Robust Management Strategies Research Articles

IMPACT OF EXTERNAL DEBTS ON ECONOMIC GROWTH IN NIGERIA

The study examined the impact of external debts on economic growth in Nigeria. Annual time-series from 2001 to 2022, sourced from Central Bank of Nigeria, Nigerian Exchange Group and Securities Exchange Commission, are adopted. The data was subjected to linear regression analysis which was used to estimate the parameters of the model. The findings revealed that external debts services, debts services costs, and exchange rate fluctuations all have a negative relationship with economic growth. This highlights that higher burdens of external debt servicing and greater exchange rate volatility are associated with reduced economic growth. Thus, the study recommends that government should implement robust debt management strategies that prioritize sustainable debt levels and efficient servicing, The government should introduce policies aimed at stabilizing exchange rates to reduce volatility. Moreso, they diversify the economy, especially by promoting sectors less susceptible to external shock, to reduce dependence on external factors that could exacerbate debt and exchange rate vulnerabilities.

Global water gaps under future warming levels

Understanding the impacts of climate change on water resources is crucial for developing effective adaptation strategies. We quantify “water gaps”, or unsustainable water use – the shortfall where water demand exceeds supply, resulting in scarcity. We quantify baseline and future water gaps using a multi-model analysis that incorporates two plausible future warming scenarios. The baseline global water gap stands at 457.9 km3/yr, with projections indicating an increase of 26.5 km3/yr (+5.8%) and 67.4 km3/yr (+14.7%) under 1.5 °C and 3 °C warming scenarios, respectively. These projections highlight the uneven impact of warming levels on water gaps, emphasizing the need for continued climate change mitigation to alleviate stress on water resources. Our results also underscore the unequal adaptation needs across countries and basins, influenced by varying warming scenarios, with important regional differences and model variability complicating future projections. Robust water management strategies are needed to tackle the escalating water scarcity caused by global warming.

Landslides in a changing world

Abstract This article investigates the multifaceted dimensions to understand the interrelatedness among global change drivers and their implications for landslide hazards and disaster risk. Drawing on empirical research, it utilised a mixed-methods design; the research combined diverse data sources and experiential insights on the interdependencies bounded by local context and global scale. The findings underscore the urgent need for holistic approaches that consider the complex dimensions of landslides as socio-natural hazards and global change, emphasising the importance of collaboration, innovation, and international cooperation in building resilience and mitigating the adverse effects of landslide disaster risk on global systems and societies. Furthermore, the challenge of reducing landslide disaster risk lies in understanding and addressing the interplay between socio-environmental transformations and geodynamic processes. The escalating effects of climate change, urban expansion, and deforestation are anticipated to magnify the occurrence of landslides, thereby posing significant risks to human lives, infrastructure, ecosystems, and livelihoods. However, most importantly, these risks are further compounded by environmental, social, economic, political, cultural, and technological spheres associated with globalisation. The systemic nature of disaster risk, particularly landslides in a changing world, highlights the interconnectedness of different systems, resulting in complex causality and cascading impacts. These insights contribute to the broader discourse on sustainability by providing empirical evidence that supports integrated approaches to achieving long-term disaster risk reduction based upon the equitable and sustainable use of territories while integrating robust disaster risk management strategies to ensure resilient communities and ecosystems.

The Influence of External Environmental to the Relationship between Infrastructure Financing and Success in Implementation of Kenya Vision 2030 Public Capital Projects

Purpose: This study examined the impact of infrastructure financing on the successful implementation of public capital projects under Kenya’s Vision 2030. It specifically focused on the mediating influence of external socio-economic and political factors and aimed to identify the extent to which these variables influence project success. Materials and Methods: A positivistic approach was adopted, utilizing quantitative data and hypothesis testing to generate conclusions. The study employed a descriptive cross-sectional research design to analyze high-impact infrastructure projects in the roads, energy, and water & sanitation sectors over the past decade under Kenya’s Medium-Term Plans (MTP I and MTP II). Data were collected from 313 projects, including 220 in roads, 20 in power and energy, and 73 in water and sanitation, achieving a response rate of 83.07%. Descriptive statistics, multiple linear regression, and factor analysis were used to explore relationships between infrastructure financing, project success, and external environment factors. Findings: The study revealed that infrastructure financing significantly influenced the success of public capital project implementation, while the external socio-economic and political environment mediated this relationship. However, these factors alone did not sufficiently explain cost and time overruns, suggesting that other unexplored variables contribute to these project inefficiencies. Implications to Theory, Practice and Policy: The findings imply that existing theories on project success must consider additional variables beyond financing and external environments to explain cost and time overruns. In practice, implementing agencies should enhance internal assessments and risk management, particularly for projects financed through public-private partnerships (PPPs). Policymakers, including the Government of Kenya, should prioritize governance frameworks and robust risk management strategies to mitigate external environmental risks, thereby improving the success rate of Vision 2030 projects.

