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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.

In this study, the authors examine the relationships between market-based regulations and corporate carbon disclosure and carbon performance. The authors also investigate whether these relationships vary across emission-intensive and non-emission intensive industries.

The study sample consists of the world's 500 largest companies across most major industries over a recent five-year period. Country-specific random effect multiple regression analysis is used to test empirical models that predict relationships between market-based regulations and carbon disclosure and carbon performance.

Results indicate that market-based regulations significantly and positively affect corporate carbon performance. However, market-based regulations do not significantly affect corporate carbon disclosure. This study also finds that the association between regulatory pressures and carbon disclosure and carbon performance varies across emission-intensive and non-emission-intensive industries.

The findings of this study have key implications for policymakers, practitioners and future researchers in terms of understanding the factors that drive businesses to increase their carbon performance and disclosure. The study sample consists of only large firms, and future researchers can undertake similar studies with small and medium-sized firms.

The results of this study are expected to help business managers to identify the benefits of adopting market-based regulations. Regulators can use this study’s results to evaluate if market-based regulations effectively improve corporate carbon performance and disclosure. Furthermore, stakeholders may use this study to evaluate and improve their businesses' reporting of carbon disclosure and performance.

In contrast to current literature that has used command and control regulations as a proxy for regulation, this study uses market-based regulations as a proxy for climate change regulations. In addition, this study uses a more comprehensive measure of carbon disclosure and carbon performance compared to the previous studies. It also uses global multi-sector data from carbon disclosure project (CDP) in contrast to most current studies that use national data from annual reports of sample firms of specific sectors.

Eco-innovations (EIs) are intended to benefit not only the environment but society and firms, but how the relationship is reconciled is unclear, particularly in emerging economies. The advancement of EI has resulted in both positive and negative relationships with sustainability, indicating that the association is more complex than a simple linear one.

Thus, the authors hypothesize that EI has a curvilinear relationship with sustainable business performance (SPB) and that market turbulence (MT) exerts stimulus that reinforces EIs. Accordingly, using the Stata software, the authors apply a moderated regression to a sample size data of 511 manufacturing firms to test the hypothesized assumptions.

Although the results attest to a positive relationship between EI and SBP, the results are synonymous with an inverted “U” shape that renders EIs unprofitable beyond a certain threshold (rebound effect). Additionally, the authors observe that the moderation stimulus of technology turbulence flattens the inverted U-shaped curve.

Built on the foundations of natural-resource-based view (NRBV) and contingency theory, the authors identify the rebound effect point of EI and SBP and the reinforcing stimulus of MT.

This paper aims to examine the question, “How do firm-level, home-country and host-country environmental performance (EP) affect the outward foreign direct investment (OFDI) of Chinese multinational enterprises (MNEs)?”

The authors examine the relationships between EP and OFDI propensity and between EP and OFDI intensity using a sample of 359 Chinese firms in industries with a significant environmental footprint between 2009 and 2019 (2,002 firm-year observations) and a Heckman two-stage model.

This study shows that the propensity for OFDI by Chinese MNEs is significantly and positively related to the firm’s prior EP and the country-level EP of China. However, the amount of FDI invested is significantly and positively related to the firm’s prior EP and negatively related to the EP of the host country.

The findings suggest that FDI in a country by an MNE is determined by a combination of firm-level EP, home-country EP and host-country EP. This study finds that the decision to undertake FDI (propensity) and the decision about how much to invest (intensity) are determined by different factors. The propensity for FDI is determined by the home-country EP and firm-level EP. However, the intensity of FDI is determined by a combination of the host country EP and firm-level EP. A limitation is that this study only examines MNEs in China, so the findings may not apply to other countries.

This paper shows that MNEs’ EP is positively related to the propensity and intensity of their OFDI decisions. However, this paper shows that the home-country and host-country EP may also play an important role in determining the propensity or intensity of OFDI.

