Bridging Knowledge Management and Competitive Advantage: the Mediating Role of Leadership Agility and Ambidextrous Innovation in Coffee Shop Sme’s

Dynamic Capabilities Theory, introduced by Teece, et al. (1997), posits that a firm’s ability to integrate, build, and reconfigure internal and external competencies to address rapidly changing environments is central to achieving and sustaining competitive advantage. This theory emphasizes three key processes: sensing opportunities and threats, seizing opportunities through strategic decision-making, and transforming resources and capabilities to maintain competitiveness over time (Teece, 2007). According to Teece (2018), dynamic capabilities enable organizations to adapt to technological shifts, market changes, and competitive pressures by fostering innovation and strategic flexibility. The theory builds on the resource-based view (RBV) but extends it by focusing on the firm’s ability to modify its resource base in response to external changes, making it particularly relevant in volatile and uncertain business environments (Eisenhardt and Martin, 2000). Dynamic capabilities are thus seen as a higher-order capability that underpins a firm’s ability to innovate, adapt, and thrive in dynamic markets (Helfat, et al., 2007).

Michael Porter initially defined competitive advantage as the ability of a firm to create superior value that its competitors cannot easily duplicate or find too costly to imitate, identifying cost leadership, differentiation, and focus as the primary means to achieve this (Porter, 1985). Porter’s framework identified cost leadership, differentiation, and focus as primary means by which companies achieve a sustainable competitive advantage. This foundational idea has driven much of the strategic management literature, with competitive advantage being seen as crucial for long-term success in the global marketplace (Barney, 1991; Porter, 1991). Further developments by Wernerfelt (1984) and Peteraf (1993) emphasized resource management, while Dierickx and Cool (1989) highlighted the critical role of resource accumulation over time. Teece, et al. (1997) later introduced the dynamic capabilities framework, underscoring a firm’s ability to adapt and innovate in response to changing environments, with Nonaka (1994) emphasizing continual learning and knowledge management as vital for maintaining a competitive edge.

In the context of SMEs, particularly coffee shops, competitive advantage is often derived from the ability to deliver unique customer experiences, innovate service offerings, and adapt swiftly to market changes. Unlike large enterprises, coffee shop SMEs typically lack extensive resources, making differentiation through customer-centric strategies and operational agility critical for sustaining competitiveness (Kim, 2005; Davis and Golicic, 2020). The dynamic capabilities framework (Teece, et al., 1997) is particularly relevant here, as it emphasizes the importance of adaptability, innovation, and knowledge management in responding to evolving market demands. For coffee shops, this translates into leveraging KM practices to enhance service quality, foster leadership agility, and balance explorative and exploitative innovations, thereby creating a sustainable competitive edge in a highly competitive and customer-driven industry (Arsawan, et al., 2022; Zhang, et al., 2024).

Knowledge Management (KM) was first delineated by Peter Drucker, highlighting its role in transforming knowledge into a critical economic asset within the knowledge society (Drucker, 1993). This concept was elaborated by Nonaka and Takeuchi through the SECI model, emphasizing the cyclic transformation of tacit and explicit knowledge essential for organizational learning and innovation (Nonaka and Takeuchi, 1995). Further expanding on these ideas, Davenport and Prusak defined KM as the process of capturing, distributing, and effectively using knowledge to boost organizational performance, a view supported by Alavi and Leidner who added the importance of knowledge storage, retrieval, and transfer in enhancing firm capabilities (Davenport and Prusak, 1998; Alavi and Leidner, 2001). In the context of SMEs, particularly coffee shops, KM plays a pivotal role in fostering innovation and adaptability, enabling these businesses to leverage customer insights, operational best practices, and market trends to enhance service quality and customer satisfaction (Massaro, et al., 2016; Arsawan, et al., 2022). Modern discourse extends KM applications to include advanced technologies such as artificial intelligence and data analytics to improve the processing and application of knowledge in businesses (Kane and Alavi, 2007). For coffee shop SMEs, this translates into using KM systems to streamline operations, personalize customer experiences, and drive both explorative and exploitative innovations, thereby maintaining competitiveness in a dynamic and customer-driven market (Cegarra-Navarro, et al., 2016; Zhang, et al., 2024).

