Can dispersed knowledge management and ERM convert green strategy into firm performance? A chain-mediation approach

In the contemporary business landscape, growing environmental pressure and rising stakeholder expectations compel firms to adopt green strategies and sustainability-oriented practices to enhance competitiveness. Since 2020, each consecutive year has set new temperature records, exacerbating the environmental difficulties documented in prior literature (Ma et al., 2020; Sadiq et al., 2022; Usman et al., 2022a; Huang et al., 2022). Consequently, stakeholders increasingly demand that organizations operate more sustainably, elevating green goals to core organizational objectives (Le, 2022; Lin et al., 2021; Yu et al., 2017). As financial incentives remain a primary motivator (Vallaster et al., 2018; Yang and Usman, 2021), green strategies and actions must be clearly linked to organizational performance.

Despite these trends, the specific mechanisms through which green strategy translates into improved performance remain largely unexplored. To address this gap, we examine how knowledge management interacts with enterprise risk management (ERM) to convert strategic environmental intent into tangible performance outcomes. Drawing on dispersed knowledge management (DKM) research, we argue that rising sustainability pressure increases the complexity of relationships between organizational agents (Bennis and Nanus, 1985), thereby complicating corporate risk scenarios (Oliva, 2016; Christofi et al., 2021)

In line with the concept of “dispersed knowledge,” our study posits that when risk-related information is fragmented across multiple sources, decision-making becomes more difficult, potentially hindering organizational performance. Our approach to DKM, focused on gathering internal risk information, is rooted in intraorganizational knowledge management research (Gomes et al., 2020; Zhang et al., 2020; Loon, 2019; Oliva and Kotabe, 2019; Wu and Hu, 2018; Martinez-Conesa et al., 2017). We argue that implementing ERM helps limit this dispersion by generating structured, integrated risk knowledge. In other words, we view DKM as a process of coordinated knowledge creation that is enhanced by ERM implementation.

Regarding green practices (GP) and green strategy (GS), this work addresses how managing dispersed risk knowledge and the ERM process contribute to organizational sustainability. This inquiry is rooted in the literature on sustainable organizations; specifically, Ghlichlee et al. (2024) note that such firms must demonstrate a “triple bottom line” orientation – balancing people, planet and profit (Elkington, 2018). Sustainability efforts manifest through either green strategic orientation (He et al., 2023; Miroshnychenko et al., 2017; Hart, 1995; Moon, 2008) or operational green practices. Regarding the profit dimension, extensive research confirms the link between a firm’s environmental and financial performance (e.g. Endrikat et al., 2014).

This study develops and tests the chain mediation chain mediation model, in which dispersed risk-related knowledge (DKM), and the ERM operate as sequential mediators linking green strategy to firm performance. This empirical approach is rooted in Durst and Zieba (2019) notion that knowledge risks are inherent in achieving sustainability through people-planet-profit orientation, and therefore organizations’ efforts toward sustainability may be supported by knowledge management. Drawing upon the Resource-Based View (RBV), the Knowledge-Based View (KBV) and ERM literature, we propose a conceptual model where green strategy (GS) and green practices (GP) serve as predictors, DKM and ERM act as mediating capabilities, and firm performance (P) constitutes the outcome. To achieve this objective, this research addresses the following question: (RQ1): How do Dispersed Knowledge Management and ERM translate Green Strategy into Firm Performance?

Our empirical investigation utilizes data collected through structured surveys of firms across diverse industries. We specifically targeted enterprises that have already implemented green innovations and operate in Silesia, Poland – a region that intensifies the need for green strategy and practices. The selection of innovative companies was driven by Oliva et al. (2021), who identified common frontiers between knowledge management, innovation and risk management. As a historically coal-dependent region, Silesia faces a significant green transition challenge (Baron, 2025). The adoption of eco-innovations and the management of associated risks are critical determinants of this regional transition (Męczyński and Ciesiółka, 2024). Therefore, studying enterprises that have experienced the internal risks of innovation while facing external pressures provides a unique and compelling setting to test the relevance of DKM and ERM implementation.

We employed partial least squares structural equation modeling (PLS-SEM) with bootstrapping to analyze the proposed mediation effects. Our results indicate that green strategy enhances firm performance indirectly through a sequential mechanism involving DKM and ERM. Specifically, green strategy significantly improves DKM, which subsequently strengthens ERM – a chain of effects that ultimately drives higher performance. Notably, the direct link between green strategy and performance via ERM alone was not significant, confirming the presence of a dominant sequential mediation.

These empirical findings contribute to the literature by highlighting the synergy between knowledge management and risk governance in implementing green strategies and improving firm performance. Consequently, our work broadens the understanding of the interactions between these constructs, equipping organizations to navigate green-transition risks more effectively.

