Search Results (4,199)

Carbon finance is widely proposed as a route to improving agroforestry viability, yet the literature appears divided, as some studies find it decisive and others insufficient. The current review asks whether that divide reflects a genuine economic variation or inconsistency in how carbon prices have been sourced and reported. 56 studies from 37 countries were selected from 471 records identified across three databases and coded across 22 variables, including system type, accounting method, implementation status, and carbon price. The latter was classified into four credibility tiers: transacted, benchmarked, assumed, or unstated. Only 14% of papers reported a price any project had actually paid, and just under half relied on an assumed, unsourced figure. Studies that concluded either that carbon pricing played a decisive role or that it was insufficient were based on price data of comparable reliability, with estimated prices appearing with similar frequency in both groups. Half of all papers never tested whether carbon payment changed any financial or land-use outcome, and among those that did, fewer than half found it decisive. Moreover, carbon rate measurements remained broadly consistent with independent global estimates. The variation between studies is mainly in the way the prices are determined, rather than in the carbon measurements. Therefore, future studies should clearly state how the carbon price is determined. Full article

General-text translation is converging toward near-full automation by large language models (LLMs), yet the translation of OTT multimedia content still demands a deliberately designed division of labor between humans and AI; this asymmetry is the starting point of this review. Korea occupies a distinctive position in this transformation: the global success of Korean content has created an asymmetric, outbound-heavy translation market in which linguistically complex Korean-source material must be localized into dozens of languages at speed, while the domestic language-service industry undergoes a structural shift from human translation to machine-translation post-editing. This paper reviews three research streams that have developed largely in isolation, namely LLM translation quality and automatic evaluation, human–AI collaboration and knowledge-worker productivity, and audiovisual translation, and integrates them through an operations-management input–process–output–outcome framework tailored to the Korean OTT context. The review finds that LLM-based post-editing improves draft quality and productivity, but that honorific register, culture-bound expressions, and speaker-relational meaning, all pervasive in Korean dialogue, lie largely outside current LLM competence. Three testable propositions are derived on how Korean-specific linguistic density conditions the productivity–quality trade-off, and a research agenda is proposed with implications for job redesign and capability development in language service providers, OTT platforms, and language-focused higher education. Designing this division of labor is a management problem before it is a technological one, and its answers lie where language expertise and operations management meet. Full article

This study examines a two-echelon cross-border e-commerce (CBEC) supply chain under the joint constraints of technical barriers to trade (TBTs) and tariffs. To capture the cumulative nature of foreign-market access, the degree of trade barrier breakthrough is modeled as a continuous-time state that converts technological innovation and compliance updating into sustained market access. A differential game is developed to compare centralized, decentralized, and modified two-part tariff contract decisions. The main conclusions are as follows: (1) Decentralized decision-making causes insufficient technological innovation and compliance updating, reducing the steady-state breakthrough level and total supply chain profit. (2) The modified two-part tariff contract internalizes the benefit–cost mismatch between the manufacturer and the retailer, reproducing the centralized investment path and total profit. (3) Government support strengthens barrier-breaking incentives, while the effect of tariffs on decentralized investment depends on the balance between subsidy support and upstream tariff pass-through; tariffs nevertheless reduce the integrated channel margin and may invalidate the contract beyond a critical threshold. (4) Product-life-cycle analysis shows that technological innovation dominates during technology dividend periods, while compliance updating becomes more valuable during bottleneck periods. (5) Multi-scenario simulations and ±20% one-factor perturbations preserve the ranking C = MT > D. These findings extend dynamic supply chain coordination research by linking investment, realized market access, and contract incentives under dual trade barriers, and provide implications for the long-term economic sustainability of CBEC supply chains. Full article

