This study examines the derivatives usage patterns among Fortune 500 companies during the 2020–2024 period, characterized by unprecedented market volatility. The objective is to investigate how derivative strategies evolved in response to the COVID-19 pandemic, subsequent inflation surge and interest rate fluctuations.
Harekrishna Manna, Mridul Das, Malay Pramanik
et al.
Urban flooding is a significant issue in coastal megacity Mumbai, where flood susceptibility is exacerbated by rapid urbanization and intense monsoon rainfall. This study develops a high-resolution flood susceptibility map for the Mumbai Metropolitan Region (MMR), using four machine learning algorithms: Random Forest, Artificial Neural Network, XGBoost, and Gradient Boosting Machine. The models were trained and validated using historical flood occurrence points, with nine conditioning factors: elevation, slope, rainfall, land use and land cover, building density, proximity to coastlines, road networks, and blue space. Models were performed with high accuracy, achieving 0.93 for GBM and XGBoost, 0.92 for RF, and 0.89 for ANN, respectively. The ensemble flood map, created based on the mean of four ML models, revealed that 25.3% of MMR is classified as high or very high flood susceptibility, while 34.3% falls into the low-susceptibility category. SHapley Additive exPlanations (SHAP) analysis showed that elevation, rainfall, and proximity to roads were the most influential predictors. Spatial validation revealed excellent overlap with historical flooding hotspots at Kurla, Chembur, and Sion. These findings provide critical policy insights for integrating flood susceptibility mapping into urban planning frameworks, supporting data-driven resilience strategies and sustainable infrastructure development in rapidly growing coastal megacities, like Mumbai.[Figure: see text]
The improvement of landslide susceptibility assessment is a long-standing problem in hazard mitigation work, wherein previous studies have proposed various training models. However, the ratio of positive to negative samples and the selection of non-landslide samples have been shown to significantly influence results. These research directions have traditionally been focal points, while datasets are often overlooked, serving merely as auxiliary tools to support the validation process. Hence, this study proposes an approach to enhance datasets through the introduction of the side-sampling method. This technique focuses on individual research cells, conducting feature sampling training on fixed regions of length M, thereby enabling more precise identification of geographical clustering characteristics. Using evaluation metrics such as accuracy, precision, recall, F1 score, and ROC curve, this study conducts a comparative analysis between the side-sampling method and traditional sampling methods, using three distinct railway lines in China as the study areas. Results show substantial improvements beyond several exceptions: accuracy (+7.68%), precision (+7.19%), recall (+13.48%), F1 score (+9.92%), and ROC (+6.22%). The results demonstrate a significant overall improvement in the performance of the trained models based on the side-sampling method, providing a positive insight into mitigating landslide hazards along railways from the dataset perspective.
Dina Ruslanjari, Retno A.P. Putri, Diana Puspitasari
et al.
The Disaster Preparedness Village (Kampung Siaga Bencana or KSB) in Special Region of Yogyakarta Province (DIY) is a community that aims to increase community preparedness and resilience to disasters through collaboration between the local government, non-government organisations and the community. This research examines the sustainability factors of KSB, namely the role of local leadership and government collaboration in disaster risk reduction (DRR) efforts. The method used in this research is a qualitative method and Strength, Weakness, Opportunity and Threat (SWOT) analysis, then using a diamond model to visualise the role of local leadership and the role of government. The results of this research show the importance of local leadership role in the sustainability of KSB. Factors contributing to the success of DIY KSB include independence, fulfillment of social granary logistics and effective two-way communication between KSB management and the village government (Kalurahan). The study supports that effective local leadership empowers the community, influences resource utilisation and facilitates collaborative efforts with the village government and volunteer organisations to address disaster management priorities. In addition, the most significant shortcomings in community leadership based on trust cultural value will negatively impact their sustainability and activeness if the local actors as mobilisers are inactive, and there is no regeneration of active new leaders. The Umbulharjo KSB case study exemplifies effective local leadership, mainly through Jagabaya, the chairman of KSB management. Strong local leadership is a fundamental element in developing a cohesive community actively involved in DRR efforts.
Contribution: The study reveals that local leadership significantly contributes to the development and sustained activity of KSB. The research concludes by emphasising the multifaceted nature of local leadership, considering various perspectives and the community’s values and goals. The diamond model illustrates the intersection between societal opportunities and government support, demonstrating the realisation of goals through effective local leadership.
