Search Results (1,490)

This study empirically delves into whether residential heating methods significantly affect apartment prices in Uiwang City, a suburban city near the Seoul Metropolitan area, South Korea. Using data from 1256 apartment sales, where both district heating systems (DHSs) and individual heating systems (IHSs) coexist, a hedonic price equation was estimated to analyze the impact of the heating method choices on housing values. Various housing attributes, including physical, locational, and environmental factors, were controlled, and multiple regression models were compared to identify the best-performing specification. The results show that apartments equipped with a DHS are priced, on average, KRW 92 million (USD 72 thousand) higher than those with an IHS. The price difference corresponds to KRW 849 thousand (USD 665) per m² and possesses the statistical significance at the 5% level. Moreover, it is quite meaningful, representing roughly 11.2% of the price of an average apartment. These findings suggest that the use of DHS has a positive effect on apartment prices that reflect consumers’ preferences, beyond its advantages in stable heat supply and energy cost savings. This article provides empirical evidence that DHS can serve as an important urban infrastructure contributing to asset value enhancement. Although this study is based on a specific geographic area and caution must be exercised in generalizing its findings, it reports the interesting finding that residential heating method significantly affects housing prices. Full article

Evaluating the economic value of carbon sinks is fundamental to advancing carbon market mechanisms and supporting sustainable regional development. This study focuses on Fujian Province in China, aiming to assess the spatiotemporal evolution of carbon sink value and analyze the influence of socio-economic drivers. Carbon sink values from 2000 to 2020 were estimated using Net Ecosystem Productivity (NEP) simulation combined with the carbon market valuation method. Eleven socio-economic variables were selected through correlation and multicollinearity testing, and their impacts were examined using Geographically and Temporally Weighted Regression (GTWR) at the county level. The results indicate that the total carbon sink value in Fujian declined from CNY 3.212 billion in 2000 to CNY 2.837 billion in 2020, showing a spatial pattern of higher values in the southern region and lower values in the north. GTWR analysis reveals spatiotemporal heterogeneity in the effects of socio-economic factors. For example, the influence of urbanization and retail sales of consumer goods shifts direction over time, while the effects of industrial structure, population, road, and fixed asset investment vary across space. This study emphasizes the necessity of incorporating spatial and temporal dynamics into carbon sink valuation. The findings suggest that northern areas of Fujian should prioritize ecological restoration, rapidly urbanizing regions should adopt green development strategies, and counties guided by investment and consumption should focus on sustainable development pathways to maintain and enhance carbon sink capacity. Full article

In high-density and land-scarce urban environments such as Taipei—a typical example of compact development in East Asia—informal green spaces (IGSs)—defined as unmanaged or unplanned vegetated urban areas such as vacant lots, street verges, and railway margins—play a growing role in urban environmental and social dynamics. This study explores residents’ perceptions of IGSs and examines how these spaces contribute to urban sustainability and land governance. Using a mixed-methods approach that combines the literature review, field observations, and a structured public opinion survey in Taipei’s Wenshan District, the study identifies key perceived benefits and drawbacks of IGSs. Findings show that residents highly value IGSs for enhancing urban greenery, offering recreational opportunities, and promoting physical and mental health. However, concerns persist regarding safety, sanitation, and maintenance—particularly fears of waste accumulation, mosquito breeding, and risks to children. The results highlight the dual nature of IGSs as both vital ecological assets and potential sources of urban disorder. These insights underscore the need for inclusive, community-based governance models that can transform IGSs into legitimate components of green infrastructure. The study contributes to emerging discussions on adaptive urban land governance by proposing that informal spaces be strategically integrated into urban planning frameworks to enhance environmental equity, resilience, and citizen well-being. Full article

This paper analyzes the factors affecting the willingness to pay of urban households concerned with efficient waste management in Bangladesh. The multistage random sampling approach selected 1400 families from seven major cities in Bangladesh. This study addresses the socioeconomic and environmental factors that influence urban households’ willingness to pay for improved waste management services in Bangladesh. This study uniquely contributes to the literature by providing a large-scale empirical analysis of 1470 households using a logit model, revealing income, education, and environmental awareness as key predictors of WTP. Detailed survey data from respondents were then analyzed using a logit model based on the contingent valuation method. Indeed, the logit model showed that six variables (education, monthly income, value of the asset, knowledge of environment, and climate change) had a statistically significant effect on the WTP of the households. The results show that 63% of respondents were willing to pay BDT 250 or more per month. The most influential factors driving this willingness to pay were income (OR = 1.35), education level (OR = 1.45), and environmental awareness (OR = 3.56). These variables all contribute positively towards WTP. The idea is that families have some socioeconomic characteristics, regardless of which they are ready to pay for a higher level of waste collection. It is recommended that government interference be affected through various approaches, as listed below: support for public–private sector undertaking and disposal, an extensive cleaning campaign, decentralized management, cutting waste transport costs, and privatization of some waste management systems. These could be used to develop solutions to better waste management systems and improve public health. Full article