Integration of ESG Data in the Retail Sector (Essential for Sustainable business and Risk Management)

The ESG data integrated into the retail industry have grown as an essential driver of sustainable business practices and robust risk management strategies. With sustainability concerns being highly critical for businesses around the world, retail organizations have taken up the ESG metrics as the yardstick to measure, report, and act upon environmental and social impact, ensuring good governance. It explains how AI-driven business intelligence integrates ESG factors for the improvement of sustainability metrics in the retail industry, focusing on how such integration supports the creation of sustainable business strategies and improves financial performance. It discusses challenges and opportunities in adopting sustainability reporting and ESG metrics, drawing on global evidence from retail performance-related studies and providing insight into how ESG adoption may influence operational efficiency, consumer trust, and long-term value creation. The study also underlines the role of AI in the automation of ESG factor scoring; it thus facilitates decision-making, transparency, and risk management. This paper also articulates how ESG integration relates to better performance of the firm within a transition towards the Circular Economy and vice versa in the retail sector. Keywords:ESG, Retail Sector, Sustainable Business Practices, AI-driven Integration, Risk Management, Sustainability Reporting, Circular Economy, Business Intelligence, Firm Performance, and Corporate Social Responsibility.

Supply Chain Disruption and Import Strategy: Evidence from the Great East Japan Earthquake

AbstractGlobal supply chain networks foster collaboration but accelerate cross‐border risk transmission. This study investigates the effect of the 2011 East Japan earthquake on Chinese firms' import strategies. The findings reveal that the disruption led to a shift toward supply chain concentration, with firms reducing the diversification of import sources. There was a slight increase in the number of countries from which firms sourced imports but import shares became more concentrated, reflecting a reliance on fewer, centralized suppliers. Firms affected by the earthquake prioritized long‐term partnerships and sought suppliers in regions with lower natural disaster risks, aiming to mitigate supply chain vulnerabilities and reduce switching costs. The findings also show that state‐owned enterprises, private firms, and research and development‐intensive firms were more inclined to centralize their import sources. This suggests that these firms, leveraging their larger scale, substantial resources, and robust risk management strategies, favored a more concentrated sourcing approach in order to better control their supply chains and ensure stability in the face of global disruptions.

An Analysis on The Fluctuations of Exchange Rate and it's Impact on Financial Performance with Special Reference to Vedanth Tech Solutions Bangalore

Exchange rate fluctuations significantly influence the financial performance of globally engaged organizations. This study examines the impact of currency volatility on the financial health of Vedant Tech Solutions, a technology firm based in Bangalore. Through a detailed analysis of financial data, the research evaluates how foreign exchange variations affect profitability, revenue, and operational costs. The study employs quantitative techniques, including trend analysis and regression models, to establish a correlation between exchange rate changes and key financial metrics. The findings highlight the need for robust foreign exchange risk management strategies to mitigate adverse impacts and enhance financial stability. To analysis the research used a secondary data from company site and research paper and ratio analysis as a statistical tool. Insights derived from this research aim to guide Vedant Tech Solutions and similar organizations in navigating exchange rate uncertainties effectively. Keywords: Exchange rate fluctuations, financial performance, foreign exchange risk, currency volatility, risk management.

