Search Results (892)

Based on survey data from 579 farmer households in major non-timber forest product (NTFP) regions of Zhejiang Province, this study comprehensively employs binary logit/ordered probit and machine learning methods for cross-validation. It systematically examines the effects of multiple factors, including perceived property rights security, technical training, village rules and regulations, ecological awareness, and economic incentives, on forest farmers’ adoption of green production technologies. The cross-validation between econometric and machine learning approaches enhances the reliability of the findings. Results show that perceived property rights security is robustly and positively associated with green production behavior, while village rules and regulations and ecological awareness emerge as the two most critical driving factors. These associations exhibit significant NTFP-type heterogeneity: the impacts of technical training and forestry subsidies vary in direction depending on the crop cultivated, rendering traditional one-size-fits-all policies ineffective. This study highlights the crucial role of informal institutions and environmental awareness in the green transition, offering empirical evidence for designing differentiated training programs, optimizing penalty gradients, and implementing targeted subsidy policies. Full article

Against the backdrop of China’s “dual carbon” strategy and green transformation, this study examines the impact of green investment on corporate financial performance and the moderating role of state-owned shareholding ratio. Using a sample of Chinese A-share listed manufacturing firms from 2014 to 2023 and adopting a dynamic panel data model, the empirical results show that green investment significantly improves corporate financial performance. Moreover, state-owned shareholding plays a negative moderating role, and high state ownership weakens the positive effect of green investment on financial performance. The results indicate that green investment can enhance profitability by improving operational efficiency, reducing compliance risks and enhancing corporate reputation. However, due to policy burdens, multiple agency problems and insufficient profit incentives, state-owned enterprises tend to deviate from efficiency-oriented goals in green investment, which reduces the economic returns of such investment. This study enriches the understanding of the economic consequences of green investment under heterogeneous ownership, and provides empirical support for enterprises to optimize green investment decisions and regulators to improve governance mechanisms. Full article

This study examines whether green factory certification improves corporate capacity utilization. As a voluntary regulatory instrument for promoting green manufacturing, green factory certification may enhance firms’ production efficiency by providing legitimacy incentives and external recognition. Using Chinese A-share listed firms from 2010 to 2024, we employ a staggered difference-in-differences model and find that green factory certification significantly increases firms’ capacity utilization. Heterogeneity analyses show that this effect is stronger for firms in regions with stricter command-and-control environmental regulation, weaker market-based environmental regulation, greater financing constraints, and weaker product advantages. Mechanism tests indicate that political legitimacy and market legitimacy are two important channels through which certification improves capacity utilization. Further analyses show that certification-induced improvements in capacity utilization increase firm value and stock liquidity. This study provides empirical evidence on the real effects of green factory certification and highlights the role of voluntary environmental governance in promoting both sustainable transformation and industrial efficiency. Full article

Digital agricultural technologies can support the living conservation and sustainable development of agricultural heritage sites, but farmers’ adoption behavior in these contexts remains underexplored. This study examines the endogenous drivers and external contextual conditions shaping such adoption. Integrating the Theory of Planned Behavior (TPB), Perceived Value Theory, and Context Effects Theory, this study develops an “external context–endogenous driving factors–adoption intention–adoption behavior” framework. Based on 399 household surveys from the Qitai Dryland Farming System in Xinjiang, the data were analyzed using PLS-SEM and multi-group analysis. The results show that subjective norms, perceived behavioral control, behavioral attitude, and perceived value positively affect adoption intention, with behavioral attitude having the strongest effect. Adoption intention promotes adoption behavior and fully mediates the perceived value–behavior relationship. Technical training, economic incentives, and policy regulations strengthen key internal driving paths, whereas publicity and education enhance attitude-based intention formation but may weaken perceived behavioral control when disseminated information diverges from farming realities. Adoption pathways differ across livelihood types, supporting differentiated promotion strategies. This study is among the first to apply PLS-SEM and multi-group analysis to farmers’ adoption of digital technologies in agricultural heritage sites, providing empirical evidence for integrating digital agriculture, heritage conservation, and sustainable development. Full article

