Search Results (146)

The siphon effect between airports has amplified the polarization in passenger throughput, undermining the balanced development and sustainability of airport clusters. The airport siphon effect occurs when one airport attracts a disproportionate share of passengers, concentrating traffic at the expense of others, which affects the overall resilience of the entire airport cluster. To address this issue, this study proposes a siphon index, expands the range of ground transportation options for passengers, and establishes a zero-siphon model to assess the impact of siphoning on the resiliency of airport clusters. Using this framework, four major airport clusters in China were selected as research subjects, with regional aviation accessibility serving as a measure of resilience. The results showed that among the four airport clusters, the siphon effect is most pronounced in the Guangzhou region. To explore the implications of this effect further, three airport disruption scenarios were simulated to assess the resilience of the Pearl River Delta airport cluster. The results indicated that the intensity and timing of disruptive events significantly affect airport cluster resilience, with hub airports being particularly sensitive. This study analyzes the risks associated with excessive route concentration, providing policymakers with critical insights to enhance the sustainability, equity, and resilience of airport clusters. The proposed strategies facilitate coordinated infrastructure development, optimized air–ground intermodal connectivity, and risk mitigation. These measures contribute to building more sustainable and adaptive aviation networks in rapidly urbanizing regions. Full article

Society’s adaptation to shared mobility services is a growing topic that requires detailed understanding of the local circumstances of potential and current users. This paper focuses on analyzing barriers to the adoption of urban bike-sharing systems in post-industrial cities, using a case study of the Silesian agglomeration in Poland. Methodologically, the article integrates quantitative survey methods with multivariate statistical analysis to analyze the demographic, socioeconomic, and motivational factors that underline the adoption of shared micromobility. The study highlights a detailed segmentation of users by income, age, professional status, and gender, as well as the observation of profound disparities in access and perceived usefulness. Of note is the study’s identification of a highly concentrated segment of young, low-income users (mostly students), which largely accounts for the general perception of economic and infrastructural barriers. These include the use of factor analysis and regression to plot the interaction patterns between individual user characteristics and certain system-level constraints, such as cost, infrastructure coverage, weather, and health. The study’s findings prioritize problem-specific interventions in urban mobility planning: bridging equity gaps between user groups. This research contributes to the current literature by providing detailed insights into the heterogeneity of user mobility behavior, offering evidence-based recommendations for inclusive and adaptive options for shared transportation infrastructure in a changing urban context. Full article

In alignment with global educational trends, Australia has adopted a pluralistic approach to initial teacher education (ITE), encompassing traditional university-based programs, employment-integrated models and vocational training routes. This diversification of pathways has emerged as a strategic response to persistent workforce challenges, including chronic shortages, uneven distribution of qualified educators, and limited demographic diversity within the profession. Rather than supplanting conventional ITE models, these alternative pathways serve as complementary options, broadening access and enhancing system responsiveness to evolving societal and educational needs. The rise in non-traditional routes represents a deliberate response to the well-documented global teacher shortage, frequently examined in comparative educational research. Central to their design is a restructuring of traditional program elements, particularly duration and delivery methods, to facilitate more flexible and context-sensitive forms of teacher preparation. Such approaches often create opportunities for individuals who may be excluded from conventional pathways due to socioeconomic constraints, geographic isolation, or non-linear career trajectories. Significantly, the diversity introduced by alternative entry candidates has the potential to enrich school learning environments. These educators often bring a wide range of prior experiences, disciplinary knowledge, and cultural perspectives, contributing to more inclusive and representative teaching practices. The implications for student learning are substantial, particularly in disadvantaged communities where culturally and professionally diverse teachers may enhance engagement and academic outcomes. From a policy perspective, the development of flexible, multifaceted teacher education pathways constitutes a critical component of a sustainable workforce strategy. As demand for qualified teachers intensifies, especially in STEM disciplines and in rural, regional and remote areas, the role of alternative pathways is likely to become increasingly pivotal in achieving broader goals of equity, quality and innovation in teacher preparation. Full article