While implementing green innovation-driven strategies when facing growing grim environmental problems and the realistic demands of achieving high-quality development is increasingly urgent, changing abruptly is inevitably detrimental to the smooth functioning of social and economic development. Restrained by resources, innovation-driven strategy is a huge strategy for an organization to shift from traditional technological innovation to green innovation. Supports and implementation in green technology investment would necessarily crowd out other business investment and lead to reduction of innovation outputs and mount of financial uncertainty. Under the guidance of harmonious balance, the equilibrium allocation between green research and non-green counterpart is badly needed to be addressed for decision-makers inside and outside the organizations. The differentiated inputs of them would lead to different effects on organizational performance in practice.

The authors first conducted a Hausman test on green research intensity (GRI) and innovation performance, economic performance, social performance, and environmental performance, respectively. Adopting the fixed effects model for estimation seems accurate, if there is no significant heteroscedasticity shown in the BP test. The authors then adopted the least square dummy variable method to handle individual heterogeneity (Xia et al., 2020). After controlling the industry effect and time effect simultaneously, the results were consistent with that of fixed effects model, thereby eliminating the impact of heteroscedasticity.

The authors construct a multi-dimensional performance system—innovation performance, economic performance, social performance, and environmental performance—to probe into the influence of GRI from the resource-based view and allocation theory. Different performance does not benefit equally from increasing the intensity of green research. Performance increase may squeeze out the quantity of total innovation but can compensate quality for knowledge spillovers of green technology. The organization's growth and long-term value may be beneficial from the increase, but not the short-term financial performance. While the relationship between GRI and social performance has the characteristic of reverse U-curve, there has to be some scale of green research to gain considerable and nonlinear environmental performance. Low level of green research may increase pollution until green research has cross over the inflection point. These relationships are intensely moderated by the environmental regulation.

Because of the focus of this study is on the organizational performance of green research, the analysis comes with some limitations that should be addressed in future research. Data were inter-professional, with large enterprises and small businesses innovating green technology at the same time. Though the hypotheses presented here were grounded in existing theoretical rationale, the generality of this study cannot be assumed. Multi-performance of green activities in small- and medium-sized businesses should be further explored. Additionally, concrete index of the corresponding evaluation system constructed here contribute more to practical activities of green innovation. Refinement of synergy performance index is the task for future work. Further, grounded in Chinese context, the authors' results could be compared with other scenario with institutional heterogeneity to provide detailed evidences for institutional theory. Future studies could also move forward to longitudinal case study to delicately investigate the performance differentiation of green research when in different development stage.

First, what and how the authors do is novel as the authors use listed Chinese manufacturing companies to probe into the complex relationship between GRI and multiple performance rather than discussing the performance of green innovation input from a single perspective merely. Second, the authors systematically define the performance as economic performance, environmental performance, social performance and innovation performance in depth, which consider adequately the tangible and intangible value as well as internal and external benefits of green research. And finally, in the context of environmental regulation, the study discusses the differentiation of the increase of green research intensity from the perspective of resource constraints, providing reference for optimizing the resource allocation in green and non-green research and solving the decoupling between earnest social appeal and sluggish or reluctant green behaviors.

The aim of this study was to investigate the impact of low-carbon city pilots (LCCPs) policy using Chinese city-level data from 2009 to 2018 and examine the mechanisms of LCCP policy using a mediation effect model.

The authors measured carbon emissions by high-resolution carbon emission data and used difference-in-difference (DID) and propensity matching score-difference-in-difference (PSM-DID) model to investigate the relationship between LCCP policy and urban carbon intensity. The complex relationship between policy and carbon intensity was evaluated through a mediation model.

