Search Results (3,443)

The purpose of this study is to explore how Zimbabwean firms use Environmental Management Accounting (EMA) and climate risk disclosure amid climate policy uncertainty and how managers perceive these practices as relevant to organisational resilience and long-term sustainability within a volatile institutional and macroeconomic context. The study was couched in the interpretivist research philosophy and adopted the inductive research approach. A case study research design, which aligns with a qualitative research design, was chosen for the study. The study employed in-depth interviews with management accountants, finance executives, and industry leaders across firms in Harare. The study adopted the cross-sectional time horizon and analysed data using thematic analysis to develop insights into the role of EMA and climate risk disclosure in times of policy uncertainty. The findings suggest that participants perceived climate policy uncertainty as influencing organisational efforts to reconfigure management accounting practices through greater environmental performance monitoring, adaptive budgeting, and scenario-based planning. The findings of this study suggest that organisational actors interpreted climate policy uncertainty as a condition requiring greater flexibility in budgeting, environmental monitoring, and strategic planning. Participants in this study associated EMA with improved environmental cost visibility and more adaptive approaches to investment appraisal and risk management under uncertain policy conditions. Similarly, participants perceived climate risk disclosure as increasingly crucial for strengthening organisational legitimacy, stakeholder confidence, and institutional credibility. While respondents linked sustainability-oriented accounting adaptation to broader organisational resilience and long-term sustainable growth aspirations, these relationships were understood through managerial perceptions and organisational experiences rather than as directly measurable macroeconomic outcomes. The study contributes to the sustainability accounting literature by providing qualitative, context-sensitive insights into how managers in an emerging economy interpret climate policy uncertainty and adapt EMA and climate risk disclosure practices within volatile institutional conditions. The study further contributes by integrating sensemaking theory and institutional theory to explain how organisational interpretations of uncertainty shape sustainability-oriented accounting adaptation and perceptions of organisational resilience. It is therefore recommended that the regulatory institutional pillar be strengthened to reduce uncertainty and enhance the EMA’s strategic adaptation. Full article

Environmental policies and intermittent renewable energy (RE) drive large-scale hydrogen production towards hybrid supply configurations, combining collocated RE units and the electricity market (EM). This links the power and hydrogen sectors through EM/hydrogen prices, dispatch, and hydrogen demand profiles. In a hybrid configuration, the strategic role of RE in the EM enhances these links by creating profit opportunities. This work develops a bi-level model, optimizing electrolyzer size and location, operational decisions and RES bidding strategies, while explicitly modeling EM clearing. In the upper-level, an EM player, owning strategically bidding RE assets, evaluates expanding into the use of electrolyzers that act as price-takers. The lower-level problem clears the EM. The proposed framework is applied to an IEEE 24-node test system. The results show how EM conditions determine investments for different hydrogen price cases. It is revealed that differentiated electricity sourcing across electrolyzers and efficiency-preserving dispatch impact operational decisions, leading to revenue improvements. Moreover, renewable capacity withholding is used to avoid zero EM prices and mitigate the economic impact of unmet hydrogen demand when RE availability is limited and electrolyzer participation in the EM is restricted. Time-window-constrained hydrogen demand mitigates unutilized RE by 39% compared to that for hourly demand. Full article

The increasing demand for lithium (Li), cobalt (Co), and rare earth elements (REEs) driven by battery technologies, electrification and renewable energy systems has intensified the interest in recovery pathways as an alternative to conventional mining. High-salinity mine waters—including lithium brines, geothermal fluids, and metallurgical effluents—represent both an environmental liability and a significant secondary resource for metal recovery. However, extreme ionic strength, complex metal speciation, and strong competition from major ions severely limit the efficiency and selectivity of traditional extraction technologies. Microalgae and cyanobacteria are promising biological agents for metal recovery via biosorption, bioaccumulation, and extracellular polymeric substance (EPS)-mediated binding, especially in saline and hypersaline systems. This review synthesises current knowledge on microalgal-based recovery of Li, Co, and REEs from high-salinity waters, emphasising co-design principles that integrate strain physiology, their adaptation to the extreme operating conditions, water chemistry, and process engineering. Halotolerant and extremophilic taxa—Nannochloropsis oceanica, Galdieria sulphuraria, and Synechococcus elongatus—are examined as representative models for complementary metal-binding mechanisms and operational niches. Limitations such as weak affinity for lithium, competitive ion suppression, desorption inefficiencies, and scale-up challenges are discussed. Emerging strategies such as modular multi-strain systems, hybrid bio-physicochemical platforms, and biomass valorisation are also addressed. The review concludes that microalgal systems, when co-designed for selectivity and resilience, can contribute to the strategic recovery of critical materials that align with EU, UK and US policies. Full article