The remainder of this paper is organized as follows. In Section 2 we provide a brief overview of the existing literature on knowledge management, ERM and green performance of the firm. In Section 3 we explain the methodical approach, and in section four we present and discuss the empirical results. Section five offers conclusions, with practical and theoretical implications.

In the aspect of theoretical background, our paper explores the intersections of three broad theoretical perspectives: KBV, ERM, and organizations’ sustainability in strategic and performance-related dimensions. Our problem in focus is a question on how dispersed knowledge about risk and the ERM process itself translates into sustainability of the organizations through enhancement of green strategy. To address this problem with PLS-SEM application, our conceptual framework introduces the rationale behind the constructs we further examine, as well as point on the black spots in examinations of their interactions reflected in the hypotheses we develop.

Organizations with a strong green strategic orientation must systematically collect and integrate environmental risk information across departments. Because sustainability efforts inherently involve “knowledge risks” (Durst and Zieba, 2019), firms pursuing green strategies are forced to manage fragmented, risk-related data. This strategic imperative drives the development of DKM processes to coordinate information regarding environmental risks, regulations and uncertainties. Furthermore, when managers align their actions with a firm’s strategic direction, they translate that intent into active knowledge-seeking behaviors (Hrebiniak and Joyce, 2005), viewing such information as valuable and actionable (Kabir and Carayannis, 2013).

Beyond knowledge, a green strategy establishes a normative link to operational behavior (Ghlichlee et al., 2024). It represents a firm’s commitment to environmental values in its decision-making (Banerjee, 2002; Delmas and Toffel, 2008). Since strategic intent precedes action, a green orientation should manifest in concrete Green Practices (GP), such as emissions reduction and stakeholder engagement. These practices are not just compliance measures; they are strategic actions that build competitive advantage (Shu et al., 2020; McWilliams and Siegel, 2000).

Finally, effective ERM requires aligning risk assessment with business strategy to ensure resilience (COSO, 2024). Firms focused on green strategies face unique sustainability risks, necessitating structured risk governance. When a strategy is environmentally oriented, knowledge management becomes the essential tool for executing that strategy through integrated risk identification and assessment (Oliva et al., 2021; Hock-Doepgen et al., 2020; Khan and Ali, 2017). Therefore, a green strategy stimulates ERM development by increasing the perceived need for robust risk-response mechanisms. Nevertheless, this direct link may depend on the presence of indirect, knowledge-based mechanisms. This is because DKM may be a prerequisite for effectively implementing an environmental strategy within the ERM.

Based on the above arguments, we propose the following hypothesis:

Knowledge management is typically structured into stages: definition, acquisition, dissemination, storage, application and evaluation (Oliva, 2014). Each stage presents unique challenges that, when combined with organizational complexity, become potential sources of risk (Oliva et al., 2021). Because risk-related information is often fragmented, it creates “knowledge silos” that complicate risk governance. Consequently, coordinated DKM is a prerequisite for effective ERM. Building on these principles, Oliva (2016) proposes a systemic method for identifying risks by mapping two areas: the Business Environment (external context) and the Environment of Value (internal relationships affecting value creation). This framework shows that structured knowledge of the organizational context serves as the operational backbone for risk identification. Ultimately, a holistic approach to ERM supports continuous learning and ensures that intangible resources – specifically knowledge – contribute to strategic goals (Latif et al., 2020). By consolidating fragmented data, DKM provides the informational foundation for integrated ERM systems.

Green Practices (GP) encompass operational environmental behaviors, such as stakeholder engagement, waste management and resource consumption (Zhu et al., 2013; Shang et al., 2010). Implementing these practices generates practical experience with environmental risks and compliance, which informs structured risk assessment. Knowledge management is critical for adopting environmental innovations (Pham et al., 2019; Shu et al., 2020), suggesting that green practices and knowledge processes are mutually reinforcing. Specifically, practices generate risk-relevant knowledge, which then enables more sophisticated environmental responses. Furthermore, organizations that leverage knowledge about their broader environment are better positioned to deploy resources efficiently (Kweh et al., 2022). As green practices accumulate operational risk data, they contribute to the maturation of ERM capabilities by providing empirical grounding for risk-response strategies. Based on the above theoretical arguments and empirical evidence, we hypothesize that:

ERM research emphasizes that integrated risk management does more than just stabilize performance; it allows firms to capitalize on opportunities and build organizational resilience (COSO, 2024). When firms integrate risk-related knowledge into their strategic practices, they enhance their productivity, competitive advantage and long-term sustainability (Castrogiovanni et al., 2016; Lim et al., 2017). By leveraging structured risk knowledge, organizations are better positioned to deploy resources efficiently (Kweh et al., 2022). Furthermore, structured knowledge management processes ensure that relevant information flows quickly and accurately to support stakeholder value (Castrogiovanni et al., 2016). Consequently, ERM functions as a proactive, performance-enhancing capability rather than a purely protective mechanism. Building on these arguments, we hypothesize that:

Building on H1a and H2a, we expect the relationship between green strategy and ERM to be indirect, operating through the mobilization of dispersed risk-related knowledge. A green strategy creates a demand for coordinated risk information; in turn, this DKM process provides the informational infrastructure required for effective ERM. When risk management is viewed as the information necessary to execute strategy (Oliva et al., 2021; Hock-Doepgen et al., 2020; Khan and Ali, 2017), DKM serves as the critical intermediate mechanism that translates strategic environmental intent into structured risk governance. This pathway aligns with the KBV, which emphasizes that knowledge mobilization is a vital precondition for developing organizational capabilities.

Similarly, green strategy provides the directional framework for developing green practices (H1b), which then generate the operational risk knowledge that feeds into ERM (H2b). This sequential logic suggests that Green Practices (GP) constitute an indirect pathway through which strategic environmental orientation activates risk management capabilities. As organizations implement these practices to meet strategic commitments, they accumulate experiential knowledge regarding environmental risks and compliance. This data progressively enriches ERM systems. Thus, the mediation of GP in the GS→ERM relationship reflects how strategic intent is operationalized through environmental actions that ultimately inform risk governance. In line with the above arguments, we hypothesize that:

Green strategy exerts organizational pressure to align risk assessment with sustainability objectives (COSO, 2024). In turn, ERM serves as the capability that transforms this alignment into measurable performance (H3). The indirect pathway GS→ERM→P reflects the KBV’s proposition strategic resources do not generate value directly, but through their integration into organizational capabilities. By converting sustainability-oriented intent into structured risk governance, ERM acts as the intermediary mechanism through which green strategy influences firm performance. This logic is consistent with research positioning ERM as a proactive, value-creating capability rather than a purely protective one (Castrogiovanni et al., 2016; Lim et al., 2017). On this basis, we hypothesize that:

Building on H1a, H2a, H3, H4a and H5, the full chain GS→DKM→ERM→P represents a sequential capability-building process. In this sequence, green strategy first stimulates knowledge mobilization; this knowledge then enables robust risk governance, which ultimately drives performance. This chain mediation logic is rooted in the KBV, which emphasizes the sequential transformation of knowledge resources into value-creating capabilities (Kogut and Zander, 1992). While DKM processes enable organizations to identify and utilize information quickly and accurately (Castrogiovanni et al., 2016), ERM translates this informational foundation into strategic performance. Consequently, this sequential pathway represents the primary mechanism through which green strategy generates organizational value.From this perspective, we hypothesize that:

Similar to H6, the chain GS→GP→ERM→P proposes that green strategy generates performance outcomes through an operationally-driven pathway. through an operationally-driven pathway. In this sequence, environmental practices activate risk management capabilities, which subsequently improve performance. Green management is a key strategic action for building competitive advantage (Shu et al., 2020; McWilliams and Siegel, 2000), and integrating these practices into ERM systems should amplify their benefits.

However, we expect this operational chain to be weaker than the knowledge-based pathway (H6). This is because green practices are sometimes treated as compliance-driven requirements rather than being strategically integrated into risk governance. Green practices are often compliance-driven in nature (Durst and Zieba, 2019). This limits their capacity to generate the informational depth required for advanced risk governance. Without complementary knowledge mechanisms, their contribution to ERM remains constrained (Jackson, 2010). Despite this potential difference in strength, the sequential logic remains theoretically sound. Consistent with this line of reasoning, we hypothesize that:

Extensive research supports the link between a firm’s environmental and financial performance (Endrikat et al., 2014). Green management is recognized as a key strategic action for achieving competitive advantage (Shu et al., 2020; McWilliams and Siegel, 2000), with high-sustainability organizations often outperforming their peers (Eccles et al., 2012). Beyond indirect pathways, a green strategy can directly improve performance by enhancing organizational culture, stakeholder relationships and reputational capital. These factors can translate into financial outcomes independently of specific knowledge or risk management processes. Drawing on this line of argument, we hypothesize that:

Knowledge is a critical value-generating resource and a primary factor of production, contributing significantly to long-term profitability (Couto et al., 2022; Alvino et al., 2020; Ghlichlee et al., 2024; Latif et al., 2020). Coordinating the mobilization of dispersed risk-related knowledge improves decision-making, reduces uncertainty, and enhances resource efficiency, thereby directly boosting performance. Conversely, because knowledge is a dynamic resource that can erode over time (Jackson, 2010), poor management introduces significant sustainability risks – such as regulatory noncompliance (Yusup et al., 2015). This suggests that the performance benefits of DKM are both value-enhancing and risk-preventive. Organizations that leverage environmental knowledge are better positioned to optimize resource deployment (Kweh et al., 2022), while structured knowledge processes ensure effective value delivery to stakeholders (Castrogiovanni et al., 2016). Empirical evidence suggests that companies which manage dispersed knowledge effectively outperform their competitors. This is because they experience reduced uncertainty when making decisions and allocate resources more efficiently (Hock-Doepgen et al., 2020; Latif et al., 2020). Building on these insights, we hypothesize that:

A firm’s commitment to sustainability is manifested through its green practices, aligning with the “people-planet-profit” orientation (Elkington, 2018). Implementing these practices – including stakeholder engagement, emissions reduction and resource efficiency – is expected to generate direct performance benefits through cost savings, regulatory compliance and enhanced stakeholder relationships. Furthermore, leveraging knowledge management fosters sustainability through innovation (Lopes et al., 2017), adding an innovation-driven pathway to the existing cost and compliance mechanisms. Extensive research confirms the positive link between environmental and financial performance (Endrikat et al., 2014), positioning green management as a key strategic action for achieving competitive advantage (Shu et al., 2020; McWilliams and Siegel, 2000). Green practices thus represent a direct operational path to improved organizational outcomes, independent of knowledge or risk management processes. Guided by this reasoning, we hypothesize that:

Given the existing literature, we identify three interconnected gaps, summarized in Table 1. First, although the KBV, RBV and NBV establish knowledge as a source of competitive advantage – and ERM research proves the strategic value of integrated risk governance – no study has examined how DKM enables ERM as a capability within a green strategy context. Second, while the sustainability–performance literature confirms a positive relationship, the mechanisms linking green strategic orientation to performance (specifically through knowledge coordination and risk management) remain empirically unresolved. Third, although scholars have explored KM in innovation and interorganizational settings, the internal management of fragmented risk knowledge and its role in translating green strategy into performance has not been systematically investigated. The present study addresses these gaps by testing the conceptual model in Figure 1 (presented in line with Bution and Oliva, 2026), in which green strategy activates DKM and GP, both of which enable ERM to drive firm performance (P).

To investigate whether DKM and ERM convert green strategy into firm performance, we utilized data from a structured survey conducted between July and September 2024, yielding 146 valid responses. Participants were selected via purposive sampling, a technique that allows researchers to intentionally select participants based on characteristics and expertise relevant to the research question (Suri, 2011). This approach is justified when the goal is to understand complex phenomena in-depth, such as the intersections of DKM, ERM, GP, GS and P, rather than broad generalizability. Consequently, purposive sampling ensured data relevance by securing informed responses from individuals with decision-making authority, including owners and senior or middle management.

The selection criteria focused on reaching innovative enterprises operating in the Silesia region of Poland. The decision to target innovative firms was guided by Oliva et al. (2021), who highlight the common frontiers between knowledge management, innovation and risk management. The regional focus on Silesia aligns with our green strategy context; as a region undergoing a green transition, Silesia presents a setting where risk, knowledge and sustainability are critical daily considerations for enterprises (Baron, 2025). Since the region’s transition depends on a shift toward green innovations (Męczyński and Ciesiółka, 2024), this sampling scheme provides deeper insight into an ecosystem characterized by intense internal and external risk pressures. This offers a unique setting to test how DKM and ERM implementation support a sustainability orientation. Table 2 details the demographic features of the surveyed enterprises.

Following established practice in management research, firm size and firm maturity were included as control variables in the structural model, given their well-documented potential to influence firm performance (e.g. Brustbauer, 2016; Bashir et al., 2024). Both variables were operationalized as ordinal single-item constructs, with firm size coded as 1 = small, 2 = medium, 3 = large, and firm maturity coded according to the age brackets reported in Table 1 (1 = 1–5 years, 2 = 6–10 years, 3 = 11–15 years, 4 = over 15 years).

To minimize the potential for common method bias (CMB), both procedural and statistical measures were employed. Procedurally, respondent anonymity was ensured and participants were informed that there were no right or wrong answers. Statistically, multicollinearity was assessed using VIF values for all constructs in accordance with Kock (2015). All values were below the suggested threshold of 3.3 (range: 1.000–2.708), indicating that CMB is unlikely to seriously threaten the validity of the results.

Our survey instrument is based on prior research into green strategy, practices, ERM and DKM (e.g. Brustbauer, 2016; Oliva, 2016; Hock-Doepgen et al., 2020; Le, 2022; Delmas et al., 2010).  Appendix – Table A1 details the constructs and their adaptation. This selection process ensured alignment with our theoretical framework and the study’s organizational context. Integrating measurement items from multiple sources is consistent with prior management research (e.g. Bashir et al., 2024; Naqshbandi et al., 2024; Rehman et al., 2024). Furthermore, we rigorously assessed construct reliability and validity through measurement model evaluation within the PLS-SEM framework ( Appendix – Table A2).

