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This study is the first to examine how big data analytics (BDA) capabilities affect green absorptive capacity (GAC) and green entrepreneurship orientation (GEO). It uses the dynamic capability view, BDA and knowledge-sharing literature. There is a lack of studies addressing the BDA–GAC and BDA–GEO relationships and their potential impact on green innovation. Continuing the ongoing research discussion, a few studies examined the vital implications of knowledge sharing (KS) on GAC, GEO and green innovation.

The study used a cross-sectional and stratified random sampling technique to collect data through self-administered surveys among Chinese manufacturing firm employees. The study applied SmartPLS to analyze the obtained data.

The findings revealed that BDA capabilities positively influence GAC and GEO. In addition, GEO and KS positively impact green innovation. The KS recorded a positive impact on GAC and GEO. Furthermore, GAC and GEO recorded a partial mediating effect.

The study acknowledges that GAC is the backbone of a firm green entrepreneurial orientation, which needs to be aligned with BDA capabilities to anticipate future green business trends. GAC's help drives GEO's green business agenda. KS plays a strategic role in developing GAC, fostering GEO and improving green innovation.

The study highlights the necessity of aligning BDA capabilities to fit firms' GEO green business agendas. This study focuses on the role of BDA capabilities in developing firms' green dynamics capabilities (e.g. GAC), which helps GEO drive superior green business growth. KS develops GAC and boosts GEO to enhance green innovation.

The purpose of this paper is to evaluate key criteria underpinning network-facilitated green innovation capability development in micro-firms.

Micro-firms, those firms with less than ten full-time employees, need to continuously innovate in order to sustain their business in the emerging green economy. This study uses an interpretive multiple case approach to explore micro-firm owner-manager (O/M) green innovation activities, encompassing O/M views on facilitated network engagement in Ireland and Canada over a 12-month period.

The findings show that proactive implementation of green innovation is influenced by the O/M’s natural environment orientation and the potential for economic gain, while facilitated networks provide an additional resource that the O/M can draw from that allows the O/M to test new ideas, comprehend new and existing legislation and identify potential supports in pursuit of green innovation capability development within the micro-firm.

This study offers a contribution to knowledge in the areas of green innovation, micro-firm capabilities and facilitated network engagement. However, the sample size is small and distance was a challenge, yet data and case protocols are in place which allow for replication of the study. As the research is embedded in the resource and capability theories, alternative theoretical frameworks may shed a different light on the research question.

Prior studies have found that facilitated networks have a positive impact on micro-firm sustainability as these networks enhance the firm’s constrained resource base. The proposed framework can be used as a guideline for support organisations including facilitated networks in assisting micro-firms in reaching their green innovation goals and objectives. It can also be used by micro-firms in the attainment of the green innovation capability.

The purpose of this paper is to investigate the relationship between firms’ life cycle stages (mature vs growth) and green process innovation performance. In addition, this research delineates the mechanism by which the mature stage firms are more strongly associated with green process innovation performance compared to growth stage firms and recognizes technological capabilities as a mediating variable fundamental to achieve a higher level of green process innovation performance.

This research collected data from 202 publicly listed Thai manufacturing firms. Initially, it used multiple regression analysis to test the relationship between mature stage firms and green process innovation performance compared to the relationship between growth stage firms and green process innovation performance. Later, this research followed Muller et al. (2005) to test the mediating role of technological capabilities and conducted (Sobel, 1982, 1986; Preacher and Hayes, 2004) tests to further validate the mediation effect.

The hypothesized relationships were found to be significant, providing a strong support that mature stage firms have higher green process innovation performance compared with growth stage firms. Moreover, the technological capabilities more strongly mediate the relationship between mature stage firms and green process innovation performance compared to growth stage firms and green process innovation performance.

This research contributes to the existing understanding about the internal drivers of green process innovation performance by incorporating and analyzing the firms’ life cycle stages as an internal driver. This research also contributes by empirically testing the mediating role of technological capabilities on the relationship between firms’ life cycle stages and green process innovation performance.

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.