Assessment of Project Risk Performance of Selected Mass Housing Infrastructures in Northern Nigeria

Mass housing projects in Northern Nigeria often suffer from insufficient risk management, impacting timely delivery, budget adherence, and quality standards. This study assesses risk vulnerabilities in selected mass housing infrastructure projects, focusing on information risks related to roles, responsibilities, scope, requirements, and operations. A mixed-methods approach was employed, with data collected from 465 construction professionals across 20 states, with a 64.58% response rate. Analytical tools, including regression and Pearson correlation, identified critical risks such as underfunding, weak project monitoring and control, and the failure to deliver end-user value. Findings reveal that these risks significantly undermine project outcomes, highlighting the need for robust risk management strategies. A risk management framework is proposed to prioritize and address these vulnerabilities throughout the project lifecycle. This research contributes to the field by offering actionable insights for policymakers and practitioners to enhance mass housing delivery, ensuring alignment with end-user needs and project goals.

Health-Economic Impact Attributable to Occurrence of Pleurisy and Pneumonia Lesions in Finishing Pigs.

Respiratory diseases, such as pleurisy and pneumonia, cause significant health and economic losses in pig production. This study evaluated 867 finishing pigs from a farm with a history of respiratory issues, using macroscopic lesion scoring (SPES and CVPC), histopathological analysis, qPCR diagnostics, and economic modeling. Severe pleurisy (scores 3 and 4) was observed in 42.1% of carcasses and was strongly correlated with higher bacterial loads of Mycoplasma hyopneumoniae, Actinobacillus pleuropneumoniae, and Pasteurella multocida. Severe lesions reduced the average daily gain (ADG) and carcass weight, leading to increased production costs and lower profitability. Economic analysis revealed that pigs with higher pleurisy scores incurred an additional cost per kg (USD 1.29 vs. USD 1.32 for milder cases), reduced total revenue by 1.36%, and decreased return on investment (ROI) from 5.33% to 3.90%. These findings emphasize the critical impact of respiratory diseases on profitability and the necessity of robust health management strategies, including vaccination and enhanced biosecurity, to minimize economic losses in swine farming.

SUPPLY CHAIN INNOVATION AND COMPETITIVE ADVANTAGE IN THE COFFEE BUSINESS IN CENTRAL ACEH DISTRICT, ACEH PROVINCE

The agriculture sector highly depends on various suppliers to meet its input requirements. Because the agriculture sector relies so heavily on its suppliers, robust supply chain management and strong supplier relationships ensure agribusiness sustainability and efficiency. Aceh's coffee supply chain is typified by low profitability and poor optimization, especially regarding Gayo Arabica coffee. The COVID-19 pandemic has elevated distribution risks at different supply chain stages, exacerbating this further. The relationship between supply chain innovation and competitive advantage in the coffee sector in Aceh Tengah District, Indonesia, is investigated in this quantitative study employing a mediation model. With 60 respondents, Central Aceh Regency was selected using a purposive sampling technique for research purposes. This study uses a Likert-scale questionnaire with structural equation modeling (PLS-SEM). This research aims to assist Acehnese coffee companies in gaining a competitive edge through innovative supply chain practices, resulting in more robust and efficient risk management and sustainability strategies. The results show that supply chain innovation and resilience capability do not affect competitive advantage, where the p-value of these two variables is 0,4. In addition, resilience capability as a mediating variable does not directly affect supply chain innovation and competitive advantage. Keywords: agribusiness, coffee, sem pls, supply chain innovation

Difficulties faced by three hospitals evacuated from the urgent protective action planning zone after the 2011 Fukushima Daiichi Nuclear power plant accident.

In radiological disasters, evacuating institutionalized individuals such as hospitalized patients and nursing home residents presents complex challenges. The Fukushima Daiichi Nuclear power plant (FDNPP) accident, triggered by the Great East Japan Earthquake (GEJE), exposed critical issues in evacuation planning. This case series investigates the evacuation difficulties encountered by three hospitals situated 20 to 30km from the FDNPP following the GEJE and FDNPP accident. Data collection involved reviewing records, stakeholder interviews and analyzing publicly available resources. Six key challenges emerged: acute phase influx-hospitals faced an abrupt surge in patients, including trauma victims and vulnerable individuals; initial discharge and transfers-coordinating patient discharges and transfers during the chaotic aftermath proved daunting; staff shortages-evacuation and personal factors lead to reduced staffing levels and strained hospital capabilities; infrastructure damage and logistics suspension-infrastructure issues, such as burst water pipes, halted gas supplies, and heavy oil shortage disrupted hospital operations; unclear evacuation criteria-ad hoc evacuation decisions underscored the lack of clear criteria; and limited preparation time-minimal preparation time hindered communication and planning. These findings underscore the need for robust disaster planning, resource management, and communication strategies to ensure the safety of patients and staff during radiological emergencies. Government interventions, early patient discharge, and improved medical record communication may alleviate the burden of evacuation. The lessons learned emphasize the importance of maintaining hospital functions in disaster-prone areas, particularly for vulnerable populations, and highlight the necessity for comprehensive community-wide disaster prevention planning.