The results show that LCCP policy can reduce urban carbon intensity (−0.287), but its effects are different in different sectors. The impact of LCCP policy is greater in the industrial enterprise sector than in the transport sector than in the agricultural sector. Second, the authors find that LCCP policy under market-driven is more effective than government intervention. Third, there is a spillover effect of LCCP policy, which is decreasing with distance. Finally, the authors explore the mechanisms of LCCP policy from multiple perspectives, such as optimizing industrial structure, green areas, promoting public transport travel, population migration and innovation. In addition, the flow of these factors can also explain the spillover effects of LCCP policy.

This study confirms that LCCP policy is an effective tool for achieving urban sustainable development. Government policy-makers should consider the differences in the impacts of LCCP policy in different sectors and the spillover effects of LCCP policy. And, it shows that the effects of LCCP policy are larger by market-driven. These findings imply that the government should take full account of city characteristics and marketisation processes when formulating carbon reduction policies.

This study analyzed the relationship between LCCP policy and urban carbon intensity based on high-resolution carbon emission data. Urban panel data are used to discuss the impacts of LCCP policy under government intervention and market-driven and the mechanisms at play. The study reveals that LCCP policy mainly acts on the industrial enterprise sector, the spillover effects and the market-driven effects.

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.

Whereas the majority of research explores the direct relationship between quality management practices and firm operational performance using data on developed economies, this paper asserts that the effect of quality management practices on firm operational performance needs to be evaluated with reference to the contingency approach, especially in developing countries. Therefore, the authors empirically test whether competitive intensity moderates the relationship between quality management practices and inventory management process.

The authors employ a fixed-effect model on data from more than 7,000 observations operating in 27 Eastern and Central European countries.

The findings reveal that the adoption of quality management practices decreases inventory days only in a highly competitive market. Additionally, the results indicate that this effect is changing when distinguishing between countries and sectors.

This study advances research on quality management practices by emphasizing the importance of contingency and institutional approach.

This study aims to explore the impact of energy investment on economic growth. Specifically, the study investigates the impact of energy consumption, foreign investment, infrastructure development, tax revenue, human capital, international tourism revenue and trade volume on economic growth.

To achieve the aim, the authors sample the 24-years (1996–2019) financial statistics of BRICS countries. Given the econometric recommendations supplemented by the Johnsen cointegration test, the current study uses the fully modified ordinary least square model for regression analysis and checks the robustness through robust least square model.

The statistical analysis shows a direct impact of energy investment on economic growth. In addition, the statistical results indicate a positive impact of energy consumption, foreign investment, infrastructure development, tax revenue, human capital and trade volume on economic growth.

The results present practical implications for policymakers regarding the adequate investment in energy production that can further promote the economic growth in BRICS countries. Policy officials should enhance the volume of renewable energy production, foreign investment and tax revenue. Additionally, it is equally suggested to policymakers regarding the development of infrastructure and human capital to ensure economic growth.

This study supplements the novel and robust evidence on investment in energy-leading economic growth.

This paper aims to providea comprehensive review of the concepts and definitions of green finance, and the importance of “green” impact investments today. The core challenge in combating climate change is reducing and controlling greenhouse gas emissions; therefore, this study explores the solutions green finance provides emphasizing their impact on the environment and firms' financial performance. With increasing attention to the concept of green finance, multiple forms of green financial tools have come to fruition; the most prominent are green bonds.

This paper compiles a comprehensive green bond dataset, presenting a statistical study of the evolution of the green bonds market from its first appearance in 2006 until 2021.

The green bond market has seen massive growth over the years reaching $1651.92bn as of 2021. Findings show that green bonds are working towards shifting from high carbon-emitting energy to renewable energy, which is vital to economic development and growth. In congruence, green bonds are aligned with the United Nation's sustainable development goals (SDGs) amounting to $550bn for 2020, with the five most covered SDGs amounting to over 60%.

With growing worldwide concern for global warming, green finance became the fuel that pushes the world to act in combating and mitigating climate change. Coupled with adopting the Paris Agreement and the SDGs, Green finance became a vital tool in creating a pathway to sustainable development, as it connects the financial world with environmental and societal benefits.