Circular economy (CE) is a recently introduced concept by the EU and several national governments that aims to reduce the total resources extracted from the environment and limit waste generated by human activities to achieve human well-being and sustainability. This review aims to bring awareness of heritage sites’ role and significance in reducing carbon footprints as a strategy for applying CE and promoting sustainable urban development. This study adopts a qualitative content analysis methodology, selecting academic literature, international case studies, and policy documents based on their relevance to CE principles and heritage conservation. The approach examines the emergence and dissemination of these concepts through published literature, including professional standards and guidelines for valuing and managing heritage sites. Key themes include adaptive re-use strategies, preventive conservation, and policy integration. A comparative reflection on international case studies was conducted to highlight trends, regional variations, and challenges. This review concludes by identifying research gaps and proposing future directions, reinforcing the value of heritage sites as pivotal assets in advancing CE frameworks. This structured synthesis provides a theoretical and practical contribution to integrating circular economy strategies in heritage conservation. Full article

This study compares two risk tolerance scales used in the Survey of Consumer Finances (SCF), namely the long-standing 4-point scale and the newer 11-point scale, to determine which better captures an individual’s investment risk preferences. The analysis includes exploring how each scale relates to household demographics, socioeconomic factors, and ownership of risky versus conservative investments. By utilizing prospect theory, the findings reveal that while both scales effectively measure risk tolerance, the 11-point scale provides a more detailed understanding of differences in asset ownership across risk levels. For financial professionals, these results highlight the value of using a more granular risk assessment tool to better align investment strategies with client preferences, leading to improved client relationships and outcomes. Full article

Over the past decade, multifactor models have shown enhanced capability compared to single-factor models in explaining asset return variability. Given the common assertion that higher risk tends to yield higher returns, this study empirically examines the augmented human capital six-factor model’s performance on thirty-two portfolios of non-financial firms sorted by size, value, profitability, investment, and labor income growth in the Indian market over the period July 2010 to June 2023. Moreover, the current study extends the Fama and French five-factor model by incorporating a human capital proxy by labor income growth as an additional factor thereby proposing an augmented six-factor asset pricing model (HC6FM). The Fama and MacBeth two-step estimation methodology is employed for the empirical analysis. The results reveal that small-cap portfolios yield significantly higher returns than large-cap portfolios. Moreover, all six factors significantly explain the time-series variation in excess portfolio returns. Our findings reveal that the Indian stock market experienced heightened volatility during the COVID-19 pandemic, leading to a decline in the six-factor model’s efficiency in explaining returns. Furthermore, Gibbons, Ross, and Shanken (GRS) test results reveal mispricing of portfolio returns during COVID-19, with a stronger rejection of portfolio efficiency across models. However, the HC6FM consistently shows lower pricing errors and better performance, specifically during and after the pandemic era. Overall, the results offer important insights for policymakers, investors, and portfolio managers in optimizing portfolio selection, particularly during periods of heightened market uncertainty. Full article

Bank operations are contingent upon investor confidence, particularly during periods of economic distress. If investor confidence drops, a bank faces difficulties obtaining money, higher borrowing costs, and lower stock values. Non-performing loans (NPLs) potentially jeopardize a bank’s long-term viability and short-term profitability, and investors are naturally wary of institutions that pose a high credit risk. The purpose of the study was to explore how non-performing loans influence investor confidence in banks. A purposive sampling technique was used to identify 253 New York Stock Exchange banks in the Thomson Reuters Eikon DataStream that satisfied all the inclusion and exclusion selection criteria. The Common Correlated Effects Mean Group (CCEMG) and Generalized Method of Moments (GMM) models were used to analyze the data, providing insight into the relationship between the variables. The study discovered that NPLs had a negative and significant influence on price–earnings (P/E) and price-to-book value (P/B) ratios. Furthermore, the bank’s age was found to have a positive and significant relationship with the P/E and P/B ratio. The moderating relationship between NPLs and bank age was found to have a negative and significant influence on price–earnings (P/E) and price-to-book value (P/B) ratios. The findings underscore the importance of asset quality and institutional reputation in influencing market perceptions. Bank managers should focus on managing non-performing loans effectively and leveraging institutional credibility to sustain investor confidence, particularly during financial distress. Full article

