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAghina et al. (2020) demonstrate that agile HR processes incorporating continuous employee feedback boost engagement by up to 20% and accelerate recruitment by 75%. Employees increasingly demand meaningful, accessible, and engaging work experiences, which is supported by agile organizational design (Xiangsheng \u0026amp; Fizz, 2024; Moh\u0026apos;d et al., 2024).\u003c/p\u003e\n\u003cp\u003eTruss (1999) and \u0026Scaron;ik\u0026yacute;ř (2014) highlight that shifting from traditional roles to teamwork increases the need for self-control, responsibility, and continuous learning, despite associated psychological pressures. Based on the presented findings, it is supposed that this theoretical framework challenges the conventional understanding of hierarchical control and reframes psychological pressure not as a disadvantage but as a driver for organizational transformation. Teams with shared mindsets and proactivity, emphasizing soft skills, strong communication, and continuous development, excel in agility (McMackin \u0026amp; Heffernan, 2020; Ranasinghe \u0026amp; Sangarandeniya, 2021, Jooss, et al., 2024). Yet challenges remain in overcoming resistance and inconsistent processes, with culture being key to innovation management (State of Agile Report, knowledgehut.com; Abdala et al., 2025). Agile HR fosters environments of collaboration, self-reflection, and human connection, critical for employee motivation and enterprise success (Moh\u0026apos;d et al., 2024; Mollet \u0026amp; Kaudela-Baum, 2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAgile Management\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eModern business demands creativity, courage, and flexibility (Suntinger, 2010). Tas (2022) conceptualizes agile leadership as integral to strategic agility, managing change in competitive environments through adaptability and team empowerment. It contrasts with traditional hierarchies by promoting autonomous, cross-functional teams, transparent communication, and accountability (Tandon et al., 2024).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis transformation generates positive outcomes, including improved productivity, satisfaction, and competitiveness (Vaszkun \u0026amp; Szir\u0026aacute;ki, 2023). Effective agile leaders facilitate knowledge sharing and trust rather than exercising control (Tandon et al., 2024). Emotional intelligence and ethical behavior underpin effective agile leadership, creating supportive environments that facilitate change acceptance (Tas, 2022). It is suggested that many organizations adopt agile frameworks superficially, maintaining traditional hierarchical structures under new terminology, which ultimately constrains genuine employee independence and strategic innovation.\u003c/p\u003e\n\u003cp\u003ePorkodi (2024) emphasizes that agile leadership directs team composition aligned with products and customer needs, a prerequisite for agility and innovation. Leaders 4.0 embody adaptability and innovation, critical for meeting the demands of today\u0026apos;s agile enterprises (Awodiji, 2024, Lanteri, 2025).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAgile Collaboration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAgile collaboration features flexibility, iteration, transparency, and collective accountability (Nold \u0026amp; Michel, 2016), enabling rapid feedback and adaptation (Crocitto \u0026amp; Youssef, 2003).\u003c/p\u003e\n\u003cp\u003eGligor et al. (2013) demonstrate that agile collaboration enables swift responses to environmental changes, crucial for competitiveness in dynamic markets. While Chakravarty et al. (2013) confirm that IT capabilities enhance organizational agility, expenditure alone is insufficient without strategic investments. Collaborative agreements expand resource access and knowledge sharing, supporting sustainable competitive advantages in turbulent environments (Mueller \u0026amp; Jungwirth, 2020; Tufan \u0026amp; Mert, 2023). Cultural and procedural shifts pose challenges, but successful agile collaboration improves team efficiency, innovation, and adaptability to new challenges (Nold \u0026amp; Michel, 2016; Mancuso et al., 2024). It is aligned with the perspective that agile collaboration\u0026apos;s effectiveness depends critically on cultural readiness and strategic implementation rather than mere adoption of collaborative frameworks, as superficial integration may yield limited competitive benefits.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAgile Structures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFlexible organizational structures enable rapid adaptation of processes and decision-making, supporting agility and innovation (Lichtenthaler, 2020). By decentralizing authority and fostering employee autonomy, enterprises can enhance responsiveness and competitiveness. Continuous learning and agile methodologies embed the resilience necessary for sustained success in dynamic environments. It is aligned with the view that structural flexibility alone is insufficient without corresponding cultural transformation, as rigid organizational mindsets can weaken even the well-designed agile frameworks.\u003c/p\u003e\n\u003cp\u003eThe literature review highlights SA as a vital capability for enterprises to rapidly adapt to market changes through flexible values, technologies, workforce, leadership, collaboration, and structures. Agile management fosters innovation, resilience, and competitive advantage by promoting open communication, empowering teams, and continuous learning.\u003c/p\u003e\n\u003cp\u003eHowever, comprehensive integration frameworks remain underdeveloped. Successful agility requires a cultural shift supported by agile leadership and integrated practices across the enterprise to navigate uncertainty and sustain long-term growth.\u003c/p\u003e"},{"header":"METHODOLOGY AND HYPOTHESES","content":"\u003cp\u003e\u003cstrong\u003eResearch Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study employs a two-phase mixed-methods approach combining primary quantitative research and systematic literature review.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhase 1.\u0026nbsp;\u003c/strong\u003eThe primary quantitative research, conducted between September 2023 and January 2024, focused on assessing the development level of individual pillars of strategic agility in European Union enterprises. The objectives were to identify the most and least developed agility dimensions, explore their interconnections, and examine the influence of organizational age on agility.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhase 2.\u0026nbsp;\u003c/strong\u003eThe second phase employed a systematic literature review (SLR) following PRISMA guidelines (Page et al., 2021) to synthesize prior research on strategic agility and to identify theoretical gaps. A structured search was conducted in Scopus (1996\u0026ndash;2025) and the Web of Science Core Collection (1996\u0026ndash;2025). Google Scholar was used as a supplementary source to capture additional records that may not be indexed in Scopus/WoS. The search string combined agility-related terms with conceptual terms using Boolean operators: (\u0026quot;strategic agility\u0026quot; OR \u0026quot;enterprise agility\u0026quot; OR \u0026quot;organizational agility\u0026quot; OR \u0026quot;business agility\u0026quot; OR \u0026quot;organizational adaptability\u0026quot;) AND (\u0026quot;framework\u0026quot; OR \u0026quot;model\u0026quot; OR \u0026quot;adaptation\u0026quot; OR \u0026quot;responsiveness\u0026quot; OR \u0026quot;flexibility\u0026quot;). Backward citation searching complemented the database search.