This study explores the spatial and social implications of urban food systems in Quito, Ecuador, focusing on how food access inequalities reflect and reinforce broader urban disparities. The research addresses a critical problem in contemporary urbanization: the disconnection between food provisioning and spatial equity in rapidly growing cities. The objective is to assess and map disparities in food accessibility using a mixed-methods approach that includes field observation, participatory mapping, value chain analysis, and statistical modeling. Five traditional and emerging food markets were studied in diverse districts across the city. A synthetic accessibility function F(x) was constructed to model food access levels, integrating variables such as income, infrastructure, transport availability, and travel time. These variables were subjected to Principal Component Analysis (PCA) and hierarchical clustering to generate three typologies of territorial vulnerability. The results reveal that peripheral areas exhibit lower F(x) values and weaker integration with the formal food system, leading to higher consumer costs and limited fresh food options. In contrast, central districts benefit from multimodal infrastructure and greater diversity of supply. This study concludes that food systems should be treated as critical urban infrastructure. Integrating food equity into land use and mobility planning is essential to promote inclusive, sustainable, and resilient urban development. Full article

The phenomenon of rising forward price volatility, both historical and implied, as maturity approaches is referred to as the Samuelson effect or maturity effect. Disregarding this effect leads to significant mispricing of early-exercise options, extendible options, or other path-dependent options. The primary objective of the research is to identify a practical way to incorporate the Samuelson effect into the evaluation of commodity derivatives. We choose to model the instantaneous variance employing the exponential decay parameterizations of the Samuelson effect. We develop efficient calibration techniques utilizing historical futures data and conduct an analysis of statistical errors to provide a benchmark for model performance. The study employs 15 years of data for WTI, Brent, and NG, producing excellent results, with the fitting error consistently inside the statistical error, except for the 2020 crisis period. We assess the stability of the fitted parameters via cross-validation techniques and examine the model’s out-of-sample efficacy. The approach is generalized to encompass seasonal commodities, such as natural gas and electricity. We illustrate the application of the calibrated model of instantaneous variance for the evaluation of commodity derivatives, including swaptions, as well as in the evaluation of power purchase agreements (PPAs). We demonstrate a compelling application of the Samuelson effect to a widely utilized auto-callable equity derivative known as the snowball. Full article

This study explores an innovative approach to incorporating option strategies into equity portfolios. It presents an alternative direction that institutional investors could take to overcome their current challenges, in a context where traditionally diversified portfolios of only equity and fixed-income assets have shown weaknesses that make it difficult for these investors to achieve their performance goals within their risk limits. We test whether a set of well-known backward-looking signals from equities markets and less-researched forward-looking ones from options markets can be used to improve the efficiency of two option strategies, namely covered call and protective put. The trend signal appears to be the one that adds the most value to both strategies. This study also shows that increasing complexity through additional trading rules does not improve the results of the more basic option strategies that make use of the signals. Full article

The market risk measurement of a trading portfolio in banks, specifically the practical implementation of the value-at-risk (VaR) and expected shortfall (ES) models, involves intensive recalls of the pricing engine. Machine learning algorithms may offer a solution to this challenge. In this study, we investigate the application of the Gaussian process (GP) regression and multi-fidelity modeling technique as approximation for the pricing engine. More precisely, multi-fidelity modeling combines models of different fidelity levels, defined as the degree of detail and precision offered by a predictive model or simulation, to achieve rapid yet precise prediction. We use the regression models to predict the prices of mono- and multi-asset equity option portfolios. In our numerical experiments, conducted with data limitation, we observe that both the standard GP model and multi-fidelity GP model outperform both the traditional approaches used in banks and the well-known neural network model in term of pricing accuracy as well as risk calculation efficiency. Full article

In response to the urgent need for the sustainable conservation of cultural heritage against the backdrop of climate change and environmental degradation, this study proposes a low-cost, non-destructive digital recording method for murals based on close-range photogrammetry. By integrating non-metric digital cameras, total stations, and spatial coordinate transformation models, high-precision digital orthophoto generation for indoor murals was achieved. Experimental results show that the resolution error of this method is 0.02 mm, with root mean square errors (RMSE) of 3.51 mm and 2.77 mm in the X and Y directions, respectively, meeting the precision requirements for cultural heritage conservation. Compared to traditional laser scanning technology, the energy consumption of the equipment in this study is significantly reduced, and the use of chemical reagents is avoided, thereby minimizing the carbon footprint and environmental impact during the recording process. This provides a green technological solution to address climate change. Additionally, the low-cost nature of non-metric cameras offers a feasible option for cultural heritage conservation institutions with limited resources, promoting equity and accessibility in heritage protection amid global climate challenges. This technology provides sustainable data support for long-term monitoring, virtual restoration, and public digital display of murals while also offering rich data resources for virtual cultural tourism, public education, and scientific research. It demonstrates broad application potential in the context of climate change and environmental protection, contributing to the green transformation and sustainable development of cultural tourism. Full article