The purpose of this study is to examine the influence of green technology innovation on sustainability performance with the moderating effect of innovation capabilities in the Malaysian manufacturing listed companies.

This was a quantitative study and carried out by applying a research survey. The questionnaire was used to collect the data from 204 Malaysian manufacturing companies of the “consumer products and services” sector listed at Bursa Malaysia, incorporating a five-point Likert scale. All the hypothesized relationships were tested by using the partial least square structural equation modeling (PLS-SEM).

The empirical results showed that the comprehensive adoption of green technology innovation significantly promotes sustainability performance including economic, environmental and social performance. In addition, innovation capabilities significantly and positively moderate the relationship between green technology innovation and sustainability performance.

The scope of this study is specifically confined to the Malaysian manufacturing listed companies, operating within the consumer products and services sector listed at Bursa Malaysia. Consequently, the findings of this study may not be generalized to manufacturing companies of the different geographical contexts.

The findings of this study may help the top management and policymakers of the Malaysian manufacturing listed companies to scrutinize green technology innovation and innovation capabilities to achieve higher sustainability performance.

This study magnifies and provides new insights into the extant literature by developing a comprehensive research model that concurrently tests the direct and moderation effects between green technology innovation, innovation capabilities and sustainability performance. Additionally, this is the first study to examine the influence of green technology innovation on sustainability performance with the moderating effect of innovation capabilities in the Malaysian manufacturing listed companies. This distinct approach significantly bolsters the originality of this study.

This study investigates the impact of big data analytics capabilities on green supply chain performance. Moreover, it assesses the mediating effect of the green innovation and moderating effect of technological intensity.

This study is based on primary data that were collected from the food and beverages manufacturing sector operating in Jordan. A total of 420 samples were used for the final data analysis. Data analysis was performed via structural equation modeling (SEM) using SmartPLS 3.3.9.

The results of the data analysis supported a positive relationship between big data analytics capabilities and the green supply chain performance as well as a mediating effect of green innovation. It was confirmed that technological intensity moderated the relationship of green innovation on green supply chain performance.

The study faced many limitations such as the method of collecting primary data, which relied on a questionnaire only and the use of cross-sectional data, as well as studying one context and in one country.

The findings can guide managers and policymakers in the Jordanian food and beverage manufacturing sector on how to manage organizational capabilities related to big data analytics to enhance green supply chain performance and improve green innovation in these firms.

This study developed a theoretical and empirical model to investigate the relationship between big data analytics capabilities, green innovation, technological intensity and green supply chain performance. This study offers new theoretical and managerial contributions that add value to the supply chain management and innovation literature by testing the moderated mediation model of these constructs in the food and beverages manufacturing sector in Jordan.

Green innovation in supply chains is crucial for socioeconomic development and stability. Factors that influence collaborative green innovation in the supply chain are complex and diverse. Exploring the main influencing factors and their mechanisms is essential for promoting collaborative green innovation in supply chains. Therefore, this study analyzes how upstream and downstream enterprises in the supply chain collaborate to develop green technological innovations, thereby providing a theoretical basis for improving the overall efficiency of the supply chain and advancing green innovation technology.

Based on evolutionary game theory, this study divides operational scenarios into pure market and government-regulated operations, thereby constructing collaborative green innovation relationships in different scenarios. Through evolutionary analysis of various entities in different operational scenarios, combined with numerical simulation analysis, we compared the evolutionary stability of collaborative green innovation behavior in supply chains with and without government regulation.

Under pure market mechanisms, the higher the green innovation capability, the stronger the willingness of various entities to collaborate in green innovation. However, under government regulation, a decrease in green innovation capability increases the willingness to collaborate with various entities. Environmental tax rates and green subsidy levels promote collaborative innovation in the short term but inhibit collaborative innovation in the long term, indicating that policy orientation has a short-term impact. Additionally, the greater the penalty for collaborative innovation breaches, the stronger the intention to engage in collaborative green innovation in the supply chain.

