Search Results (4,080)

Proximity to transportation infrastructure is an amenity that adds market value to residential property. However, not all infrastructure adds market value equally. For example, the empirical evidence suggests proximity to rail infrastructure adds more market value than proximity to pedestrian infrastructure, even though surveys show a willingness on the part of buyers to pay for the latter. Further, proximity to transportation infrastructure such as airports may subtract market value from residential property due to the disamenity of noise. In order to isolate the amenity or disamenity effect of proximity to airports, this study adopts a multilevel approach to residential property transactions, which encompasses the complement of air, bus, pedestrian, and rail infrastructure in an entire region. Analysis of thirteen years of residential property transactions near two international airports advances knowledge on the amenity effect of proximity to airports in light of the amenity effect of pedestrian infrastructure. Unsurprisingly, subregional differences in the amenity effect of proximity are evident due to differences in land use near the respective airports. The latter result suggests airports are not necessarily detrimental to the accrual of value in proximate residential property markets. The latter result also calls into question public policy interventions to mitigate regional disamenity effects of airport proximity evident elsewhere in the empirical literature. Full article

Within the framework of the carbon market mechanism, corporate investments to secure forestry carbon credits play a pivotal role in mobilizing social capital for ecological construction and realizing the value of ecosystem services. This study integrates information decision theory and Bayesian network analysis to simulate corporate investment decision-making for forestry carbon sequestration within China’s carbon market. Through this approach, we explore the decision-making mechanisms behind corporate investments in forestry carbon sequestration and conduct decision simulations. The findings reveal several key insights: (1) External factors, including tax incentives, consumer preference for low-carbon products, and societal environmental awareness, exert a significant impact on the valuation of forestry carbon sequestration investments. Internally, the challenge posed by technological costs in achieving emission reductions significantly influences the evaluation of forestry carbon sequestration investments. (2) Investment value judgments are shaped by the nature of the decision-making problem, which inherently involves a synergistic relationship. (3) Corporations recognize the importance of forestry carbon sequestration in reducing the costs of emission reduction, formulating low-carbon development plans, expanding investment opportunities, and enhancing the quality of forestry carbon sequestration. (4) The collective value judgment of corporates regarding forestry carbon sequestration in terms of cost reduction for emission reduction, low-carbon development planning, investment opportunity expansion, and corporate image enhancement significantly influences their investment decisions in forestry carbon sequestration. (5) Corporate investment decisions exhibit a strong preference for market-based pricing and risk-sharing mechanisms. Consequently, enhancing the carbon information disclosure system and the carbon market trading mechanism, as well as establishing price protection and income stabilization expectations for forestry carbon sequestration, can encourage corporates to make investments in this area. This not only aids in the green, low-carbon transformation of businesses but also addresses the challenge of positive externalities associated with forestry carbon sequestration through market-oriented solutions. Full article

Sustainability is increasingly viewed as a crucial element shaping contemporary transport policies and operational strategies. This article presents a comprehensive economic evaluation of Polish international road freight carriers in 2024 compared with the results from previous years. It introduces an original and innovative method for assessing the economic condition of transport companies, based on real-time operational data and an integrated demand–supply diagnosis of the road freight market, which also supports macroeconomic forecasting. The study covers carriers operating in Eastern and European Union (EU) markets and spans an exceptionally long period (2009–2024), enabling the identification of long-term trends across four business cycles. Unlike existing research, which typically analyses isolated profitability or efficiency indicators, the proposed method offers a universal and contextual framework linking economic outcomes with detailed company characteristics. It provides a structured assessment of cost components across eight categories and reveals relationships between economic performance and factors such as transport directions, fleet utilisation, company size, diversification strategies, and region of origin. The analysis includes a comparison of two carrier groups, statistical profiling of companies, and average vehicle kilometre costs by company size and transport direction. This contextual analysis, including a comparison between the Polish and Lithuanian markets, strengthens the credibility of the results by situating them within a broader comparative framework and supporting a more accurate interpretation of the observed patterns. The pilot nature of this cross contextual approach constitutes an additional contribution of the study, providing a basis for future comparative research on the functioning of transport enterprises across the EU and the Eastern markets. In addition, the assessment incorporates a pilot comparative study of external factors influencing the transport market, conducted among Polish and Lithuanian companies. This multifaceted and internationally unprecedented approach strengthens the interpretability of the results and offers a robust foundation for strategic decision-making and organisational adaptation in an increasingly competitive and uncertain transport market. Full article