Recent studies highlight the essential connections between knowledge management, leadership agility, ambidextrous innovation, and competitive advantage. Băeşu and Bejinaru (2020) establish that effective knowledge management systems are pivotal in enhancing leadership agility, allowing leaders to make quick, informed decisions that are crucial in dynamic market conditions. Further, Hayaeian and Hesarzadeh (2023) demonstrate that effective management of knowledge enhances ambidextrous innovation by facilitating the seamless integration and exploration of new opportunities alongside the exploitation of existing resources. This capability is critical for maintaining competitive relevance, as indicated by a study by Jia, et al. (2022), which found that companies proficient in ambidextrous innovation generally achieve higher performance metrics. Ultimately, Azeem, et al. (2021) argue that these capacities lead directly to competitive advantage by improving operational efficiency and customer satisfaction, proving the strategic value of knowledge management in fostering overall business success. Thus, we hypothesize the following:

• H1: Knowledge Management has a significant direct effect on Leadership Agility

• H2: Knowledge Management has a significant direct effect on Ambidextrous Innovation

• H3: Knowledge Management has a significant direct effect on Competitive Advantage

Leadership Agility, initially articulated by Bill Joiner and Stephen Josephs, highlights the capacity of leaders to navigate complex, rapidly changing environments by embodying flexibility, balance, and adaptability (Joiner and Josephs, 2006). This concept is crucial in a volatile, uncertain, complex, and ambiguous (VUCA) world, enabling leaders to continuously adjust strategies, mindsets, and operational tactics. Researchers have linked such agility to vital organizational outcomes like innovation, resilience, and employee engagement, noting that agile leaders use emotional and social intelligence to enhance workplace creativity and team dynamics (Riggio and Reichard, 2008; Tandon, et al., 2024). For SMEs, particularly in the coffee shop industry, leadership agility is critical for responding to shifting consumer preferences, competitive pressures, and market trends. In this context, agile leaders must quickly adapt service offerings, optimize customer experiences, and foster a culture of continuous learning to maintain relevance and competitiveness (Arsawan, et al., 2022; Zhang, et al., 2024). As coffee shops operate in a highly customer-centric and dynamic environment, the ability of leaders to balance short-term operational demands with long-term strategic innovation is essential for sustaining growth and differentiation (Kang and Yang, 2016; Adawiah, et al., 2021). Thus, leadership agility not only drives organizational success but also ensures that coffee shop SMEs can thrive in an ever-evolving market landscape (Petrie, 2014; Uhl-Bien and Arena, 2018).

The relationship between leadership agility and competitive advantage has been rigorously examined in recent studies, establishing a critical link between agile leadership and enhanced organizational performance. Yusuf, et al. (2022) found that agile leaders, capable of swiftly adapting strategies in response to environmental changes, significantly contribute to creating a sustainable competitive advantage by fostering innovation and responsiveness. This finding is supported by Medeiros and Maçada (2022), who observed that agility in leadership practices correlates strongly with higher profitability and market differentiation. Furthermore, agility in leadership is instrumental in driving strategic initiatives that align with evolving market demands, enhancing both customer satisfaction and operational efficiency, as detailed by Battour, et al. (2021) and Zhang and Suntrayuth (2024). These studies collectively underscore the significant impact of leadership agility on maintaining a competitive edge, essential for thriving in today’s fast-paced business environments. Thus, the hypothesis is as follows:

• H4: Leadership Agility has a significant direct effect on Competitive Advantage.