GRANTWRITING DURING MARTIAL LAW: RISKS IN AN ENVIRONMENT OF INSTABILITY

The article examines the essence of the category of «risk» in the context of grant-making in martial law. The author analyses the specific threats faced by grantees in the context of armed conflict, including political instability, economic crisis, humanitarian disaster, and logistical problems. Particular attention is paid to assessing the likelihood of these risks, their impact on project implementation, and developing strategies to mitigate the negative consequences. The aim of the study is to develop practical recommendations for grantees and grantors that will facilitate more efficient use of grant funds and establish close cooperation between all stakeholders. The document emphasizes the importance of collective efforts to overcome the challenges of martial law and achieve common goals. The study delves into the multifaceted nature of risks in wartime grantmaking, taking an interdisciplinary approach. It draws on knowledge from different fields such as management, sociology and political science to develop a comprehensive understanding of the challenges and opportunities. This interdisciplinary approach allows us to find innovative solutions and develop more robust risk management strategies. The study highlights the importance of proactive risk management and contingency planning. By anticipating potential risks and developing strategies to mitigate their impact, grantees can increase the likelihood of project success. The paper emphasizes the need for flexible and adaptive approaches that can respond to rapidly changing circumstances. It also highlights the importance of collaboration between grantees, donors and other stakeholders to share knowledge, resources and best practices. By developing strong partnerships, complex problems can be addressed and the resilience of conflict-affected communities can be strengthened. The findings of this study have important implications for policy makers, practitioners and researchers. By providing a deeper understanding of the risks and challenges associated with grantmaking in wartime, this research can contribute to the development of more effective grantmaking policies and practices. In addition, the recommendations presented in the paper can help grantees and donors make more informed decisions and allocate resources more effectively.

Simulating groundwater flow and contaminant transport

This study presents a comprehensive simulation of groundwater flow and contaminant transport using advanced numerical modeling techniques. The research focuses on understanding the complex interactions between groundwater movement and pollutant dispersion across various geological settings. By applying the governing equations of fluid dynamics and solute transport, the model incorporates essential parameters such as hydraulic conductivity, porosity, and dispersivity, enabling the accurate prediction of contaminant behavior over time. Simulations were carried out under a range of scenarios to assess the effects of differing recharge rates and contaminant source configurations on groundwater quality. The results provide critical insights into the mechanisms governing contaminant migration, highlighting the importance of soil properties, boundary conditions, and flow dynamics in influencing transport behavior. Moreover, the study demonstrates how variations in geological features and pollutant sources can significantly alter contaminant dispersal patterns. This work contributes to the development of robust groundwater management strategies and emphasizes the role of simulation tools in assessing environmental risks tied to groundwater contamination.

Improving realised volatility forecast for emerging markets

AbstractAccurate forecasting of realised volatility is essential for financial risk management and investment decision-making in emerging markets, taking the South African financial market as a benchmark. This study examines the predictive performance of four prominent models: HAR (Heterogeneous AutoRegressive), realised GARCH (Generalized AutoRegressive Conditional Heteroscedasticity), Recurrent Conditional Heteroskedasticity (RECH), and the Rough Fractional Stochastic Volatility (RFSV) models. These models are specifically tailored to capture the complex dynamics and long-range dependence observed in financial time series. We illustrate the challenges and limitations of these models outside the context of established markets. Our empirical findings reveal unique strengths for each model. The HAR model excels in capturing long-term volatility patterns, while realised GARCH models effectively capture volatility clustering and persistence. RECH model showcases their ability to forecast Value-at-Risk, while the RFSV model successfully captures irregular and long-memory characteristics. We provide empirical evidence that the South African financial market is rough. Moreover, this study provides valuable insights into forecasting realised volatility in the South African market, and the findings can assist practitioners and investors in making informed decisions and developing robust risk management strategies.