\u003c/p\u003e\n\u003cp\u003eEligible studies were peer-reviewed, English-language journal articles and conference proceedings published between 1996 and 2025 that addressed strategic agility concepts, frameworks, or applications. Records were exported, duplicates were removed, and titles/abstracts were independently screened by two reviewers. Full texts were then assessed for eligibility. The initial search yielded a large pool of records (with Google Scholar providing approximate hit counts rather than exact database records). Following screening and full-text assessment, 126 articles were reviewed in full, and 77 studies were retained for synthesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research focused on enterprises operating in the European Union. EU member states share common regulatory frameworks and economic integration while demonstrating sufficient regional diversity to provide comprehensive insights into strategic agility implementation across varying organizational contexts. Following Louangrath (2017) and Faeron (2017), the minimum sample size was calculated using the standard formula, considering a confidence interval (at 95% reliability level, z = 1.96), margin of error 5%, proportion of the sign (p = 0.5 for unknown value), and population size of approximately 24 million EU enterprises. The minimum sample size was set at 380 enterprises.\u003c/p\u003e\n\u003cp\u003eAn electronic survey was distributed to 2,560 enterprises using email contacts sourced from a European business database. Out of 2,560 questionnaires sent, 742 responses were received (28.98 % response rate). After discarding 286 incomplete or non-representative responses, the final sample included 456 enterprises. Missing or partially completed data within valid questionnaires were handled using mean substitution to maintain consistency across variables.\u003c/p\u003e\n\u003cp\u003eSample representativeness was verified using Pearson\u0026apos;s Chi-square goodness-of-fit test, comparing enterprise size distribution against reference data from Statista. The test confirmed sample representativeness, with p = 0.570 exceeding the significance level of \u0026alpha; = 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn anonymous electronic questionnaire was developed to ensure objective responses without concerns about potential consequences. The identification section collected data on enterprise size (micro: 1-9, small: 10-49, medium: 50-249 employees) to verify sample representativeness.\u003c/p\u003e\n\u003cp\u003eThe research section contained 24 questions divided into six categories according to agility dimensions: (1) organizational values, (2) implementation of new technologies and innovations, (3) employees, (4) management and leadership, (5) cooperation within and outside the enterprise, and (6) organizational structure and hierarchy. The structure reflects theoretically grounded pillars of agility and allows for statistical analysis of interrelationships between dimensions.\u0026nbsp;Each dimension was assessed using four Likert-type items (where 1 indicates high agility, 2 moderate agility, 3 low agility, and 4 no agility).\u003c/p\u003e\n\u003cp\u003eTo verify internal consistency and reliability of the questionnaire, a pilot test was conducted on a sample of 50 respondents. Cronbach\u0026apos;s alpha coefficient was used to assess internal consistency (Cronbach, 1951). Analysis demonstrated Cronbach\u0026apos;s alpha value of \u0026alpha; = 0.913, indicating reliability and exceeding the minimum recommended threshold of 0.7 for exploratory research. The questionnaire was therefore used in the main research without modifications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData analysis included descriptive statistics (arithmetic mean, mode, and median) to compare agility across dimensions, rated on a 1 to 4 scale (1 = high agility; 4 = absence of agility).\u003c/p\u003e\n\u003cp\u003eThe Friedman test was used to confirm significant differences in agility across dimensions (p = 0.0). Wilcoxon signed-rank tests identified which dimensions differed significantly. Pearson correlation analysis revealed interdependence among all six agility dimensions, particularly between management and employees, management and collaboration, management and structures, and collaboration and structures. Spearman\u0026apos;s correlation assessed the impact of demographics (gender, education, job position, tenure, company size, sector, and company age) on agility dimensions, showing only weak but significant correlations with employment length and enterprise age. One-way ANOVA and the ETA coefficient (\u0026eta;) were used to analyze differences in agility dimensions across industries.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypotheses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the literature review and empirical evidence, four hypotheses were formulated to be tested in the context of EU enterprises:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH1:\u003c/strong\u003e Collaboration and organizational values will show a mean score \u0026le; 2.20 on a 4-point agility scale and will be significantly different from the least agile dimension (p \u0026lt; 0.05) in EU enterprises.\u003cbr\u003e\u0026nbsp;Research by Camarinha-Matos (2019) has shown that globalization and digitalization have significantly increased the need for effective collaboration in today\u0026apos;s business environment. Holbeche (2018) highlights that investments in tools and training that support collaboration directly contribute to increasing agility in this area. Shams et al. (2021) point out that the development of agile values requires an emphasis on corporate values, ethics, and social responsibility, which form the basis of an agile culture. These findings support the assumption that it is collaboration and agile values that are among the most developed dimensions of agility in EU enterprises.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH2:\u003c/strong\u003e Management will exhibit a mean score \u0026ge; 2.25 on a 4-point agility scale and will be significantly less agile than the most agile dimension (p \u0026lt; 0.05) in EU enterprises.\u003c/p\u003e\n\u003cp\u003eResearch by Yang and Liu (2012) points out that traditional hierarchical structures in enterprises often hinder managerial agility by slowing down decision-making processes and reducing the ability to respond flexibly to dynamic market changes. In such systems, managers tend to be less inclined to take risks and innovate, which weakens overall management agility. At the same time, Zitkus (2011) points to the cultural specificities of the European management approach, which emphasizes consensus and long-term stability, factors that can hinder fast and flexible decision-making. These findings suggest that management, as a pillar of agility, remains the least developed in European enterprises.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH3:\u003c/strong\u003e Strategic agility represents an integrated system where all dimensions show significant positive correlations (p \u0026lt; 0.01), confirming the interdependence between the different pillars of agility.\u003c/p\u003e\n\u003cp\u003eSeo et al. (2025) point out that enterprises function as integrated systems in which the parts are interconnected and interact with each other. Therefore, improving one area of agility often requires or naturally leads to changes in other pillars. For example, the implementation of agile methodologies in product development inevitably affects organizational structure, internal communication, and collaborative culture. Interdependence is also reflected in the fact that neglecting one dimension can hinder progress in other areas. If an enterprise focuses solely on technology but neglects human capital or corporate values, its ability to achieve higher levels of agility may be limited. This complex nature of agility is supported by the empirical findings of authors such as Wise (2015), Rigby et al. (2020) and Hoda et al. (2020), whose studies suggest that successful agile transformations require simultaneous changes across multiple pillars. Based on these findings, it is assumed that agility in organizations is a complex and interconnected system in which progress in one dimension supports the development of the others. It is important to note, however, that while this hypothesis has strong theoretical and empirical underpinnings, the exact nature and strength of the relationships between the different dimensions of agility may depend on the specific enterprise, its size, industry, and other factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH4:\u003c/strong\u003e There is a negative relationship between the age of the enterprise and the level of managerial agility.