Climate-related production variability and increasing market uncertainty pose significant challenges for Mediterranean olive systems. This study examines the long-term production dynamics, market vulnerability, and ecological functions of Mediterranean olive systems under climate change through an integrated assessment combining statistical production analysis, descriptive economic analysis, and a structured ecological literature synthesis. Olive and olive oil production trends were analyzed for Greece, Spain, Italy, and Portugal using FAOSTAT data (1960–2020), together with European Commission statistics (2010/11–2021/22) on production, prices, and trade. The results reveal significant long-term production trends, with greater year-to-year fluctuations observed in several countries, particularly after 2010. These fluctuations may reflect the combined influence of climatic variability and structural changes affecting Mediterranean agricultural systems, although their relative contribution was beyond the scope of the present study. Despite maintaining a leading position in global olive oil production and trade, the European Union recorded a 52% increase in export volume and a 125% increase in export value, highlighting both market expansion and increasing exposure to international market dynamics. The ecological synthesis indicates that traditional and low-input olive groves provide important ecosystem functions, including biodiversity conservation, soil protection, water regulation, and soil-carbon maintenance, supporting the long-term sustainability of Mediterranean olive systems. Overall, the findings highlight the need for integrated adaptation strategies combining environmentally sound land management, value-chain coordination, and policy support to strengthen the long-term sustainability of Mediterranean olive systems. Full article

The European Union now routinely leverages economic governance to tackle strategic vulnerabilities caused by geopolitical rivalry, foreign dependencies, and supply chain shocks. This article analyses this shift, exploring how the EU adapts its economic toolkit and what restricts its capacity to act as a geoeconomic power. It builds an analytical framework connecting external pressures, strategic vulnerabilities, policy choices, and institutional barriers. Methodologically, the study combines qualitative document analysis of EU policy frameworks with trade metrics and evidence from the Geoeconomic Interconnectivity Index. The findings show a clear expansion in investment screening, anti-coercion tools, targeted industrial policy, and supply-chain diversification—all aimed at safeguarding core sectors and curbing asymmetric exposure. These steps mark a departure from purely regulatory-market logic towards a hybrid model blending market openness, defensive controls, and capacity-building. Persistent institutional splits, conflicting national priorities, technological gaps, and reliance on foreign markets limit the effectiveness of this transition. Ultimately, the EU’s evolving geoeconomic stance aims not for total self-sufficiency, but for the deliberate, strategic management of interdependence. Full article

China’s Carbon Emissions Trading (CET) Pilot Policy may alter corporate information environments and demand for auditors with industry-specific experience. Using the staggered launch of regional carbon markets as a quasi-natural experiment, this study examines whether policy exposure changes auditor industry specialization among Chinese A-share listed firms from 2010 to 2022. Specialization is measured by the logged share of an auditor’s client assets in a given industry; it does not represent an audit-fee premium or direct carbon-assurance expertise. Staggered difference-in-differences estimates show that CET pilot exposure increases this specialization measure. The result is robust to event-study, placebo, propensity-score-matched, and Callaway–Sant’Anna specifications. Channel regressions are consistent with financing-constraint and leverage pathways, while evidence for controlling-shareholder fund occupation is weak and not interpreted as causal mediation. Pairwise tests identify regional differences but no statistically significant ownership or pollution-intensity differences. By linking carbon-market policy to auditor-client matching, the study shows that sustainability policy can reshape the professional-service infrastructure supporting firms’ low-carbon transition. Allocating industry-experienced auditors to policy-exposed firms may strengthen the credibility and comparability of sustainability-related financial information and support regulatory monitoring. These implications concern the institutional capacity for sustainable development; the study does not directly measure sustainability performance or carbon-assurance quality. Full article

