Blue economy implementation and sustainability in coastal MSMEs Open Access

The blue economy has emerged as a global development agenda aimed at reconciling economic growth with environmental sustainability through the responsible use of ocean and coastal resources (Mohabir et al., 2025). As marine ecosystems face increasing pressure from overexploitation, pollution, biodiversity loss, and climate change, governments and international organizations have promoted the blue economy as a pathway to achieve sustainable development while maintaining the productivity of ocean-based sectors (Lee et al., 2021). This approach has become particularly significant for coastal and island regions, where economic structures, livelihoods, and food systems are closely dependent on marine and coastal ecosystems (Aprizal et al., 2025). Bibliometric evidence confirms the rapid expansion of blue economy research at the global and national levels, including in Indonesia, with sustainability as its dominant conceptual foundation (Ahmadi et al., 2024).

Despite its growing prominence in policy and academic discourse, the implementation of the blue economy remains uneven and largely conceptual, especially at the operational level of economic actors (Martínez-Vázquez et al., 2021). In many coastal regions, micro, small, and medium-sized enterprises (MSMEs) dominate key blue economy sectors such as small-scale fisheries, aquaculture, seafood processing, and coastal tourism (Ayilu et al., 2022). These enterprises are simultaneously drivers of local economic development and direct users of marine resources, placing them at the center of sustainability challenges (Silvestri et al., 2023). However, coastal MSMEs often operate under conditions of limited technological capacity, weak managerial skills, restricted access to green finance, and insufficient institutional support, which constrain their ability to adopt blue economy principles effectively (Saarani et al., 2023). The limited diffusion of advanced and environmentally friendly technologies further exacerbates these constraints (Ghoneim et al., 2025). This limitation should not be viewed solely as a resource constraint, but rather as a broader structural obstacle involving weak technology transfer systems, uneven access to maritime innovation infrastructure, fragmented institutional coordination, and limited dissemination of environmentally sustainable technologies across coastal business ecosystems. These structural barriers often prevent coastal MSMEs from fully adopting blue economy practices despite growing policy support for sustainable marine development.

Previous studies on the blue economy have made substantial contributions by mapping thematic areas such as marine governance, fisheries management, aquaculture development, blue tourism, renewable marine energy, and ecosystem services (Lu and Li, 2025). Bibliometric and systematic reviews highlight sustainability as the dominant theme shaping blue economy research globally (Hutajulu, 2025; Mohabir et al., 2025). Sector-focused bibliometric analyses further enrich the literature by examining specific domains such as coastal tourism and food security within the blue economy framework (Kabil et al., 2021; Yılmaz and İlal, 2024). Other streams of research emphasize the nexus between blue economy development and food security, particularly in fisheries- and aquaculture-dependent regions (Lefilef et al., 2025). Nevertheless, much of this literature remains focused on macro-level policy analysis or sectoral assessments, with limited attention to firm-level implementation and performance outcomes (Vega-Muñoz et al., 2021).

Although MSMEs are widely acknowledged as essential actors in coastal and marine economies, empirical research examining how blue economy principles are implemented at the MSME level is still scarce (Hendarman et al., 2024). Existing studies tend to analyze economic performance and environmental sustainability separately, resulting in fragmented insights into the trade-offs and synergies between these two dimensions (Sugiyanto et al., 2025). Moreover, few studies have employed integrative analytical frameworks capable of explaining the mechanisms through which blue economy practices influence sustainability outcomes via internal firm capabilities and external ecosystem support (Li et al., 2025). Research on ocean literacy and stakeholder awareness further indicates that limited knowledge transfer and capability development constrain effective blue economy implementation at the enterprise level (Paredes-Coral et al., 2021).

This study addresses an important theoretical gap by shifting blue economy analysis from macro-policy discourse toward firm-level sustainability mechanisms within coastal MSMEs. While prior studies predominantly examine blue economy through governance, sectoral performance, and national policy perspectives, limited empirical evidence explains how blue economy practices are operationalized by individual enterprises and how these practices translate into measurable sustainability outcomes. In particular, the mediating role of MSME capabilities and the enabling role of ecosystem support remain underexplored. This study extends the literature by demonstrating that blue economy implementation does not automatically generate sustainability outcomes; rather, its effectiveness depends on the development of internal organizational capabilities and supportive institutional ecosystems.

