Local embeddedness, technological capability and collaboration as catalysts for circular economy social performance: insights from social embeddedness and network theories

In consensus with global debates, the circular economy (CE), defined as an economic system focused on substituting the concept of “end-of-life” with strategies such as reduction, reuse, recycling, and recovery of materials throughout production, distribution, and consumption processes (Kirchherr et al., 2017), has emerged as one of the most promising approaches for reconciling economic growth with environmental sustainability, drawing growing attention from academics, policymakers, and practitioners alike (Scarpellini, 2022; D'Adamo et al., 2022; Zhang et al., 2026). However, despite the traction, CE scholarship faces a fundamental and largely unresolved issue, in that, the framework that promises systemic transformation has overwhelmingly prioritized environmental and economic outcomes while neglecting the social dimension, especially community-level social development, that is equally central to sustainable development goals (SDGs) (Padilla-Rivera et al., 2020; Liu, 2024). This omission is crucial because if CE is to serve as a genuine pathway toward SDGs, its social dimension cannot remain under-explored. In this regard, the CE's social dimension must be treated as a core performance objective, equally as important as environmental and economic outcomes (Liu, 2024; Baah et al., 2023).

In line with this, scholars are calling for studies that investigate the social dimensions or impacts of CE (Al Haj Eid et al., 2025; Baah et al., 2023; Ghisellini et al., 2016; Mies and Gold, 2021). While scholars have identified a range of potential CE social benefits, including improved living standards, greater social equality, expanded employment opportunities, and enhanced working conditions (Geissdoerfer et al., 2017; Ghisellini et al., 2016), the mechanisms under which firms actually generate these outcomes remain insufficiently understood. Exploring the mechanisms towards CE-related social gains, we argue that local embeddedness is a critical, yet underexplored, antecedent that can facilitate CE social value creation (Nuur, 2026; Lambert et al., 2022). Local embeddedness, defined as a firm's ability to have a deeper understanding of and integration with the local environment (London and Hart, 2004), promotes contextual understanding, local organizational identity, local reputation, and improved competitiveness (Adomako and Tran, 2022; Ng and Feldman, 2014).

According to social embeddedness theory, firms and individuals that are locally embedded gain in-depth local perspectives and ties to their environment, community, or society (McKeever et al., 2014). Such local embeddedness forms the basis for making contextually informed decisions regarding complex social and economic situations (Adomako and Tran, 2024). Local embeddedness further helps firms identify the specific needs of their stakeholders and resolves such issues, thereby enhancing social performance (Amato et al., 2026; Adomako and Tran, 2022). Using firms in Ghana, scholars reveal that local embeddedness significantly influences corporate social performance (Adomako and Tran, 2022). This is because locally embedded firms can identify and understand the social needs of stakeholders within the community, aiding them to engage in practices that respond to stakeholder social needs. However, within the context of CE, current research has not yet thoroughly examined how local embeddedness contributes to CE social performance, specifically, which capabilities are required and the mechanisms through which these result in social outcomes (De Bernardi et al., 2025; Padilla-Rivera et al., 2020). This gap in understanding not only restricts theoretical insights but also leaves practitioners without practical guidance on how to effectively leverage local embeddedness as a strategic tool for creating social value within existing CE frameworks.

This gap is particularly salient among firms in emerging economies, where the challenges are greatest and available insights are limited. Firms, including small and medium-sized enterprises, form the backbone of productive systems in these regions; however, they encounter significant resource constraints that hinder their capacity to independently implement CE initiatives (Baah et al., 2023; Kusi-Sarpong et al., 2019; Mishra et al., 2021). Gaining a clear understanding of how these firms translate local embeddedness into CE social performance and the mechanisms involved, despite resource limitations, is crucial, as this is vital for the development of inclusive and effective CE policies that support achieving social objectives.