This paper develops a novel hybrid framework that integrates clustering-enhanced Particle Swarm Optimization (PSO) with stretching techniques to solve Markowitz’s quadratic portfolio optimization problem. The proposed approach avoids local optima traps that plague traditional optimization methods, while the stretching function modifications enhance the algorithm’s global search capabilities. The framework comprises four distinct algorithmic variants: a baseline SWARM PSO with stretching algorithm, and three clustering-enhanced extensions incorporating Hierarchical, K-means, and DBSCAN techniques. These clustering enhancements strategically group assets based on risk–return characteristics to improve portfolio diversification and risk management. Implementation in R enables comprehensive analysis of portfolio weight allocation patterns and diversification metrics across varying market structures. Empirical validation using daily price data from six major international stock market indices spanning January 2020 to December 2025 demonstrates the framework’s generalization capability in constructing buy-and-hold investment portfolios. The results reveal significant market-specific algorithmic effectiveness, with K-means variants achieving competitive efficacy in Eurostoxx and Belgian markets, DBSCAN demonstrating strong effectiveness in Chinese equity markets, Hierarchical clustering showing robust results in Indian market conditions, and the baseline SWARM algorithm exhibiting relative efficiency in French and Danish indices. Performance evaluation encompasses comprehensive risk-adjusted metrics, including Portfolio Return, Volatility, Sharpe Ratio, Calmar Ratio, and Value at Risk, providing portfolio managers with an adaptive, market-responsive optimization toolkit. Full article

Financial regulation assumes that parent firms reliably support distressed subsidiaries during crises. We test this assumption with evidence from the 2007–2009 financial crisis and find that parent support was selective rather than reliable. Using novel measures of sibling distress and granular parent-affiliate funding flows, our findings reveal that capital allocation within bank holding companies (BHCs) disproportionately favored stronger affiliates. The results show that BHCs channeled capital toward more liquid and resilient subsidiaries while limiting support to weaker ones. Profitable parents became increasingly selective under stress, and nonbank subsidiaries emerged as critical internal liquidity providers when external markets froze. This selective reallocation highlights a gap between regulatory doctrine and actual behavior: intra-group capital allocation mechanisms can amplify systemic stress rather than mitigate it. By examining overlooked internal market dynamics during this major financial crisis, the study offers insights for strengthening financial stability against future systemic shocks. Assessing parent firm strength alone appears insufficient. Effective crisis prevention requires supervisory frameworks that monitor sibling fragility across conglomerates, evaluate the liquidity roles of nonbank affiliates, and stress test intra-group capital flows. Full article

This study investigates how financial literacy, FinTech adoption, and financial attitudes shape economic decision-making among millennials in Lebanon, a crisis-affected emerging economy. The study examines whether enhancing financial literacy can strengthen economic resilience through improved financial behavior, with financial attitudes acting as a mediator. Guided by Behavioral Finance Theory, the study employs a quantitative approach using data from 390 Lebanese millennials collected via a structured questionnaire. Structural equation modeling was applied to test direct and mediating effects. Both financial literacy and FinTech adoption were found to significantly influence millennials’ financial behavior, with financial literacy emerging as the stronger predictor. The findings also revealed that financial attitude significantly mediates the link between literacy and behavior, suggesting that financial knowledge alone is insufficient without attitudinal reinforcement. This study fills a critical empirical gap in the MENA region by offering evidence from a highly under-researched, crisis-affected emerging market. It introduces an integrated model combining technological, cognitive, and attitudinal dimensions of financial behavior. The study offers practical implications for policymakers, financial institutions, and international development actors seeking to strengthen financial inclusion and household stability in similar turbulent contexts. Full article

