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This study aims to respond to the latest research calls to precisely revisit the nexus between corporate green innovation (CGI) and financial decisions through deeply investigating the mediating effect of corporate environmental performance measured by the effectiveness of emission reduction.

This study analyzes nonfinancial-listed firms on the Australian Securities Exchange from 2002 to 2019 using multiple regression analysis on a panel data set. Initially, different static panel data approaches were used. To account for the potential endogeneity issue and generate robust outcomes, the authors apply the one-step system generalized method of moment, two-stage least squares and lagged model approaches.

The results provide a clear indication that the practices of green innovation can favorably contribute to the level of environmental performance, which in turn affect the firm’s ability in opening the new financial doors and shape solid capital structure. In this context, the effective environmental performance fully mediates the nexus between CGI and capital structure of a firm. More importantly, the outcomes are robust and coherent across different estimation techniques.

The originality of this study lies in its utilization of mediation analysis to explore the relationship between CGI and a firm's financial structure. This approach distinguishes it from previous research by offering a thorough and nuanced understanding of how green innovation practices influence the financing decisions of a firm.

This research has presented a paradigm model to explore the interrelationships among green human resource management practices, green innovation and sustainable performance, demonstrating its suitability within Vietnam's hospitality sector.

The study used a mixed-method approach, detailing the collection and analysis of both qualitative and quantitative data. In-depth interviews were carried out to examine various aspects of green human resource management practices. Following this, PLS-SEM statistical techniques were applied to survey responses to test the proposed hypotheses (N = 574).

This study identified several less common green human resource management practices, such as green job descriptions and analysis, green performance management, green health and safety, green involvement and empowerment and green discipline management that enhance green innovation and sustainable performance. Notably, the study highlighted the significant impact of green discipline management on green innovation and sustainable performance in the Vietnamese context.

The study emphasizes that hotel managers in Vietnam should recognize the crucial role of green innovation in effectively implementing green initiatives, as it is a key driver of sustainable performance in hotels.

This study developed a unique framework highlighting green innovation's mediating role. It demonstrates the relationships between green HR practices and environmental, economic and social performance, offering practical insights for hotel and business managers.

In view of the significance of intangible organizational resources and firm sustainability, this study investigates the mediating role of ambidextrous green innovation and the moderating effects of resource orchestration capability in the relationship between green entrepreneurial orientation and green performance.

The research employed a quantitative analysis technique using hierarchical linear regression and a moderated mediation approach on a sample of 409 managers from UAE manufacturing firms to investigate the proposed relationships among the variables.

The research results show that a firm’s green performance is influenced by its green entrepreneurial orientation. Green innovation, both exploratory and exploitative, mediates the link between green entrepreneurial orientation and green performance. Moreover, the association between green entrepreneurial orientation and exploitative green innovation, as well as between exploitative green innovation and a firm's green performance, is strengthened by resource orchestration capability. The findings of the moderated mediation show that when resource orchestration capacity is high, exploitative green innovation has a greater mediating effect on green entrepreneurial orientation and green performance.

This study provides valuable insights for manufacturing firms to achieve sustainable performance and reduce their environmental impact. Firms should adopt proactive environmental strategies and innovative approaches to achieve sustainable green performance by adopting green entrepreneurship and establishing ambidextrous green innovation.

This study contributes to the literature on GEO, ambidextrous green innovation, resource orchestration capability, and green performance. These results provide insight into fostering green innovation in the manufacturing industry, deepen the theoretical foundation for green entrepreneurship, and advance the field of green entrepreneurship study.

This study attempts to explore the linkages between reliable big and cloud data analytics capabilities (RB&CDACs) and the comparative advantage (CA) that applies in the manufacturing sector in the countries located in North Africa (NA). These are considered developing countries through generating green product innovation (GPI) and using green process innovations (GPrLs) in their processes and functions as mediating factors, as well as the moderating role of data-driven competitive sustainability (DDCS).

To achieve the aim of this study, 346 useable surveys out of 1,601 were analyzed, and valid responses were retrieved for analysis, representing a 21.6% response rate by applying the quantitative methodology for collecting primary data. Convergent validity and discriminant validity tests were applied to structural equation modeling (SEM) in the CB-covariance-based structural equation modeling (SEM) program, and the data reliability was confirmed. Additionally, a multivariate analysis technique was used via CB-SEM, as hypothesized relationships were evaluated through confirmatory factor analysis (CFA), and then the hypotheses were tested through a structural model. Further, a bootstrapping technique was used to analyze the data. We included GPI and GPrI as mediating factors, while using DDCS as a moderated factor.