Peru holds a prominent position in international fresh asparagus trade, with a strong export profile and a well-established presence in global markets. Nevertheless, sustaining this position requires diversification toward a more resilient and sustainable portfolio of destination markets. This study assessed the global competitive sustainability of Peru’s asparagus agro-export industry during 2010–2024. Official data from the World Bank, Veritrade, CEPII, and the Peruvian Ministry of Foreign Trade and Tourism (MINCETUR) were analyzed using a quantitative longitudinal single-case study design with descriptive and explanatory components. The results show that the Herfindahl–Hirschman Index (HHI) for Peruvian asparagus exporters remained low, indicating limited firm-level concentration and a relatively diversified supply structure. Thus, Peruvian asparagus exports did not depend on a single dominant firm but were distributed among multiple exporters. In contrast, the HHI for destination markets revealed high geographic concentration of demand. Regarding competitiveness, Peru maintained a strong net-export position, with trade competitiveness index values close to 1. The Revealed Symmetric Comparative Advantage (RSCA) index showed favorable performance in markets such as the United States, Spain, The Netherlands, and the United Kingdom, although this advantage had not yet reached full structural stability. The gravity model, estimated using EGLS with Panel-Corrected Standard Errors (PCSE), identified destination-country economic size as the most important determinant of Peruvian asparagus exports. Geographic distance constrained exports, whereas trade agreements did not show a consistent statistical effect. Potential expansion opportunities were identified in China, Australia, Norway, Ecuador, Sweden, Austria, Russia, Poland, New Zealand, and Romania. Consequently, the competitive sustainability of Peruvian asparagus depends not only on preserving export leadership but also on reducing destination-market concentration, improving logistical efficiency, expanding production capacity, and directing trade policy toward markets with favorable economic fundamentals. Full article

Increasing variability in electricity production and demand contributes to greater electricity price volatility across different markets. The effective implementation of business processes related to broadly defined electricity trading therefore requires reliable electricity price forecasts. Consequently, electricity price forecasting has grown in both importance and research interest. This article presents an in-depth literature review of short-term point electricity price forecasting at the native temporal resolutions of the reviewed markets, primarily hourly and 30 min intervals, with selected studies using 15 min and 5 min intervals. The review concerns forecasts of individual market-interval prices and does not address forecasts of daily aggregated prices. The analysis covers the input data used in forecasting models, the main forecasting approaches, modelling techniques, and error measures. Forecast quality is examined with respect to market characteristics, forecasting methods, and explanatory variables. General trends in the reported results are identified, together with descriptive relationships among selected error measures. Particular attention is given to the RMSE-to-MAE ratio, referred to in this review as the Error Dispersion Factor (EDF), which is treated solely as a descriptive summary of the relative inequality of absolute forecast-error magnitudes in a given sample. The article concludes with findings and recommendations concerning best practices in electricity price forecasting. The review differs from broader conceptual and market-specific surveys by focusing narrowly on short-term point forecasts for individual market delivery intervals and by providing a structured quantitative synthesis of studies published between January 2021 and May 2026. Full article

Consumers’ risk attitudes shape how they evaluate and trade off product attributes, yet most preference estimation approaches overlook risk attitudes, assuming risk neutrality. The resulting preference structures may fail to capture the heterogeneity essential for effective market segmentation and product strategy. We propose a risk-driven preference learning framework that reconceptualizes risk attitude as an integral factor shaping preference structures. Its core is a risk-contingent value function in which risk attitude determines how attributes are traded off. This function infers risk attitudes through deviations from full compensation among attributes under risk neutrality, endogenizing risk-attitude inference within preference estimation, and yields preference structures from behavioral data. The method also identifies distinct preference subtypes within the same risk-attitude category. Validated on 114,317 vehicle reviews from Edmunds, an automotive e-commerce platform, the approach achieves strong in-sample fit to behavioral data. Results show that risk-averse, risk-neutral, and risk-seeking consumers exhibit different preference structures, and the risk-averse group shows pronounced internal heterogeneity. The proposed framework offers a structurally interpretable tool for intelligent decision support in consumer segmentation and product strategies. Full article

The growing adoption of renewable energy and small-scale power producers has increased the need for reliable and transparent peer-to-peer (P2P) energy trading. Traditional centralized markets often struggle with high transaction fees, limited transparency, and a greater risk of manipulation, which restrict efficient energy distribution. To overcome these issues, this study presents a decentralized P2P trading framework that implements a fully functional blockchain-based trading system with smart grid simulation and demonstrates a prototype machine learning forecasting module (Random Forest, 84% accuracy) designed for future integration. The trading mechanism is developed using Ethereum smart contracts and a custom ERC-20 token, the TUM Energy Coin (TEC), enabling secure and traceable energy exchange. System security is strengthened through dual confirmation steps, role-based access control, and consensus-driven market clearing. A double-sided auction model is used to match buyers and sellers fairly. Real-time grid behavior such as fluctuating loads, prosumer generation, and consumer demand is modeled using MATLAB Simulink to reflect realistic operating conditions. To enhance decision-making, a Random Forest model is integrated for load forecasting and dynamic pricing, achieving an accuracy of 84%. The simulation results show improved transaction throughput, more stable pricing, and strong resilience against false-data injection attacks. The primary novelty of this work lies in (1) an entirely operational and validated blockchain-trading system simulation with synchronized time using Simulink, (2) a working Random Forest forecasting tool demonstrating feasibility for incorporation in the future, and (3) an analysis of the system’s robustness in the case of FDIA attacks. The authors point out that the ML component used is a prototype and not yet integrated into the functioning block chain. Full article