The novelty of this study lies in the development and empirical testing of a structural model of blue economy implementation at the coastal MSME level, integrating economic and environmental sustainability within a single analytical framework. Figure 1 illustrates the bibliometric network of blue economy research using VOSviewer. The dominant clusters are concentrated around sustainability, fisheries, governance, aquaculture, and environmental protection, indicating that existing studies largely focus on macro-level policy and sectoral management. In contrast, MSME-related research appears weakly connected to these central clusters, suggesting that enterprise-level implementation remains underexplored. This visual evidence supports the research gap of the present study by highlighting the limited integration of MSME capability development and firm-level sustainability outcomes within the mainstream blue economy literature (Mohabir et al., 2025). This pattern is consistent with global bibliometric findings showing thematic imbalances and underrepresentation of MSME-centered empirical studies (Hutajulu, 2025; Li et al., 2025). By explicitly positioning coastal MSMEs as the primary unit of analysis and modeling the roles of internal capabilities and external ecosystem support, this study addresses an underexplored area within the blue economy literature. The research contributes theoretically by extending blue economy analysis to firm-level sustainability mechanisms, methodologically by applying structural equation modeling, and practically by providing evidence-based insights to support inclusive blue economy development (Lestari et al., 2025).

Based on the identified gaps, this study aims to develop and empirically validate a structural model that explains the implementation of blue economy principles in coastal MSMEs and their impacts on economic and environmental sustainability. Specifically, the research seeks to examine the direct effects of blue economy practices on sustainability outcomes, as well as the mediating roles of MSME internal capabilities and the supporting ecosystem, thereby enhancing understanding of how blue economy strategies can be operationalized at the MSME level to support sustainable coastal development.

The blue economy is widely defined as an economic development approach that promotes the sustainable use of ocean and coastal resources while maintaining ecosystem integrity and supporting human well-being (Santos, 2022). Recent literature emphasizes that effective blue economy implementation requires not only environmental protection but also the generation of economic value through innovation, efficiency, and responsible resource utilization (Lee et al., 2021). In this context, sustainability is conceptualized as a multidimensional outcome encompassing both economic viability and environmental stewardship (Aprizal et al., 2025).

Empirical studies indicate that blue economy practices such as waste reduction, resource efficiency, circular use of marine inputs, and adoption of environmentally friendly technologies can enhance long-term economic performance by reducing costs, increasing product value, and strengthening market competitiveness (Sugiyanto et al., 2025). At the same time, these practices contribute directly to environmental sustainability by lowering pollution, conserving marine ecosystems, and supporting biodiversity (Hasanah et al., 2024). However, most existing studies assess these outcomes at the sectoral or policy level, leaving firm-level empirical evidence relatively limited, particularly for MSMEs (Li et al., 2025).

This relationship is theoretically grounded in the Natural Resource-Based View (NRBV), which argues that firms that strategically integrate environmental resources, pollution prevention, and sustainable operational practices can develop long-term competitive advantages while improving ecological performance (Hart, 1995). In the context of coastal MSMEs, blue economy practices represent strategic environmental capabilities that enhance both economic resilience and environmental sustainability.

Based on the sustainability and natural resource based view of the firm, enterprises that integrate environmental considerations into their core business strategies are more likely to achieve durable economic advantages while minimizing ecological impacts (Lee et al., 2021).

The successful implementation of blue economy principles at the enterprise level depends heavily on internal firm capabilities, including human capital, managerial competence, innovation capacity, and environmental literacy (Saarani et al., 2023). Coastal MSMEs often operate with limited resources and informal structures, making their internal capabilities a critical determinant of whether sustainability-oriented practices can be adopted and sustained over time (Ayilu et al., 2022).

In this study, MSME capabilities are conceptualized as a multidimensional construct consisting of three major dimensions: managerial capability, innovation capability, and environmental capability. Managerial capability refers to the ability of MSME owners and managers to make strategic decisions and adapt business models to sustainability demands. Innovation capability reflects the ability to adopt new technologies and improve operational processes, while environmental capability refers to environmental awareness and the ability to implement responsible resource management practices. This decomposition helps clarify how internal capabilities function as a mechanism linking blue economy implementation and sustainability outcomes.

Prior studies highlight that MSMEs with stronger learning capacity, access to knowledge, and innovation-oriented cultures are better positioned to adopt green technologies, circular production processes, and sustainable resource management practices (Elston et al., 2024). Moreover, exposure to blue economy principles can itself stimulate capability development by encouraging skills upgrading, process innovation, and strategic reorientation toward sustainability (Layman et al., 2022). This reciprocal relationship suggests that blue economy implementation not only depends on existing capabilities but can also enhance them.