The empirical findings indicated that the proposed moderated-mediation model was accepted due to the relationships between the constructs being statistically significant. Further, the findings showed that there is a significant positive effect in the relationship between reliable BCDA capabilities and CAs as well as a mediating effect of GPI and GPrI, which is supported by the proposed formulated hypothesis. Additionally, the findings confirmed that there is a moderating effect represented by data-driven competitive advantage suitability between GPI, GPrI and CA.

One of the main limitations of this study is that an applied cross-sectional study provides a snapshot at a given moment in time. Furthermore, it used only one type of methodological approach (i.e. quantitative) rather than using mixed methods to reach more accurate data.

This study developed a theoretical model that is obtained from reliable BCDA capabilities, CA, DDCS, green innovation and GPrI. Thus, this piece of work bridges the existing research gap in the literature by testing the moderated-mediation model with a focus on the manufacturing sector that benefits from big data analytics capabilities to improve levels of GPI and competitive advantage. Finally, this study is considered a road map and gaudiness for the importance of applying these factors, which offers new valuable information and findings for managers, practitioners and decision-makers in the manufacturing sector in the NA region.

This study aims to find the key drivers of green innovation in family firms by examining firm characteristics and geographical factors. It seeks to develop a conceptual framework that explains how internal resources and external environments influence environmental innovation practices in these businesses.

Using machine learning (ML) methods, this study develops a predictive model for green innovation in family firms, drawing on data from 3,289 family businesses across 27 EU Member States and 12 additional countries. The study integrates the Resource-Based View (RBV) and Location Theory to analyze the impact of firm-level resources and geographical contexts on green innovation outcomes.

The results show that both firm-specific resources, such as size, digital capabilities, years of operation and geographical factors, like country location, significantly influence the likelihood of family firms engaging in environmental innovation. Larger, technologically advanced firms are more likely to adopt sustainable practices, and geographic location is crucial due to different regulatory environments and market conditions.

The findings reinforce the RBV by showing the importance of firm-specific resources in driving green innovation and extend Location Theory by emphasizing the role of geographic factors. The study enriches the theoretical understanding of family businesses by showing how noneconomic goals, such as socioemotional wealth and legacy preservation, influence environmental innovation strategies.

Family firms can leverage these findings to enhance their green innovation efforts by investing in technology, fostering sustainability and recognizing the impact of geographic factors. Aligning innovation strategies with both economic and noneconomic goals can help family businesses improve market positioning, comply with regulations and maintain a strong family legacy.

This research contributes a new perspective by integrating the RBV and Location Theory to explore green innovation in family firms, highlighting the interplay between internal resources and external environments. It also shows the effectiveness of machine learning methods in predicting environmental innovation, providing deeper insights than traditional statistical techniques.

The study aims to build upon the Resource-based view of the firm (RBV) and Dynamic Capability Theory (DCT) to perform a meta-analysis on the eco-innovation/SMEs’ sustainable performance relationship.

Employing a psychometric meta-analytic approach with a random-effects model, the study examines a sample of 134,841 SMEs covering 99 studies and 233 study effects. Subgroup and meta-regression analysis were used to test the study`s hypotheses in Comprehensive Meta-Analysis (CMA) statistical software.

Results unveil that the average impact of eco-innovation on SMEs` sustainable performance is positively significant but moderate. Moreover, it was found that eco-process, eco-product, eco-organizational, and eco-marketing innovations positively influence SMEs’ sustainable performance, but the impact of eco-organizational innovation is the strongest. Findings further reveal that eco-innovation positively influences economic, social, and environmental performance, but its effect on social performance is the largest. Moreover, our findings reveal that contextual factors, including industry type, culture, industry intensity, global sustainable competitive index, and human development index, moderate the eco-innovation/SMEs’ sustainable performance relationship. Lastly, methodological factors, namely sampling technique, study type, and publication status, account for study-study variance.

Our findings imply that investing in eco-innovation is worthwhile for SMEs. Therefore, CEOs/managers of SMEs must adopt eco-innovation initiatives by establishing a sustainability vision, developing employee environmental development and training, building a stakeholder management system, and promoting employee engagement in sustainability activities.

The study develops a holistic conceptual framework to consolidate the distinct types of eco-innovation and their association with the sustainable performance of SMEs for the first time in this research stream, thereby resolving the anecdotal results and synthesizing the fragmented literature across culture, discipline, and contexts.

The present research aims to analyze the influence of Green Supply Chain Management (GSCM) on the Sustainable Performance (SP) of Spanish wineries, examining the intermediary roles of Circular Economy Capability (CEC) and Green Ambidexterity Innovation (GAI) within this primary relationship. In particular, the study seeks to answer the following Research Questions (RQs): (RQ1), does GSCM exert a positive impact on wineries’ SP? (RQ2), does CEC play a mediating role in the interconnection between GSCM and wineries’ SP? And (RQ3), does GAI function as a mediator in the interplay between GSCM and wineries’ SP?

