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The aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.

Fuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.

Digital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.

This study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.

This paper aims to explore the impact of green finance on the heterogeneity of enterprise green technology innovation and the underlying mechanism between them.

Using the data of China's A-share listed enterprises from 2008 to 2020 and the fixed effect model, the authors empirically explore the relationship and mechanism between green finance and green technology innovation by constructing the green finance index while considering both the quality and quantity of innovation.

The study suggests that green finance is positively related to the quality and quantity of enterprise green technology innovation, while green finance is more effective in stimulating the quality of green technology innovation than quantity. In addition, alleviating financial mismatch and improving the quality of environmental information disclosure are core mechanisms during the process of green finance facilitating green technology innovation. Furthermore, green finance exerts a more positive effect on the quality and quantity of green technology innovation with large-size enterprises, heavily polluting industries and enterprises in the eastern region.

This paper enriches the literature on green finance and green technology innovation and provides practical significance for green finance implementation.

The green innovation behavior of construction enterprises is the key to reducing the construction industry's carbon emissions and realizing the green transformation of the construction industry. The purpose of this study is to reveal the evolutionary mechanism of green innovation behavior in construction enterprises.

This study is based on resource-based theory, Porter's hypothesis and signaling theory. First, a measurement model of the green innovation behavior of construction enterprises was constructed from three aspects: environmental regulation, enterprise resources and public opinion through hierarchical analysis. Then, the state values of the measurement model of green innovation behavior of construction enterprises were calculated through the time series data from 2011–2018. Finally, the Markov chain model was used to predict the evolutionary trend of green innovation behavior of construction enterprises, and the accuracy of the prediction effect of the Markov chain model was verified using the time series data of 2019.

The Markov chain model of green innovation behavior of construction enterprises constructed in this study has high accuracy. This model finds that the transition of the growth state of green innovation behavior in China's construction industry is fluid and predicts the evolution trend of the innovation behavior of construction enterprises. In the future, the green innovation behavior of construction enterprises has a probability of 70.17% to be in a continuous growth state and 40.27% to be in a rapid growth state.

Based on the Markov chain model of green innovation behavior of construction enterprises, this study finds that the transition of the growth state of green innovation behavior of construction enterprises in China has the characteristics of liquidity. In addition, it reveals the development process of the green innovation behavior of construction enterprises from 2011–2018 and predicts the evolution trend of the green innovation behavior of construction enterprises.

Drawing on the “Resource- Capability – Competitive advantage” framework within Natural Resource-Based View, this study is purposed to address problems of manufacturing companies “turning into the green” issues, providing references for manufacturing companies to achieve green competitive advantage via internal motivation and identity perspectives.

This study collected survey data from 112 Chinese manufacturing listed enterprises from the Shanghai Stock Exchange, and obtained 418 questionnaires. Following an empirical design, hierarchical regression analysis and Bootstrapping analysis were applied to examine these hypotheses.

Results show that green innovation behaviors positively mediate the positive relationship between organizational environmental identity and green competitive advantage. Furthermore, slack resource not only positively moderates the interaction effect between organizational environmental identity and green product innovation behaviors, but also moderates the mediation role of green product innovation behavior in the main effect.

The study is limited to the data samples and dynamic evolution between variables. More longitudinal designs and diverse enterprise fields will be considered in future.

The findings provide guidance for manufacturing enterprises to gain green competitive advantage in green manufacturing era from identity value origins. Moreover, the results provide practical suggestions for manufacturing enterprises to enhance green innovation behaviors and integrate useful but slack resources.

The findings provide implications for manufacturing industry to increase both the awareness of organizational environmental identity and green innovation behaviors, all of which helps promote the corporate environmental responsibility.

The study breaks the limitation of the existing literature which focuses on the influence of external push factors (e.g. environmental regulation), and bring new visions in constructing green competitive advantage in green manufacturing era, not only extending the identity theory and upper echelon theory, but also enriching the current studies on green management. Also, these findings provide deeper and new insights into risks and uncertain features of green manufacturing era, analyzing how polluted manufacturing enterprises obtain green competitive advantages through the mediating role of green innovation behaviors and the moderating role of slack resource.

The purpose of this paper is to develop a collaborative agent-based web architecture and an agent-based green IS assessment tool to aid information technology (IT) practitioners in data centers assess their current green information systems (IS) practice toward attaining sustainability.

The methodology comprises that the collaborative agent-based web architecture, agents’ algorithm and the green IS assessment tool, which is validated by employing focus group questionnaire targeting IT practitioners in seven Malaysian-based enterprises that have an in-house data centers. With 105 valid samples at hand, descriptive analysis and exploratory factor analysis was utilized to determine the applicability of the implemented agent-based green IS assessment tool.

Findings reveal that the agent-based green IS assessment tool possesses the capability to evaluate benchmark and rate enterprise data centers current green IS practice. Additional findings indicate that the agent-based green IS assessment tool provide suggestions on how green IS practice can be improved in enterprise data centers.

This study only collected data from 105 IT practitioners in enterprise data centers based in Malaysia; as such results from this research cannot be generalized to other countries. Moreover, the developed collaborative agents for green IS practice assessment can only be fully deployed after domain experts has added green IS practice assessment questions and alternative answers.

This study presents an autonomous agent-based green IS assessment tool that supports the assessment of enterprise toward inclusion of sustainability considerations to enhance enterprise environmental performance.

This study provides empirical evidence for data centers efficacy leading toward a greener society for environmental conservation for future generations to come.