Indian metropolitan cities such as Mumbai grapple with rapid urbanisation, extreme urban density, high built-up areas, loss of green cover, and shrinking open spaces, resulting in increased impermeable surfaces, urban heat island effects, and frequent flooding occurrences. Modern stormwater management has increasingly been characterised by integrated grey-green approaches; however, cities in the Global North benefit from established policies, technical expertise, and financial resources that enable the systematic and large-scale integration of Blue-Green Infrastructure (BGI) through district-wide geospatial assessment frameworks, unlike many cities in the Global South. Despite growing interest in nature-based stormwater solutions, there remains a dearth of geospatial empirical research from India examining the placement, distribution, performance, and functionality of BGI integrated with existing stormwater management systems in cities such as Mumbai. Furthermore, hydrological modelling using tools such as the Storm Water Management Model (SWMM) for the design, planning, and implementation of BGI in Indian cities remains largely unexplored. This study explores the role of BGI strategies in improving urban stormwater management within high-density Indian cities under a 25-year return period extreme rainfall scenario. Using an integrated approach that combines QGIS-based spatial analysis with EPA-SWMM hydrologic-hydraulic modelling, the research examines runoff behaviour, identifies flooding hotspots, and evaluates the effectiveness of Low Impact Development (LID)-based BGI measures such as permeable pavements, infiltration trenches, and green roofs applied at the ward level in Mumbai’s F/North and G/North Wards. Detailed land use classification, spatial mapping, and rainfall simulation corresponding specifically to a 25-year return period rainfall event was used to assess pre- and post-intervention conditions. The findings indicate that the applied BGI measures led to a 12.6% reduction in peak runoff (137.6 m³/s to 120.2 m³/s) and a 5.5% decrease in total runoff volume (783,510 m³ to 740,410 m³). More importantly, the peak flooding flow rate decreased by 45% (94.1 m³/s to 51.7 m³/s), demonstrating that BGI measures can efficiently reduce peak flooding flows by extending runoff hydrographs during extreme rainfall events. These findings are specifically applicable to the simulated 25-year return period extreme rainfall scenario and may vary under different rainfall intensities or return periods. Less extreme events could potentially experience even greater relative reductions or prevent flooding altogether, while also easing downstream hydraulic loads. Overall, strategically placed BGI interventions can significantly reduce surface runoff and peak flow, thereby enhancing stormwater resilience within spatially constrained urban environments. This study provides a replicable, data-driven framework for catchment-scale stormwater planning in dense Indian cities under extreme rainfall conditions, offering practical insights into methods, local contextual considerations, and spatial planning strategies for policymakers and urban planners seeking to retrofit and adapt existing infrastructure under increasing hydrologic stress and climate variability. Full article

Sustainability transitions confront firms with the following informational paradox: the regulatory pressure to innovate green has intensified, yet the knowledge required to do so is dispersed across agencies, sectors, and jurisdictions that rarely speak to one another. Treating data as a strategic factor of production, this paper asks whether and how opening public data—the systematic release of government-held datasets—reconfigures the conditions under which firms generate green innovation. We model the green-innovation ecosystem as a Complex Adaptive System (CAS) in which heterogeneous, bounded-rational agents co-evolve with a data-mediated selection environment. Within this frame, public data openness (PDO) is not marginal input but an exogenous shock to the fitness landscape that propagates through three coupling channels—supply–demand alignment, recalibration of government intervention, and amplification of green credit. Formal derivations link each channel to a testable proposition, and a multi-period Difference-in-Differences (DIDs) design built on the staggered roll-out of Chinese municipal open-data platforms identifies the causal effects, with Callaway–Sant’Anna estimators and double/debiased machine learning (DDML) addressing recent econometric critiques. The evidence supports each proposition and reveals the following distinctive heterogeneity signature consistent with absorptive-capacity heterogeneity: the policy is most consequential where agents and ecosystems are best able to convert data into knowledge. Reframing PDO as a systemic enabler clarifies why uniform rollouts yield uneven returns and motivates a tiered design that scales with the absorptive capacity of recipient firms and regions. Full article

