Search Results (1,612)

Towards achieving carbon neutrality, it is important to produce carbon-free hydrogen from renewables at an acceptable cost. At the same time, power retailers that own renewables must manage their imbalances between planned and actual generation. This paper proposes an economically viable carbon-free hydrogen method for such retailers, utilizing both positive imbalances of renewables and electricity from the market with non-fossil certificates. The proposed method enables geographically flexible hydrogen production through the power grid while utilizing renewable imbalances within actual power business operations. This paper develops solutions to an optimization problem that minimizes the hydrogen variable cost and offsets the imbalances using an electrolyzer and a battery while accounting for imbalance uncertainty. The case study in Tokyo, Japan demonstrates that imbalance compensation reduces the hydrogen variable cost by 30%. The minimum levelized cost of hydrogen (LCOH) is approximately 60 JPY/Nm${}^3$ when the electrolyzer operates at a 40% capacity factor. Furthermore, sensitivity analysis of market prices indicates that the LCOH can decline to 50 JPY/Nm${}^3$ under lower price conditions. The results suggest that market-independent cost components, such as wheeling and renewable energy charges and non-fossil certificates, remain major obstacles to further reducing hydrogen costs. Full article

The growing environmental crisis, particularly water pollution from detergents, necessitates a shift from reactive compliance to proactive eco-innovation, as current methods often fail to systematically resolve trade-offs between performance, safety, and ecology. This study develops and illustrates the application of the Evolutionary-Driven Design Framework (EDDF), an integrated methodology that combines PESTEL analysis, historical evolutionary pattern analysis, Quality Function Deployment (QFD) with a novel contradiction index, Theory of Inventive Problem Solving (TRIZ), and environmental assessment. The framework was applied to redesign a conventional laundry detergent with the objectives of zero phosphates, superior biodegradability (>85%), maintained efficacy, and controlled cost. The quantitative contradiction index matrix prioritized critical unsustainable parameters (e.g., EDTA, Cocamide DEA) for substitution over mere optimization. Through an iterative feedback loop, the process evolved from a biobased concentrate to an “enzymatic power tablet” (Concept B). This waterless, solid formulation uses sodium citrate as a biodegradable builder and an encapsulated multi-enzyme system, achieving an estimated >90% biodegradability and zero phosphates while meeting technical and economic targets. The EDDF provides a structured, anticipatory roadmap that transforms regulatory and market pressures into drivers of innovation, offering companies a promising method for designing sustainable products by proactively resolving contradictions and avoiding historical mistakes. Full article

Using data from the 41 companies listed on the Borsa Istanbul Sustainability Index between 2020 and 2024, this study examines the relationship between board characteristics, concentrated ownership structure, shareholder activism and sustainability transparency. Reports published on a voluntary basis were subjected to content analysis based on criteria selected from the Global Reporting Initiative (GRI) standards, and a sustainability disclosure score was calculated. The relationship between board characteristics, concentrated ownership structure, shareholder activism, financial metrics identified as control variables, and sustainability scores was evaluated via robust random effects (static) and System Generalized Method of Moments (System GMM) (dynamic) panel data estimators. According to the static estimation results, board meeting frequency and the ratio of female members serve as positive drivers for sustainability transparency. In the dynamic model estimates, these governance mechanisms lose their explanatory power and show no statistically observable effect. However, across both methodological approaches, firm size, which was integrated as a control factor, consistently demonstrates a robust positive correlation with levels of disclosure. These findings reveal that governance mechanisms such as the percentage of female members and meeting frequency have a short-term and marginal effect, but structural factors such as company size are the main determinants for a long-term and sustainable level of transparency in Türkiye. Consequently, market regulators should deploy policy frameworks that incentivize disclosure trajectories aligned with international frameworks while fostering voluntary reporting. Concurrently, corporate managers should look beyond mere statutory compliance and continuously embrace extensive global reporting standards. Full article