The ERM scale comprises items covering risk identification, measurement, response and ownership (Brustbauer, 2016; Gleißner and Berger, 2024). The DKM scale includes items related to gathering fragmented risk knowledge through reporting, periodic updates of risk registers, and knowledge verification (Brustbauer, 2016; Leva et al., 2017). The GS construct captures a strategic orientation toward environmental objectives and forward-looking decisions (Mazzanti et al., 2016; Rehman et al., 2024; Delmas and Toffel, 2008), specifically acknowledging green investments as a key strategic hallmark (Mazzanti et al., 2016). The GP scale captures practices such as product design, pro-environmental actions, waste management, resource consumption and customer communication regarding environmental impacts (Rehman et al., 2024; Alam and Islam, 2021; Zhu et al., 2007; Shang et al., 2010). Finally, firm performance (P) utilizes common financial variables representing profitability and growth perspectives (e.g. Šafár et al., 2025).

All items were assessed using a seven-point Likert scale (1 = strongly disagree to 7 = strongly agree). We assessed internal consistency using Cronbach’s alpha (Cronbach, 1951), with all constructs demonstrating satisfactory reliability (see  Appendix – Table A3).

Empirical analyses were performed using PLS-SEM (SmartPLS 4.1.1.7), which is well-suited for theory-building research involving latent constructs (Hair et al., 2021, 2022). Following the evaluation of the reflective measurement model, we assessed the structural model. Direct and indirect (mediating) effects were examined using bias-corrected and accelerated (BCa) bootstrapping with 10,000 resamples (two-tailed, α = 0.05). Mediation was confirmed when the 95% confidence interval for the indirect effect did not include zero. In accordance with PLS-SEM guidelines (Hair et al., 2022), this two-stage assessment ensured that measurement quality was established prior to hypothesis testing. After reviewing initial item loadings, the following indicators were removed because they fell below the recommended threshold: DKM_4, GP_4, GS_1, P_1, P_2 and P_3.

For reflective measurement models, the evaluation focuses on indicator reliability, internal consistency and construct validity (convergent and discriminant validity). Indicator reliability was assessed via outer loadings, using 0.708 as the recommended threshold (Hair et al., 2019). As shown in Figure 2, the majority of indicators exceeded this criterion. While two items (ERM_4, GP_5) reported slightly lower loadings (0.698 and 0.700, respectively), they were retained. Consistent with Chin (1998), items marginally below the threshold may be kept when theoretically justified and when their removal does not improve the construct’s reliability or validity.

All constructs demonstrated satisfactory reliability and convergent validity (Table 3). Cronbach’s alpha and composite reliability (CR) values for each construct exceeded the recommended threshold of 0.70, confirming adequate internal consistency. Moreover, the average variance extracted (AVE) values were above the minimum criterion of 0.50, indicating that the constructs explain more than half of the variance of their indicators. These results collectively confirm that the measurement model exhibits acceptable reliability and convergent validity in line with recommended PLS-SEM standards (Hair et al., 2019).

The results confirm that discriminant validity is satisfactory across all constructs (Table 4). First, all HTMT values fall below the conservative threshold of 0,85 (Henseler et al., 2016), indicating that no pair of constructs demonstrates problematic conceptual overlap. Although the highest HTMT values are observed between STR–GP, ERM–DKM and STR–DKM, suggesting closer conceptual relatedness, they remain within acceptable limits and therefore do not indicate redundancy. Lower HTMT ratios involving firm performance (P) confirm a clear empirical distinction between the performance outcome and the antecedent constructs.

The Fornell–Larcker criterion also supports discriminant validity. In each case, the square root of AVE (diagonal values) exceeds the correlations with other constructs, confirming that each construct shares more variance with its own indicators than with any other latent variable (Hair et al., 2022). The strongest correlations appear between STR, GP and ERM-related constructs, which is theoretically consistent given the expected alignment between environmental strategy, sustainability practices and knowledge- and risk-related processes. Nonetheless, these correlations remain below the AVE square roots, reinforcing construct distinctiveness. In summary, both HTMT and Fornell–Larcker results demonstrate that the constructs are empirically distinct and that discriminant validity is established, confirming that the measurement model is appropriate for subsequent structural model analysis.

Following the confirmation of the measurement model’s validity, the significance of the structural relationships was assessed using the nonparametric PLS bootstrapping procedure (Hair et al., 2022). The estimated structural model, including factor loadings, path coefficients, effect sizes and construct-level quality criteria, is presented in Figure 2.

This enabled the evaluation of path coefficients (β) and the empirical testing of direct effects, presented in Table 5.