Crisis management has evolved from a reactive organizational function into a strategic capability grounded in organizational learning, knowledge-based processes, and behavioral alignment, thereby enhancing institutional resilience in volatile environments. This study examines how organizational and financial determinants contribute to crisis management success in the United Arab Emirates (UAE). It integrates crisis management culture as a learning-oriented mediating capability. It incorporates a Theory of Planned Behavior (TPB)-based behavioral extension to explain how attitude, subjective norms, and perceived behavioral control shape intention toward crisis-related compliance. Using SPSS regression analysis and Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings indicate that policies, procedures, and financial stability exert significant positive effects on crisis management success, whereas trained human resources show no direct significant impact. Crisis management culture emerges as a key mediating mechanism that enables knowledge integration, supports organizational learning processes, and translates structural preparedness into coordinated action. The TPB-based extension further shows that attitude, subjective norms, and perceived behavioral control significantly predict intention, and that intention is positively associated with crisis management success. The results suggest that effective crisis governance depends not only on formal structures and financial resources but also on learning-oriented cultures and behavioral mechanisms that transform institutional knowledge into coordinated crisis responses. Full article

The sustainable transformation of idle built environments represents a critical pathway for advancing low-carbon development and achieving carbon neutrality targets. This study examines how idle rural building stocks may contribute to sustainable built environment systems through rural building repurposing and regeneration strategies. It introduces the concept of Green Rural Centers (GRCs), multifunctional facilities formed through the adaptive reuse of idle buildings that integrate low-carbon design, community services, and local economic functions. Within the proposed framework, GRCs are conceptually characterized as facilities that may: (1) achieve 50–70% reductions in operational energy demand through passive and renewable measures, (2) incorporate two or more community-oriented functions (e.g., education, governance, cultural services), and (3) demonstrate embodied carbon savings of ≥40% compared to demolition-and-rebuild scenarios. Grounded in fieldwork from Fujian Province, China, and aligned with national policies, the study evaluates spatial transformation, carbon mitigation, and institutional integration. Using a mixed-methods approach that combines scenario-based carbon-reduction estimation and appraisal, spatial analysis, comparative case studies, and policy evaluation, the findings indicate that retrofitting 30% of approximately 68,000 idle rural schools could achieve approximately 734,400 metric tons of cumulative CO₂ reduction by 2060 under the baseline scenario. Under conservative and ambitious implementation conditions, the estimated cumulative reductions are approximately 408,000 and 1,224,000 metric tons of CO₂, respectively. Sensitivity analysis shows that moderate improvements in retrofit quality or implementation rates significantly amplify emissions reduction outcomes. Beyond environmental performance, the proposed framework may also support community resilience, decentralized service provision, and socio-economic revitalization. This research reframes idle building stock as a strategic asset within sustainable built environment systems, policy-relevant exploratory framework potentially adaptable to comparable rural contexts. This study contributes to the sustainable built environment discourse by demonstrating how underutilized rural building stocks can function as broader low-carbon rural regeneration systems. Full article

Digital policy has become an important instrument for promoting sustainable agricultural modernization. However, its effectiveness depends on the strategic responses of the government, agricultural operators, and farmers. This study develops a theoretical framework to examine how digital policy affects sustainable agricultural modernization through multi-agent interaction. Specifically, it constructs a three-party evolutionary game model and a Stackelberg game model to analyze strategy evolution under different implementation costs, subsidies, and penalties, as well as the government’s first-mover role in subsidy design. The results show that digital policy does not promote sustainable agricultural modernization through a simple linear pathway. Instead, it operates by reshaping the incentive structures of agricultural operators and farmers. Lower government implementation costs increase the likelihood of active policy implementation, while subsidies for agricultural operators and farmers strengthen their willingness to adopt digital tools, engage in standardized production, and participate in digital agricultural activities. However, the marginal effect of subsidies weakens as participation and digitalization increase, indicating that unlimited subsidy expansion may reduce policy efficiency and increase fiscal pressure. This study contributes to the literature by linking digital policy design, multi-agent strategic interaction, and sustainable agricultural modernization within a unified theoretical framework. It highlights that effective digital agricultural policy requires incentive compatibility, fiscal sustainability, inclusive participation, and adaptive governance, rather than reliance solely on digital technology investment or subsidy expansion. Full article

Northeast China is one of China’s major commodity grain bases and plays a strategic role in national food security. Against the background of rural population outflow and agricultural modernization, new agricultural business entities (NABEs), including family farms, farmers’ cooperatives, and agribusinesses, have become important actors in reshaping agricultural production organization. Based on registration data for 2014, 2018, and 2023, this study uses kernel density estimation (KDE), standard deviational ellipse (SDE) analysis, spatial autocorrelation analysis, ordinary least squares (OLS) regression, and multiscale geographically weighted regression (MGWR) to examine the spatiotemporal patterns and driving factors of NABEs in Northeast China. The results show that: (1) NABEs expanded rapidly from 2014 to 2023 and became increasingly concentrated in agriculturally advantageous plain areas. (2) Family farms showed the fastest expansion, farmers’ cooperatives had the widest spatial coverage, and agribusinesses were mainly concentrated around transport corridors and market nodes. (3) In terms of industrial structure, crop-production entities remained dominant, followed by animal husbandry entities, while forestry, fishery, and agricultural support service entities accounted for relatively small shares; however, their numbers continued to increase. (4) The OLS results showed that the reclamation rate and road network density had relatively stable associations with the spatial distribution of multiple entity types, whereas economic development, science and technology investment, and fiscal support showed differentiated relationships across entity types and regions. (5) The MGWR results further reveal spatial heterogeneity in the effects of driving factors. These findings provide empirical evidence for type-specific cultivation and differentiated policy support for NABEs in major grain-producing areas. Full article