The growing penetration of renewable energy has intensified building load fluctuations, substantially increasing balancing costs. Electric vehicles (EVs) in building clusters often have considerable idle parking time beyond essential charging needs, enabling them to provide significant flexibility while meeting scheduled demands. This EV flexibility can balance intra-day load deviations and enable arbitrage in day-ahead electricity markets. However, conventional model-based approaches are fundamentally limited by their dependence on forecasting accuracy under high uncertainty from renewable generation and EV behavior. To address this, we propose a novel bi-level online optimization framework. The upper level employs a Lyapunov optimization-based algorithm that operates without predictions, making real-time decisions on total EV charging power to balance supply-demand mismatches. The lower level introduces novel flexibility metrics for individual EVs—encompassing temporal, volumetric, and cross-day dimensions—and optimizes power allocation by minimizing flexibility loss. Furthermore, we model EV flexibility as virtual queues and rigorously derive mathematical bounds on their limits, providing theoretical support for managing flexibility reserves. Rigorous analysis validates the framework’s feasibility, and comprehensive simulations demonstrate its superiority over benchmark algorithms, achieving significant cost reductions under various uncertainty scenarios. Full article

In the strategic context of China’s efforts to promote agricultural power and modernization, the key to achieving sustainable development for agricultural enterprises lies in fostering breakthrough innovations and enhancing their market competitiveness. This paper uses Chinese agricultural enterprises listed on the A-share market from 2009 to 2024 as its research sample. From the perspective of breakthrough innovation in agriculture-related enterprises, it examines the association between agricultural new quality productivity and the sustainable development of agricultural enterprises. The regression results show that, first, agricultural new quality productivity is positively associated with breakthrough innovation in agricultural enterprises. After a series of robustness tests, these findings remain valid. Second, the bootstrap mediation results indicate that this relationship operates mainly through government policy orientation and enterprise knowledge creation capacity, while the indirect effects of government resource support and independent R&D capacity are weaker and not statistically robust. Furthermore, a heterogeneity test revealed that agricultural new quality productivity has a more pronounced positive association with breakthrough innovation in regions with strong intellectual property protection and high environmental regulations, as well as in samples where corporate executives demonstrate greater environmental awareness and companies achieve higher overall ESG scores. Finally, further analysis shows that as the level of corporate green transformation increases, the enabling effect of agricultural new quality productivity on breakthrough innovation in agricultural enterprises becomes more pronounced, providing evidence on how ANQP may support the sustainable development of agricultural enterprises. Full article

Leadership competency is critical for sustainable organizational performance, yet the mechanisms driving this relationship in high power distance (HPD) emerging markets remain underexplored. Western-centric models predominantly emphasize employee engagement, often overlooking contextual institutional and cultural pathways. This study tests a dual-pathway model wherein leadership competency influences sustainable performance via psychological activation (employee engagement) and institutional embedding (organizational culture). Three-wave, multi-source data were collected from 215 leadership units in Ethiopia’s commercial banking sector and analyzed using structural equation modeling (5000 bootstrap resamples) and dominance analysis. Results reveal statistically significant but modest indirect effects. Among the two mediators, the institutional pathway (organizational culture) transmits approximately twice the relative influence of the psychological pathway (employee engagement): 24.8% versus 11.1% of total effect (β = 0.058, 95% CI [0.014, 0.109] versus β = 0.026, 95% CI [0.010, 0.046]). Dominance analysis, computed over the two mediators only, indicates culture’s greater relative explanatory weight (68.2% versus 31.8%, p = 0.003). However, leadership competency retains a substantial direct effect (64.1% of total effect), meaning the dual pathways collectively account for only 35.9% of leadership’s total influence. A robustness test using archival performance data alone yields a smaller but directionally consistent institutional indirect effect (β = 0.041, 95% CI [0.009, 0.078]), while the psychological pathway becomes non-significant, suggesting that the institutional route is robust but modest once perceptual common-source variance is removed. These findings contextualize engagement-dominant Western models by demonstrating that cultural embedding operates as a relatively stronger mediator in HPD settings. The modest absolute mediation effects and persistent direct path highlight the need for context-sensitive leadership development and suggest that additional institutional or capability-driven mechanisms warrant future investigation. Full article