The Effect of Natural Disaster on Regional Economic Growth: Evidence from an Earthquake in İzmir/Türkiye

This study examines the economic impact of the Aegean Sea Earthquake, which struck İzmir, Türkiye, on October 30, 2020, focusing on how it affected local businesses and financial resilience. Using a combination of survey data and regression analysis, the study investigates the operational disruptions experienced by companies of varied sizes and sectors. Findings show that while large firms displayed resilience, small businesses suffered significant operational and financial setbacks, prolonging the economic recovery process. The study also highlights the compounded effects of the COVID-19 pandemic, which intensified the challenges that companies faced. The results underscore the importance of developing robust crisis management strategies and fostering economic structures that are more resilient to both natural disasters and global crises. The study concludes with recommendations for policymakers and business leaders to enhance financial resilience to future shocks.

Utilizing Distribution of Relaxation Times Analysis for Water Content Management in Anion Exchange Membrane Fuel Cells

Amid escalating concerns over air pollution and energy scarcity, Anion Exchange Membrane Fuel Cells (AEMFCs) are increasingly recognized as a viable solution for power generation, offering high efficiency, and zero emissions. Water plays a critical role within these systems as a reactant, consumed at the cathode and generated at the anode. This process can lead to disparities in water content, potentially compromising the cell's performance. Therefore, it is imperative to maintain optimal water distribution to facilitate effective charge transport and enhance electrochemical reaction kinetics. Consequently, devising a robust water management strategy is essential to ensuring the sustained operation and longevity of AEMFCs.Characterizing the water conditions at the anode and cathode under various operational states (normal, drying, or flooding) is a pivotal step underpinning effective water management strategies. Electrochemical Impedance Spectroscopy (EIS) provides a valuable tool for examining various resistances associated with kinetics, mass transport, and ohmic losses across different operational timescales, thereby facilitating a detailed assessment of water transport dynamics. Traditional analyses of EIS data often depend on equivalent circuit models, which require predefined assumptions and the selection of initial components. However, this study adopted the Distribution of Relaxation Times (DRT) methodology for its exceptional capability to disaggregate components, enabling a more nuanced analysis of the polarization processes. The DRT methodology was applied to scrutinize the patterns of loss and variation within each polarization process under varying water flooding and drying conditions at the anode and cathode. Moreover, to deepen our comprehension of how water content influences mass transport and electrochemical reaction kinetics, a three-dimensional multi-physics model for AEMFCs was developed. This model comprehensively integrates considerations of water phase transitions, heat and mass transfer, as well as the transport of liquid and dissolved water, alongside electrochemical reactions. These efforts collectively forge a comprehensive and systematic framework to advance the application of the distribution of relaxation times in optimizing fuel cell performance.

Characterization of virus species associated with sweet potato virus disease in Costa Rica and riboprobe development for its rapid detection

AbstractSweet potato (Ipomoea batatas) is a crucial crop for food security and economic stability in many regions, including Costa Rica. This study aimed to assess the prevalence and genetic diversity of two major viruses associated with sweet potato virus disease (SPVD) in Costa Rica: sweet potato feathery mottle virus (SPFMV) and sweet potato chlorotic stunt virus (SPCSV). A total of 50 leaf samples displaying typical viral disease symptoms were collected from major sweet potato‐growing regions. Using multiplex reverse transcription (RT)‐PCR, SPFMV was detected in 82% of the samples and SPCSV in 52%, with a coinfection rate of 48%. Genetic analysis revealed that SPFMV isolates belonged predominantly to phylogenetic group B, while SPCSV isolates clustered with the West African (WA) strain. The low genetic diversity within these viral populations suggests a limited number of initial infection events followed by local spread. Riboprobe technology was evaluated as an alternative to RT‐PCR for virus detection. While the riboprobes for SPFMV demonstrated sensitivity comparable to RT‐PCR, the SPCSV riboprobes showed slightly lower sensitivity, particularly when using crude leaf extracts. Despite this, riboprobes offer significant advantages in terms of cost and ease of use for large‐scale screening. Our findings underscore the need for robust diagnostic and management strategies to control SPVD and highlight the importance of continuous monitoring and research to mitigate the impact of viral diseases on sweet potato production in Costa Rica. These insights contribute to the global understanding of SPVD and support collaborative efforts in plant pathology research.