Background: Highly pathogenic avian influenza (HPAI) poses a critical global threat to both the poultry industry and public health. Although Morocco currently maintains HPAI-free status, the country faces substantial risk due to its location along major migratory flyways and its extensive commercial trade networks within the poultry sector. Available data indicate that the links between live bird markets, production farms, and related facilities in the poultry sector constitute a pivotal determinant of disease epidemiology. This study aimed to analyze these movements and determine how they can influence the spread of the disease and to guide policymakers in developing effective risk-based surveillance and control strategies tailored to the local context.: A questionnaire-based cross-sectional survey was conducted across the Casablanca-Settat region, including nine provinces and 138 municipalities, to investigate the movement patterns within the poultry sector in this region. Social network analysis (SNA) was employed to construct a movement network, and findings were spatially visualized using Geographic Information Systems (GIS) and analyzed through network analysis in R.: A total of 945 transport routes were recorded in 126 municipalities. Centrality measures identified three predominant network nodes exhibiting high degree and betweenness centrality values. Our findings indicate that although the network has a low density, the transmission of IAHP remains critical due to frequent bidirectional links and a heterogeneous network structure. The high concentration of movements by a few “hub” municipalities leads to an early emergence and rapid dissemination.: The identification of highly influential nodes allows veterinary authorities to prioritize and target surveillance activities toward municipalities with the greatest likelihood of disease introduction or persistence. The network’s structural connectivity suggests a theoretical potential for rapid HPAI spread, underscoring the importance of the frequent bidirectional links identified between municipalities. This protects both Morocco’s poultry industry and public health. Full article

Adoption of peer-to-peer (P2P) trading is very challenging, mainly due to numerous issues and limitations such as lack of trust in the concept and awareness of the technical, economic and social benefits. This paper aims to understand how blockchain technology can address the current issues/limitations of P2P distributed solar energy (DSE) trading. A series of semi-structured interviews were conducted with 23 community energy stakeholders to confirm and expand the stakeholder issues identified in the literature review. A case representing community energy projects was selected to (1) develop and implement a blockchain system and (2) evaluate its ability to eliminate (or reduce) stakeholder issues and meet stakeholder expectations. A blockchain-enabled P2P trading platform was developed using an Ethereum backend. The system clearly demonstrated its ability to deliver full or partial solutions to 12 stakeholder issues. Two stakeholder issues are unable to be addressed via the blockchain platform since they uncovered the weaknesses of blockchain technology. The P2P trading platform has also demonstrated its ability to facilitate decentralized trading and data management. The outcome of this study indicates the areas of P2P trading projects that can be improved by the application of blockchain technology. Full article