The Agile principal-based regulation is necessary for adaptation to rapid technology changes. The fast-paced progress in digital technology can be a challenge to traditional regulation which is often process-based and consultative. These challenges require regulatory actions that minimize the risk and while being agile enough to allow research, innovation and technology diffusion to continue. Agile regulation offers advantages such as information capabilities and industry communication improvement, cost reduction and performance and efficiency increase. In this paper, tools for agile governance and regulation are introduced, and some approaches for expanding regulation beyond the governance and the key principles for agile regulation are discussed. Further, the important issues of agile regulation such as joint-up regulation, outcome-focused regulation and international cooperation are discussed and regulation management approaches to ensure suitability for the future. Finally, based on the findings of this research, we propose an agile regulatory framework for Iran. This proposed framework can play an important role in organizing the regulation of the digital economy and determining the connections between its parts.
Regulation of industry, trade, and commerce. Occupational law, Islamic law
Purpose: This study aims to analyze effective corporate financial management practices and their implications. The focus is on identifying key determinants, examining their impact on firm performance and shareholder value, and exploring moderating effects of contextual factors such as industry characteristics and regulatory environments. Practical implications for corporate managers, investors, policymakers, and stakeholders are also provided. Research Design and Methodology: A quantitative descriptive research design is employed, synthesizing insights from existing literature. Data is collected through comprehensive literature searches in academic databases, journals, books, and conference proceedings. Thematic analysis, content analysis, and narrative synthesis are used to identify key themes, theoretical frameworks, and empirical findings. Findings and Discussion: Findings reveal that strategic financial planning, capital structure decisions, effective risk management, and transparent financial reporting are crucial components of effective corporate financial management. Strategic financial planning guides decision-making and resource allocation. Optimal capital structure decisions balance debt and equity to maximize shareholder value. Effective risk management enhances financial stability and resilience, while transparent financial reporting fosters investor trust and market efficiency. Strong corporate governance mechanisms are essential for ensuring transparency, accountability, and ethical conduct in financial management practices. Implications: Practical implications include adopting an integrated approach to financial management, encompassing financial planning, capital structure decisions, risk management, and transparent reporting. Emphasizing strong corporate governance is crucial for ethical and accountable financial practices. Future research should explore emerging trends, challenges, and opportunities in corporate financial management, ensuring organizations remain resilient and adaptable in a dynamic business environment.
Fanni Vasvári, Márta Juhász, Katalin Gerákné Krasz
Introduction: This study focuses on one of the largest Hungarian companies with a century-long history in the electricity supply business. It aims at examining the relationship between leadership style and safety-awareness in the perceptions of leaders and subordinates. Method: Middle-level managers (N=163) completed the MLQ. Subordinates (N=650) completed the MLQ and expanded with specific subscales, along which employees judged the leadership style of their managers. We relied on some approaches and on analysis of the interviews with participants. To measure safety-awareness, we use 3 different scales. Results: Based on the results, in the subordinates’ sample, all scales of Transformational leadership positively significantly correlated with all component of safety-awareness, while all scales of Transactional leadership negatively significantly correlated with every component of safety-awareness. In the managers’ sample, both the Transformational and Transactional leadership showed a significant positive correlation with all component of safety-awareness except for the Laissez-Faire leadership, where a negative significant relationship was found. Conclusions: In case of subordinates, safety-awareness is associated with their leader’s transformational leadership. From the perspective of managers, it appears that a basic level of safety-awareness is associated to Transactional leadership traits, while a higher level of safety-awareness requires a Transformational leadership.
Engineering (General). Civil engineering (General), Risk in industry. Risk management
COVID-19 has created an entirely new unknown environment with new risks. Various restrictive national measures seeking to protect health took precedence over economic measures. Moreover, a large number of businesses are entirely dependent on international trade and exports. The aim of this paper is to map and analyze the development of small and medium enterprises’ exports during the COVID-19 pandemic in the Czech Republic. Moreover, it identifies the most significant export risks and their perception by small and medium enterprises. The chi-square test, Cramer’s coefficient, and exact binomial test were used to verify the statistical dependencies of research questions and hypotheses.Empirically, the statistically significant impact of the COVID-19 pandemic on the decline in small and medium enterprises’ exports was confirmed. In connection with the effectiveness of risk management, it was found that less than 50% of enterprises in the research sample are not ISO 31000-certified. The study concluded that the most significant export risks confirmed by statistical testing were COVID-19 risks and payment morale of foreign trading partners.