This argument is supported by Dynamic Capability Theory, which explains that firms must continuously integrate, build, and reconfigure internal competencies to respond to rapidly changing environmental and market conditions (Teece et al., 1997). Blue economy adoption often requires MSMEs to develop new knowledge, technological adaptability, and managerial flexibility. From a dynamic capabilities perspective, sustainability-oriented practices act as catalysts for capability development by pushing firms to reconfigure resources and adapt to environmental and market pressures (Vega-Muñoz et al., 2021).

Firm-level capabilities play a central role in translating sustainability-oriented strategies into tangible economic and environmental outcomes (Saarani et al., 2023). MSMEs with higher levels of managerial competence, innovation capacity, and environmental awareness are more likely to improve operational efficiency, enhance product quality, and access higher-value or environmentally sensitive markets (Silvestri et al., 2023). These outcomes contribute directly to economic sustainability through income stability, growth potential, and competitiveness.

This relationship is explained through the Resource-Based View (RBV), which argues that valuable, rare, and difficult-to-imitate internal capabilities serve as strategic resources that enhance organizational performance and long-term competitiveness (Barney, 1991). Strong MSME capabilities enable firms to convert sustainability strategies into measurable economic and environmental outcomes.

At the same time, capable MSMEs are better equipped to implement environmentally responsible practices, such as efficient resource use, waste minimization, and compliance with environmental regulations (Hasanah et al., 2024). Empirical evidence suggests that capability-driven sustainability initiatives are more consistent and effective than those driven solely by external pressure or regulation (Li et al., 2025). Nevertheless, capability effects may be constrained when external institutional support is weak or when market incentives for sustainability remain low. This indicates that internal capabilities alone may not be sufficient unless they are supported by favorable external conditions. This indicates that internal capabilities function as a key mechanism linking blue economy practices to sustainability outcomes.

Beyond internal capabilities, the effectiveness of blue economy implementation is strongly influenced by the external ecosystem in which MSMEs operate, including government policies, institutional support, infrastructure, market access, and partnerships (Pace et al., 2023). Supportive policy environments and access to training, finance, and technology have been shown to enhance MSMEs’ ability to adopt sustainability-oriented practices (Hendarman et al., 2024).

This argument aligns with Stakeholder Theory and Institutional Theory, which suggest that organizational sustainability performance is shaped not only by internal resources but also by external institutional pressures, stakeholder collaboration, and policy environments (Freeman et al., 2021; Richard, 2008). For coastal MSMEs, ecosystem support reduces implementation barriers and strengthens sustainability outcomes.

Studies on blue economy governance emphasize that fragmented or inconsistent policy frameworks can limit the impact of sustainability initiatives, particularly for small-scale enterprises with limited adaptive capacity (Martínez-Vázquez et al., 2021). Conversely, coordinated ecosystem support can amplify the economic and environmental benefits of blue economy practices by reducing adoption costs and increasing returns (Elston et al., 2024). In this study, ecosystem support is positioned as a direct enabling antecedent rather than a moderating variable. It represents the external institutional conditions that directly facilitate sustainability outcomes by reducing barriers to adoption and strengthening enterprise resilience. This clarification is important to ensure consistency between the conceptual model, hypothesis development, and empirical testing. This suggests that ecosystem support may exert both direct effects on sustainability outcomes and indirect effects by strengthening the impact of internal capabilities.

While blue economy implementation is expected to influence sustainability outcomes directly, its effects are likely to be partially mediated by internal MSME capabilities (Li et al., 2025). Without sufficient skills, knowledge, and managerial capacity, sustainability-oriented practices may remain symbolic or yield limited impact (Saarani et al., 2023). Capability development therefore serves as a critical transmission mechanism through which blue economy principles are converted into measurable economic and environmental performance.

The mediating mechanism is supported by Dynamic Capability Theory (Teece et al., 1997), which explains that strategic initiatives generate performance improvements only when firms possess the internal capabilities necessary to transform strategic intentions into operational outcomes. Thus, MSME capabilities serve as an important transmission mechanism linking blue economy implementation and sustainability performance.

Empirical studies in sustainability and innovation literature support the mediating role of firm capabilities in linking strategic orientations to performance outcomes (Vega-Muñoz et al., 2021). Applying this logic to the blue economy context suggests that capability development is a necessary condition for the long-term effectiveness of blue economy implementation at the MSME level. Rather than assuming that blue economy practices automatically improve sustainability performance, this study argues that internal capability development explains why some MSMEs successfully translate sustainability strategies into measurable outcomes while others experience only symbolic adoption.