Sustainable agriculture is critical to sustainable development and climate resilience, yet evidence of its multidimensional environmental, social and economic benefits and trade-offs remains limited, especially in regions most vulnerable to climate change. This study addresses this gap in Vietnam’s Mekong Delta (MKD), where decades of intensive rice farming has bolstered rice yields at the expense of environmental quality and farmers’ health. This study presents a multi-criteria analysis (MCA) comparing organic rice (OR) and conventional rice (CR) farming systems in the MKD. We applied a weighted sum model to evaluate the environmental, social and economic performance of the two production systems. The assessment drew on quantitative and qualitative primary data collected through stakeholder engagements and field measurements from Vinh Long province between 2023 and 2025, as part of the OrganoRice project. Overall, OR farming performed cumulatively better (0.663 and 0.695) than CR farming (0.496 and 0.484). OR scores were higher across most sub-criteria, particularly “farmers’ income” and “biodiversity”. However, CR outperformed OR for “rice yield” and “farmers’ workload”. Comparable water and soil quality scores, due to the presence of pesticide residues in both systems, suggest that the environmental performance of OR farming was likely dampened due to cross-contamination from surrounding or upstream non-organic farms. The expansion of OR farming in the MKD has the potential to enhance environmental, social and economic performance of rice production in the region. However, in order to achieve the full scope of these benefits, short-term measures should aim to reduce the financial risks of conversion for farmers, ensure access to affordable organic inputs, increase farmer training, ensure reliable premium contracts for rice producers and support them in accessing organic markets. Longer-term measures must improve irrigation water management and infrastructure to minimise cross-contamination risks. Coordinated marketing campaigns are needed to develop a trusted regional brand for organic rice from the MKD to create new opportunities in international and domestic markets. Moreover, long-term monitoring of post-transition outcomes is important to capture the full impacts of conversion. As OR cultivation continues to expand across the MKD, evidence on its benefits and trade-offs is essential to guide this transition effectively. This study provides that evidence, offering a context-specific, multidimensional evaluation to inform OR policy and practice in the region. Full article

Carbon pricing has emerged as a central policy tool for addressing climate change and advancing corporate environmental responsibility, yet its impact on firm-level investment and capital allocation remains insufficiently understood, particularly in emerging economies. This study examines whether emissions trading systems (ETS) influence corporate investment behavior and the reallocation of capital, using China as a representative case within the Asia-Pacific region. Employing a panel dataset of 5000 Chinese listed firms (approximately 80,000 firm-year observations) over the 2008–2023 period and a difference-in-differences framework, we identify the causal effect of carbon pricing on corporate investment decisions. The results show that firms exposed to carbon pricing experience a statistically significant reduction in investment following policy implementation. This effect is more pronounced in high-emission industries and operates through declines in profitability and tighter financial conditions. Asset-weighted measures indicate that the adjustment is concentrated among larger firms, and industry-level analysis shows that reductions are disproportionately driven by high-emission sectors. This pattern of heterogeneous investment responses is consistent with carbon pricing influencing investment allocation across firms; however, we do not directly observe the subsequent destination of capital or whether reduced investment in exposed firms is transferred toward cleaner activities. These findings provide new micro-level evidence that carbon markets shape corporate environmental management and real economic decisions by altering firm incentives, cost structures, and expectations. The study contributes to the literature by linking environmental policy tools to firm-level investment behavior and offers practical insights for policymakers and managers navigating the low-carbon transition in emerging economies. Full article

This article examines the moderating effect of the economic cycle on the relationship between tax avoidance and the value relevance of Brazilian publicly traded companies, through the lens of Signaling Theory. The sample comprises 278 companies, yielding 2327 firm-year observations over the period from 2014 to 2024. Multiple panel regressions were estimated using the fixed effects method with robust standard errors. The results indicate that the Brazilian market places greater values on more conservative tax avoidance strategies, associating them with managerial efficiency and value creation. In contrast, companies exhibiting low or excessive levels of tax aggressiveness are penalized, particularly during periods of economic expansion, when the quality of financial information becomes especially important. The study incorporates economic fluctuations, characterized by alternating periods of recovery and prosperity and periods of relative stagnation or recession. The findings also show that, during recovery periods, the market is more tolerant of aggressive tax strategies, reflecting companies’ need to preserve cash. Overall, the results reinforce the view that the relationship between tax avoidance and value relevance is non-linear and contingent on the macroeconomic context. Although an overall moderating effect (H₂) was observed, H₃ was rejected because no statistically significant moderating effect was identified during contraction and recession phases. These findings provide insights for investors, regulators, and managers into how tax planning is perceived across different stages of the economic cycle, thereby broadening the understanding of corporate governance and value creation in emerging markets. By examining the moderating effect of the economic cycle, this study contributes to the literature on tax planning and firm valuation in developing markets, representing an original contribution to the field. Full article