The research utilizes Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate the hypothesized theoretical model using primary data collected from 196 Spanish wineries from September 2022 to January 2023.

The results reveal a positive relationship between GSCM and SP in Spanish wineries, as well as the existence of positive partial mediations of CEC and GAI in this main linkage, which allows an affirmative answer to the three RQs formulated.

Distinguished by its innovative exploration, this research marks a pioneering effort in the uncharted field of scrutinizing CEC and GAI as mediating factors in the GSCM-SP nexus, thereby enriching the existing body of knowledge and opening new avenues for future academic research on sustainability in the wine industry.

Green entrepreneurship (GE) is a novel concept in business and enhances environmentally friendly production and operation activities for “sustainable development” (SD). The aim of this study is to determine the drivers that contribute to the growth and success of “micro, small, and medium enterprises” (MSMEs) in the manufacturing sector in India. The study also examines the mutual and cause-and-effect relationships among these identified drivers.

The study used integrated research methodology and identified nine key drivers of GE (GEDs) through extensive literature reviews, theoretical perspectives (i.e. “resource-based view” (RBV), “natural resource-based view” (NRBV) and “critical success factor theory” (CSFT)), and expert opinions. Further, “total interpretive structural modeling” (TISM) and “matrice d'impacts croisés multiplication appliquée á un classment” (MICMAC) analysis are used here to develop a hierarchical model and cluster the drivers, and fuzzy “decision-making trial and evaluation laboratory” (fuzzy-DEMATEL) is used to develop causal relationships among the drivers. Further, a sensitivity analysis is conducted to ensure the robustness of the results.

Results indicated that green manufacturing and operation capability development, green business process management and attitudes toward developing sustainable business models significantly impacted GE and SD. The findings of this study help managers, policymakers, and practitioners gain an in-depth understanding of the drivers of GE.

The study considers a limited number of drivers and is specific to Indian manufacturing MSMEs only. Further, a limited number of experts from different enterprises are considered for data analysis. This study is also based on interrelationships and their relative importance based on multicriteria decision-making techniques. This study aids government decision-making, policy formulation and strategic decision-making for manufacturing businesses in achieving SD goals. In addition, this research also encourages green entrepreneurs to start eco-driven companies and facilitate the use of environmentally friendly goods to offset environmental challenges and accomplish sustainable development goals.

This study proposes an integrated methodology that will benefit managers, practitioners and others in developing strategies and innovations to improve and develop green practices. This study further helps with responsive, sustainable business development in various manufacturing MSMEs.

This study examines green absorptive capacity as an important intervening variable that elucidates the relationship between green supply chain management (GSCM) practices (specifically, green purchasing, customer cooperation and investment recovery) and firm performance.

Drawing from the theoretical underpinnings of the natural-resource-based view theory and information processing theory, a research model is developed and tested using data obtained from 368 manufacturing firms in Ghana. Data analysis was conducted using structural equation modeling.

The results indicate that green purchasing, customer cooperation and investment recovery have a direct positive and significant effect on firm performance. Additionally, green purchasing and customer cooperation have a positive and significant effect on green absorptive capacity but investment recovery does not. Further, the results show that the paths from green purchasing and customer cooperation to firm performance are positively mediated by green absorptive capacity.

The study reveals to supply chain managers that green absorptive capacity is an important conduit through which firms can achieve enhanced firm performance from GSCM initiatives.

This study makes a contribution by integrating the absorptive capacity literature and green management literature and establishes green absorptive capacity as a mechanism through which GSCM practices enhance firm performance.

Drawing an inference from institutional theory and dynamic capabilities view, this study empirically examined the impact of three institutional dimensions (regulative, normative and cognitive) and green entrepreneurial orientation (GEO) on a business firm’s performance. In addition, the moderating effect of dynamic capabilities on the relationship between GEO and firm performance was also explored.

The data were collected from 527 information technology (IT) firms in Pakistan using paper–pencil questionnaires, and the hypotheses were tested using structural equation modeling.

The findings showed that the regulative and normative institutional dimensions enhance GEO and firm performance in the selected developing country. However, the cognitive institutional dimension fails to report any substantial influence on GEO and firm performance. The findings raised concerns about lower individual accountability as well as the promotion of green practices and firm performance. In addition, dynamic capabilities positively moderate the GEO influence on firm performance.

With the interplay of institutional dimensions, GEO (as mediator) and dynamic capabilities (as moderator), this study developed and tested a unique framework to understand their influence on firm performance. Specifically, we extended the literature by giving evidence that among the three institutional dimensions, only regulative and normative are considered more important because of their direct and indirect (through GEO) positive effect on firm performance. In contrast, the cognitive institutional dimension failed to report any significant direct or indirect impact on firm performance in our study.