To address the above, we utilize network theory alongside social embeddedness theory, highlighting that local embeddedness allows firms to identify social needs and opportunities, while network alliances facilitate the implementation of these initiatives by enabling firms to accumulate external resources to support addressing such CE-related social issues. Specifically, we propose that locally embedded firms develop two strategic capabilities, technological and collaboration capabilities, that function as mechanisms to translate local embeddedness into CE social outcomes. More specifically, the network theory explains that firms expand and access external resource pools through the formation of strategic network alliances (Agyabeng-Mensah et al., 2022; Baah et al., 2023). Such alliances facilitate collaboration, innovation, and the development of technological capabilities, ultimately enhancing overall corporate performance. As well, firms in emerging economies often lack sufficient resources to independently pursue CE practices; therefore, they rely on collaboration capabilities to secure external know-how, resources, and support to achieve CE outcomes (Kusi-Sarpong et al., 2019; Mishra et al., 2021). Consequently, these capabilities are essential pathways toward realizing CE social goals.

By integrating social embeddedness and network theories, we can examine how local embeddedness influences the development of technological and collaboration capabilities, as well as CE social performance. This theoretical integration is essential because while social embeddedness enables firms to understand and learn from their social contexts, identifying knowledge, stakeholder needs, and growth opportunities (Sharafizad et al., 2022), network theory provides firms with the means to acquire external resources that can be leveraged to meet stakeholder needs and capitalize on social opportunities (Baah et al., 2023). Specifically, we argue that through local embeddedness, firms can better understand and respond to the social needs of their stakeholders and communities, thereby enhancing CE social performance. We further contend that, despite resource limitations, firms can rely on their networks to amass resources that foster technological capabilities and embolden collaborative capabilities, which can then be used in ultimately contributing to improved CE social outcomes.

Particularly, we contend that without understanding these mechanisms, CE scholarship risks producing a theoretically insufficient and practically inadequate framework, one that cannot guide firms, especially resource-constrained firms in emerging economies, toward realizing CE's full social transformative potential. Thus, using a sample of 215 survey responses from managers of manufacturing firms, we examined (1) the impact of local embeddedness on CE social performance, collaboration capabilities, and technological capabilities. Additionally, we investigated the mediating roles of (2) technological capabilities and (3) collaboration capabilities in the relationship between local embeddedness and CE social performance, as illustrated in Figure 1. This study makes several contributions to the existing literature. First, it expands the social dimension of community engagement research by providing empirical evidence that local embeddedness significantly influences CE social performance outcomes. Second, by integrating social embeddedness and network theory, we propose that firms embedded within their local communities can better identify key stakeholder needs and opportunities, leveraging their networks to acquire resources and develop capabilities to address these needs and capitalize on market opportunities. Third, by identifying technological and collaboration capabilities as mediating mechanisms, this study unpacks the explanatory mechanisms between local embeddedness and CE social performance, a process-level account that prior CE social research has not provided. Fourth, this study provides empirical insights within an emerging economy, addressing a recognized gap and contributing to the understanding of community engagement in such settings.

The remaining sections of this paper are organized as follows: Section 2 reviews the theoretical background and outlines the hypotheses; Section 3 details the research methodology; Section 4 presents the results; Section 5 discusses the findings, implications for theory and management; and Section 6 presents the conclusion.

Social embeddedness theory, based on the foundational work of Granovetter (1985), suggests that economic activity does not occur in isolation but is inherently influenced by the social relationships, norms, and institutional environments in which firms operate (McKeever et al., 2014). Despite the increasing attention and interest surrounding this theory, it continues to be a source of significant confusion, as some scholars interpret the theory from an individual perspective (Anderson and Miller, 2003; McKeever et al., 2014), while others approach it from an organizational viewpoint (Heidenreich and Mattes, 2012; Rooks et al., 2000; Wang and Altinay, 2012). This study adopts a firm-centric perspective consistent with Heidenreich and Mattes (2012) to posit local embeddedness as a dynamic and mutually constitutive process via which firms and their environments actively interact to shape each other. Here, the more a firm interacts with its environment, the greater its opportunity to obtain local knowledge and share information, a process that can enhance the firm's understanding of stakeholder expectations, potentially fostering a sense of social responsibility (Adomako and Tran, 2022; De Bernardi et al., 2025; Sidorenko et al., 2025). In the context of CE, we argue that local embeddedness promotes the identification and resolution of social issues, thereby boosting CE social performance.