Renewable energy sources are fast becoming the most cost-effective option for adding new power generation capacity globally. In South Africa (SA), the transition from fossil fuels to renewable energy has steadily gained momentum over the years. However, this transition is beset by complex and multidimensional barriers. This research study analyses and prioritises renewable energy barriers and mitigation strategies in South Africa. The DEMATEL multi-criteria decision-making technique was employed to rank the barriers and assess their cause-and-effect relationships. The findings reveal the top three barrier categories as Agreement, Market, and Knowledge. The study further employed an integrated hybrid CRITIC-TOPSIS technique to prioritise the proposed mitigation strategies for each barrier in a defined category. The results indicate that strengthening local community engagement is the most suitable solution to the adoption of renewable energy in SA. A sensitivity analysis model was conducted to validate the robustness of the results. The findings validate the consistency of the methods, with the ranking of the barriers and mitigation strategies remaining stable under various scenarios. This study presents a context-specific causal analysis of barriers and an objective prioritisation of mitigation strategies in South Africa using an integrated hybrid DEMATEL and CRITIC–TOPSIS approach, providing policymakers and decision-makers with valuable insights to develop strategic plans and policies that address the identified barriers. Full article

Against the backdrop of the dual-carbon strategy, China’s civil aviation industry, as a high-energy-consumption and high-carbon-emission sector, faces mounting pressure for low-carbon transformation. As the dominant airlines within China’s civil aviation system, Air China, China Eastern Airlines, and China Southern Airlines play a pivotal role in guiding the industry’s high-quality development. Employing the Global Malmquist–Luenberger (GML) index model, this study constructs a global production frontier incorporating undesirable outputs to systematically measure the dynamic evolution of total factor productivity (TFP) for the three major airlines in the period 2005–2023, and further applies a combined static-dynamic regression framework to identify the firm-level heterogeneous mechanisms through which explanatory factors operate. The results reveal significant heterogeneity in TFP trajectories: China Southern Airlines exhibits the most stable efficiency with the lowest volatility; China Eastern Airlines displays the greatest volatility but the strongest post-crisis rebound; and Air China occupies an intermediate position in both efficiency level and volatility. This differentiation stems from fundamental differences in market positioning, strategic orientation, and resource allocation patterns. Market competitiveness exerts a significantly positive effect on TFP for both Air China and China Eastern Airlines. Technological innovation investment generates short-run negative effects across all three airlines, albeit with divergent magnitudes. Human capital accumulation acts as a positive driver for Air China but produces a negative effect for China Southern Airlines, attributable to a structural mismatch between aggressive talent upgrading and organizational absorptive capacity. Shifting the unit of analysis to the firm level, this study identifies three heterogeneous strategic archetypes—market-led, scale-expansion, and regional-deepening—and constructs a differentiated “one firm, one policy” framework to provide targeted policy guidance for improving airline efficiency and facilitating low-carbon transition under carbon constraints. Full article

The General Data Protection Regulation (GDPR), adopted by the European Union in 2018, aims to enhance consumer trust and market efficiency by strengthening data protection. The concurrent stringent compliance requirements raise operational costs and could reshape competition by favoring larger firms with greater regulatory capacity. While the GDPR reduces data-related risks and promotes global digital trade through its extraterritorial reach, the potential advantage to larger firms could incentivize strategic responses such as mergers and acquisitions (M&A) to consolidate market power. Given the rapid expansion of Chinese digital firms in e-commerce, social media, and cloud services across the EU, this study examines how the GDPR has affected their cross-border M&A activities between 2014 and 2021. Based on difference-in-difference analysis, the study finds that the GDPR did not have a statistically significant impact on the number or value of mergers and acquisitions by Chinese digital firms in the EU in the short term. This suggests that firms may enhance their institutional adaptability by strengthening their compliance capabilities. However, institutional and cultural differences pose long-term entry barriers for the firms. The study contributes by highlighting how firms adjust internationalization strategies under stringent regulatory regimes, offering policy-relevant insights for governments and regulatory authorities. Full article