The direct effect results reveal a nuanced pattern of relationships, indicating that the theorized model is partially supported. Green strategy (GS) exhibits strong and highly significant effects on both DKM and green practices (GP), with large effect sizes (f² = 0,661 and f² = 1,095, respectively). These findings demonstrate that environmental strategic intent is effectively translated into organizational knowledge processes and operational initiatives, confirming a robust internalization of green strategic priorities. This evidence aligns with Hrebiniak and Joyce (2005) and Kabir and Carayannis (2013), who argue that managers acting on strategic direction translate intent into knowledge-seeking behaviors. It also supports (Baumgartner and Rauter, 2017), who establish a direct normative link between sustainability-oriented strategy and corporate practices.

These findings demonstrate that environmental strategic intent is effectively translated into organizational knowledge processes and operational environmental initiatives, suggesting a robust internalization of green strategic priorities. This aligns with Hrebiniak and Joyce (2005) and Kabir and Carayannis (2013), who demonstrate that managers acting in accordance with strategic direction translate intent into knowledge-seeking behaviors, and with Baumgartner and Rauter (2017), who establish a direct normative link between sustainability-oriented strategy and corporate practices. However, the nonsignificant direct effect of GS on ERM (f² = 0,022, small effect) indicates that a green strategic orientation does not automatically enhance ERM capabilities. This reveals a gap between sustainability-oriented strategizing and risk governance, suggesting that ERM development requires organizational enablers beyond mere strategic intent. This is consistent with Oliva et al. (2021) and Khan and Ali (2017), who position knowledge management as the necessary interface to realize the relationship between strategy and risk management.

DKM exerts a strong and significant positive influence on ERM, with a large effect size (f² = 0,453), confirming that the distribution and integration of risk-related knowledge is a primary antecedent of effective ERM. This extends the work of Oliva (2016), who argues that systematic risk identification requires structured knowledge of the organizational environment, and corroborates Latif et al. (2020) regarding the necessity of knowledge resources for holistic ERM. In the controlled model, green practices also exert a significant effect on ERM (β = 0,197, p = 0,048), suggesting that environmental operational initiatives contribute to risk management development, albeit modestly (f² = 0,046, small effect), although their influence remains weaker than that of knowledge-based processes. Crucially, their influence remains weaker than that of knowledge-based processes.

The discrepancy between statistical significance and the small effect size suggests that while environmental practices activate a company’s ERM system, their practical contribution remains limited. Compared to knowledge-based processes, their impact is marginal, positioning DKM as the dominant mechanism. This weaker effect aligns with Jackson (2010) and Durst and Zieba (2019), who suggest that sustainability-related practices often operate in a compliance-driven mode rather than being strategically integrated. This limits their capacity to activate higher-order risk capabilities without complementary knowledge mechanisms.

The direct effects of both DKM and GP on performance are not only nonsignificant but marginally negative, with negligible effect sizes with negligible effect sizes (f² = 0,001 and f² = 0,000, respectively). This suggests that these constructs do not independently drive performance outcomes; instead, their contribution is channeled through ERM, a pattern consistent with the mediation logic explored below. This is theoretically coherent with Kogut and Zander (1992) and Priem and Butler (2001), who argue that knowledge generates competitive advantage only through its integration into organizational capabilities, rather than in its raw form.

The inclusion of firm size and firm maturity as control variables confirms that neither significantly influences firm performance (firm size: β = −0,051, p = 0,491; firm maturity: β = −0,025, p = 0,771), supporting the robustness of the structural model. Notably, in the controlled model the direct effect of GS on performance reaches significance (β = 0,267, p = 0,038), with a small but non-negligible effect size (f² = 0,034). This suggests a modest but direct contribution of green strategy to firm performance beyond the indirect pathways, aligning with Shu et al. (2020) and McWilliams and Siegel (2000), who document a direct contribution of green management to competitive advantage.

Finally, the positive and significant effect of ERM on firm performance (f² = 0,068, medium effect) confirms its strategic value, supporting the view that integrated risk management contributes to superior organizational outcomes. The strength of this effect reinforces the argument that ERM acts as a performance-enhancing capability rather than a purely protective mechanism. This finding extends Castrogiovanni et al. (2016), who argue that firms integrating risk knowledge into strategy-supporting systems achieve superior performance, while also specifying the necessary upstream condition – DKM mobilization – under which this effect is realized. Overall, the pattern of results suggests that the pathway from green strategy to performance is not primarily direct but is conditioned by knowledge-based and risk-based organizational capabilities. This underscores the significance of the indirect mechanisms explored in the subsequent mediation analyses.

Building on the direct effects reported in Table 5, we conducted subsequent analyses to assess whether green strategy influences ERM and firm performance through indirect pathways. To achieve this, simple mediation effects were examined; these results are presented in Table 6.