The participants in this study were owners or managers of coastal micro, small, and medium enterprises (MSMEs) operating in South Sulawesi Province, Indonesia. These enterprises are engaged in various marine-based economic activities, including capture fisheries, aquaculture, seafood processing, marine-based products, and coastal tourism. South Sulawesi was deliberately selected as the research setting because the province is one of Indonesia’s strategic coastal economic regions, where a large proportion of local livelihoods depend on marine and coastal resources. At the same time, coastal MSMEs in this region face significant challenges related to environmental sustainability, technological adoption, and resource management. Therefore, the province provides a relevant empirical context for examining how blue economy practices are implemented at the MSME level and how these practices influence economic and environmental sustainability outcomes.

The study specifically focused on coastal MSMEs located in Makassar City, Selayar Islands Regency, Bulukumba Regency, Takalar Regency, Pinrang Regency, and Palopo City. These locations were selected because they represent diverse coastal economic structures within South Sulawesi, ranging from fisheries and aquaculture centers to marine product processing and coastal tourism activities. Concentrating on these coastal regions also allows the study to obtain relatively homogeneous data regarding the regional policy environment, institutional support systems, and coastal development strategies, thereby improving the internal validity of the findings.

Given the absence of a comprehensive and up-to-date registry of coastal MSMEs across the selected regions, this study employed a purposive sampling technique. Respondents were required to meet several criteria: (1) being the owner, co-owner, or manager of a coastal MSME; (2) actively involved in business decision-making; (3) operating in marine- or coastal-based economic activities; and (4) having at least one year of operational experience. A total of 400 questionnaires were distributed through field surveys and collaboration with local MSME associations and coastal community organizations. After removing incomplete responses, 350 valid questionnaires were retained for analysis.

According to Baruch and Holtom (2008), this represents an effective response rate of 87.5%, which is substantially higher than the commonly accepted threshold for organizational and field survey research. Furthermore, an a priori statistical power analysis using G*Power indicated that a minimum of 146 respondents was required, assuming an effect size of 0.15, statistical power of 0.95, and six predictors in the structural model. Therefore, the final dataset of 350 valid responses exceeded the minimum sample size requirement, ensuring sufficient statistical power for hypothesis testing using Partial Least Squares Structural Equation Modelling (PLS-SEM).

The demographic and business characteristics of the respondents are presented in Table 1. The majority of respondents were male (205 respondents, 58.6%), while female respondents accounted for 145 (41.4%). In terms of education, most respondents had completed senior high school (171 respondents, 48.9%), followed by bachelor’s or master’s degrees (97 respondents, 27.7%) and diploma-level education (82 respondents, 23.4%). Regarding business scale, micro enterprises constituted the largest group (216 enterprises, 61.7%), followed by small enterprises (103 enterprises, 29.4%) and medium enterprises (31 enterprises, 8.9%). Sectorally, capture fisheries and aquaculture represented the largest proportion of businesses (133 enterprises, 38.0%), followed by seafood processing and marine-based products (97 enterprises, 27.7%), coastal tourism and supporting services (67 enterprises, 19.1%), and other marine-related activities (53 enterprises, 15.2%). As shown in Figure 2, these MSMEs are geographically distributed across coastal areas in South Sulawesi, indicating a diverse yet representative distribution of businesses across different sectors and locations.

All constructs in this study were adapted from previously validated measurement instruments and aligned with recent empirical research in the fields of blue economy, sustainability, and MSME studies to ensure content validity and construct reliability. Each construct was operationalised using multiple reflective indicators measured on a five-point Likert scale (1 = strongly disagree; 5 = strongly agree).

The study includes five latent constructs: Blue Economy Implementation (BEI), MSME Capabilities (CAP), Ecosystem Support (ECO), Economic Sustainability (ES), and Environmental Sustainability (ENS). To improve measurement transparency, Table 2 now explicitly presents the measurement items for each construct, their supporting literature sources, and the Likert scale used for all indicators, as recommended by the reviewer.

In addition, MSME Capabilities (CAP) were measured as a multidimensional construct reflecting managerial capability, innovation capability, and environmental capability. This multidimensional approach ensures conceptual consistency with the theoretical framework and better captures how internal capabilities function in supporting sustainability outcomes.

Measurement validity and reliability were assessed using indicator loadings, Average Variance Extracted (AVE), Composite Reliability (CR), and Cronbach’s Alpha (α). Consistent with established PLS-SEM guidelines, all constructs met or exceeded the recommended threshold values, indicating satisfactory convergent validity and internal consistency (Hair and Alamer, 2022). The complete measurement model, including constructs, indicators, and supporting references, is presented in Table 2, which forms the basis for subsequent measurement model and structural model evaluation.