The Tianbao melon (Cucumis melo subsp. agrestis) is a highly valued regional horticultural crop, yet its sustainable development is severely constrained by a narrow genetic base and widespread varietal admixture in the market. In this study, a panel of 32 Tianbao melon accessions was systematically evaluated by integrating field-based phenotypic assessment with genome-wide single-nucleotide polymorphism (SNP) analysis via whole-genome resequencing. Phenotypic analysis based on ten quantitative traits revealed low overall morphological variability, indicating limited discriminatory power of morphological traits alone. In contrast, 173,497 high-quality SNPs uncovered substantial hidden genetic differentiation, partitioning the accessions into four distinct genotypic groups. Notably, accessions TB-17 and TB-27, though nearly indistinguishable morphologically, exhibited clear genetic divergence in both phylogenetic and principal component analyses. Furthermore, a panel of 20 core SNPs with conserved flanking sequences was selected, generating unique molecular fingerprint profiles for all 32 accessions and achieving high discriminatory resolution (pairwise differences ranging from 10 to 13 SNPs). These findings demonstrate that the integration of phenotypic and genome-wide SNP data provides a robust framework for genetic diversity assessment and DNA fingerprinting in Tianbao melon, offering a scientific basis for cultivar identification, intellectual property protection, and precision breeding to support sustainable development of the regional melon industry. Full article

In green credit markets, information asymmetry and corporate greenwashing increasingly undermine the efficiency of resource allocation, while traditional assessment models relying on static, self-reported environmental data fail to impose effective constraints. To address this limitation, this paper develops a dynamic corporate carbon credit evaluation framework by integrating multiple sources of physical (hard) signals and embeds it into commercial banks’ credit management systems. Anchored in multi-source power-carbon signals (e.g., carbon intensity and compliance records), the framework integrates verifiable physical metrics with ESG disclosures via a Bayesian AHP–CRITIC weighting scheme to construct a dual-dimensional classification scheme (“Credit Rating–Green Label”). It further embeds carbon credit scores into dynamic adjustments to credit limits and differentiated interest rate pricing, forming an integrated risk management mechanism. Empirically, a stratified validation strategy is adopted. Analysis based on a sample of 3327 firms shows that the proposed framework achieves a classification consistency of 81.3%, significantly outperforming both a financial-only baseline model (46.8%) and models based on voluntary carbon disclosure (61.4%). Ablation studies further confirm that physical (hard) signal indicators contribute substantially to ranking stability. Moreover, panel regression analysis, based on 36,185 firm-year observations from 3327 firms over the period 2000–2023, demonstrates that carbon credit scores have robust predictive power for future financial distress. Overall, the proposed framework offers a sustainable, data-driven approach to green credit risk management. Full article

Combining oxygen-enriched combustion CO₂ capture technology and CO₂ hydrogenation with methanol technology, a new power–chemicals cogeneration (PCC) design is proposed for thermal power stations with CO₂ capture and utilization under the power-to-liquid concept. For material integration, CO₂ from an oxygen-enriched thermal power station and H₂ from water electrolysis using renewable power serve as raw materials for the methanol production process. O₂ from water electrolysis using renewable power is supplied to the oxygen-enriched thermal power station; thus, electricity can be saved and investment in an air separation unit can be beneficial. For energy integration, power for gas compression and heat for methanol rectification in the methanol production process are supplied by an oxygen-enriched thermal power station. The energy released from the methanol production process is fully recovered for extra power generation. Energy analysis results show that a high CO₂ capture and utilization ratio, which is defined as the ratio of the captured and utilized CO₂ to the total CO₂ generation, of 78.1% could be achieved. By integrating the system in a 600 MW thermal power station, the net power generation and methanol production of the proposed design reaches 473.1 MW and 56.1 kg/s, respectively. Economic analysis results show that the power cost is estimated to be 62.8 $/MWh, which has great market competitiveness compared to the conventional thermal power station with CO₂ capture. Due to the saved material expense and power and heat expense, the methanol cost is reduced from 1.33 $/kg to 1.20 $/kg. The H₂ expense by water electrolysis using renewable power has a decisive influence on the methanol cost. Full article