This study creates awareness by presenting the green IS practice to be implemented by IT practitioners in data centers. In addition, the agent-based green IS assessment tool provides a web-based platform for promoting environmental sustainability by supporting data centers toward evaluating, benchmarking and rating their current green IS practices.

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.

The purpose of this study is to explore how digital construction policy (DCP) drives enterprise green innovation (EGI) from an information processing theory (IPT) perspective, including the mediating mechanisms of market information accessibility and operational risk, the moderating role of intellectual property protection (IPP) and product market competition (PMC) and the heterogeneous effects of ownership, Internet development and managerial ability.

Based on the matched panel data of A-share listed enterprises from 2011 to 2019 and the Broadband China policy as a quasinatural experiment, this study investigates the impact of DCP on EGI by constructing a multi-time point difference-indifferences (DID) model.

Digital construction policies can significantly promote EGI. DCP works in two fundamental ways, namely by increasing market information accessibility and reducing operational risk. IPP and PMC significantly increased the contribution of digital construction policies to EGI. Heterogeneity analysis found that digital technology has a stronger promotion effect for SOEs, high-managerial-ability enterprises and enterprises in regions with low Internet development levels.

The study provides new insights about the antecedents of EGI from a DCP perspective. It also enlightens emerging economies to actualize green innovation under the digital wave.

From the perspective of IPT, this study explains the mechanism of DCP-driven EGI. It enhances understanding of the relationship between DCP and EGI.

Toward sustainable development, radical green innovation (RGI) is necessary. Despite extensive research on the factors influencing green innovation, few studies have been conducted on the precursors. Based on upper echelons (UE) theory, dynamic capability (DC) theory, “stimulus-organism-response” (SOR) theory, social information processing (SIP) theory and cognitive appraisal (CA) theory of emotion, the study explores how digital leadership (DL) affects RGI and investigates the mediating effects of green organizational identity (GOI) and the moderating effects of digital threat (DT) and technology for social good (TSG), as well as the multiple concurrent causalities that trigger high RGI.

The method of combining structural equation model (SEM) and fuzzy-set qualitative comparative analysis (fs QCA) is adopted in the study. Data from 233 questionnaires were collected at two different time points.

This study's findings indicate that the four dimensions of DL can positively influence RGI and GOI partially mediates between the four dimensions of DL and RGI. DT has a negative moderating effect between DL and GOI, while TSG is positively regulated between them, DT and TSG linkage moderates the partial mediating effect of GOI in DL and RGI. Further, fs QCA is used to analyze the causal complexity of DL dimensions and GOI to RGI and nine effective configuration paths are identified. It is found that the synergy of digital thinking ability (DTA), digital detection ability (DDA), digital social ability (DSA), digital reserve ability (DRA) and GOI is crucial to high RGI. Among them, GOI core appears the most times, indicating that GOI plays a vital role in improving enterprise RGI.

This study expands the literature on leadership and innovation by constructing a framework of “DL-GOI-RGI” and exploring the transmission of GOI and the boundary effect of DT and TSG. The study used fs QCA and SEM to better understand the statistical associations and the set relations between the conjunctions and conditions.

As an effective tool to promote rational resource allocation and facilitate the development of green management practices such as enterprise digital innovation, the green credit policy has recently gained extensive attention. The purpose of this paper is to analyze the relationship between green credit policies and the digital innovation of enterprises, and to further explore the mechanism of action between them and their boundary conditions.

Based on micro-level data on Chinese firms from 2007 to 2019, this paper constructs a difference-in-differences (DID) model to investigate the impact and intrinsic mechanisms of green credit policies on firms' digital innovation and its boundary conditions, with the help of a quasi-natural experiment, i.e. the Green Credit Guidelines.

Green credit policies inhibit digital innovation and fail to compensate for innovation. The analysis of the mechanism shows that the implementation of green credit policies has a negative impact on digital innovation by increasing the financing constraints faced by firms, and has also a crowding-out effect on R&D investment, resulting in a disincentive to digital innovation. Further analysis reveals that the negative impact of green credit policies on digital innovation is more pronounced in state-owned enterprises, enterprises without financially experienced executives, and in the eastern regions of China.

This study provides empirical evidence to understand the effectiveness and mechanism of influence of green credit policies on enterprise digital innovation, providing also a basis to further improve green credit policies.

This study aims to empirically examine how blockchain, one of the emerging Industry 4.0 technologies, can combat climate change by improving their green innovation performance, particularly under conditions of policy uncertainty.

This study utilizes the difference-in-difference-in-difference (DDD) method to explore the effect of blockchain on enterprises' green innovation performance. The analysis is based on data from Chinese-listed enterprises spanning the period from 2013 to 2021.

First, the adoption of blockchain in enterprises registered in areas designated as low-carbon pilot cities can significantly improve their green innovation performance. Second, the enhancement of green innovation efficiency emerges as the primary driving force behind the adoption of blockchain, thereby leading to improved green innovation performance. Lastly, it is observed that blockchain adoption has a greater positive impact on improving green efficiency in private enterprises compared to state-owned enterprises in China.

For managers, the findings can provide valuable insights to help them better prepare for the challenges and opportunities presented by the era of Industry 4.0. For policymakers, this study offers valuable insights into the interaction between new technologies in Industry 4.0 and the performance of green innovation, thereby aiding in the formulation of effective policies.

This study contributes to bridging the existing gap between the adoption of new technologies, such as blockchain, and their potential impact on climate change. Moreover, this research enriches practitioners' understanding of how new technologies in the era of Industry 4.0 can be applied to address significant challenges like climate change.