Green hydrogen—hydrogen produced from renewable electricity—is central to global decarbonization strategies. However, despite their fragile governance, damaged infrastructure, water scarcity, and limited investment security, conflict-affected developing economies remain largely absent from hydrogen research. This study addresses that gap by developing and validating a multi-evidence strategic framework for green-hydrogen (GH₂) adoption in fragile institutional environments, using Palestine as a challenging test case. Methodologically speaking, the framework integrates four evidence streams—barrier prioritization by 45 Palestinian experts using the Analytic Hierarchy Process (AHP); structural modeling of barrier–adoption–sustainability relationships using partial least squares structural equation modeling (PLS-SEM); strategic-pathway ranking using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS); and an original Sustainable Development Goal (SDG) Contribution Index—externally validated by an independent panel of 120 energy experts across 18 Middle East and North Africa (MENA) countries. Three findings stand out. Firstly, expert perception and structural evidence diverge: technical barriers receive the highest expert weight (56.2%) yet show the weakest structural effect on adoption (β = −0.230), whereas social barriers, weighted lowest by experts (4.8%), rank second in predictive power (β = −0.310). Secondly, Small-Scale Community Production is the most robust deployment pathway, ranked first under every weighting scenario tested. Thirdly, government policy quality acts as a governance multiplier, raising the sustainability returns of adoption by 20.2%, with benefits concentrated in SDGs 7, 13, 8, and 9. Practically speaking, the framework yields seven strategic goals and a phased 2026–2040 roadmap for fragile developing economies. Full article

Against the backdrop of China’s strategic goals of achieving carbon peaking and carbon neutrality, a key question is whether renewable electricity generation (REG) is associated with lower carbon emission intensity (CEI). To address this issue, this study employs panel data from 30 Chinese provinces from 2005 to 2024 and combines the Tapio decoupling model, Moran’s I test, and the spatial Durbin model (SDM), with the ordinary least squares (OLS) used as a benchmark to analyze the decoupling evolution, spatial spillover associations, and potential transmission channels between REG and CEI. The findings show that: (1) the relationship between REG and CEI evolves from weak decoupling to strong decoupling, suggesting a potentially nonlinear relationship; (2) CEI exhibits significant spatial autocorrelation and regional clustering; (3) REG is significantly associated with lower CEI, with both local and spatial spillover associations; (4) the local mitigation association is stronger in eastern and higher-CEI provinces, while spillover effects are more pronounced in western, northeastern, and resource-based provinces; and (5) the REG-CEI association may operate through energy structure (ES) optimization and energy intensity (EI) reduction, while environmental regulation (ER) may strengthen this association. The endogeneity tests provide supplementary evidence consistent with these findings, although they should not be interpreted as definitive causal proof. Overall, this study contributes to the sustainability literature by showing that the REG-CEI relationship is not merely a static local association, but a dynamic and spatially differentiated pattern shaped by regional coordination and energy-system adjustment. These findings provide evidence relevant to sustainability-oriented energy policy by suggesting that renewable electricity development should be assessed not only by generation scale, but also by its association with carbon-intensity reduction, spatial coordination, and energy-system efficiency. Full article

Rural electrification in Sub-Saharan Africa faces a trilemma: cutting carbon emissions, making it economically viable, and achieving fair access to energy for all. This paper develops a multi-objective framework that optimises carbon revenue, net present value (NPV), total energy supply, cooking fuel (firewood and LPG), health costs, and benefit to society. The model uses continuous decision variables: daily energy allocation among four sources (solar, generator, firewood, LPG) to three population groups (men, women, children). The case study is a rural community of 7000 people in Nigeria (Tier 1 energy consumers). Six policy scenarios are considered: baseline, high carbon price, low carbon price, microfinance, government subsidy and community cooperative. This study compared algorithms and identified a hybrid Non-dominated Sorting Genetic Algorithm and Particle Swarm Optimisation II as the most suitable algorithm for solving the formulated optimisation problem. It was found that NPV and unit cost of energy would increase to $175,500 and 26.4 ¢/kWh, respectively, by increasing the price of carbon from $8/ton to $12/ton. Firewood generates health savings and carbon revenue in the range of $4100–$12,270/year. Prices below $8/ton do not induce optimal reconfigurations in the system. The best energy supply (2825 kWh/day) and the lowest unsatisfied demand occur in the government subsidy scenario with the greatest disparity index, displaying an equity-efficiency trade-off. The framework shows that sustainable access to energy can be unlocked using strategic integration of carbon finance, valuation of health benefits and equity constraints. Full article