To ensure methodological rigor and data quality, this study employed a structured, multi-stage data collection process (Alrasyid et al., 2026). First, the questionnaire was developed in English and subjected to a back-translation procedure. Independent bilingual experts translated the instrument from English into Bahasa Indonesia and subsequently back into English to ensure semantic equivalence, cultural appropriateness, and clarity of meaning (Sekaran and Buogie, 2016). This process minimised potential misinterpretation of survey items (Brislin, 1970; Chang et al., 2019).

Second, a pilot study involving 40 coastal MSMEs not included in the final sample was conducted to assess measurement clarity, reliability, and contextual suitability. The pilot test enabled early detection of potential response bias, common method variance, and ambiguous wording validity (Fowler, 2013; Latan et al., 2021). Feedback from pilot respondents confirmed the relevance and comprehensibility of the questionnaire items, leading to minor refinements prior to the main survey (Podsakoff et al., 2012).

Third, the main data collection was conducted between September and December 2025 using a combination of assisted field surveys and guided questionnaire administration. This approach was adopted to accommodate varying levels of literacy and digital access among coastal MSMEs and has been shown to be effective in community-based and MSME research contexts (Hamid et al., 2022). Follow-up visits and reminder communications were employed to enhance participation and minimise non-response bias.

Participation in the study was entirely voluntary, and respondent anonymity was strictly maintained to ensure confidentiality and ethical compliance. Informed consent was obtained prior to participation, and no personally identifiable information was collected. The extended data collection period allowed sufficient time to obtain a reliable and representative sample of coastal MSMEs across the selected regions of South Sulawesi.

This study employed several statistical indicators, such as Cronbach's Alpha, Composite Reliability (CR), and Average Variance Extracted (AVE), to assess the validity and reliability of the measurement model. To guarantee the internal consistency, construct dependability, and convergent validity of latent constructs, these metrics are frequently used in PLS-SEM research (Hair and Alamer, 2022; Hair et al., 2011, 2017; Ringle et al., 2020).

As shown in Table 3, all indicator loadings exceeded the recommended threshold of 0.70, indicating that each item strongly reflects its corresponding construct. The factor loadings for the Blue Economy Implementation (BEI) construct ranged from 0.873 to 0.923, demonstrating strong indicator reliability. Similarly, the loadings for MSME Capabilities (CAP) ranged between 0.846 and 0.894, while the Ecosystem Support (ECO) construct showed loadings between 0.826 and 0.895. For the sustainability constructs, Economic Sustainability (ES) exhibited loadings ranging from 0.892 to 0.921, and Environmental Sustainability (ENS) showed loadings between 0.865 and 0.934. These results indicate that all measurement items contribute substantially to explaining their respective latent constructs.

Convergent validity was further assessed using the Average Variance Extracted (AVE). The AVE values for all constructs exceeded the recommended minimum threshold of 0.50, indicating that the constructs explain more than half of the variance of their indicators (Hair et al., 2017). Specifically, the AVE values were 0.792 for BEI, 0.760 for CAP, 0.740 for ECO, 0.827 for ES, and 0.805 for ENS. These results confirm that the constructs demonstrate satisfactory convergent validity.

In terms of internal consistency reliability, both Composite Reliability (CR) and Cronbach’s Alpha values were examined. The CR values ranged from 0.919 to 0.950, exceeding the recommended threshold of 0.70 and indicating strong internal consistency among the indicators measuring each construct. Similarly, Cronbach’s Alpha values ranged from 0.883 to 0.934, which also surpasses the minimum acceptable level of 0.70. These findings confirm that all constructs exhibit high reliability.

Overall, the results demonstrate that the measurement model satisfies the recommended criteria for indicator reliability, convergent validity, and internal consistency reliability. Therefore, the constructs used in this study are considered valid and reliable for subsequent structural model analysis.

Discriminant validity was assessed to ensure that each construct in the model is empirically distinct from the other constructs. In PLS-SEM, discriminant validity is commonly evaluated using the Fornell–Larcker criterion and the Heterotrait–Monotrait ratio of correlations (HTMT) (Hair and Alamer, 2022; Hair et al., 2011, 2017; Ringle et al., 2020). The Fornell–Larcker criterion compares the square root of the Average Variance Extracted (AVE) of each construct with the correlations between that construct and other constructs in the model. Discriminant validity is established when the square root of the AVE is greater than the correlations with other constructs.

As presented in Table 4, the diagonal elements represent the square root of the AVE for each construct. The findings indicate that the square root of the AVE values for Blue Economy Implementation (0.879), Economic Sustainability (0.889), Ecosystem Support (0.873), Environmental Sustainability (0.856), and MSME Capabilities (0.895) are generally higher than their corresponding inter-construct correlations. This indicates that each construct shares more variance with its own indicators than with other constructs in the model, thereby satisfying the Fornell–Larcker criterion for discriminant validity.