Nonetheless, social embeddedness theory alone is insufficient in accounting for how firms translate their local embeddedness into strategic CE social outcomes, given their resource constraints. Given this background, the network theory emerges as a relevant theoretical lens that addresses this limitation, hence their integration in this study. More specifically, the network theory focusses on how firms leverage relational ties and strategic alliance structures to access external resources and enhance organizational capabilities (Borgatti and Halgin, 2011). The network theory proposes that organizations that actively cultivate network alliances are better positioned to develop collaboration capabilities, facilitating access to external resources and stakeholder integration (Chen and Yu, 2022), as well as technological capabilities, improving technical expertise and driving product and process innovations that support long-term competitiveness (Heredia et al., 2022; Tzokas et al., 2015). These collaborations help overcome resource constraints that might otherwise hinder firms from independently pursuing circular economy initiatives.

While each theory provides valuable insights, their integration is both theoretically necessary and empirically supported. Social embeddedness theory describes how locally embedded firms develop an in-depth understanding of community needs and a sense of social obligation to address them, while network theory functions at the resource and capability level, explaining how firms translate this awareness into action by leveraging alliance structures to build technological and collaborative capabilities. Neither theory alone offers a comprehensive explanation; social embeddedness theory does not address how resource-constrained firms acquire the means to act on local knowledge, and network theory does not clarify what motivates firms to form specific alliances or prioritize capabilities. As such, when combined, these theories form a comprehensive explanatory model, where local embeddedness fosters awareness and intent to address community social needs, while network alliances provide the resources and capabilities necessary to do so, ultimately enhancing social performance in shared CE social value creation (Adomako and Tran, 2022; Baah et al., 2023).

Grounded in the social embeddedness theory, local embeddedness drives firms to invest in the local environments (Sharafizad et al., 2022). This is because as firms integrate into their operating context, they develop a sense of social obligation. This encourages organizations to pursue innovative social initiatives that address significant social challenges, thereby enhancing their corporate social performance (Adomako and Tran, 2022). In particular, companies transitioning toward CE must ensure the availability of trained personnel with the necessary skills to operate systems effectively (Mies and Gold, 2021). By investing in the training and development of such personnel, firms establish mechanisms that substantially contribute to social benefits associated with CE. Furthermore, according to Jabbour et al. (2019), promoting social inclusiveness, creating jobs, and ensuring employee safety during the transition to CE enhances social responsibility and organizational performance, which are key aspects of a sustainable CE implementation. We argue in line with Moreau et al. (2017) that by engaging in CE initiatives based on knowledge and insight generated from local embeddedness, firms generate more substantial responses to societal concerns through the implementation of CE. Specifically, we emphasize that firms must be integrated within their local communities in order to identify, understand, and address social issues that arise in their environment. Additionally, local embeddedness allows firms to assess the expertise, skills, and capabilities of industry personnel, helping to determine when additional training or development programs are necessary, and to create more CE-related employment opportunities for successful CE implementation (Adomako and Tran, 2022). Therefore, we contend that being territorially and socially embedded enables businesses to acquire local knowledge that enhances the ability to develop solutions to social challenges, generate societal value, and improve skills and capabilities to ensure personnel safety. Therefore, we hypothesize that:

Local embeddedness not only enables strong networking behavior in firms, but also promotes technological transfers (Wei, 2015; Jin et al., 2024). This is because firms embedded in local networks can seek and share technological know-how and expertise. Adding to this, Dogbe et al. (2020) highlight that local embeddedness promotes collaborations between local firms and external stakeholders, which further improves the quality of technological innovations and capabilities. Comparing 242 indigenous and multinational manufacturing firms in Canada, Gertler et al. (2000) found that indigenous firms performed better in terms of innovation, technological, and collaboration capabilities due to the firms' local knowledge base and their ability to quickly source innovative ideas as well as resources from local stakeholders such as customers, suppliers, governmental agencies, among others. However, local embeddedness can be a double-edged sword accruing both advantages and disadvantages for firms (Meyer et al., 2011). Here, being locally embedded burdens firms automatically to engage in social initiatives to satisfy network actors whether the resources to do such initiatives are available or not (Kim, 2016). Thus, local embeddedness presents firms with dilemmas, especially when they face significant resource constraints and are also competing for technological know-how and crucial information or knowledge. Consequently, while studies on embeddedness primarily focus on positive outcomes, there are potential negative sides that can equally limit innovation, collaboration, and the development of technological capabilities (Kim, 2016; Kitsos et al., 2023; Meyer et al., 2011). This suggests that local context can considerably impact the quality and extent of collaboration and technological capabilities. Despite the potential drawbacks, we contend that local embeddedness offers many firms a valuable opportunity to acquire and utilize local knowledge, thereby fostering collaboration and enhancing technological capabilities. Therefore, we hypothesize that:

Drawing on the network theory, collaboration capability, defined as the ability to work effectively with network stakeholders to accomplish tasks that achieve collectively shared objectives (Liao et al., 2021), can foster innovation, which in turn leads to improved corporate social outcomes (Baah et al., 2023). The network theory highlights that organizations experiencing resource limitations can establish and utilize strategic alliances to access resource pools that are not available internally (Baah et al., 2023). Additionally, McDonald and Young (2012) emphasize that engaging in partnerships is essential for developing and executing responses to social issues, primarily because it enables the pooling of external support and resources. Through collaborations, firms can draw on partners' strengths and resources to achieve higher social goals. Within the CE context, the deployment of collaboration capabilities by businesses transitioning towards CE business models can promote organizational learning, stakeholder integration, and higher CE performance (Köhler et al., 2022; Mishra et al., 2021). Indeed, collaborating with stakeholders enables CE to tackle employment and urbanization issues, consumption and production concerns, skill development, and technical know-how concerns, ultimately contributing to CE social performance. Ghisellini et al. (2016) add that collaboration in CE facilitates a shared understanding of environmental and social issues, which can be resolved through collective planning and resource sharing. In this regard, developing collaborations can be a conduit for CE to achieve higher social benefits such as equality, financial inclusion, and employment (Lemille, 2019). Primarily, we contend that collaborations established through insights gained from local embeddedness will significantly enable firms to work collaboratively on initiatives that address stakeholder social concerns while strengthening their legitimacy. From the discourse, we hypothesize that:

While technological capability, defined as the effective use of technical knowledge and competencies (Aydin, 2021), has largely been identified as a crucial facilitator of higher environmental performance in CE literature (Antoni et al., 2020; Ahmad, 2014), less is known about how technological capability contributes to social performance. Consistent with network theory's emphasis that firms can develop technological capabilities through strategic alliances and external resource mobilization (Bag et al., 2024), Geissdoerfer et al. (2017) highlight the importance of technological capabilities in achieving sustainable CE business models and solutions. The authors emphasize that the private sector plays a substantial role in achieving CE outcomes since they command diverse technological capabilities needed for higher CE performance. Similarly, Yu et al. (2022), through a study involving 286 respondents in the Chinese automobile industry, emphasize the importance of technological capabilities in advancing environmentally sustainable product design and processes. Additionally, Rahman et al. (2023) showed that a B2B firm's technological readiness and ICT capability support AI-based customer relationship management capability, which also in turn contributes to relationship performance and overall social sustainability performance.

Similarly, we assert that technological capabilities can drive social innovation, which in turn promotes eco-innovation and further supports CE practices (Vence and Pereira, 2019; Al-Emran, 2023). Businesses can leverage technological capabilities and innovative strategies to address social challenges during CE transitions. More specifically, technological capabilities enable firms to engage in social innovation, defined as developing effective, efficient, and sustainable solutions to social issues (Adomako and Tran, 2022; Lee et al., 2019). When companies pursue social innovation, they address social concerns at various levels both within and beyond the organization. In this context, through technological capabilities developed via strategic networks and alliances, firms can advance social innovation, thereby creating key mechanisms that proactively improve social outcomes (Fakhimi and Miremadi, 2022; Satar et al., 2024). Overall, we contend that effectively addressing the social interests of stakeholders, particularly those within circular economy value chains, is best achieved when firms are locally embedded and actively develop networks that enable the acquisition of local insights and the enhancement of technological capabilities for social innovation. Among these factors, technological capability is particularly vital in contributing to the social performance of CE initiatives. We hypothesize that:

Demonstrating its commitment to achieving the SDGs, Ghana is actively promoting transitions toward a CE. Recently, the nation co-chaired the United Nations' SDGs advocacy initiative aimed at fostering transformative and ambitious development both domestically and internationally (Agyabeng-Mensah et al., 2022; Baah et al., 2023; Kwarteng et al., 2022). Ghana has launched its inaugural National Plastic Management Policy and the Global Plastic Action Partnership (GPAP) to support the attainment of SDGs and facilitate CE transitions. These initiatives serve as foundational steps for scholars to investigate CE within this emerging market context. We selected the constructs and measurement items based on a comprehensive review of existing literature, which facilitated the identification of validated measures. By utilizing these empirically supported, well-tested, and contextually appropriate measurement items, we ensure the robustness and rigor of the study. Our outreach to manufacturing firms was guided by three primary selection criteria (Agyabeng-Mensah et al., 2022; Kwarteng et al., 2022): (1) the firm must be involved in the production of tangible goods; (2) it must be engaged in some form of social circular economy initiatives; and (3) complete and accurate contact information must be available. A total of 342 managers of manufacturing firms were initially selected for participation in the study. Following preliminary contact, 310 managers of manufacturing firms consented to participate in the survey. Questionnaires were subsequently distributed to these firms. A total of 261 responses were received from the 310 questionnaires sent out. After further review, 46 responses were excluded due to incomplete data. Consequently, 215 valid responses were obtained corresponding to the variables under investigation, resulting in a response rate of 69%.

A five-point Likert scale, ranging from 1 (Strongly Disagree) to 5 (Strongly Agree), was utilized to assess the constructs based on a comprehensive review of existing literature. Local embeddedness was measured using four items adapted from Adomako and Tran (2022), Ernst et al. (2015), and Halaszovich and Lundan (2016). Collaboration capability was evaluated through four items adapted from Bag and Rahman (2023) and Liao et al. (2021). Technological capability was assessed using four items adapted from Aydin (2021) and Zhou and Wu (2010). Finally, social performance within the context of the circular economy was measured using four items related to social aspects, identified from Mies and Gold (2021) and Padilla-Rivera et al. (2020). The measurement items and their respective factor loadings are presented in Table 1.

In preparing the questionnaire, we followed the guidelines of Podsakoff et al. (2003) to ensure issues of CMB were reduced. Three academics and four managers reviewed the content and language of the reflectively modeled constructs and measurement items. Based on their feedback, the questionnaire was refined to improve conciseness, clarity and ease of understanding. Additionally, Harman's one-factor test indicated no issues of CMB, since it was identified that the single factor explained 40.82% of the total variance below the accepted threshold of 50%. Adding to this, we further examined the variance inflation factors (VIFs) to confirm if CMB was an issue in this study. The results, reported in Table 1, showed that all VIFs were below the recommended threshold of 3.3, suggesting that common method bias was not a serious threat in this study (Kock, 2015). The Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) and Bartlett's Test of Sphericity show the study sample is good for factor analysis since the results indicated acceptable values of 0.900 and p < 0.001, respectively. To further demonstrate that the study does not have issues related to non-response bias, a t-test was conducted, indicating no statistically significant difference between early and late responses.

The largest portion of respondents (28%) are employed in the manufacturing of wood, lumber products, and related activities. This is followed by 24% of respondents involved in the production of food and beverages, 20% engaged in the manufacture of rubber and plastic products, 18% working in leather product processing, and 10% participating in other activities. In terms of job credentials, 31% of individuals identified as business owners, 23% as senior executives, 19% as middle managers, 17% as department heads, and 10% as supervisors. Regarding accumulated employment experience, the largest proportion of respondents (49%) reported having 11–15 years of total work experience, followed by those with 5–10 years (22%), 16–20 years (15%), and less than 5 years (14%). The sample was primarily composed of organizations with between 501 and 1,000 employees (40%), followed by those with between 101 and 500 employees (38%), organizations with fewer than 100 employees (12%), and enterprises exceeding 1,000 employees (10%). Lastly, regarding firm age, 33% of firms had operated for less than 5 years, 34% for 5–10 years, 12% for 11–15 years, 7% for 16–20 years, and 14% for more than 20 years.

Given our reflectively modeled constructs and the predictive nature of the research framework, we utilized variance-based structural equation modeling (VB-SEM), recognized as a robust statistical method for evaluating both reflective and predictive models (Hair et al., 2019). Specifically, we utilized SmartPLS 4 software, a leading PLS software platform, to execute our structural model and evaluate our hypothesized relationships. During the bootstrapping process, we opted for a bias-corrected bootstrap with 10,000 resamples and a two-tailed significance threshold of 0.05.