Introduced by Michael Tushman and Charles O’Reilly, the concept of ambidextrous innovation describes an organization’s capability to simultaneously pursue explorative and exploitative innovations, crucial for navigating through rapid market changes and technological advancements (Tushman and O’Reilly, 1996; O’Reilly and Tushman, 2008). Achieving this requires not just strategic resource allocation but also aligning organizational structures and cultures to foster separate units for different innovation types, addressing the complexities of managing these dual paths and the inherent leadership challenges (Gibson and Birkin-shaw, 2004; Jansen, et al., 2006). In the context of SMEs, particularly coffee shops, ambidextrous innovation is vital for balancing the refinement of existing services with the exploration of new offerings, enabling these businesses to adapt to evolving consumer preferences and market trends. For instance, coffee shop SMEs can leverage exploitative innovation to optimize operational efficiency and customer service while simultaneously engaging in explorative innovation to introduce novel menu items, unique customer experiences, or sustainable practices (Cegarra-Na-varro, et al., 2016; Zhang, et al., 2024). Raisch, et al. (2009) underscore that ambidextrous innovation significantly enhances firm adaptability and performance, stressing the importance of continuous adaptation to maintain competitive advantage in dynamic environments. In the highly competitive and customer-driven coffee shop industry, this dual approach allows SMEs to remain relevant, differentiate themselves from competitors, and sustain long-term growth (Kang and Yang, 2016; Adawiah, et al., 2021).

Ambidextrous innovation has been identified as a key driver of competitive advantage in recent research, emphasizing its crucial role in enabling organizations to simultaneously explore new opportunities while exploiting existing capabilities. A study by Zhang, et al. (2022) highlights that firms practicing ambidextrous innovation achieve superior performance metrics by balancing these dual strategies, which fosters both incremental and radical innovations. Similarly, Khan, et al. (2022) confirm that such innovation strategies significantly enhance market share and customer retention by continuously adapting to changing market conditions and customer needs. Additionally, the work of Wang and Fang (2022) supports these findings, suggesting that ambidextrous innovation leads to improved financial performance and strategic positioning by leveraging organizational flexibility and responsiveness. Collectively, these studies underscore the critical impact of ambidextrous innovation in sustaining competitive advantages in various industry sectors, from technology to consumer goods. Thus, the hypothesis is as follows:

• H5: Ambidextrous Innovation has a significant direct effect on Competitive Advantage.

The theoretical framework guiding this study integrates key concepts of Knowledge Management (KM), Leadership Agility, Ambidextrous Innovation, and Competitive Advantage, as illustrated in the conceptual model (see Figure 1). Grounded in Dynamic Capabilities Theory (Teece, et al., 1997), the framework posits that KM serves as the foundational driver, enhancing leadership agility and ambidextrous innovation, which in turn mediate the relationship between KM and competitive advantage. Leadership agility enables SMEs, particularly coffee shops, to adapt swiftly to market changes and customer demands, while ambidextrous innovation allows them to balance explorative and exploitative strategies, fostering both incremental improvements and radical innovations. Together, these elements create a synergistic effect, enabling coffee shop SMEs to achieve and sustain a competitive edge in a dynamic and customer-centric industry. This framework provides a comprehensive lens for understanding how KM practices can be strategically leveraged to drive innovation, agility, and long-term competitiveness in the context of coffee shop SMEs.

Figure 1.

Conceptual model

(Source: Author’s own research)

This study adopts a quantitative research design, utilizing a survey-based approach to collect primary data from coffee shop SMEs in Malang City. The selection of this location was strategic, as Malang City is known for its vibrant coffee shop culture, with numerous establishments scattered across the city, making it an ideal setting for investigating the interplay between knowledge management, leadership agility, ambidextrous innovation, and competitive advantage. The research sample consisted of owner or manager of each coffee shop SMEs, as they are the key decision-makers responsible for implementing KM practices, driving innovation, and ensuring competitive advantage. These respondents were chosen due to their in-depth understanding of operational strategies, customer engagement, and market dynamics within their businesses. The sampling method employed was purposive sampling, targeting coffee shop SMEs that met specific criteria, such as being independently owned and operated, having 10-20 employees, and operating within Malang City.

This approach ensured that the sample was representative of the SME coffee shop sector in the region. Data collection was conducted directly with the assistance of Google Forms, using a structured questionnaire designed to capture respondents'perceptions and evaluations of KM practices, leadership agility, ambidextrous innovation, and competitive advantage. A total of 54 completed questionnaires were obtained, representing a 100% response rate. This sample size is considered adequate as it meets the minimum requirement of 10 observations per indicator (Hair, et al., 2022). The data collection process ensured anonymity and confidentiality, encouraging respondents to provide honest and accurate responses. The use of Google Forms facilitated efficient data collection while adhering to ethical research practices.