The Circular Economy (CE) offers an alternative to the traditional “take–make–dispose” model and is increasingly important in hospitality due to the sector’s high resource consumption. This systematic review analyzes 159 studies published between 1995 and 2024, sourced from ABI, BSP, and WoS, and consolidates scattered knowledge on CE practices in hotels. It outlines five strategies for transitioning to CE: energy efficiency, renewable energy, water management, waste reduction, and carbon footprint reduction. These are supported by green procurement, local supply chains, eco-certifications, and regenerative branding, all of which help hotels fulfill stakeholder expectations and support local economies. Guest engagement—through nudges, incentives, co-creation, and digital tools for monitoring and feedback—is becoming increasingly important. The review shows that CE adoption is driven by internal factors such as leadership, staff training, culture, and resources, as well as external factors such as regulation, institutional pressure, and consumer demand for authenticity. Effective collaboration among managers, staff, suppliers, policymakers, and certifiers is essential for achieving systemic adoption. CE is moving from operational efficiency to broad innovation benefiting the environment, economy, and society, despite financial, regulatory, and behavioral challenges. Future research should prioritize establishing measurement standards, addressing scalability issues, and evaluating the global effectiveness of implementation. Full article

This study empirically examines the impact of natural resource rents (NRR), a proxy for economic benefits and costs of natural resources, on green growth (GG) in Organization for Economic Co-operation and Development (OECD) countries from 1996 to 2020, while accounting for the moderating roles of green innovations and environmental regulations. Using the Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators as our baseline model, the analysis reveals a significantly negative association between natural resource rents and green growth in OECD countries, consistent with the resource curse hypothesis, which reflects heightened economic, institutional, and environmental risks associated with resource reliance. Furthermore, the results indicate that green innovations and environmental regulations not only promote green growth but also weaken the adverse association between natural resource rents and green growth, thereby suggesting their positive roles in managing resource-related risks. These findings remain robust across alternative variable definitions and model specifications. Overall, the empirical evidence highlights the importance of adopting policy measures, such as increased investment in sustainable technology research and development and providing incentives for firms to implement environmentally friendly practices, to manage resource-related risks and support the transition toward sustainable development. Full article

Toxic metal pollution in farmland soils has become a critical environmental issue threatening land security and agricultural sustainability. This study develops an evolutionary game model involving the government, enterprises, the public, and environmental public-interest organizations to analyze the dynamic interactions underlying multi-actor governance. By combining equilibrium analysis with numerical simulations, the study examines the conditions for collaborative governance and the effects of key parameters on the system’s evolution. The results reveal a stage-based trajectory: weak regulation and limited participation in the early stage lead to persistent illegal discharge; strengthened government intervention and rising social participation in the transitional stage promote more coordinated supervision, although enterprises may still behave non-compliantly; in the mature stage, favorable cost–benefit conditions induce enterprises to adopt compliant treatment, reducing reliance on continuous external oversight. Further analysis shows that effective incentive and deterrence mechanisms are essential for activating multi-actor responses, while enterprises’ strategies are mainly driven by pollution-control costs, expected returns, and potential losses, and social participation depends on monitoring costs, expected benefits, and government support. Initial strategy distributions have limited influence on long-term outcomes. These findings provide policy-relevant insights for improving institutional design and strengthening collaborative governance in the management of toxic metal pollution in China’s farmland soils. Full article

With the strategic advancement of energy structure transformation and the implementation of carbon peaking and carbon neutrality goals, the Integrated Energy System (IES) has become a core research direction owing to its superior performance in multi-energy complementation, operational efficiency, and low-carbon emission characteristics. Nevertheless, existing studies reveal that the optimal operation of IES still faces significant challenges, including the high complexity of multi-energy coupling, supply–demand imbalance caused by renewable energy penetration, and insufficient exploitation of demand-side flexibility. As a core measure of demand-side management, demand response (DR) provides an effective approach to motivate users to adjust power load via price incentives or direct load control. DR can effectively smooth load profiles, improve resource utilization, and boost the consumption level of renewable energy. To meet the operational demands of modern IES, this paper establishes a security-constrained economic dispatch model embedded with multi-level demand response mechanisms. The proposed framework is divided into four key modules: First, a price-based demand response strategy is developed to dynamically guide users in regulating multi-energy consumption behaviors. Second, electric vehicles (EVs) are considered flexible demand-side resources with unique response characteristics. An aggregated EV charging–discharging model is established to suppress power fluctuations and support high proportions of renewable energy integration. Third, to precisely calculate the overall operating cost of IES, a combined economic evaluation index integrating time-of-use tariff and Levelized Cost of Electricity is adopted. It maintains a balance between amortized long-term generation investment and short-term operational expenditure, and coordinates the economic benefits and operational reliability of the whole system. Finally, numerical simulations are performed on a coupled test system comprising an IEEE 33-bus distribution network and a 20-node natural gas network. Simulation results verify that the proposed co-optimization model can effectively reduce total system operating costs and greatly improve the local assumption of fluctuating renewable energy. Full article