This research was conducted on small farms in Republika Srpska, an entity of Bosnia and Herzegovina. Data were collected through direct interviews on five farms, each with 8–15 dairy cows, which at some point diversified their production from selling raw milk to processing and selling fresh cheese. Due to low productivity and limited economies of scale, calculated indicators such as net present value, internal rate of return, and payback period are insufficient to consider traditional milk production economically justified. However, further analysis using Monte Carlo simulations and the real options method demonstrated that diversifying production into cheese processing is economically feasible, as confirmed by the strategic net present value calculated using Black–Scholes and binomial approaches. The results indicate that small, extensive family farms should focus on higher levels of product finalization. Although their production volumes are limited and they are not cost-competitive in raw milk markets, they gain a competitive advantage by adding value through their own labor and selling products via short supply chains. Diversification enables these farms to improve profitability, achieve financial stability, and strengthen market positioning, demonstrating that value addition is essential for the sustainability of small-scale dairy enterprises. Full article

As global climate change intensifies and the Paris Agreement advances low-carbon transformation, frequent local policy adjustments under China’s dual carbon goals have made climate-policy uncertainty a core challenge for corporate sustainability. Environmental, social, and governance (ESG) performance has grown exponentially in international capital markets, evolving from a peripheral concept to a key investment decision-making dimension. This study uses China’s carbon peaking and neutrality policies as a quasinatural experiment, applying the difference-in-differences (DID) method to the panel data of Chinese A-share listed companies (2014–2023). Taking high-energy-consuming enterprises as the treatment group, this study identifies net policy effects via the interaction of policy and time dummy variables. The results show that carbon peaking and neutrality policies significantly suppress the ESG performance of energy-intensive firms; mediating effect tests confirm that the policy harms ESG performance by increasing uncertainty. Implications include enhancing policy transparency and predictability and optimizing resource allocation to strengthen ESG resilience. Future research should focus on micro-level policy indicators and long-term effect tracking to provide theoretical and practical support for synergizing dual carbon goals with high-quality economic development. Full article

After numerous false starts, the global microalgae industry is re-emerging, driven by its potential to address critical challenges in food and nutrition, sustainable energy, nutraceuticals, cosmetics and pharmaceuticals, and climate change mitigation. Although technical advances in microalgae production show value adding potential, progressing from innovation to product launch and competitiveness is complex. It requires an integrated understanding of technology readiness, regulatory compliance, financial necessities, and market competition. This study presents a novel analytical framework underpinning a data-enabled, evidence-based approach to navigating the innovation pathways to market and beyond. The framework integrates value-add opportunities, identifying key stages faced in pre-competitive (including Technology Readiness Level (TRL), R&D spend, and patent trends), and competitive market stages (including product launches, product claims, market size, market share, growth/maturity, international markets, distribution channels, sectoral profile, and competitive landscape), aligned with regulatory requirements. Although not without limitations, such as incomplete data for emerging products, as well as reliance on secondary sources for product stage determination and market size estimates which can influence the accuracy of TRL classification and market potential estimates. This integration of multiple analyses can help in identifying market opportunities and business competitiveness via product, business, and industry level analyses in the pre-competitive (pre-market launch) and competitive (on market) landscapes. Building on the team’s interdisciplinary experience of developing interactive dashboards for food and beverage industries, and microalga processes, this paper provides an overview of the framework, which was designed to guide businesses and researchers in an emerging microalgae industry through the complex landscape of product development along regulatory and commercial pathways. Full article

Many companies in the mining industry include decarbonization of production among their key strategic goals as part of their internal sustainability strategy. This need is driven by a number of factors: stricter regulation in the area of carbon footprint (introduction of carbon taxes, emissions quotas, reporting requirements); sustained growth in demand for electricity and rising market prices; economic feasibility—the need to optimize operating costs and improve energy efficiency. This study provides a comprehensive technical and economic justification for implementing a hybrid power supply system—combining a solar power plant (SPP) and a gas engine power plant (GPP)—at Solidcore Resources’ Varvarinsky hub in Kazakhstan. The methodology includes modeling the energy balance of the real asset (156.9 GWh of annual energy consumption), calculating the output of a 22.6 MW SPP based on local GHI/PR/η parameters, forming and determining the adaptability coefficient Kₐ (proportion of PV in total monthly electricity generation), conducting an economic assessment (NPV, payback period, sensitivity), and inventorying CO₂ emissions under Scope 1–2. The SPP provides approximately 41.3 GWh of electricity generation per year, with an average annual K_a = 0.263; the 40 MW installed capacity of the gas piston power plant covers the residual demand, forming a stable daily and seasonal balance. The project demonstrates a positive NPV (After Tax) = USD 23.65 million with an estimated payback period of 10 years, while the cost of energy in extraction and processing is reduced by almost three times, and the total reduction in CO₂ emissions will be 51%. Thus, hybridization of energy supply systems is a practical compromise between reliability and decarbonization. Determining the adaptability coefficient K_a allows the flexibility of the system to be taken into account, shows how effectively the new energy system uses renewable energy sources, and can be used to optimize the operation of the energy system to achieve the company’s internal sustainable development goals. Full article