AcknowledgmentThis study is co-financed by DKRVO 2022/04 Lean a Project Management in manufacturing Industry in the Czech Republic.
Anna Bottasso, Pier Giuseppe Giribone, Michelangelo Fusaro;
et al.
Certificates are structured financial instruments that aim to provide investors with investment solutions tailored to their needs.
Certificates can be modeled using a bond component and a derivative component, typically an options strategy. The pricing of
certificates is typically performed using the Monte Carlo numerical methodology. Such method allows for projections of the
underlying using series of random numbers. The results obtained display an error (standard deviation) that depends on the number of simulations used and on the specific characteristics of the structured product. This work has the objective of minimizing the experimental error, and, consequently, of accelerating the speed of convergence using statistical techniques known in the literature as variance reduction methods. The most popular stochastic dynamics have been analyzed, like the classical Black and Scholes model, the Local Volatility model and the Heston model. Three certificates are analyzed in the paper and they are characterized by different payoffs. The variance reduction techniques, implemented in different programming languages (Python, Matlab and R), are: Latin Hypercube, Stratified Sampling, Antithetic Variables, Importance Sampling, Moment Matching and Control Variates.
Based on the data of Chinese A-share pharmaceutical industry companies from 2017 to 2020, this paper analyzes the impact of ESG information disclosure on financial risk. The results show that good ESG information disclosure can significantly reduce the financial risk of enterprises. The effect of ESG information disclosure on financial risk control of non-state-owned enterprises is more prominent, and the higher the degree of marketization, the more obvious the positive effect.
Background The accumulation of risk for the development of rheumatoid arthritis (RA) is regarded as a continuum that may start with interacting environmental and genetic factors, proceed with the initiation of autoimmunity, and result in the formation of autoantibodies such as anti-citrullinated peptide antibodies (ACPA). In parallel, at-risk individuals may be asymptomatic or experience joint pain (arthralgia) that is itself non-specific or clinically suspicious for evolving RA, even in the absence of overt arthritis. Optimal strategies for the management of people at-risk of RA, both for symptom control and to delay or prevent progression to classifiable disease, remain poorly understood. Methods To help address this, groups of stakeholders from academia, clinical rheumatology, industry and patient research partners have collaborated to advance understanding, define and study different phases of the at-risk state. In this current report we describe different European initiatives in the field and the successful effort to build a European Registry of at-risk people to facilitate observational and interventional research. Results We outline similarities and differences between cohorts of at-risk individuals at institutions spanning several countries, and how to best combine them within the new database. Over the past 2 years, besides building the technical infrastructure, we have agreed on a core set of variables that all partners should strive to collect for harmonization purposes. Conclusion We emphasize to address this process from different angles and touch on the biologic, epidemiologic, analytic, and regulatory aspects of collaborative studies within a meta-database of people at-risk of RA.
PurposeMedical equipment’s supply chains play a vital role in performance of national 1healthcare systems. This supply chain is confronted with different internal and external risks. The purpose of this study is to investigate and find the key factors affecting the resilience of the supply chain of medical equipment and to examine the dynamic relations among these factors.Design/methodology/approachA hybrid methodology is used for meeting the purpose of this study. First, the Delphi method is extended by using hesitant fuzzy linguistic term sets to identify the key factors of supply chain resilience. At the second phase, using the system dynamic methodology, the dynamic relations among identified resilience factors are analyzed.FindingsUsing the Delphi method, agility, collaboration among actors, sharing of information, trust among actors, explicitness of supply chain, risk management culture, adaptability, structure, funding and environment conditions are identified as ten major factors affecting medical equipment’s supply chain resilience. Also, four scenarios are simulated along with their impacts on the system.Originality/valueThe main contribution of this study is extending a hesitant fuzzy linguistic term sets-based Delphi and applying it along a system dynamic analysis to identify the key factors affecting resilience of medical equipment’s supply chain for the first time.