The mediation results provide selective support for the hypothesized indirect mechanisms. The indirect effect of green strategy (GS) on ERM through DKM is positive and highly significant (β = 0,348, p = 0,000), indicating a strong mediating role for DKM. This finding reinforces the argument that GS influences ERM primarily when risk-related knowledge is effectively disseminated and leveraged across the organization. This evidence extends Hock-Doepgen et al. (2020) and Oliva et al. (2021), who theorize knowledge management as the primary interface through which strategic intent is converted into risk governance. Essentially, environmental strategic intent translates into enhanced risk management capability only when supported by knowledge-based processes, highlighting DKM as a critical organizational conduit linking strategy to risk governance.

In contrast, the indirect effect of green strategy on ERM through green practices (GP) is statistically significant at the 5% threshold (β = 0,142, p = 0,050), albeit marginal. This finding suggests that environmental operational initiatives can contribute to ERM development; however, the weakness of this effect implies that green practices alone constitute a limited pathway to risk management maturity. Such practices likely require complementary knowledge-based mechanisms to generate meaningful risk governance outcomes. This is consistent with Lopes et al. (2017), who show that sustainability-driven performance benefits emerge primarily when knowledge management underpins green practices.

Overall, of the three hypothesized indirect pathways, two received empirical support. GS influences ERM through DKM strongly and significantly, and through GP marginally but significantly; however, the indirect effect of GS on firm performance through ERM alone is not supported. This pattern suggests that the role of ERM as a mediator is contingent on the nature of the upstream pathway. Knowledge-based mechanisms prove more consequential than operational green initiatives in activating risk governance, while ERM alone is insufficient to mediate the full strategy-to-performance chain.

Similarly, the indirect effect of GS on firm performance (P) through ERM is nonsignificant. This finding provides no support for the assumption that ERM acts as a simple mediator between green strategy and performance. Although ERM is confirmed as a direct performance driver, this result indicates that it does not automatically convert strategic environmental orientation into performance gains. This suggests that the pathway from strategy to outcomes is more complex than a single-step mediation, requiring multi-stage mechanisms – as anticipated in the subsequent serial mediation analysis.

Taken together, these findings confirm two indirect pathways through which green strategy shapes ERM: strongly via DKM and marginally via GP. However, the strategy-to-performance chain through ERM alone remains unsupported. The results underscore the primacy of knowledge mobilization over operational green practices in translating strategic environmental ambitions into risk governance capabilities. Ultimately, this points to the need for more complex, multi-stage mechanisms to bridge the gap between green strategy and firm performance – a process explored in the following serial mediation analysis.

Table 7 demonstrates the serial mediation results, providing definitive evidence on the mechanisms through which green strategy (GS) affects firm performance (P). The sequential indirect effect of GS on P through DKM and ERM is positive and significant (β = 0,126, p = 0,019), confirming the proposed serial mediation; this relationship remains robust after the inclusion of control variables. This suggests that GS enhances performance primarily by stimulating the development of DKM processes, which in turn strengthen ERM, ultimately leading to performance improvements.

This finding advances prior sustainability–performance research (Eccles et al., 2012; Endrikat et al., 2014) by specifying the internal organizational mechanism through which this effect operates – a dimension largely absent from existing quantitative studies in this domain. The validated GS → DKM → ERM → P pathway highlights that strategic environmental intent must be channeled through knowledge mobilization and risk management capabilities to generate measurable organizational value. Essentially, green strategy contributes to performance indirectly via a sequential capability-building mechanism triggered by DKM and realized through ERM.

This study demonstrates how DKM and ERM convert green strategy into firm performance. Our empirical findings confirm that a sequential mechanism – operating through risk-related DKM – is the primary pathway through which green strategy (GS) translates into improved performance (P). This highlights the essential role of knowledge mobilization in converting strategic intent into organizational outcomes. Within this framework, ERM functions as the integrative capability that transforms this knowledge foundation into tangible performance effects.

Notably, while green practices (GP) contribute to ERM development, albeit with limited practical effect (f² = 0,046), they do not initiate a chain of influence strong enough to generate comparable performance outcomes on their own. This suggests that while operational initiatives support risk governance, they have a limited role in driving bottom-line results compared to knowledge-based processes. Overall, these results indicate that the relationship between green strategy and performance is complex and nonlinear; its success depends heavily on the synergy between knowledge-based and risk-based organizational capabilities.