The valuation of biological assets represents a crucial component for the generation of accounting information, especially in the context of the agricultural sector, where assets subject to continuous transformation processes predominate. This study aims to analyze, through a systematic review of the literature, how the measurement methods established by International Accounting Standard 41 (IAS 41) affect the quality, accuracy, and usefulness of accounting reports. The results show that the correct valuation of biological assets significantly improves strategic and financial decision-making by providing more reliable and representative data on the economic reality of the sector. Finally, the study highlights the main practical challenges in the application of IAS 41, including fair value volatility, the subjectivity of estimates, the limited availability of reliable data, and the need for more flexible accounting frameworks that consider the cultural, climatic, and productive realities of each environment. Based on these findings, the importance of strengthening transparency and accounting disclosure and adapting measurement methods to the particularities of the agricultural sector in order to improve the quality of information and the confidence of external users is highlighted. Full article

With wildfires becoming more frequent and severe in fire-prone regions affected by warmer and drier climate conditions, reducing hazardous fuels is increasingly recognized as a preventative strategy for promoting sustainability and safeguarding valued resources. Prescribed fire is one of the most cost-effective methods for reducing hazardous fuels and hence wildfire severity, yet empirical research on its effectiveness at minimizing damage to highly valued resources and assets (HVRAs) remains limited. The overarching objective of this study was to evaluate wildfire severity under differing weather conditions across various HVRAs characterized by diverse land uses, vegetation types, and treatment histories. The findings from this study reveal that wildfire severity was generally lower in areas treated with prescribed fire, although the significance of this effect varied among HVRAs and diminished as post-treatment duration increased. The wildland–urban interface experienced the greatest initial reduction in wildfire severity following prescribed fire, but burn severity increased more rapidly over time relative to other HVRAs. Elevated drought conditions had a significant effect, increasing wildfire severity across all HVRAs. The implications of this study underscore the role of prescribed fire in promoting sustainable land management by reducing wildfire severity and safeguarding both natural and built environments, particularly in the expanding wildland–urban interface. Full article

Microgrids and load shifting can improve resilience and lower costs for electricity customers. The costs to deploy each have decreased and helped accelerate their deployment in the U.S. and globally. However, previous research has focused minimally on the combined benefit or “stacked economic value” that these assets could provide jointly. This article evaluates the financial value when those assets are combined and optimized jointly. The methods are demonstrated for a U.S. government facility with an existing microgrid and building automation system, with optimizations that vary the percentage load shifted and the duration of time the load can be shifted. The economic benefits of load shifting are greater when combined with a microgrid and coordinated dispatch of loads and microgrid assets. The methods and case study results illustrate “stacked economic value” showing energy charge reductions are 56–252% greater and demand charge reductions are 96–226% greater when load shifting is combined with a microgrid as compared to load shifting without a microgrid. Increasing the amount and duration of load shifting improves the stacked economic value as more loads are scheduled coincident with on-site generation to offset or completely avoid utility purchases during peak pricing periods, an underlying behavior that enables stacked economic value and increased financial savings. The percentage reduction in demand charges is greater than energy charges—a generalizable finding—but the relative impact on utility expenditures is dependent on the utility tariff structure and composition of demand charges and energy charges in the utility bill. In this case study, demand charge reductions were four times greater than energy charge reductions, but the financial savings of demand charges are less due to their smaller proportion of utility charges. This suggests that the stacked economic value of microgrids and load control may be even more significant in locations with electricity tariffs that more heavily weight billing towards demand charges than energy charges. Full article

Urban food markets are increasingly being recognized not only as centres of cultural identity and tourism but also as pivotal spaces for promoting urban sustainability. This study explores the role of urban markets in advancing sustainable cultural tourism, using Obor Market in Bucharest as a case study. As a historic marketplace and cultural landmark, Obor Market embodies Bucharest’s traditional commercial practices and community-oriented values. Through a mixed-methods approach, combining Geographic Information Systems (GIS) mapping and systematic surveys, we evaluate the location of markets, cultural authenticity, and visitor satisfaction. The quantitative findings reveal meaningful correlations between demographic factors (particularly nationality and age) and visitor perceptions, highlighting the market’s appeal through its authentic culinary offerings and immersive sensory experience. However, this study also identifies shortcomings in current promotional strategies employed by local stakeholders. The results suggest that urban food markets can serve as sustainable urban assets, fostering cross-cultural integration, supporting local economies, and encouraging environmentally conscious tourism behaviours. We argue for data-informed urban cultural policies that enhance the visibility, accessibility, and sustainability of such spaces, reinforcing their dual role as economic drivers and cultural touchstones. Full article