\u003c/p\u003e\n\u003cp\u003eNewly established enterprises are typically required to respond swiftly and flexibly to rapidly changing market conditions to survive and grow. Unlike long-standing enterprises, younger enterprises often operate without entrenched hierarchical structures and rigid bureaucratic procedures, enabling faster decision-making and more agile implementation of innovations. Furthermore, these enterprises tend to be built on modern technologies and progressive business models from the outset, which enhances their capacity to adapt to emerging trends and competitive pressures (Hsueh, Tu, 2004). Their organizational culture is often characterized by openness to experimentation, continuous learning, and a readiness to embrace change\u0026mdash;attributes that collectively support higher agility in management (Govuzela, Mafini, 2019). These characteristics suggest that organizational youth can foster a more flexible, dynamic approach to leadership and operations, which forms the basis for the hypothesis that more recently established enterprises tend to demonstrate greater management agility.\u003c/p\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cp\u003eThis part presents the key findings of the research, followed by their interpretation in the context of existing literature. The analysis focuses on evaluating the level of development across six dimensions of strategic agility in European Union enterprises, identifying the most and least developed pillars, and exploring their interrelationships.\u003c/p\u003e\n\u003cp\u003eFirstly, the research results were evaluated by simple statistical tools: mean, mode, and median, which enabled comparison of the six dimensions and the degree of agility achieved in each of them. The \u003cstrong\u003ehighest agility\u0026nbsp;\u003c/strong\u003ewas observed in the \u003cstrong\u003ecollaboration\u003c/strong\u003e dimension, where the mean on a scale of 1 to 4 (where 1 indicates high agility, 2 moderate agility, 3 moderate deviation from agility, and 4 no agility) was 2.13, followed by the value dimension, which achieved the mean value of 2.15. The management (mean of 2.28) and the workforce (mean of 2.23) dimensions ranked as the least agile. It should be noted that the differences in obtained mean values are rather small, and all dimensions show signs of moderate agility, as the mean values are close to the value of 2. However, despite the small differences, the dimensions can be ranked from the least to most agile, as viewed in Figure 1.\u003c/p\u003e\n\u003cp\u003eIt is interesting to find out that the \u003cstrong\u003emanagement\u003c/strong\u003e and workforce were identified by respondents as the \u003cstrong\u003eleast agile\u003c/strong\u003e dimensions within the overall sample of EU enterprises. On the other hand, collaboration was identified as the most agile dimension, which may slightly contradict. This apparent contradiction may be explained by the finding, confirmed by Soda and Zaher (2012), that effective collaboration often occurs horizontally among colleagues rather than within formal management structures.\u003c/p\u003e\n\u003cp\u003eTheoretical framework on strategic agility in business (Beck et al., 2001; Huck-Fries, 2025; Meister et al., 2022; Gligor et al., 2013) emphasizes the importance of collaboration, as well as the essential role of corporate values for sustaining agility. Higher agility in both of these dimensions (2.13 and 2.15) may be the result of better employee engagement and effective adoption of shared values. In practice, higher agility in these dimensions indicates that the enterprise has well-established mechanisms to support teamwork and value sharing, which can be key to swift and successful adaptation to change. Enterprises that emphasize collaboration and incorporate agility in their value system may naturally exhibit higher agility in these areas (Chakravarty et al., 2013). Management and the workforce, on the other hand, may still have different approaches and perspectives on agility, which could explain lower scores in both of these dimensions. Although the enterprise possesses a clear system of agile values and has implemented agile principles, their manifestation through the actual behavior of the enterprise\u0026rsquo;s management and workforce may lag behind.\u003c/p\u003e\n\u003cp\u003eTo summarize the above reasoning and provide clear arguments, high agility in the collaboration dimension indicates that enterprises have a strong culture of teamwork, which is enhanced by effective communication among employees. This environment then promotes rapid information exchange, collective decision-making, and the ability to respond quickly to change (Vaszkun, Szir\u0026aacute;ki, 2023). The second place for the value dimension could be explained by enterprises placing an emphasis on shared values and principles that guide their activities and processes. This approach tends to promote consistent behavior and decision-making across the enterprise, increasing its ability to adapt to new challenges and environments (Satell, Windschitl, 2021). On the other hand, lower agility in management may signal that executives may have difficulty in adapting to agile methods or supporting agile processes across the enterprise or may be unwilling to do so. This may include their conscious or unconscious resistance to change, lack of flexibility in management structures, or a lack of skills necessary to effectively manage independent agile teams. Lower levels of agility among the workforce may indicate problems such as a lack of training in agile methods, low levels of engagement and intrinsic motivation, resistance to changing work processes, or, potentially, fear of taking responsibility for such action. The findings align with those of Sherehiy and Karwowsky (2014), who observed that enterprises with effective collaboration and clearly defined values may be able to swiftly respond to market changes and innovate their processes. However, deficiencies in management and employee agility can limit the full potential of the enterprise, which can have a negative impact on its overall performance and competitiveness.\u003c/p\u003e\n\u003cp\u003eThe research has been approached from the perspective of comparing the agility scores in all six dimensions. Friedman\u0026rsquo;s test confirmed that the six dimensions of agility in targeted enterprises are not equally important, since p-value \u0026lt; 0.001, proving that not all agility dimensions have the same impact or are equally implemented. Wilcoxon signed rank test (Table 1) was applied to determine which dimensions are more significant than the others.\u003c/p\u003e\n\u003cp id=\"_Toc175561571\"\u003eTable\u0026nbsp;1 Wilcoxon signed rank test for agility dimensions\u003c/p\u003e\n\u003ctable style=\"width: 4.5e+2pt\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eTest Statistics\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eV-C\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eS-V\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eT-S\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eZ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-1.078\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-2.361\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.274\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAsymp. Sig. (2-tailed)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.784\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eW-T\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eM-W\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eZ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-1.149\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-2.203\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAsymp. Sig. (2-tailed)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003ea. Wilcoxon Signed Ranks Test\u003c/p\u003e\n \u003cp\u003eb. Based on negative ranks.