We introduce the factors influencing green innovation capability and social benefits in the study of the innovation behavior of upstream and downstream enterprises, expanding the research field of collaborative innovation in the supply chain. By comparing the collaborative innovation behavior of various entities in the supply chain under a pure market scenario and government regulations, this study provides a new perspective for analyzing the impact of corresponding government policies on the green innovation capability of upstream and downstream enterprises, enriching theoretical research on green innovation in the supply chain to some extent.

Adopting an EU policy lens, this chapter primarily addresses the proposed pivotal role of firm-level innovation capability (FLIC) in small and medium-sized enterprises (SMEs) as a stimulant of sustainable development (SD) and green growth in Ireland/Wales. The chapter specifically examines the scale and scope of the green economy (GE), and considers the importance of organizational inherent “green” innovation capabilities (GICs) to achieve it. Underpinning the study is the methodology and concept of utilizing a facilitated cross-border multi-stakeholder learning network to enable knowledge transfer and exchange practices to flourish between partners, acting as a significant predictor of the development of SME GICs structures. Specifically, against the backdrop of the Green Innovation and Future Technologies (“GIFT” hereafter) INTERREG 4A Project, the research assesses how academic–industry partner exchange and inter-group learning and cooperation facilitates the development of GICs in smaller enterprises to realize a sustainable smart green economy in Ireland.

This research aims to explore the concept of green dynamic capabilities, which can facilitate the adoption of green technological innovations for the purpose of enhancing brand sustainability. Specifically, the study seeks to investigate the mediating role of green technological innovations in the relationship between green dynamic capabilities and brand sustainability.

To achieve this aim, the study employed partial least squares structural equation modeling (PLS-SEM) and surveyed 316 managers of manufacturing enterprises.

The results showed that all relationships tested were positive and significant, and green technological innovation was found to be a significant mediator in the relationship between green dynamic capabilities and brand sustainability.

By adding a mediating variable (green technological innovations), this study adds to the literature on sustainability as well as contributes to the on-going debate on how manufacturing firms can be related to environmental issues in their productions.

Green innovation strategy is not only a new idea to achieve green development but also the inevitable choice for enterprises to upgrade. At present, the research on the driving forces of green innovation strategy mainly focus on direct impact of single factor, lacking the overall consideration of internal and external environment. At the same time, research on the contingency effect of top management’s environmental awareness is scarce. This paper aims to explore how external environment pressures (policy pressures and market pressures) and internal environment driving force (innovation resources and innovation capability) make enterprises to choose green innovation strategy with moderating effect of top management’s environmental awareness.

Based on the sample of 216 enterprises, this paper explores the relationship between policy pressure, market pressure, innovation resources, innovation capability and the green innovation strategy with moderating effect of top management’s environmental awareness from inside and outside driving angle.

The results of the hierarchical regression model show, first, the driving effect of factors in the external environment. The coercive policy has an inverted U-shaped impact on the green innovation strategy. The incentive policy and the market pressure both have a significant positive impact on the green innovation strategy. Second, the driving effect of factors in the internal environment. The innovation capability has a significant positive impact on the green innovation strategy. The innovation resources have no significant impact on the green innovation strategy. Third, the moderating effect of top management’s environmental awareness. The relationship between the green innovation strategy and the coercive policy is stronger when the top management’s environmental awareness higher. The relationship between the green innovation strategy and the market pressure is stronger when the top management’s environmental awareness higher. The relationship between the green innovation strategy and the innovation resources is stronger when the top management’s environmental awareness higher. Otherwise, the relationship between the green innovation strategy and the innovation capability is weaker when the top management’s environmental awareness higher. And there is no significant change about the relationship between the green innovation strategy and the incentive policy when the top management’s environmental awareness higher.

First, the authors have promoted the integrated research on the drivers of the enterprise’s green innovation strategy. From the perspective of internal and external environment driving forces, this paper analyzes the key factors influencing the decision-making of the green innovation strategy. Second, the study has contributed to the strategic choice theory. This paper studies the driving mechanism of the green innovation strategy from a new perspective of the strategic choice theory.