Based on the results of the descriptive analysis on Table 1, it is known that the majority of respondents in the study are male, accounting for 70%. Meanwhile, female respondents account for 30%. Additionally, the highest percentage of respondents’ age is below 25 years at 44%. The fewest respondents are above 45 years old, totaling 6%. Regarding education, 70% of respondents have a high school degree, 13% have a diploma degree, and 17% have obtained a bachelor's degree.

This study examines four key variables: Knowledge Management, Leadership Agility, Ambidextrous Innovation, and Competitive Advantage. The questionnaire was developed based on validated measurement scales from existing literature to ensure reliability and validity, with all items measured using a 5-point Likert scale. The indicators for each variable, adapted from previous studies, are detailed in Table 2, while the complete scales are provided in the Appendix.

Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 3.0 software. PLS-SEM was selected as the analytical tool for this study due to its suitability for several key reasons. First, PLS-SEM is widely recognized in SME research for its ability to handle small sample sizes and analyze complex models with multiple constructs and mediating relationships, making it ideal for this study’s context (Hair, et al., 2022). Second, PLS-SEM is particularly effective for predictive modeling and theory development (Sarstedt, et al., 2021), aligning with the study’s objective of exploring how knowledge management influences leadership agility, ambidextrous innovation, and competitive advantage. Third, PLS-SEM is well-suited for validating reflective measurement models, as it employs bootstrapping techniques and rigorous measurement model assessment to ensure construct validity and reliability. Finally, given the study’s sample size (n = 54), PLS-SEM is appropriate as it does not impose strict sample size requirements while providing robust parameter estimation (Hair et al., 2019).

The analysis involved two main assessments (Hair, et al., 2019):

• Measurement Model Assessment: This stage examined factor loadings, Cronbach’s alpha, composite reliability, and Average Variance Extracted (AVE) to assess convergent validity and reliability. Additionally, the Heterotrait-Monotrait (HTMT) ratio was used to evaluate discriminant validity, ensuring that the constructs were distinct and free from redundancy.

• Structural Model Assessment: This stage evaluated path coefficients, R-squared values, and bootstrapping results to test the significance of the hypothesized relationships, providing insights into the direct and mediating effects within the model.

Evaluating the measurement model is an essential step in determining the model’s appropriateness and confirming its alignment with the research data, as detailed in Table 3. This study utilizes a reflective measurement model and adheres to several established criteria by Hair, et al. (2019). We verified that the loadings of the reflective indicators reached a minimum factor value of 0.708. Both Cronbach’s alpha and composite reliability were kept within the range of 0.7–0.95 to ensure reliability while preventing indicator redundancy. Furthermore, convergent validity was evaluated using the Average Variance Extracted (AVE) method, where a model showing an AVE score of 0.5 or higher was considered to have strong convergent validity, reflecting that the constructs capture a substantial amount of variance relative to measurement error. Convergent validity and reliability are shown in Table 3.

The evaluation of the measurement model included an assessment of discriminant validity, which was conducted using the Heterotrait-Monotrait (HTMT) ratio of correlations, as described by Hair, et al. (2019). The HTMT criterion stipulates that values should be below 0.85 to confirm adequate discriminant validity. The analysis of discriminant validity, as presented in Table 4, verified that all measures adhered to the standards prescribed by the HTMT method.

After confirming the validity and reliability of the measurement model, the next step was to evaluate the structural model to assess its robustness and predictive power. This evaluation focused on three key aspects: collinearity, explanatory power (R²), and the significance of path coefficients (Hair, et al., 2019). Each of these elements provides critical insights into the model’s ability to explain the relationships between the constructs and predict outcomes effectively.

To assess collinearity among the constructs, Variance Inflation Factor (VIF) values were calculated. Collinearity can distort the interpretation of path coefficients, so it is essential to ensure that VIF values are below the threshold of 3.3, as recommended by Kock, et al. (2012) and Kock and Gaskins (2014). In this study, the VIF values for all constructs-Knowledge Management (2.134), Leadership Agility (2.349), Organizational Innovation (2.241), and Competitive Advantage (2.483)-were well below 3.3 (Table 5). This indicates that collinearity is not a concern, confirming that the structural model is robust and free from multicollinearity or common method bias. These results allow for a reliable interpretation of the relationships between the constructs.