\u003c/p\u003e\n \u003cp\u003eDimensions: V \u0026ndash; values, T \u0026ndash; technologies, W \u0026ndash; workforce, M \u0026ndash; management, C \u0026ndash; collaboration, S \u0026ndash; structures\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: authors\u003c/p\u003e\n\u003cp\u003eAs can be deduced from Figure 1, the \u003cstrong\u003evalue\u003c/strong\u003e and \u003cstrong\u003ecollaboration\u003c/strong\u003e dimensions achieved the lowest values (ranging from 1 to 4), and are thus the \u003cstrong\u003emost agile\u003c/strong\u003e. High agility in the value dimension indicates that enterprises have a strong foundation in an agile culture. In the collaboration dimension, high agility indicates effective teamwork and communication. This foundation is crucial as Abdala et al. (2025) emphasize that fostering a corporate culture that prioritizes continuous learning, encourages experimentation, and supports strategic pivots when necessary allows managers to align business direction with evolving market demands, regulatory requirements, and consumer preferences, creating a proactive mindset that enables enterprises to remain competitive and responsive to both opportunities and threats in the ever-changing business landscape. The achieved values were highest in \u003cstrong\u003emanagement\u003c/strong\u003e; therefore, it proves to be the \u003cstrong\u003eleast agile\u003c/strong\u003e dimension. This suggests that management may be the biggest barrier to the implementation of agility in European enterprises. This may reflect traditional hierarchical structures or rigid management processes that are rather difficult to transform, and means that this area requires the most attention in agile transformation (Waardenburg, Vliet, 2013; Boehm, Turner, 2002). The other dimensions \u0026ndash; technology, workforce, and structures, ranked in between, indicating that in agility, enterprises perform on average in these areas. In structures, this may reflect a partial adaptation to more agile organizational forms. In technology, average scores suggest some degree of adoption of agile technology solutions, while there is undoubtedly room for improvement. As to the workforce dimension, the scores prove that employees are partially ready for agile working practices; nevertheless, there is still potential for development. This aligns with the findings by Mancuso et al. (2024), who demonstrate that by allowing enterprises to access innovative products and services from startups, they provide a swift and flexible means of reconfiguring the competencies and resources of an enterprise, suggesting that workforce agility can be enhanced through external partnerships that bring fresh perspectives and innovative approaches to internal teams.\u003c/p\u003e\n\u003cp\u003eIt is advisable for the EU enterprises to build on their strength in the values and collaboration dimensions by using the corporate culture in spreading the agile values, as well as the collaboration of teams to develop creativity and innovation in their operations. On the other hand, attention should be paid to the transformation of management towards agile practices (Lichtenthaler, 2020). Since enterprises prove to have agile values, it is likely that the problem of implementing them into management\u0026rsquo;s behavior and actions. Therefore, since there are differences between dimensions, a holistic approach appears to be appropriate for the agile transformation of EU enterprises. Improvement in one dimension can positively impact other dimensions, and the valuable insight into the relative strengths and weaknesses of different aspects of agility allows EU enterprises to prioritize their efforts in implementing agile practices, while on one hand strengthening their strengths and on the other, addressing the areas that need attention.\u003c/p\u003e\n\u003cp\u003eAs part of the research, the Pearson correlation analysis was used to investigate the correlation between the six agility dimensions. The test confirmed a direct dependence among all dimensions (Table 2), while a strong direct correlation between management and employees (rs = 0.730), management and collaboration (rs = 0.746), management and structures (rs = 0.742), and collaboration and structures (rs = 0.702) were discovered. These findings mean that the more agile the management of an enterprise is, the more agile are the employees. Furthermore, with more agile collaboration, the agility in structures increases, and higher agility in collaboration brings more agile structures.\u003c/p\u003e\n\u003cp id=\"_Toc175561572\"\u003eTable\u0026nbsp;2 Correlations between agility dimensions\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\n \u003cp\u003e\u003cstrong\u003eCorrelations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePearson Correlation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.681\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.693\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.680\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.649\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.664\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePearson Correlation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.681\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.633\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.687\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.679\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.673\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePearson Correlation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.693\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.633\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.730\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.686\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.658\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePearson Correlation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.680\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.687\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.730\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.746\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.742\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePearson Correlation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.649\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.679\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.686\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.746\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.702\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePearson Correlation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.664\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.673\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.658\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.742\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.702\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\n \u003cp\u003e**. Correlation is significant at the 0.01 level (2-tailed).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: authors\u003c/p\u003e\n\u003cp\u003eThe fact that a direct dependence between all dimensions was confirmed suggests that agility is a complex and interrelated concept, and should be approached as such. The interdependence between all six dimensions indicates that improvement in one single dimension positively influences the other five dimensions, which supports the suggestion for a holistic approach to implementing agility.