Personalized Recommendation Intelligent Fuzzy Clustering Model for theTourism

Personalized recommendations in tourism have transformed the way travellers explore new destinations, offering tailored experiences that align with individual preferences and interests. As the travel industry increasingly harnesses data analytics and artificial intelligence, tourists can now receive customized suggestions that reflect their unique tastes, whether they seek adventure, relaxation, cultural immersion, or culinary exploration. This paper explores the implementation and effectiveness of intelligent tourism management strategies using fuzzy clustering and personalized recommendations. By analyzing various scenarios, including baseline, personalized recommendations, dynamic pricing, crisis management, and enhanced resource allocation, the study demonstrates how advanced data-driven techniques can significantly improve key performance indicators such as visitor satisfaction, total revenue, repeat visitation rates, and operational efficiency. The simulation results reveal that personalized recommendations and optimized resource allocation are particularly effective in enhancing visitor experiences and economic outcomes. Conversely, the analysis underscores the critical need for robust crisis management strategies to maintain performance during adverse events. This research provides valuable insights into the transformative potential of intelligent systems in modern tourism management, offering a pathway towards more resilient and competitive tourism destinations. For instance,personalized recommendations increased average visitor satisfaction from 7.2 to 8.5, total revenue from $500,000 to $600,000, and the repeat visitation rate from 35% to 45%. The dynamic pricing strategy improved visitor satisfaction to 7.8 and revenue to $550,000, while enhanced resource allocation resulted in a satisfaction rate of 7.9 and revenue of $570,000. Conversely, crisis management showed the importance of preparedness, as satisfaction dropped to 6.5 and revenue to $450,000. These results underscore the critical need for robust management strategies.

Analysis of the Impact of Liquidity Policy and Economic Fluctuations on Asset and Wealth Management in the Banking Sector in Indonesia

This study analyzes the impact of liquidity policy and economic fluctuations on asset and wealth management in the Indonesian banking sector. Utilizing a quantitative approach, data were collected from 150 banking professionals through a structured questionnaire and analyzed using Structural Equation Modeling (SEM) with Partial Least Squares (PLS) version 3. The results demonstrate that economic fluctuations significantly impact both asset and wealth management, with a stronger influence on wealth management. Liquidity policy also plays a crucial role in improving asset and wealth management practices, though its impact is moderate compared to economic fluctuations. These findings suggest that banks must adopt robust liquidity management and risk mitigation strategies to navigate periods of economic uncertainty and optimize asset and wealth management practices. The study provides important insights for banking professionals and policymakers aiming to enhance financial stability and operational efficiency in the banking sector.

Artificial Intelligence-Powered Risk Assessment in Supply Chain Safety

The increasing complexity and globalization of supply chains necessitate robust risk management strategies to ensure safety and resilience. Traditional risk assessment methods often fall short in dynamically adapting to the rapidly changing conditions and voluminous data inherent in modern supply chains. This study explores the potential of Artificial Intelligence (AI)-powered risk assessment to address these limitations in the context of Malaysia's supply chain industry. By employing AI technologies such as machine learning, IoT, and predictive analytics, organizations can significantly enhance their risk management capabilities, improving predictive accuracy, real-time monitoring, and overall operational efficiency. Through a qualitative analysis involving in-depth interviews with supply chain managers, AI experts, and technology vendors, the study identifies the strategies employed for AI integration, the perceived effectiveness of these technologies, and the challenges faced in implementation. The findings highlight the importance of robust data governance, the development of explainable AI models, and continuous skill development to overcome barriers related to data quality, model interpretability, and high implementation costs. The study concludes with recommendations for fostering a safer and more resilient logistics environment in Malaysia, emphasizing the need for comprehensive AI adoption frameworks and scalable solutions for small and medium-sized enterprises.