The explanatory power of the model was evaluated using the coefficient of determination (R²), which measures the proportion of variance explained in the endogenous constructs. According to Hair, et al. (2022), R² values range from 0 to 1, with higher values indicating greater explanatory power.

In this study, the R² values for the endogenous constructs were as follows: Leadership Agility (R² = 0.378), Organizational Innovation (R² = 0.393), and Competitive Advantage (R² = 0.532). These results suggest that the model has moderate explanatory power for Leadership Agility and Organizational Innovation while demonstrating strong explanatory power for Competitive Advantage. Specifically, 37.8% of the variance in Leadership Agility is explained by Knowledge Management, 39.3% of the variance in Ambidextrous Innovation is explained by Knowledge Management and Leadership Agility, and 53.2% of the variance in Competitive Advantage is explained by Knowledge Management, Leadership Agility, and Organizational Innovation. These findings highlight the meaningful impact of the predictors on the endogenous constructs, particularly in explaining Competitive Advantage.

The significance of the hypothesized relationships was tested using bootstrapping with 5,000 subsamples to evaluate the path coefficients. All direct hypotheses (H1 - H5) were supported, with significant positive relationships (significant level of 5%; t-statistics > 1.96; p-value < 0.05) (see Table 6). Specifically, Knowledge Management was found to significantly influence Leadership Agility and Organizational Innovation, underscoring its foundational role in fostering adaptive leadership and innovation capabilities. Additionally, Leadership Agility and Organizational Innovation significantly influenced Competitive Advantage, emphasizing their critical roles in driving sustainable competitive advantage. These results confirm the theoretical model’s validity and provide empirical evidence supporting the proposed relationships.

This study contributes to the existing body of knowledge by extending the application of Dynamic Capabilities Theory (Teece, et al., 1997) to the context of service-oriented SMEs, particularly coffee shops. It demonstrates how knowledge management (KM) serves as a foundational driver for enhancing leadership agility and ambidextrous innovation, bridging the gap between theoretical frameworks traditionally applied to large enterprises and their relevance to SMEs. By empirically validating the mediating roles of leadership agility and ambidextrous innovation in the relationship between KM and competitive advantage, the study enriches the strategic management literature. It highlights the mechanisms through which KM practices translate into sustainable competitive advantages, particularly in dynamic and customer-centric industries. Additionally, the study advances the discourse on innovation by showing how KM enables SMEs to balance explorative and exploitative innovations, a concept that has been underexplored in the context of service-oriented SMEs. These findings provide a nuanced understanding of how KM fosters both incremental and radical innovations, contributing to the growing body of research on innovation strategies in SMEs (Durst, et al., 2024; Zhang, et al., 2024).

The findings of this study offer actionable insights for coffee shop SMEs aiming to enhance their competitive advantage. Investing in robust KM systems that facilitate knowledge sharing, storage, and application is crucial for capturing customer feedback, operational best practices, and market trends. These insights can inform decision-making and innovation strategies, enabling SMEs to adapt to rapidly changing market demands. Leadership agility plays a critical role in navigating the complexities of a dynamic market, emphasizing the need for coffee shop leaders to develop adaptive capabilities. Training programs and workshops on agile leadership can help managers enhance their decisionmaking skills and emotional intelligence, which are essential for driving organizational success. Ambidextrous innovation is another key takeaway, as it allows SMEs to balance the refinement of existing services with the introduction of new offerings. For instance, while improving operational efficiency and customer service, businesses can experiment with new menu items, unique customer experiences, or sustainable practices. This dual approach ensures that SMEs remain competitive while meeting evolving customer demands. Policymakers and industry stakeholders can also benefit from these findings by designing targeted support programs, such as funding for KM infrastructure, training initiatives for agile leadership, and incentives for innovation. These efforts can create an enabling environment for SMEs to thrive in a rapidly changing market landscape.