As a crucial nature-based climate change solution, the realization of blue carbon’s value is primarily impeded by three interrelated obstacles in developing nations: a weak scientific foundation, fragmented market structures across different levels, and the absence of dedicated institutional frameworks. This study focuses on the institutional bottlenecks hindering the marketization of blue carbon in developing countries. By integrating Complex Adaptive Systems (CASs), Coase’s Theory of Property Rights, and the Institutional Analysis and Development (IAD) framework, we constructed a theoretical framework encompassing five dimensions: transaction objects, transaction participants, transaction markets, transaction rules, and benefit distributions. This framework was validated through an empirical analysis of the blue carbon practice in Ningbo, China. The research identified three critical stages in Ningbo’s governance trajectory: initial founding, synergistic stagnation, and iterative upgrading. The core determinant of governance success or failure lies in the capacity to continuously optimize this five-dimensional rule system through a combination of “top-down regulation” and “bottom-up innovation”, thereby reducing transaction costs and generating effective incentives. The findings indicate that successful blue carbon governance depends on establishing a rule system that is both locally adaptive and dynamically adjustable. The analytical framework proposed in this study offers a systematic new perspective for developing countries to remedy institutional gaps in blue carbon governance. By demonstrating China’s locally adapted innovations in resource rights delineation and value realization, it also promotes greater inclusiveness and diversity within the global blue carbon standard system, contributing a governance approach from the Global South that is applicable to countries at varying stages of development. Full article

Workplace heat exposure under climate change is not only a physical hazard but also a recurrent governance problem involving regulators, employers, and workers. This paper develops a tripartite evolutionary game to examine how workplace heat-risk governance evolves through the interaction of strict regulation, employer prevention investment, and worker symptom reporting. Normal-form Nash and Stackelberg benchmarks are used to clarify the static and sequential counterparts of the evolutionary stability conditions. Heat-risk intensity is introduced as an environmental state that affects accident probability, expected losses, governance costs, and institutional benefits. The model identifies a heat-dependent cooperative stability region: full cooperation is locally stable only when digital monitoring, enforcement incentives, employer investment support, and worker reporting protection jointly satisfy threshold conditions. Extended payoff specifications allow monitoring and regulatory strictness to directly affect worker reporting incentives and link government payoffs to accident-risk reduction. The results show that monitoring and reporting protection may be partially substitutable in the worker-reporting channel but remain non-equivalent at the system level. Long-horizon, shock-recovery, and industry-specific diagnostics further show that isolated instruments often generate partial-governance regimes rather than system-wide cooperation. The findings frame workplace heat adaptation as a complex adaptive governance problem requiring coordinated technological visibility, credible enforcement, employer incentives, and protected worker reporting. Full article

In China, the environmental protection tax constrains and incentivizes firms to cut emissions and lift efficiency. To examine the effect and mechanism of environmental regulation as a driver of corporate green transformation, this study uses data on Chinese listed manufacturing firms from 2011 to 2022. It takes the 2018 environmental fee-to-tax reform as a quasi-natural experiment and employs a difference-in-differences model. The core DID coefficient is 0.0088 (p < 0.05). After the reform was implemented, manufacturers in higher-tax regions achieved better green transformation by increasing pollution costs, adjusting investment and improving executives’ green awareness. The policy effects were more pronounced for low-profit, non-state-owned, non-patent and labor-intensive firms in regions with higher tax burdens. Additionally, the policy effect exhibited a time lag. The incentive effect was stronger for heavily polluting enterprises, and the policy simultaneously boosted corporate economic performance. Accordingly, we propose broadening the taxable scope, tightening supervision, optimizing tax incentives and adopting targeted policies to support corporate green transformation. Full article