As sustainability becomes increasingly central to organizational strategy, social economy organizations (SEOs) are rethinking their business models. This study employs stakeholder analysis using the value mapping (VM) tool developed by Short, Rana, Bocken, and Evans for the development of the VOLTO JÁ project. The objective of the VOLTO JÁ project is to operationalize a senior exchange programme between SEOs. The VM approach extends beyond conventional customer value propositions to prioritize sustainability for all stakeholders and identify key drivers of sustainable business model (SBM) innovation. The multi-stakeholder methodology comprises the following elements: (1) sequential focus groups aimed at enhancing sustainable business thinking; (2) semi-structured interviews; and (3) workshop to facilitate qualitative analysis and co-create the VM. The findings are then categorized into four value dimensions: (1) value captured—improved participant well-being, enhanced reputational capital, mitigation of social asymmetries, and affordable service experiences; (2) value lost—underused community assets; (3) value destroyed—institutional and systemic barriers to innovation; and (4) new value opportunities—knowledge sharing, service diversification, and open innovation to foster collaborative networks. The study demonstrates that the application of VM in SEOs supports SBM development by generating strategic insights, enhancing resource efficiency, and fostering the delivery of socially impactful services. Full article

Dissolved gas analysis remains the most widely utilized non-intrusive diagnostic method for detecting incipient faults in insulating liquid-immersed transformers. Despite their prevalence, conventional ratio-based methods often suffer from ambiguity and limited potential for automation applicrations. To address these limitations, this study proposes a unified multiclass classification model that integrates traditional gas ratio features with supervised machine learning algorithms to enhance fault diagnosis accuracy. The performance of six machine learning classifiers was systematically evaluated using training and testing data generated through four widely recognized gas ratio schemes. Grid search optimization was employed to fine-tune the hyperparameters of each model, while model evaluation was conducted using 10-fold cross-validation and six performance metrics. Across all the diagnostic approaches, ensemble models, namely random forest, XGBoost, and LightGBM, consistently outperformed non-ensemble models. Notably, random forest and LightGBM classifiers demonstrated the most robust and superior performance across all schemes, achieving accuracy, precision, recall, and F1 scores between 0.99 and 1, along with Matthew correlation coefficient values exceeding 0.98 in all cases. This robustness suggests that ensemble models are effective at capturing complex decision boundaries and relationships among gas ratio features. Furthermore, beyond numerical classification, the integration of physicochemical and dielectric properties in this study revealed degradation signatures that strongly correlate with thermal fault indicators. Particularly, the CIGRÉ-based classification using a random forest classifier demonstrated high sensitivity in detecting thermally stressed units, corroborating trends observed in chemical deterioration parameters such as interfacial tension and CO₂/CO ratios. Access to over 80 years of operational data provides a rare and invaluable perspective on the long-term performance and degradation of power equipment. This extended dataset enables a more accurate assessment of ageing trends, enhances the reliability of predictive maintenance models, and supports informed decision-making for asset management in legacy power systems. Full article

This study examines the effects of capital lease arrangements on the operating performance of shipping firms as proxied by Return on Assets (ROA). The maritime industry is highly capital-intensive, often requiring substantial investments in fleet acquisition and maintenance, making ROA particularly relevant as it captures the effectiveness of firms in utilizing their leased and owned assets to generate operating income. As such, many firms rely on lease arrangements to access necessary resources while preserving liquidity and financial flexibility. Using an international sample of 209 shipping firms, we estimate fixed effects regressions to assess the relationship between lease intensity and performance of the shipping firms. The findings reveal that capital lease intensity is positively associated with operating performance, indicating that leasing can be a value-enhancing financing strategy in this sector. However, the performance benefits of capital leases diminish under IFRS 16 reporting, particularly for firms with higher leverage. These findings offer important implications for investors, regulators, and managers evaluating capital structure decisions and financial reporting strategies in capital-intensive industries post-IFRS 16 implementation. Full article