This paper analyzes the measurement of intellectual capital in the context of the increasing importance of ESG factors and current economic changes, highlighting the role of intangible assets in supporting company performance. The existing literature emphasizes the limitations of traditional models, such as the Value-Added Intellectual Coefficient (VAIC), which do not adequately capture the contribution of the modern dimensions of intellectual capital. The study is based on a quantitative approach and uses a sample of 75 companies listed on the Bucharest Stock Exchange. The data were analyzed using IBM SPSS Statistics, Version 26.0 through the application of principal component analysis (PCA), linear regression, and ANOVA tests. The results show that the traditional model does not significantly explain market performance measured by Tobin’s Q, while the modern model, based on human, structural, relational capital, and ESG factors, provides a more comprehensive conceptual perspective, although its statistical explanatory power remains limited. The paper contributes to the existing literature by proposing an extended approach to intellectual capital evaluation, adapted to the current context, and offers useful implications for investors, managers, and other users of financial information. Full article

This article examines the process of the European Union’s geopolitisation within the context of intensifying geopolitical competition and uncertainty in a shifting global order. It focuses on how this process reshapes the EU’s character as a political actor and identifies the structural constraints that limit its geopolitical agency. The study employs a conceptually oriented qualitative research design based on interpretative analysis and the triangulation of theoretical frameworks, policy documents, and selected empirical cases. The findings demonstrate that the EU’s geopolitical turn does not represent a transformation into a traditional state-centric power; rather, it constitutes a process of strategic adaptation within a complex multi-level governance system. Furthermore, geopolitisation manifests unevenly across policy domains, with the most pronounced impacts identified in enlargement, geoeconomics, and external border management. Despite rising ambitions, the EU’s capacity to act remains constrained by internal fragmentation, dependence on member states, and challenges regarding political legitimacy. The primary contribution of this article lies in its conceptualisation of EU geopolitisation as a hybrid and multidimensional process—one that is not a linear transformation towards a traditional geopolitical power, but an outcome of the interaction between regulatory, market, and strategic logics. These findings contribute to the ongoing academic debate by highlighting the necessity of theoretical pluralism when examining the EU in a geopolitical context. Full article

The transition of thermal power systems toward lower-carbon electricity raises a critical strategic question: whether to rely on cross-border electricity imports or reactivate domestic nuclear capacity under supply constraints. This study examines the trade-offs between these alternatives within a sustainable finance framework. A contingent-claim model is developed in which a life insurer provides long-term financing to a biomass-energy supplier, a thermal power plant, and a nuclear power plant operating under carbon-pricing regulation. The framework links electricity-market decisions with financial risk valuation, allowing the joint effects of biomass utilization, carbon regulation, electricity imports, and nuclear-security risks to be evaluated. The results show that biomass integration and tighter carbon regulation reduce short-term profitability in thermal generation but support long-run decarbonization. Cross-border electricity imports improve system flexibility and reduce operational volatility, strengthening the financial position of thermal producers. In contrast, nuclear-security disruptions significantly increase default risk for nuclear assets, reflecting their exposure to operational and regulatory uncertainty. By integrating energy-transition strategies with contingent-claim valuation, the analysis highlights the role of financial intermediation in shaping investment incentives and risk allocation in the electricity sector. The findings suggest that coordinated policies combining market integration, low-carbon transition strategies, and stable financing mechanisms can enhance system resilience. Full article