In numerous domains of finance and economics, modelling and predicting stock market volatility is essential. Predicting stock market volatility is widely used in the management of portfolios, analysis of risk, and determination of option prices. This study is about volatility modelling of the daily Johannesburg Stock Exchange All Share Index (JSE ALSI) stock price data between 1 January 2014 and 29 December 2023. The modelling process incorporated daily log returns derived from the JSE ALSI. The following volatility models were presented for the period: sGARCH(1, 1) and fGARCH(1, 1). The models for volatility were fitted using five unique error distribution assumptions, including Student’s t, its skewed version, the generalized error and skewed generalized error distributions, and the generalized hyperbolic distribution. Based on information criteria such as Akaike, Bayesian, and Hannan–Quinn, the ARMA(0, 0)-fGARCH(1, 1) model with a skewed generalized error distribution emerged as the best fit. The chosen model revealed that the JSE ALSI prices are highly persistent with the leverage effect. JSE ALSI price volatility was notably influenced during the COVID-19 pandemic. The forecast over the next 10 days shows a rise in volatility. A comparative study was then carried out with the JSE Top 40 and the S&P500 indices. Comparison of the FTSE/JSE Top 40, S&P 500, and JSE ALLSI return indices over the COVID-19 pandemic indicated higher initial volatility in the FTSE/JSE Top 40 and S&P 500, with the JSE ALLSI following a similar trend later. The S&P 500 showed long-term reliability and high rolling returns in spite of short-run volatility, the FTSE/JSE Top 40 showed more pre-pandemic risk and volatility but reduced levels of rolling volatility after the pandemic, similar in magnitude for each index with low correlations among them. These results provide important insights for risk managers and investors navigating the South African equity market. Full article

Municipalities face increasing vulnerability to climate-related risks, giving rise to a set of different challenges and problems, ultimately threatening long-term sustainability. Addressing these challenges requires proactive adaptation measures, innovative solutions, and stakeholder engagement to enhance climate resilience at the municipal level. This study adapts the Prospective Rapid Impact Assessment (PRIA) approach for planning critical climate change actions, promoting environmental, social, and economic sustainability. Using a case study in Tauragė, Lithuania, the study explores the PRIA method’s application in municipal planning. Various stakeholders and experts participated in testing the method, emphasising the need for inclusive governance in sustainable urban development. The research identifies key climate challenges and corresponding adaptation actions across three tiers: individual (person), household, and municipal levels, underscoring a multi-scale approach to sustainability. A five-point Likert scale was used to evaluate challenges, with the five most significant ones highlighted for each tier. A comprehensive list of sustainability-driven climate actions was compiled, and experts prioritised the most impactful and feasible strategies. These recommendations were presented to Tauragė’s decision-makers to inform the development or revision of the municipal Action Plan, ensuring that climate resilience, resource efficiency, and social equity are embedded in local policies. Furthermore, the study demonstrates the effectiveness of the PRIA method and the practical utility of the InTo tool in assessing climate actions and identifying priority sustainability measures. By integrating sustainability considerations into municipal strategic planning, the findings underscore the necessity of proactive, forward-thinking approaches to safeguard communities and ecosystems against climate change. The study results confirm that the PRIA method can be successfully utilised as a robust framework for regional and municipal climate change action planning. It facilitates the identification of key issues, the prioritisation of actions, stakeholder engagement, and the integration of interdependencies within the climate change action planning process. This approach ensures that actions are well-founded, specifically tailored to the needs of various community levels, and account for the interdependencies among different climate change mitigation and adaptation options. Full article

Forward-looking metrics of uncertainty based on options-implied information should be highly predictive of equity market returns in accordance with asset pricing theory. Empirically, however, the ability of the VIX, for example, to predict returns is statistically weak. In contrast to other studies that typically analyze a short time-series of option prices, I make use of a ‘VIX-type’ but a text-based measure of uncertainty starting in 1890, which is constructed using the titles and abstracts of front-page articles of the Wall Street Journal. I hypothesize that uncertainty timing might increase Sharpe ratios because changes in uncertainty are not necessarily correlated with changes in equity risk and, therefore, not offset by proportional changes in expected returns. Using a major US equity portfolio, I propose a dynamic trading strategy and show that lagged news-based uncertainty explains future excess returns on the market portfolio at the short horizon. While policy- and war-related concerns mainly drive these predictability results, stock market-related news has no predictive power. A managed equity portfolio that takes more risk when news-based uncertainty is high generates an annualized equity risk-adjusted alpha of 5.33% with an appraisal ratio of 0.46. Managing news-based uncertainty contrasts with conventional investment knowledge because the strategy takes relatively less risks in recessions, which rules out typical risk-based explanations. Interestingly, I find that the uncertainty around governmental policy is lower and, by taking less risk, it performs better during periods when the Republicans control the senate. I conclude that my text-based measure is a plausible proxy for investor policy uncertainty and performs better in terms of predictability compared to other options-based measures. Full article