Following the guidelines of Hair et al. (2011), we assessed the measurement model's reliability and validity through confirmatory factor analysis (CFA) on all items and constructs. The CFA results indicated that all constructs satisfied the necessary criteria for convergent validity (AVEs greater than 0.50), discriminant validity (HTMT ratios below 0.900), composite reliability (CR above 0.70), and internal consistency (Cronbach's Alpha greater than 0.70), as presented in Table 1. The model demonstrates acceptable reliability, with CA and CR values ranging from 0.710 to 0.873.

The assessment of the structural model further demonstrated that both the outer and inner variance inflation factor (VIF) values are below 3, indicating that multicollinearity is not a concern in this study (Henseler et al., 2015). Concerning predictive capacity, assessed through R-squared (R²), the findings demonstrate that the structural model possesses predictive validity, accounting for 31.4%, 55.7%, and 38.5% of the variance in collaboration capability, CE social performance, and technological capability, respectively. Furthermore, the predictive relevance of the model was examined using the PLSpredict/CVPAT procedure, which revealed that the model exhibits predictive relevance, as indicated by Stone-Geisser's Q² values ranging from 30.3% to 42.5%, exceeding the recommended threshold of zero. The average variance extracted (AVE), used to assess convergent validity, was within acceptable limits, ranging from 0.533 to 0.634. Regarding discriminant validity, the HTMT ratio confirms discriminant validity, as all values were below 0.900. The results pertaining to discriminant validity are presented in Table 2.

After verifying that the model meets the criteria for reliability, validity, and predictive accuracy, we proceeded to test the proposed relationships. Regarding direct effects, the results indicate that local embeddedness has a significant and positive impact on CE social performance (β = 0.356, f² = 0.157, t = 5.694), collaboration capability (β = 0.560, f² = 0.457, t = 9.989), and technological capability (β = 0.620, f² = 0.625, t = 14.502). Additionally, collaboration capability significantly influences CE social performance positively (β = 0.255, f² = 0.086, t = 4.000), and technological capability also has a significant effect on CE social performance (β = 0.235, f² = 0.067, t = 3.838). For the indirect effects, a bias-corrected bootstrapping method with 10,000 samples was employed (Hair et al., 2011; Henseler et al., 2015). The results, summarized in Table 3 and Figure 2, demonstrate that both collaboration capability (β = 0.143, t = 3.760) and technological capability (β = 0.145, t = 3.562) function as partial mediators in the relationship between local embeddedness and CE social performance.

Moreover, we controlled for firm industry, firm size, firm age, and accumulated employment experience. The results showed that firm industry had no significant impact on CE social performance (β = −0.011, p = 0.801). Firm size had no significant relationship (β = 0.086, p = 0.050) on CE social performance. Firm age was not significantly associated with CE social performance (β = 0.043, p = 0.381), and employment experience also showed no significant effect (β = 0.017, p = 0.729). Overall, these control variables did not significantly affect CE social performance.

Fundamentally, the study examines how businesses can improve CE social performance through local embeddedness, using knowledge from the social embeddedness theory as well as network theory to build and develop technological and collaboration capabilities. The study further investigates the indirect mechanisms through which technological and collaboration capabilities support obtaining higher CE social performance. Consistent with social embeddedness theory and prior research (Adomako and Tran, 2022; Baù et al., 2019), the findings support Hypothesis 1 (a, b, and c). Specifically, local embeddedness not only enhances commitment to local stakeholders but also facilitates the acquisition of knowledge about social actors and their needs. The results show that as the level of local embeddedness increases, firms become more dedicated to addressing social concerns within their environment and are motivated to improve working conditions, personnel development, and employment opportunities during the adoption and implementation of CE practices. This sense of social responsibility and accountability contributes to improved social performance in CE initiatives (Adomako and Tran, 2022). The consistent and significant results underscore the importance of the local context in achieving higher social performance in circular economy efforts. Importantly, local embeddedness encourages firms to move beyond passive awareness of social issues and actively engage in socially responsible CE practices by acquiring the local knowledge necessary to identify and address stakeholder social concerns (Jabbour et al., 2019; Dogbe et al., 2020). Furthermore, local embeddedness offers a foundation for enhanced collaboration and technological development. This aligns with Gertler et al.’s (2000) assertion that firms with strong local embeddedness exhibit greater innovation and capability growth, as proximity to local stakeholders facilitates better identification and integration of contextually relevant technical and collaborative resources (Baù et al., 2019; Doucet et al., 2025; Sharafizad et al., 2022).