\u003c/p\u003e\n\u003cp\u003eStrong \u003cstrong\u003ecorrelation between management and employees\u003c/strong\u003e (r = 0.730) highlights the key role of people in the enterprise in promoting agility at all levels of the hierarchy. This finding aligns with the research by Xiangsheng \u0026amp; Fizz (2024), which similarly confirmed a positive correlation between human resources and strategic agility. Although management\u0026rsquo;s agility scores are the lowest, it is the managers who set the tone and communicate the benefits of agility and its principles across the whole enterprise. Managers also create an environment of autonomy, flexibility, and innovation among employees (Clayton, 2021). Conversely, agile employees may require and encourage more agile approaches from their management, which, as proved by the results, may be a way to build up the overall enterprise agility.\u003c/p\u003e\n\u003cp\u003eStrong \u003cstrong\u003ecorrelation between management and collaboration\u003c/strong\u003e (r = 0.746) suggests that the more agile management is, the more it contributes to effective collaboration in an enterprise. Managers who adopt agile practices promote open communication, teamwork and knowledge sharing, which reflects in developing innovation and creativity among cooperating employees (Ivari, Ivari, 2011). This aligns with findings by Runping et al. (2025), who discovered that ventures should establish an efficient system for distributing, interpreting, and implementing strategic knowledge through cross-departmental meetings, information-sharing platforms, and collaboration mechanisms that enhance the dissemination and application of strategic knowledge. It works vice versa as well, the more cooperative and collaborative the workforce is, the more agile approach from the managers is required.\u003c/p\u003e\n\u003cp\u003eAnother strong \u003cstrong\u003ecorrelation\u0026nbsp;\u003c/strong\u003ewas found \u003cstrong\u003ebetween management and structures\u003c/strong\u003e (r = 0.742), which indicates that agile management is closely linked to the creation and maintenance of agile corporate structures. This also applies in terms of hierarchy, which means that an organizational structure that is flatter, more open, and more flexible can easily affect the way an enterprise is managed. Flatter hierarchies mean fewer decision-making levels, and smoother, faster communication of information, roles, or tasks, as well as a less complex system of authorities and their delegation (Bueechl et al., 2021). The strong \u003cstrong\u003ecorrelation between collaboration and structures\u003c/strong\u003e (r = 0.702) suggests that agile organizational structures significantly promote effective collaboration. This is further supported by Mukherjee et al. (2015), who found that flexible, less hierarchical enterprises are likely to facilitate better, faster, and easier communication and collaboration between different parts of the enterprise.\u003c/p\u003e\n\u003cp\u003eFrom the above, it can be concluded that management appears to be a key factor in agile transformation as it correlates strongly with several other dimensions. These strong correlations enable authors to claim that agile transformation should be a comprehensive process and should not be implemented as isolated initiatives. Improvements in one dimension, especially in management, will lead to improvements in other dimensions, creating a virtuous cycle of agile transformation. This perspective is reinforced by Lanteri (2025), who argues that since organizations need to constantly transform themselves and continuous innovation is key to survival, they should be designed and led for constant transformation. With this in mind, a conclusion can be made that the focus in adopting and/or improving agile practices should be primarily on management as a potential catalyst for overall agile transformation.\u003c/p\u003e\n\u003cp\u003eBesides searching for correlations among the individual dimensions, the relationship between each agility dimension and the demographic data of respondents were also investigated. To determine the relations, the Spearman\u0026rsquo;s correlation coefficient test was used, measuring the strength and direction of monotonic association between two variables (Table 3).\u003c/p\u003e\n\u003cp id=\"_Toc175561573\"\u003eTable\u0026nbsp;3 Spearman\u0026apos;s correlation coefficient of the relationship between agility dimensions and respondents\u0026rsquo; demographics\u003c/p\u003e\n\u003ctable style=\"width: 4.6e+2pt\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpearman\u0026apos;s rho \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eO25\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eO26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eO27\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eO28\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eO29\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eO31\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCorrelation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.106*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.454\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCorrelation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.011\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.059\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCorrelation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.132**\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.042\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; 0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCorrelation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.105*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.112*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.769\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCorrelation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; 0.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCorrelation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.121**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.382\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.010\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.213\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\n \u003cp\u003e*. Correlation is significant at the 0.05 level (2-tailed).\u003c/p\u003e\n \u003cp\u003e**. Correlation is significant at the 0.01 level (2-tailed).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\n \u003cp\u003eO25 \u0026ndash; respondent\u0026rsquo;s gender\u003c/p\u003e\n \u003cp\u003eO26 \u0026ndash; respondent\u0026rsquo;s education\u003c/p\u003e\n \u003cp\u003eO27 \u0026ndash; respondent\u0026rsquo;s position in the enterprise\u003c/p\u003e\n \u003cp\u003eO28 \u0026ndash; respondent\u0026rsquo;s length of service in the enterprise\u003c/p\u003e\n \u003cp\u003eO29 \u0026ndash; size of the enterprise\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eO30 \u0026ndash; sector in which the enterprise operates\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eO31 \u0026ndash; length of time the enterprise has been in the market\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: authors\u003c/p\u003e\n\u003cp\u003eRegarding gender, education level, respondent\u0026rsquo;s position in the enterprise, and the size of the enterprise, the research results confirmed no correlation, as all p-values are greater than 0.05. This means that it cannot be certainly claimed that these factors influence agility in enterprises. The lack of correlation in terms of gender suggests that men and women perceive the status of agility similarly, which indicates that agile practices and principles are universally applicable regardless of gender. The lack of correlation in education suggests that the perception of agility implementation is not influenced by the highest achieved level of formal education. According to Tripathi et al. (2020), this likely suggests that agile principles are a matter of practice and culture rather than formal education. For the respondent\u0026rsquo;s