Since the 1960s, ABA has been applied to individuals with developmental and behavioral differences, including those later recognized as Autistic. While ABA is grounded in behavioral science, its historical application has raised significant ethical concerns. Early implementations often prioritized enforcing neurotypical conformity over the autonomy and well-being of Autistic individuals, contributing to psychological harm, the development of masking behaviors, and a disregard for neurodivergent needs. These concerns were further exacerbated by the exclusion of Autistic voices in defining intervention goals and measuring outcomes. This paper examines the historical context of ABA, critiques raised by the #ABAisAbuse movement, and the role of social media in amplifying both awareness and misconceptions about behavioral interventions for Autistic individuals. It highlights the challenges posed by self-diagnosis, the limitations of current therapeutic options, and systemic inequities in access to care. A critical analysis underscores the need for standardized, neurodivergent-affirming, and assent-based practices that prioritize the autonomy and individuality of Autistic people. The findings emphasize the necessity of reforming ABA through collaboration with the Autistic community, ensuring their involvement in shaping governance, intervention design, and ethical standards. By addressing historical harms and embedding neurodivergent-affirming principles, ABA can evolve into a practice that supports authentic engagement and fosters trust within the Autistic community. This transformation is not only a professional responsibility but an ethical imperative to align interventions for Autistic individuals with principles of dignity, equity, and inclusion. Full article

This paper develops a strategic framework that integrates the theoretical perspectives of evolutionary economic geography and economic complexity to identify green export opportunities. By combining feasibility factors—such as green specialization, relatedness, and trade inertia—with desirability criteria like income, equity, and low emissions, the framework offers a comprehensive approach to identify green export diversification. The empirical application, focused on the Southern Cone (Argentina, Brazil, Chile, Paraguay, and Uruguay), suggests that economies should prioritize green opportunities aligned with their existing capabilities, gradually expanding into higher-risk, higher-return options. The study provides tailored green export diversification portfolios for each country, identifying key opportunities in renewable energy products for Argentina and Brazil, lithium-related inputs for Chile, biofuels for Paraguay, and green hydrogen for Uruguay. These findings offer valuable insights for the design of public policies aimed at fostering green export diversification. Full article

Cities are looking for an approach to affordable, integrated and sustainable transport systems across all transport modes and services. Automated vehicle (AV) technologies use emerging technologies to integrate multimodal transport systems and ensure sustainable mobility in a city. Vehicle automation has entered the public conscious with several auto companies leading recent developments in legislation and affordable cars. Governments support AVs through policies and legal frameworks, and it is the responsibility of AV dealers to comply with legal and policy provisions so that the benefits of this new and promising industry can be felt. Despite the growing interest in AVs as a potential solution for sustainable transportation, several research gaps remain in relation to technology and infrastructure readiness, policy and regulation, equity and accessibility concerns, public acceptance and behaviour, and integration with public transport. This paper discusses the challenges and dilemmas of adopting AVs within the existing urban transportation system and within existing design standards in the United Kingdom and explores the progress and opportunities related to policies of transportation that may stem from the emergence of AV technologies in the UK. The potential of AVs is still limited by cyber insecurity, incompetent infrastructure, social acceptance, and public awareness. However, AVs are crucial to a city’s efficiency and prosperity and will become essential components for the provision of more flexible, convenient, integrated and sustainable travel options. Full article

This paper presents a method for hedging in markets of two-factor diffusion and jump diffusion models under the restriction of a specified probability of success. In addition, a method for hedging with a given shortfall amount is developed. A maximal perfect hedging set is constructed for options involving the exchange of one asset for another. The developed method is applied to the pricing of equity-linked life insurance contracts, such as “pure endowments with a guarantee”. Traditional pricing approaches for hedging options often yield minimal returns for investors. By accepting a predefined level of risk, investors can achieve higher returns. In light of this, this paper proposes risk management strategies applicable to these hybrid financial and insurance products. Full article