Concerning collaboration capability, the findings suggest that firms that are locally embedded not only directly achieve stronger collaboration capability but also achieve higher CE social performance via the indirect effect of collaboration (Wang and Zhang, 2025; Baah et al., 2023). This finding is further supported by Baah et al. (2023) who argue that collaboration capability leads to higher corporate social outcomes because for firms to be able to collaborate with stakeholders in their social context and amass external resources, these firms need to meet the social requirements of stakeholders. In the same light, we explain that local stakeholders have social demands, which they tend to leverage as requirements for collaborations. Thus, for firms to gain local collaborations and improve networking capabilities, they must meet or respond to the social demands of stakeholders, consequently leading to higher CE social performance.

While the technological capabilities of organizations have been widely studied, there is limited research examining the relationship between these capabilities and social performance. To address this gap, this study explores whether technological capability influences CE social performance. The results indicate that technological capabilities enable companies to develop innovative strategies that positively impact CE social outcomes, supporting findings from Rahman et al. (2023). Likewise, Al-Emran (2023) observed that technological utilization significantly affects social, economic, and environmental performance. We propose that firms with technological capabilities are better equipped to implement safer production processes and monitor overall operations, thereby facilitating the identification of social risks, strengthening accountability and enhancing transparency (Malakar et al., 2025; Mies and Gold, 2021). Specifically, companies can utilize their technological resources to enhance the monitoring and enforcement of labor standards and strengthen social responsibility within their CE initiatives (Al-Emran, 2023; Malakar et al., 2025). In this way, technological capabilities serve as strategic tools that enable organizations to identify and address social concerns, ultimately improving CE social performance.

Furthermore, collaboration and technological capabilities partially mediate the relationship between local embeddedness and CE social performance. The results suggest that technological capabilities support firms in leveraging locally embedded knowledge and networking skills to access resources, expertise, and experience. Adding to this, technological competencies facilitate the deployment of digital tools and initiatives to promote the implementation and sustainability of CE social practices and outcomes. In the context of Ghana, current technologies are primarily focused on ensuring safer production processes and reducing hazards through the adoption of lean production systems (Afum et al., 2023). Moreover, technological skills are employed to innovatively transform locally embedded knowledge and information to achieve social objectives within the CE framework (Fakhimi and Miremadi, 2022; Satar et al., 2024). Generally, collaborative capabilities enable firms to build networks with local stakeholders to access resources, while technological capabilities are utilized to effectively deploy digital tools and leverage local knowledge for circular social initiatives, thereby enhancing overall CE social performance.

This study makes three contributions to the CE literature. First, it extends CE research by providing empirical evidence that embedding within local contexts produces significant social performance outcomes, addressing the limited research on the social implications of CE (Bianchini et al., 2022; Mies and Gold, 2021). Specifically, this contribution advances previous studies by moving beyond the normative acknowledgment of CE's social potential to empirically demonstrate that locally embedded firms in Ghana exhibit notably higher CE social performance. This supports the theoretical perspective that positive social outcomes in CE are not automatically achieved through implementation alone but are realized through integration within local contexts that enable firms to identify and address key social issues.

Second, by integrating social embeddedness and network theories, we propose that firms embedded within their communities can effectively identify critical stakeholder needs and opportunities, subsequently mobilizing resources and developing capabilities through their networks to meet stakeholder demands and capitalize on market opportunities. Consequently, social embeddedness theory enables firms to acquire local knowledge and identify potential collaborators, while network theory provides the mechanisms for leveraging this information to develop and sustain collaboration and technological capabilities that enhance overall CE social performance (Baah et al., 2023; Ike, 2025). We posit and confirm that neither theory alone is sufficient to explain how local embeddedness results in CE social performance. In this sense, their integration provides a more comprehensive approach in advancing both CE social performance literature and the broader body of research on organizational capabilities in emerging economies.

Third, by examining the mediating variables that link local embeddedness to CE social performance, we demonstrate, within the context of an emerging economy, how collaboration and technological capabilities can be employed by firms to generate improved social outcomes in CE, essential mechanisms that past research has not yet examined. This contribution holds particular significance for CE scholarship by reframing technological and collaborative capabilities not only as drivers of environmental or economic performance, as traditionally emphasized in the literature, but as enablers of strategic CE social performance. This perspective opens new theoretical pathways for exploring how firm capabilities can be intentionally developed and directed to achieve social objectives within CE frameworks, especially in resource-constrained emerging economy contexts.