The entry of JD.com into the food delivery sector and the ensuing subsidy competition have resulted in irrational competition, merchant profit squeezes, and food safety risks in China. This study therefore investigates the collaborative governance mechanisms for food delivery platforms under involutionary competition driven by traffic contestation. A two-agent evolutionary game model between platforms and merchants is developed, and Q-learning simulations are conducted to capture dynamic learning behaviors. The analysis examines the effects of coupon face value, cost-sharing mechanisms, traffic incentives, and government incentive-penalty policies on the strategic choices of both agents. Key findings reveal that merchants are more sensitive than platforms to traffic incentives and government penalties. Traffic-dependent merchants and traffic-independent merchants exhibit significantly different responses to government interventions. The coupon face value demonstrates a threshold effect, where only a reasonable range encourages compliant behavior among both parties. Based on these results, a collaborative governance framework is proposed. For traffic-dependent merchants, the government should focus on regulating platform behaviors and supervising coupon value controls, while platforms should establish a reward-oriented, penalty-supported incentive mechanism. For traffic-independent merchants, the government should strengthen consumer-reporting penalty mechanisms and strictly control collusion risks between platforms and merchants. Platforms should increase inspection frequency and reinforce penalties to prevent, at the source, the decline in product quality and market disorder induced by involutionary competition. This study provides strategic insights for achieving collaborative governance of involutionary competition in platform economies under intense traffic contestation. Full article

To address the effective dispatch and coordinated control of ESS, EV, and HVAC resources in building parks participating in grid frequency regulation under the virtual power plant (VPP) architecture, this paper proposes a multi-time scale frequency regulation strategy based on state priority and the Stackelberg game. First, a state-based upward and downward frequency regulation priority model is established to dynamically dispatch ESS, EVs, and HVAC systems according to their operating states. Second, a multi-time-scale frequency regulation Stackelberg game model considering priority incentives is constructed with the goal of economic optimality. A comprehensive utility function integrating the startup threshold and regulation rigidity is designed to achieve a balanced optimization that considers both the operational economy of the VPP and the user comfort of the underlying devices. Finally, considering the frequency regulation response characteristics of the resources, a multi-time-scale dynamic weight optimization and reconstruction method is proposed. Case study results show that the proposed strategy can efficiently dispatch park resources, track automatic generation control (AGC) commands with high precision, and significantly reduce system frequency fluctuations. It ensures the safe operation of the system and user comfort while achieving economic optimality. Full article

In the last 10 years, the global green bond market has reached an estimated value of USD 6.8 trillion. However, credibility concerns persist due to greenwashing risks and issues regarding the reporting system. The current measurement, reporting, and verification systems (MRV) have high uncertainty levels of 10–30%, and so they contribute to information asymmetries and fuel investor skepticism when allocating capital to green bond instruments. The scope of this study is to develop an integrated management approach that links air quality and greenhouse gas monitoring with financial incentives throughout the lifecycle of green bonds. The central contribution is a four-phase lifecycle model covering issuance, allocation, monitoring, and impact reporting, which systematically identifies where greenwashing risks and verification gaps arise across the investment cycle. Methodologically, the study combines qualitative content analysis, a novel Disclosure Quality Score (DQS) instrument, based on the Regulation (EU) 2023/2631, four documentary case studies, and an advanced verification framework. The content analysis shows that regulatory and market-performance studies dominate the literature, while integrated lifecycle verification frameworks remain less explored. The DQS uses eight indicators, applied to a matched sample of green bonds, in accordance with the European Green Bond Standard (EuGB) and the ICMA Green Bond Principles (GBP). The results demonstrate that bonds issued under the EuGB present higher disclosure quality (mean DQS = 15.4/16) compared to GBP-aligned bonds (mean DQS = 11.4/16). Case studies show strong issuance-stage disclosure, but weak post-issuance verification. The framework enables lifecycle-wide accountability by reducing information asymmetry. The proposed lifecycle framework and DQS instrument offer a replicable model for improving disclosure quality and ESG performance standards, with direct implications for sustainable investment screening and ESG fund selection. Overall, the findings show that improving green bond credibility requires moving beyond issuance-focused disclosure toward lifecycle-wide verification. Full article

Green retrofit of existing residential communities (GRERC) is critical for upgrading aging building stocks, but their true value extends far beyond physical improvements. A successful retrofit must simultaneously deliver economic, social, and ecological benefits. However, in practice, the value realization is often constrained by a complex network of interdependent factors. This study maps these underlying structures. We first extracted a preliminary set of variables from existing literature and case studies, validating them through survey data. By applying Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) techniques, subsequently, the reciprocal influences and the multi-level structural organization within the identified system were mapped. Our analysis isolates three foundational drivers: government evaluation standards, policy incentives, and ecological awareness. Crucially, these elements do more than exert direct pressure—they dictate the systemic transmission pathways that enable value realization. To bridge the gap between policy and practice, regulators must prioritize making evaluation standards practically actionable. Furthermore, scaling GRERC effectively will require redesigning incentive mechanisms to attract broader social participation and dramatically improving public access to retrofit information. Full article