Our study offers a substantive theoretical contribution to the discourse on knowledge management and ERM within green strategic management. First, it advances the understanding of DKM by conceptualizing and empirically validating it as a pivotal mechanism linking green strategy to organizational risk management. Specifically, it extends the KBV (Kogut and Zander, 1992; Priem and Butler, 2001) to the sustainability–risk nexus, responding to calls by Hock-Doepgen et al. (2020) and Oliva et al. (2021) for empirical research on the KM–ERM interface. By focusing on internal risk information, these findings specifically enrich the theory of intraorganizational knowledge management (Gomes et al., 2020; Zhang et al., 2020; Oliva and Kotabe, 2019). We demonstrate that managing fragmented, cross-functional risk knowledge – and the interconnections between these domains – is not only critical for enhancing ERM maturity but is also fundamental to enabling effective sustainable business transformation.

Furthermore, we provide evidence of the indirect influence of ERM on firm performance, elucidating the sequential pathway through which DKM contributes to performance within a sustainability-oriented context. This study reframes ERM as a performance-enhancing capability contingent upon upstream knowledge mobilization, extending Castrogiovanni et al. (2016) by specifying the conditions under which ERM’s performance contribution is realized. The large effect size of DKM on ERM (f² = 0,453) confirms this. Knowledge mobilization is not merely a supporting factor. It is the primary organizational lever through which green strategy generates value. By confirming the pivotal role of dispersed knowledge, our results extend prior research emphasizing the importance of knowledge integration for green practices and strategy (Durst and Zieba, 2019). Consequently, this study reinforces and broadens perspectives that position knowledge as a key sustainability driver, demonstrating that its value lies not in its mere existence, but in its mobilization through risk-oriented capabilities. Ultimately, the findings advance the understanding of how sustainability-related knowledge is transformed into competitive performance, highlighting knowledge-based capabilities as essential conduits linking environmental strategy to organizational outcomes (Le, 2022; Lin et al., 2021; Yu et al., 2017).

Our evidence suggests that green strategy improves performance primarily by triggering DKM processes, which then enhance ERM to drive better organizational outcomes. Thus, we infer that a firm’s environmental strategic intent must be translated through knowledge mobilization and risk management capabilities to produce tangible value. We also find a modest but significant direct effect of green strategy on performance. This indicates that beyond mediated pathways, a strategic environmental orientation contributes directly to organizational outcomes, potentially through factors such as reputational capital or brand equity.

A primary recommendation for managerial practice is to recognize that green strategies do not automatically translate into improved performance; instead, they require robust knowledge mobilization processes. Investing in DKM systems that effectively capture and share risk-related environmental information is essential for converting strategic intent into actionable insights. The large effect sizes of this pathway (f² = 0,661 for GS→DKM; f² = 0,453 for DKM→ERM) underscore this point. Investment in knowledge mobilization yields disproportionately greater returns than investment in green practices alone. Equally important is the integration of this knowledge into ERM, which serves as the capability transforming environmental knowledge into performance outcomes. Managers should, therefore, approach environmental capability-building as a sequential process, strengthening DKM foundations to provide the necessary inputs for enhanced ERM practices.

Our results also suggest that relying solely on green practices is insufficient to generate the full sequential influence required for performance, as their contribution is limited to a marginal activation of risk governance. To fully leverage environmental strategies, firms must align their green initiatives with supporting organizational capabilities, fostering cross-functional collaboration between sustainability, risk management and operational units. Ultimately, repositioning ERM as a strategic platform for value creation, rather than a mere compliance tool, helps firms systematically embed green knowledge into decision-making. From a policy standpoint, regulatory frameworks should extend beyond practice-level mandates to incentivize the development of the organizational infrastructure – specifically knowledge systems and risk structures – through which environmental commitment translates into long-term performance.

This study is subject to several limitations. First, the sample was regionally focused on innovative enterprises, which may restrict the generalizability of the findings. Future research should examine different geographical contexts, industries or organizational settings to validate and extend these results. Second, the data were collected through self-reported surveys, which can be prone to response bias. Although we employed rigorous measurement procedures to ensure reliability, future studies could adopt alternative methods – such as longitudinal designs, objective performance metrics or qualitative approaches – to further explore the role of DKM. Expanding the scope of measurement scales and incorporating additional variables will provide a more comprehensive understanding of how knowledge mobilization drives sustainable, risk-informed performance. Third, the cross-sectional design does not allow for causal inference in a strict sense, as temporal precedence between variables cannot be established. While longitudinal data would be more appropriate for testing causal chain models, cross-sectional survey designs are widely adopted in knowledge management and strategic management research (e.g. Naqshbandi et al., 2024). Therefore, although our study cannot definitively establish causality, the cross-sectional approach remains suitable for exploring the relationships among DKM, ERM, green strategy and firm performance. Fourth, the set of control variables included in the structural model was limited to firm size and firm maturity. Future research could incorporate additional controls, such as industry type, firm ownership structure or managerial experience, which may further account for heterogeneity in the sample.

The authors would like to thank the Editor and the anonymous reviewers for their constructive comments and valuable suggestions, which have significantly improved the quality of this paper.