In addition to the Fornell–Larcker criterion, discriminant validity was also examined using the Heterotrait–Monotrait ratio (HTMT). The HTMT values, shown above the diagonal in Table 4, were all below the recommended threshold of 0.90, indicating that the constructs are empirically distinct from one another (Henseler et al., 2015). Furthermore, the confidence intervals of the HTMT values did not include the value of 1, which further supports the presence of discriminant validity. Overall, the results demonstrate that the constructs included in this study exhibit satisfactory discriminant validity. This confirms that each construct captures a unique conceptual domain and is sufficiently distinct from the other constructs in the measurement model, thereby supporting the adequacy of the measurement model for subsequent structural model analysis.

After confirming the adequacy of the measurement model, the structural model was evaluated to test the proposed hypotheses and examine the relationships among the constructs. The structural model assessment was conducted using Partial Least Squares Structural Equation Modelling (PLS-SEM) by analyzing the path coefficients (β), t-statistics, and p-values obtained through bootstrapping procedures. In addition, the coefficient of determination (R²) and predictive relevance (Q²) were examined to assess the explanatory power and predictive capability of the model.

The results of the hypothesis testing are presented in Table 5. The findings indicate that Blue Economy Implementation (BEI) has a positive and significant effect on both sustainability dimensions. Specifically, BEI positively influences Economic Sustainability (ES) (β = 0.052, t = 7.770, p < 0.001), supporting H1, and Environmental Sustainability (ENS) (β = 0.037, t = 9.058, p < 0.001), supporting H2. These results suggest that the adoption of blue economy practices contributes to improving both the economic performance and environmental responsibility of coastal MSMEs. Furthermore, BEI was found to have a significant positive effect on MSME Capabilities (CAP) (β = 0.010, t = 89.309, p < 0.001), supporting H3. This finding indicates that the implementation of blue economy principles can enhance internal organizational capabilities, such as managerial competence, innovation capacity, and sustainability awareness within MSMEs.

Furthermore, BEI was found to have a significant positive effect on MSME Capabilities (CAP) (β = 0.010, t = 89.309, p < 0.001), supporting H3. Although the standardized path coefficient of BEI → CAP is relatively small (β = 0.010), its practical significance should be interpreted within the context of coastal MSMEs, where capability transformation typically occurs incrementally rather than instantaneously. Small enterprises often face financial limitations, technological constraints, and human capital shortages, making capability upgrading a gradual process.

The statistically significant relationship indicates that blue economy implementation contributes to cumulative capability development through continuous learning, gradual technology adoption, managerial adaptation, and repeated exposure to sustainable operational practices. Therefore, while the short-term economic magnitude appears modest, the long-term strategic implications remain meaningful because capability accumulation often generates delayed but sustainable competitive benefits. This finding also suggests that blue economy implementation may exert stronger indirect effects through mediating mechanisms than through immediate direct organizational transformation, which is consistent with Dynamic Capability Theory.

The results also show that MSME Capabilities significantly influence sustainability outcomes. CAP positively affects Economic Sustainability (β = 0.042, t = 7.937, p < 0.001), supporting H4, and Environmental Sustainability (β = 0.042, t = 8.230, p < 0.001), supporting H5. This suggests that MSMEs with stronger internal capabilities are better positioned to achieve sustainable economic growth while maintaining environmentally responsible business practices. In addition, Ecosystem Support (ECO) was found to have a significant positive impact on both sustainability dimensions. ECO positively influences Economic Sustainability (β = 0.043, t = 5.494, p < 0.001), supporting H6, and Environmental Sustainability (β = 0.043, t = 7.091, p < 0.001), supporting H7. These findings highlight the importance of supportive external environments, including government policies, institutional assistance, and access to resources, in enabling coastal MSMEs to achieve sustainable outcomes.

The mediating role of MSME Capabilities was also examined. The findings indicate that CAP significantly mediates the relationship between Blue Economy Implementation and both sustainability outcomes. The indirect effect of BEI → CAP → ES is significant (β = 0.038, t = 7.041, p < 0.001), supporting H8, while the indirect effect of BEI → CAP → ENS is also significant (β = 0.039, t = 8.980, p < 0.001), supporting H9. These results indicate that MSME capabilities act as an important mechanism through which blue economy practices influence both economic and environmental sustainability. In terms of explanatory power, the coefficient of determination (R²) indicates that MSME Capabilities have an R² value of 0.826, suggesting substantial explanatory power. Meanwhile, Economic Sustainability shows an R² value of 0.888, and Environmental Sustainability has an R² value of 0.912, both indicating very strong explanatory power according to the commonly accepted thresholds of 0.75 (substantial), 0.50 (moderate), and 0.25 (weak).