position in the enterprise, there has also been noted a lack of correlation, indicating that the perception of agility implementation is similar across different levels of the corporate hierarchy. This may suggest that agile principles are sufficiently embedded across the organization and that communication and training efforts related to agility are reaching employees regardless of their formal position. The uniform perception also implies that agile practices may be integrated into day-to-day operations across departments and management layers. The lack of correlation for the size of enterprise suggests that agility is not necessarily dependent on the size, and agile practices are applicable across enterprises of different sizes. These results support the idea that agility is a universal concept that is not dependent on demographic or business characteristics. Instead of focusing on demographic or structural factors, enterprises may decide to pay attention to building an overall agile culture and implementing agile practices. The lack of correlation in gender, education, and employee position suggests that agility provides equal opportunities for all employees. Lack of correlation in size of enterprise supports the idea that agile principles can be adapted to serve different types of enterprises.\u003c/p\u003e\n\u003cp\u003eIn the question about how long the respondents have been working in their enterprise, a \u003cstrong\u003eweak direct relationship\u003c/strong\u003e in the value (rs = 0.106), workforce (rs = 0.132), management (rs = 0.105), and structures (rs = 0.121) dimensions were confirmed. While these correlations are statistically significant, their strength is very low, indicating minimal practical impact. This means that although there is a tendency for shortly employed employees to perceive greater agility, the differences are not strong enough to suggest a substantive behavioral or structural distinction within the organization. This finding supports the research of Jooss et al. (2024), who, by unpacking both initial and dynamic skills-matching mechanisms, adopt a processual view on human resource management and respond to the call for more dynamic approaches to managing talent, suggesting that tenure alone may not be the primary determinant of agile perception, but rather the dynamic adaptation and skills development throughout employment.\u003c/p\u003e\n\u003cp\u003eThe weak positive correlations in the \u003cstrong\u003evalues\u003c/strong\u003e dimension may indicate that employees employed for a shorter time have a slightly better understanding and identification with the agile values of the enterprise. These employees tend to rate themselves and their co-workers as more adaptable, flexible, and open to change. This could also suggest that newer employees are already hired with greater emphasis on agile skills and thinking and are thus somewhat naturally more open to new methods and approaches. Employees working in their enterprise for a longer time may be assumed to have ingrained older work habits, which are less compatible with agile values.\u003c/p\u003e\n\u003cp\u003eThe strongest, although still weak, correlation in the \u003cstrong\u003eworkforce\u003c/strong\u003e dimension may indicate that short-term employers may also perceive themselves and their colleagues as slightly more agile, as they have less embedded work habits, and this makes employees more open to new, innovative approaches. Aghina et al. (2020) similarly conclude that it is effective for an enterprise to emphasize recruiting such employees who manifest an agile mindset and appear more flexible and open to change. Another benefit of these employees is that they may tend to see things more positively and idealistically, having a limited view of the barriers to agility in the enterprise, which are more visible to employees with longer work tenure.\u003c/p\u003e\n\u003cp\u003eThe weak positive correlation in \u003cstrong\u003emanagement\u003c/strong\u003e may indicate that with shorter tenure, employees tend to view management as slightly more agile, rating the enterprise leaders as more flexible. adaptable and open to change. Newer employees may, undoubtedly, have less bias against management and may be more open to perceiving their efforts to be more agile. Koutsikouri et al. (2020) found that these employees have not yet had the opportunity to experience situations where management might exhibit less agile behavior. Thus, they tend to see management in a more positive light during their first months or years in the enterprise.\u003c/p\u003e\n\u003cp\u003eThe weak positive correlation in the \u003cstrong\u003estructure\u003c/strong\u003es dimension may indicate that employees working in the enterprise for a shorter time tend to perceive organizational structures, hierarchies, processes, and systems as slightly more agile. Newer employees may not yet have had sufficient time to encounter the rigid aspects of corporate structures, if there are any, and may have less understanding about how traditional corporate structures work. Another aspect worth considering is the new employees\u0026rsquo; optimistic expectations about the flexibility and adaptability of corporate structures and processes. This perspective is supported by empirical findings of Malik et al. (2025), who emphasize the importance of digital orientation as an antecedent that requires intermediate steps of information governance and digital transformation to influence digitally enabled strategic agility, suggesting that newer employees may better recognize and appreciate digitally enhanced structural elements that contribute to organizational agility. On the other hand, as Gregory et al. (2022) found, established employees have most likely experienced attempts by the enterprise to reorganize or any unsuccessful change efforts, which have affected their perceptions of the agility of structures. Newer employees would also typically compare current structures to previous employers. while employees working in an enterprise for a longer period tend to compare them to the past structures within the same enterprise.\u003c/p\u003e\n\u003cp\u003eWhen searching into the enterprise\u0026rsquo;s length on the market, a weak direct relationship was found in the management dimension (rs = 0.112), meaning that the shorter the enterprise has been operating on the market, the more agile the management is. Spearman\u0026rsquo;s rank coefficient proved a weak direct dependence between the enterprise\u0026rsquo;s time in the market and management agility. This finding provides an interesting insight into the relationship between the age of an enterprise and the agility of its management. The result suggests that younger enterprises tend to have more agile management, which can be explained by newer enterprises being established with modern management practices and philosophies that place more emphasis on agility. Organizational structures and corporate processes of these enterprises are less rigid, allowing for greater flexibility in management. Newer enterprises have also emerged in a more dynamic market environment, which itself requires a more agile approach to management. Moreover, they often employ young managers who are more open to agile methods. Similar conclusions were reached by Permatasari and Abadi (2024), whose research suggests that newer employees, still acclimating to the company\u0026apos;s environment and less resistant to adopting agile methodologies, exhibit the highest levels of agility and adaptability in project execution. These enterprises face more pressure to innovate and adapt quickly in order to maintain their position in the market, which is reflected in more agile management. What aligns with the previous findings is that new enterprises have not had time to build complex bureaucratic structures that can hinder agility.\u003c/p\u003e\n\u003cp\u003eA one-way analysis of variance (ANOVA) using the ETA coefficient (\u0026eta;) was applied to investigate the potential relationship between the level of each agility dimension and the industry in which the enterprises operate (Table 4).