With the advancement of the dual carbon goals and the rapid increase in the proportion of new energy installations, the power system faces multiple challenges including insufficient flexibility resources, intensified fluctuations in generation and load, and reduced operational safety. Integrated energy systems (IESs), serving as key platforms for integrating diverse energy sources and flexible resources, possess complex internal structures and limited individual regulation capabilities, making direct participation in grid dispatch and market interactions challenging. To achieve large-scale resource coordination and efficient utilization, this paper investigates external characteristic modeling and cluster aggregation optimization methods for IES, proposing a comprehensive technical framework spanning from individual external characteristic identification to cluster-level coordinated control. First, addressing the challenge of unified dispatch for heterogeneous resources within IES, this study proposes an external characteristic modeling method based on operational feasible region projection. It constructs models for the active power output boundary, marginal cost characteristics, and ramping rate of virtual power plants (VPPs), enabling quantitative representation of their overall regulation potential. Second, a cluster aggregation optimization model for integrated energy systems is established, incorporating regional autonomy. This model pursues multiple objectives: cost–benefit matching, maximizing renewable energy absorption rates, and minimizing peak external power purchases. The Gini coefficient and Shapley value method are introduced to ensure fairness and participation willingness among cluster members. Furthermore, an optimization mechanism incorporating key constraints such as cluster scale, grid interaction, and regulation complementarity is designed. The NSGA-II multi-objective genetic algorithm is employed to efficiently solve this high-dimensional nonlinear problem. Finally, simulation validation is conducted on a typical regional energy scenario based on the IEEE-57 node system. Results demonstrate that the proposed method achieves average daily cost savings of approximately 3955 CNY under the optimal aggregation scheme, reduces wind and solar curtailment rates to 5.38%, controls peak external power purchases within 2292 kW, and effectively incentivizes all entities to participate in coordinated regulation through a rational benefit distribution mechanism. Full article

Analysis of game management and trophy game populations in Osijek-Baranja County shows that this region is one of the most valuable hunting areas in Croatia, with rich populations of red deer, roe deer, and wild boar, as well as stable annual population growth. The methodological framework included products and services in hunting based on data analysis from the Croatian Hunting Association, big-game trophy records (ETD forms), the Central Hunting Register, and the official price list of game culling and hunting services. Data on harvests and trophy values indicate long-term population stability and high economic potential of hunting, with red deer generating the highest total revenue (EUR 7.29 million), while roe deer and wild boar contribute to overall stability and harvest volume. The total trophy value over 12 hunting seasons reaches EUR 11.99 million, underscoring the economic importance of hunting tourism for local communities. Differences among hunting ground users suggest that private companies and the state company Croatian Forests Ltd. often achieve higher trophy values, while county hunting associations report more modest results. However, regression analysis shows there is not a strong statistical correlation between management structure and trophy outcomes, highlighting the significant influence of ecological and spatial factors on game quality. International hunters, primarily from Germany and Austria, represent a key segment of demand, confirming the market potential for further development of hunting tourism. Despite the rich natural base, results indicate the need for better marketing approach, digital visibility, and integration of hunting products with other forms of tourism, such as gastronomic, wine, and nature tourism. Effective positioning of Croatia as a competitive hunting destination requires adaptation to contemporary market trends and adherence to international sustainable management guidelines (FAO, ELC, CBD). In conclusion, hunting in Croatia represents an important non-wood forest product and a vital resource for rural and economic development. Sustainable population management, quality promotion, and integration of traditional and innovative practices are essential for reinforcing biodiversity conservation, supporting community livelihoods, and strengthening Croatia’s role in the European and global hunting-tourism market. Full article