The predictive relevance of the model was further assessed using the Stone–Geisser Q² value. The results show Q² values of 0.624 for CAP, 0.729 for ES, and 0.730 for ENS, all of which are greater than zero. This indicates that the structural model has strong predictive relevance and is capable of accurately predicting the endogenous constructs in the model.

Overall, the structural model results confirm that blue economy implementation, MSME capabilities, and ecosystem support play significant roles in enhancing the economic and environmental sustainability of coastal MSMEs. Moreover, the mediating role of MSME capabilities highlights the importance of strengthening internal organizational capacity to maximize the sustainability benefits of blue economy practices.

This study aimed to examine how the implementation of blue economy principles influences the economic and environmental sustainability of coastal MSMEs, while also considering the roles of MSME capabilities and ecosystem support. The results provide several important insights into the mechanisms through which sustainability-oriented practices can be operationalized at the MSME level in coastal economic systems.

First, the findings indicate that blue economy implementation positively affects both economic and environmental sustainability of coastal MSMEs. This result supports the argument that integrating sustainability principles into business operations can generate both economic and ecological benefits. In the context of coastal MSMEs, practices such as efficient resource utilization, waste reduction, and environmentally responsible production processes can simultaneously improve operational efficiency and reduce environmental pressures. These findings are consistent with prior studies suggesting that sustainability-oriented strategies can assist MSMEs in improving long-term business performance while maintaining ecosystem integrity (Lee et al., 2021; Sugiyanto et al., 2025). The results also reinforce the view that the blue economy is not solely an environmental agenda but also a viable economic development pathway for coastal communities.

Second, the study found that blue economy implementation significantly strengthens MSME capabilities. Rather than producing immediate large-scale transformation, the findings suggest that capability development occurs gradually through continuous organizational learning, technological adaptation, and sustainability-driven managerial adjustments. This explains why the statistical relationship remains significant despite its relatively small direct coefficient. From a dynamic capabilities perspective, sustainability initiatives often require firms to reconfigure resources, adopt new technologies, and develop new knowledge. As a result, the process of implementing blue economy practices can act as a catalyst for capability development within MSMEs. This finding aligns with previous research emphasizing that exposure to sustainability frameworks can encourage learning, innovation, and organizational adaptation in small businesses (Elston et al., 2024; Saarani et al., 2023).

Third, the results demonstrate that MSME capabilities play a significant role in enhancing both economic and environmental sustainability outcomes. Enterprises with stronger internal capabilities are better able to implement efficient production processes, adopt environmentally friendly technologies, and access more competitive markets. These capabilities enable MSMEs to balance economic growth with environmental responsibility, thereby supporting long-term sustainability. This finding is consistent with the natural resource-based view of the firm, which suggests that firms possessing superior capabilities in environmental management and innovation are more likely to achieve sustainable competitive advantages (Vega-Muñoz et al., 2021).

Fourth, the study highlights the important role of ecosystem support in promoting sustainability among coastal MSMEs. The results show that institutional and environmental support mechanisms such as government policies, training programs, infrastructure development, and access to finance significantly contribute to improving both economic and environmental sustainability outcomes. This finding confirms previous studies that emphasize the importance of enabling environments in facilitating the adoption of sustainability practices, particularly among small-scale enterprises with limited internal resources (Hendarman et al., 2024; Pace et al., 2023). Without adequate ecosystem support, MSMEs may face difficulties in adopting new technologies or implementing environmentally responsible business practices.

Another important finding of this study is the mediating role of MSME capabilities in the relationship between blue economy implementation and sustainability outcomes. The results show that MSME capabilities partially mediate the effects of blue economy implementation on both economic and environmental sustainability. This indicates that the benefits of blue economy practices are not realized automatically but depend on the internal capacities of firms to effectively implement and manage sustainability-oriented strategies. In other words, blue economy initiatives are more likely to produce meaningful sustainability outcomes when MSMEs possess adequate skills, knowledge, and organizational capabilities.

Overall, these findings contribute to the growing literature on the blue economy by providing empirical evidence at the enterprise level, particularly in the context of coastal MSMEs. While many previous studies have focused on macro-level policy analysis or sectoral assessments, this study highlights the importance of firm-level mechanisms such as internal capabilities and external ecosystem support in translating blue economy principles into measurable sustainability outcomes. By integrating these factors into a structural model, this study offers a more comprehensive understanding of how blue economy practices can support sustainable coastal economic development.