This study offers several valuable insights for managers. First, managers can leverage their embeddedness within their local context to cultivate relationships with key stakeholders, including customers, NGOs, government, and other community organizations, not solely for legitimacy purposes but also as an active knowledge acquisition strategy. Indeed, through these collaborations, firms can acquire critical knowledge about key stakeholders, relevant social issues, and labor concerns, which they can proactively address to improve legitimacy. Additionally, utilizing such contextual insights can help firms to establish and maintain mutually beneficial relationships within their operating context. By so doing, local embeddedness becomes a strategic asset in generating higher long-term CE social outcomes. Secondly, managers must recognize that the collaboration and technological capabilities developed through local engagement are not only essential for achieving economic and environmental objectives but also play a vital role in enhancing social performance. Specifically, these capabilities should be intentionally cultivated with a focus on social outcomes, enabling them to be effectively directed toward addressing social issues within the local community. Additionally, considering the resource constraints commonly encountered by firms in emerging markets, collaborative capabilities can facilitate joint efforts with local partners to address social risks and support the advancement of social innovation.

Third, managers should systematically align organizational strategies with the social and environmental expectations of local stakeholders, integrating these considerations into core strategic planning rather than treating them as secondary obligations. This involves continuously evaluating the local environment, identifying specific stakeholder needs, and developing targeted, evidence-based responses. Such an approach enhances legitimacy, builds stakeholder trust, and sustains CE social performance over time. Equally important is fostering collaboration between managers and policymakers. Local managers possess detailed, on-the-ground knowledge of community social challenges, workforce skill gaps, and barriers to implementing CE social initiatives that policymakers may not directly access. Sharing this knowledge through policy dialog can significantly improve the relevance of CE social policies, enabling policymakers to design more effective interventions, such as subsidies for workforce training aligned with environmental goals, incentives for socially responsible technology adoption, and institutional support mechanisms that promote employee well-being, community development, and operational efficiency. These collaborative partnerships between policy and practice represent a strategically valuable opportunity to enhance CE social performance at both the firm and community levels.

Considering resource constraints faced by firms, especially in emerging economies, this study provides empirical evidence that firms can leverage external resources and technological expertise to overcome limitations in their circular economy social initiatives by strengthening local embeddedness and developing relevant capabilities. While the research offers valuable theoretical and practical insights, certain limitations should be acknowledged for future investigation. Primarily, the findings are specific to the Ghanaian context, which may limit their generalizability to other regions. Future studies could explore different geographic settings to better understand how local embeddedness influences circular economy performance outcomes across diverse environments. Additionally, the reliance on self-reported and perceptual data, along with the cross-sectional research design, may introduce biases. Future research should consider implementing strategies to reduce respondent bias and employ longitudinal approaches to examine the long-term relationships among the variables studied. Finally, future research may explore whether factors such as firm size, industry sector, or firm age influence the relationship between local embeddedness, capability development, and CE social outcomes.

This research contributes to the ongoing discourse regarding the social implications of CE. By applying social embeddedness and network theories, the study investigates whether local embeddedness enhances the social performance of circular economy initiatives and supports the development of collaboration and technological capabilities. Additionally, it examines whether these capabilities mediate the relationship between local embeddedness and social performance within the circular economy. Data collected from 215 managers of manufacturing firms in Ghana, an emerging economy, was analyzed to test a novel conceptual model. The findings indicate that local embeddedness, collaboration, and technological capabilities collectively accounted for 55.7% of the variance in circular economy social performance, after controlling for firm age, industry, size, and employment experience. Empirical results demonstrate that higher levels of local embeddedness significantly and positively influence CE social performance, as well as technological and collaboration capabilities. The study further reveals that both technological and collaboration capabilities serve as key mechanisms through which local embeddedness impacts social performance in circular economy initiatives. These insights suggest that managers can strategically enhance their firms' social contributions by fostering collaboration and technological development. While collaboration allows firms to leverage local partners' resources and strengths to address social issues related to CE, technological capabilities enable the implementation of digital tools and initiatives for monitoring and managing such concerns.