\u003c/p\u003e\n\u003cp id=\"_Toc175561574\"\u003eTable\u0026nbsp;4 ANOVA analysis of the effect of industry on enterprise agility dimensions\u003c/p\u003e\n\u003ctable style=\"width: 4.5e+2pt\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\n \u003cp\u003e\u003cstrong\u003eANOVA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSum of Squares\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003edf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMean square\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eETA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ebetween groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.932\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.185142\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewithin groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e195.294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003etotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e202.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ebetween groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.1917\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewithin groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e195.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003etotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e202.666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ebetween groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.886\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.198885\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewithin groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e150.619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003etotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e156.822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ebetween groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.548\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.212093\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewithin groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e160.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003etotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e167.789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ebetween groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.187368\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewithin groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e171.746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003etotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e177.995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ebetween groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewithin groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e194.341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003etotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e197.910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: authors\u003c/p\u003e\n\u003cp\u003eThe results of the analysis revealed statistically significant differences between industries in all agility dimensions, with the exception of structures. The ETA coefficient indicates a weak to moderate dependence between industry and five agility dimensions. The strongest association was observed in management (\u0026eta; = 0.212), followed by the workforce (\u0026eta; = 0.1988), technology (\u0026eta; = 0.1917), collaboration (\u0026eta; = 0.1874), and values (\u0026eta; = 0.185) dimensions. In structures, no statistically significant relationship relevant to industry was proved. These findings mean that the industry has some, although not dominant, influence on various aspects of corporate agility. The most pronounced relationship appears to be in management, which may imply that management practices vary across most industries. The absence of a significant relationship in structures suggests that organizational structures may be similarly agile (or non-agile) across industries. Based on the research results, it can be concluded that the industry has some influence on the agility of EU enterprises, but is not a major factor. Other factors, e.g. corporate culture, enterprise size, or strategy, may have a greater impact on agility than the industry itself. Khan et al. (2022) also emphasize that enterprises should consider the specific aspects of their industry when implementing agile practices, especially in the management dimension. The more unstable and faster the industry changes, the harder it is for enterprises to be flexible and high-performing. This is further supported by research findings of Tufan \u0026amp; Mert (2023), who reveal the journey of transforming knowledge into performance, showing that in the manufacturing industry, which is affected by rapid change and environmental uncertainties, the absorptive capacity for the success of SMEs is transformed into an advantage in competitive environments through strategic agility, becoming one of the main drivers of sustainable business performance.\u003c/p\u003e"},{"header":"HYPOTHESES EVALUATION","content":"\u003cp\u003eThis section presents a detailed evaluation of the four key hypotheses that formed the study on SA in EU enterprises. Using a combination of quantitative analysis and qualitative insights, the development and interrelations of agility pillars were assessed. The findings shed light on strengths and weaknesses within enterprises, offering a comprehensive understanding of agility dynamics and areas for improvement.\u003c/p\u003e\n\u003cp\u003eH1: Collaboration and organizational values will show a mean score \u0026le; 2.20 on a 4-point agility scale and will be significantly different from the least agile dimension (p \u0026lt; 0.05) in EU enterprises.\u003c/p\u003e\n\u003cp\u003eAnalysis of mean scores shows that collaboration (2.13) and agile values (2.15) are the two most agile dimensions, with lower scores indicating higher agility. This finding is statistically reinforced by the Wilcoxon signed-rank test, where both dimensions show significantly higher agility than others (p \u0026lt; 0.05). From a theoretical perspective, this aligns with expectations\u0026mdash;strong teamwork and shared values are widely recognized as core enablers of agility. The data provides robust support for Hypothesis 1, confirming that collaboration and values are the strongest pillars of agility within EU enterprises.\u003c/p\u003e\n\u003cp\u003eH2: Management will exhibit a mean score \u0026ge; 2.25 on a 4-point agility scale and will be significantly less agile than the most agile dimension (p \u0026lt; 0.05) in EU enterprises.\u003c/p\u003e\n\u003cp\u003eManagement exhibits the highest mean score (2.28), indicating it is perceived as the least agile dimension. Wilcoxon test results confirm this, showing statistically significant differences\u0026mdash;e.g., management is less agile than the workforce (p = 0.028). Qualitative insights support this view, highlighting resistance to change, hierarchical inertia, and slower adoption of agile practices within management structures. The evidence firmly supports Hypothesis 2, establishing management as the weakest link in agility among EU enterprises.\u003c/p\u003e\n\u003cp\u003eH3: Strategic agility represents an integrated system where all dimensions show significant positive correlations (p \u0026lt; 0.01), confirming the interdependence between the different pillars of agility.\u003c/p\u003e\n\u003cp\u003ePearson correlations reveal strong, statistically significant relationships (p \u0026lt; 0.01) among all six agility dimensions, illustrating the systemic nature of agility. Particularly strong correlations include management \u0026amp; workforce: r = 0.730, management \u0026amp; collaboration: r = 0.746, management \u0026amp; structures: r = 0.742, collaboration \u0026amp; structures: r = 0.702. These results underscore the interdependence between dimensions; improving one area, especially management, can have a ripple effect across others. Hypothesis 3 has been accepted, as Pearson correlations reveal strong, statistically significant relationships (p \u0026lt; 0.01) across all six agility dimensions (highlighting their systemic interdependence), where improvements in one area, particularly management, can positively influence others.