Organic fruit and vegetable production in the United States is increasingly popular, driven by consumer interest in foods associated with healthier lifestyles and environmentally friendly practices. This review synthesizes evidence on the production of this subsector from 1960 to 2021, using major literature databases (Agricola, ScienceDirect, and Google Scholar), to summarize health and environmental implications, economic importance, research trends, and persistent challenges. The production of fruits and vegetables is frequently reported to exhibit favorable quality and safety attributes, including higher antioxidant capacity and lower levels of cadmium, pesticides, and other chemical residues, supporting its relevance to nutrition and human health. This type of practice is also described as contributing to environmental restoration and preservation through improved soil conditions, reduced reliance on synthetic inputs, enhanced nutrient cycling, and climate-smart benefits such as increased soil organic matter and lower energy intensity. Nevertheless, it faces constraints that increase costs and limit scalability, including high labor demand, limited effectiveness and availability of some organic pest control tools, perishability, post-harvest losses, certification burdens, and market access regulations. Despite these barriers, data indicate growth: from 2007 to 2021, acreage increased by more than 100%, farm-gate value rose from $685 million to $1913 million, and the number of participating farms increased by more than 100%. Moreover, it accounts for 0.9% of the total value of the agricultural production in the U.S. Overall, the outlook for U.S. organic fruit and vegetables is encouraging, supported by expanding consumer demand, government support, and improved conditions for international trade. Full article

Olive oil is a high-value product that is highly exposed to fraud, making robust traceability systems essential to protect authenticity, consumer trust, and competitiveness. This study examines how digital traceability technologies influence fraud mitigation and the sustainable performance of olive oil mills in southern Brazil. A systematic literature review, conducted according to the PRISMA 2020 protocol in Scopus and Web of Science, identified state-of-the-art supply chain and authentication technologies, including blockchain, IoT, RFID, QR codes, cloud computing, Big Data, artificial intelligence, and physicochemical methods. Two structured questionnaires were then applied to managers from nine mills in the main Brazilian olive oil cluster, and the data were analyzed using descriptive statistics, Chi-Square tests, and correlation measures within a framework grounded in Resource-Based View and Institutional Isomorphism theories. The results show that adoption of digital traceability is still incipient, while internal factors such as organizational commitment and marketing strategies play a more decisive role than external pressures in explaining adoption. Although managers do not yet perceive a direct impact on fraud mitigation, adoption is positively associated with economic, environmental, and social sustainability outcomes. Given the exploratory design and the small, non-probabilistic sample (n = 9), the findings should be interpreted as indicative rather than definitive. The proposed framework is intended as a transferable analytical lens that can be adapted and further validated in other agri-food and industrial contexts using larger samples and objective fraud-related indicators. Full article

Soil mulching materials play an important role in regulating the greenhouse crop microclimate, as they influence light distribution, plant physiological activity, and crop yield. The aim of this study was to evaluate the effects of two plastic mulches (black polypropylene and white polyethylene mulch) on the microclimate, photosynthetic activity, crop development, yield, and fruit quality of sweet pepper (Capsicum annuum L.) grown under greenhouse conditions. The trial was developed during a spring–summer growing cycle in a single multispan greenhouse divided into two compartments (sectors) separated by a vertical polyethylene sheet. In the eastern sector of the greenhouse (control treatment), a black polypropylene agrotextile mulch with a thickness of 2500 μm was installed, while in the western sector, a white polyethylene plastic mulch (black on the inner side) with a thickness of 30 μm was used. The use of white polyethylene mulch resulted in slightly higher mean and maximum PAR inside the greenhouse by up to 3.7% compared with black polypropylene mulch, leading to slightly higher leaf-level PAR and net photosynthetic rate. Although no significant differences were observed in plant morphology or fruit quality parameters, marketable yield increased by 66% and total yield by 40% under white polyethylene mulch. Slight increases in internal air temperature were recorded without exceeding critical thresholds, while relative humidity remained largely unaffected. The use of reflective mulches may represent a promising low-cost and sustainable strategy to improve pepper yield and radiation-use efficiency in passively ventilated greenhouse systems under Mediterranean climatic conditions. Full article