This study examined the implementation of blue economy principles in coastal micro, small, and medium enterprises (MSMEs) and their impacts on economic and environmental sustainability in South Sulawesi, Indonesia. By integrating internal firm capabilities and external ecosystem support within a structural model, the study provides empirical insights into how sustainability-oriented practices can be operationalized at the MSME level.

The findings reveal that blue economy implementation positively influences both economic and environmental sustainability of coastal MSMEs. These results indicate that the adoption of sustainable resource management practices, environmentally friendly production processes, and responsible marine resource utilization can simultaneously enhance business performance and environmental protection. The results therefore confirm that the blue economy framework can function as an effective pathway for promoting sustainable coastal economic development.

The findings further demonstrate that sustainable outcomes are strengthened when blue economy implementation is supported by strong internal capabilities and favorable institutional ecosystems. This suggests that long-term sustainability depends on the interaction between organizational readiness and external support systems rather than solely on direct blue economy adoption.

Furthermore, the findings emphasize the importance of ecosystem support, including institutional assistance, policy support, and access to resources, in enabling MSMEs to achieve sustainability goals. The results also confirm that MSME capabilities mediate the relationship between blue economy implementation and sustainability outcomes, suggesting that internal capabilities function as a key mechanism through which sustainability initiatives generate tangible benefits.

Overall, this study provides empirical evidence that the successful implementation of the blue economy at the MSME level requires a combination of sustainability-oriented business practices, strong internal capabilities, and supportive external ecosystems. These elements collectively contribute to enhancing the resilience and sustainability of coastal economic systems.

This study contributes to the growing body of literature on the blue economy and sustainable entrepreneurship by extending the analysis of blue economy implementation to the firm level, particularly within the context of coastal MSMEs. While much of the existing literature has focused on macro-level policy frameworks or sectoral analyses, this study provides empirical evidence on how sustainability principles are implemented by individual economic actors.

The study also contributes theoretically by integrating blue economy implementation, MSME capabilities, ecosystem support, and sustainability outcomes into a single structural model. This integrative approach provides a more comprehensive understanding of the mechanisms through which sustainability-oriented practices influence both economic and environmental performance.

In addition, the findings support theoretical perspectives such as the natural resource-based view (NRBV) and dynamic capabilities theory, which suggest that firms that develop strong capabilities related to environmental management and innovation are more likely to achieve sustainable competitive advantages. By demonstrating the mediating role of MSME capabilities, this study highlights the importance of internal organizational capacity as a critical link between sustainability strategies and performance outcomes.

The findings of this study provide several practical implications for policymakers, development agencies, and MSME practitioners involved in coastal economic development. First, the Ministry of Marine Affairs and Fisheries, local governments, and regional development agencies should introduce targeted policy instruments such as tax incentives for environmentally friendly production equipment, subsidized green financing schemes, and regulatory incentives for sustainable fisheries and aquaculture practices.

Second, the results highlight the importance of capacity-building initiatives for coastal MSMEs. Universities, vocational institutions, and business incubators should develop structured training programs focusing on sustainable production techniques, digital marketing, innovation capability, and environmental management systems for coastal MSMEs.

Third, Financial institutions and public development banks should expand access to blue financing programs, while local governments should improve supporting infrastructure such as cold storage facilities, sustainable logistics systems, and digital market access platforms. In terms of implementation pathways, stronger collaboration between government agencies, universities, private sector actors, and community organizations is needed to create integrated blue economy clusters that support technology transfer, business mentoring, and market expansion.

Finally, strengthening the integration between sustainability policies and MSME development strategies may help create a more inclusive and resilient coastal economy while simultaneously supporting marine ecosystem conservation.

Despite its contributions, this study has several limitations that should be acknowledged. First, the study was conducted in a single provincial context, South Sulawesi, which may limit the generalizability of the findings to other coastal regions with different socio-economic or institutional conditions. Future research could expand the scope of analysis by including multiple provinces or conducting cross-country comparisons to examine the broader applicability of the proposed model.

Second, the study relied on cross-sectional survey data, which captures relationships between variables at a single point in time. Longitudinal studies would provide deeper insights into how the implementation of blue economy practices evolves over time and how it influences sustainability outcomes in the long term.

Third, the study focused primarily on internal capabilities and ecosystem support as mediating and explanatory factors. Future research may explore additional variables, such as technological innovation, digital transformation, market orientation, or stakeholder collaboration, which may further influence the effectiveness of blue economy implementation. Finally, future studies could also adopt mixed-method approaches, combining quantitative modeling with qualitative case studies to obtain richer insights into how coastal MSMEs operationalize blue economy principles in different economic and cultural contexts.