\u003c/p\u003e\n\u003cp\u003eH4: There is a negative relationship between the age of the enterprise and the level of managerial agility.\u003c/p\u003e\n\u003cp\u003eThe Spearman correlation between management agility and enterprise age is positive and significant (r = 0.112, p = 0.017), suggesting younger enterprises may perceive their management as more agile. However, the correlation is weak, and interpretation should be cautious, this could reflect generational attitudes or limited exposure rather than structural differences. The hypothesis 4 has been preliminary accepted, recognizing that while the relationship is statistically significant, its weakness highlights the need for further research, ideally through long-term studies.\u003c/p\u003e\n\u003cp\u003eThe findings confirm the prominence of collaboration and values, highlight management as the weakest pillar, demonstrate agility\u0026rsquo;s systemic nature, and suggest a preliminary link between younger enterprises and higher management agility, pointing to directions for future research.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe research findings confirm that agility in European enterprises is a multidimensional concept, with varying levels of agility observed across the six dimensions studied. Collaboration and values emerged as the most agile dimensions, likely due to strong interpersonal trust and established value systems that support teamwork and adaptability. Conversely, management and workforce scores were perceived as the least agile, suggesting the need for greater emphasis on leadership development and employee empowerment in agile transformations. Statistical tests confirmed significant differences among the dimensions, supporting the importance of a targeted yet holistic approach to agility enhancement. Strong interdependencies among dimensions, especially involving management, highlight its central role in enabling or constraining overall enterprise agility. Interestingly, demographic factors such as gender, education, or enterprise size had no significant influence on perceived agility, emphasizing that agility is rooted more in culture and practices than structural characteristics. Overall, the findings suggest that strengthening management agility may serve as a strategic lever, amplifying agility across the organization due to its strong interconnectivity with other dimensions.\u003c/p\u003e\n\u003cp\u003eEnterprises should therefore prioritize cultivating an agile mindset during recruitment and onboarding, ensure consistency of agile practices across all hierarchical levels, and tailor agility efforts to industry volatility and innovation demands based on the pace and nature of change in their industry. Fostering adaptability, openness to innovation, and continuous feedback mechanisms will help embed agility more deeply across departments.\u003c/p\u003e\n\u003cp\u003eThe limitations of the research were mainly due to the geographic focus, potential subjectivity of responses, and a short timeframe. While the quantitative findings provide useful statistical insight, future studies should consider incorporating qualitative methods, such as interviews or focus groups. These would help uncover the reasons behind the observed perceptions of agility, especially in the areas where correlations were weak or absent and where quantitative measures alone may not capture deeper organizational dynamics. A qualitative approach could also explore how organizational culture, leadership behavior, or internal communication influence employees\u0026rsquo; views on agility.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work was supported by the VEGA Grant Agency under project No. 1/0120/25.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMal\u0026aacute; Denisa was responsible for methodological design and data processing. She developed the empirical part of the article, performed analytical procedures, and ensured the validity and reliability of the applied methods. She also contributed to interpretation of the empirical results and their managerial implications.Min\u0026aacute;rov\u0026aacute; Martina contributed to the conceptual framing of strategic agility, developed the theoretical background, and designed the research model. She carried out extensive literature research focused on defining key constructs and differentiating agility from related concepts. She also prepared the introductory sections and formulated the research gaps.Sedliačikov\u0026aacute; Mariana worked on the development of the practical perspective of the study, especially regarding strategic agility and business sustainability. She synthesized theoretical findings with current trends and designed the discussion section. She also revised the manuscript from the perspective of applicability and relevance for organizations.Musa Hussam coordinated the writing process and carried out the final editorial revisions of the manuscript. He contributed to the formulation of conclusions, ensured consistency across all parts of the text, and provided critical revisions of the argumentation. He also managed communication with the journal and prepared the manuscript for submission.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis paper was supported by Grant number VEGA 1/0120/25 of the Scientific Grant Agency of the Ministry of Education, Research, Development and Youth of the Slovak Republic and the Slovak Academy of Sciences.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdala, S., Amankwah-Amoah, J., Khan, Z., Hirekhan, M. (2025). 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A framework on the use of agile methods in logistics startups. \u003cem\u003eLogistics\u003c/em\u003e, 6(1), 19. https://doi.org/10.3390/logistics6010019\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"global-journal-of-flexible-systems-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jfsm","sideBox":"Learn more about [Global Journal of Flexible Systems Management](http://link.springer.com/journal/40171)","snPcode":"40171","submissionUrl":"https://submission.springernature.com/new-submission/40171/3","title":"Global Journal of Flexible Systems Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"strategic agility, agile management, innovation, digital technologies, decision-making","lastPublishedDoi":"10.21203/rs.3.rs-9481289/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9481289/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe paper aims to investigate how strategic agility enables organizational adaptation in evolving business environments, focusing on European enterprises. While extant agility research often focuses on isolated organizational aspects, comprehensive strategic agility requires coordinated development across dimensions, challenging conventional structures and prompting organization wide transformations in organizational responses to the market. Drawing on quantitative research of EU enterprises (n\u0026thinsp;=\u0026thinsp;456) conducted between 2023 and 2024, six interconnected dimensions are examined: agile values, collaborative workforce, technological flexibility, agile management practices, adaptive organizational structures, and innovation capacity. The findings reveal that only 23% of organizations achieve a high level of strategic agility, with critical drivers including digital technology investments, decentralized decision-making, and employee involvement in innovation. Management agility shows the strongest cross-dimensional interconnectedness, while demographic factors show no significant influence on perceived agility. 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