To meet climate goals, the automotive industry is transitioning to electromobility, reshaping vehicle model variants, market composition and therefore influencing purchasing decisions. To cover the full range of possible vehicle models for the German passenger vehicle market, a machine learning-based manufacturer agent was developed, incorporating a comprehensive technology database and historical vehicle data. Over 3000 new BEV models were generated and evaluated for possible year of market entry. Relevant models were integrated into the VECTOR21 vehicle technology scenario model to assess their market potential against competing drivetrains. The scenario results for Germany show that LFP vehicles can capture more than 18% overall market share in 2030, while Ni-rich cells remain competitive in long-range variants with up to 53% market potential by 2035. On the other hand, BEVs powered by sodium-ion batteries could reach up to 9% market potential by 2030, potentially exceeding 17% if cell prices fall below 50 EUR/kWh. However, sensitivity analysis reveals So-Ion market potential is highly sensitive to model availability, dropping to 6% or 2% in constrained scenarios, primarily replaced by LFP variants. These findings suggest that alongside cost reductions, sufficient model availability can also play a significant role in realizing the market potential of next-generation battery technologies. Full article

Previous studies on rural development and agribusiness value chains have largely examined these issues separately, with limited attention to how organizational capacity shapes value chain performance and sustainable rural development outcomes in transmigration areas. This gap is particularly important in emerging rural regions where institutional constraints, market dependency, and limited coordination continue to hinder local economic transformation. This study examines the role of organizational capacity in shaping value chain performance and its implications for sustainable rural development in transmigration areas. Using a qualitative case study approach, data were collected through in-depth interviews, field observations, focus group discussions, and secondary data analysis. The data were analyzed using thematic analysis supported by NVivo software, with triangulation applied to ensure validity and reliability. The findings reveal that although local institutions—such as village-owned enterprises (BUMDes), cooperatives, and farmer groups—are present, their organizational capacity remains limited, particularly in managerial skills, coordination, and aggregation functions. This limitation leads to inefficient value chain performance, characterized by low bargaining power, high dependency on intermediaries, high logistics costs, and limited value-added creation. Consequently, rural income remains suboptimal, social dependency is high, and environmental sustainability risks are insufficiently managed. The study contributes to the literature by demonstrating that organizational capacity acts as a structural determinant of value chain performance, which in turn influences sustainable rural development outcomes. It also proposes a capacity strengthening model integrating human resources, institutional capacity, stakeholder networks, and technology. Policy implications emphasize strengthening local institutions, promoting value chain digitalization, and implementing data-driven interventions. The study highlights that strengthening organizational capacity is a strategic pathway toward achieving sustainable rural development, particularly in emerging rural contexts such as transmigration areas. Full article

Property taxation serves as a critical instrument for fiscal efficiency and equitable distribution, yet implementation faces significant challenges including valuation inaccuracies, insufficient administrative capacity, and diminished public trust. Indonesia’s Land and Building Tax (PBB-P2) utilizes the Sales Value of Taxable Objects (NJOP) as an administrative proxy for market value, which frequently deviates from actual land prices. These disparities create horizontal inequities, diminish local revenue potential, and generate taxpayer resistance, especially in decentralized regions with constrained technical resources. This research presents the Spatially Adaptive Land Value Determination (SALAD) model as a comprehensive framework for enhancing property tax governance and modernizing fiscal cadastre systems. Unlike conventional mass appraisal methods, SALAD integrates spatial zoning, assessment ratio analysis, land-use characteristics, and the Index of Developing Villages (IDM) with socio-economic indicators including purchasing power and community fiscal behavior. The model incorporates structured social validation to improve public acceptance. Field validation in Lebak Regency employed mixed-methods design with surveys of 75 respondents across 20 villages and interviews with village heads and tax officials. Results demonstrate that transparency, fairness, and visible public benefits are essential for community support. Validation indices vary significantly by IDM category (ANOVA: F = 4.23, p = 0.03 for economic; F = 3.81, p = 0.04 for institutional), confirming that the SALAD model’s adaptive mechanism is empirically grounded. Full article