Abstract: Food security, defined as universal access to sufficient, safe, and nutritious food, is a complex and multi-dimensional issue involving agricultural, ecological, and sociological systems. This paper explores food security through the development of a stylized mathematical model focused on the UK pork industry, an agricultural system shaped by environmental, economic, and social factors. The model employs coupled ordinary differential equations (ODEs) to capture dynamic interactions among key variables such as capital, inventory, demand, and price, reflecting core economic and ecological processes. Bayesian estimation techniques are used to assess parameter uncertainty and enhance the model's robustness in addressing disruptions like Brexit and the COVID-19 pandemic, which have strained supply chains and labor markets. The findings provide insights into the sustainable capacity of the UK pork industry while offering methodological tools for analyzing food system resilience in the face of environmental and market fluctuations.

Abstract: As cities confront rising populations and mounting environmental pressures, waste is rapidly transforming from a logistical liability into a strategic economic resource. In this article, we investigate the evolving nexus between waste and urban economic systems by analysing over 2,000 scientific publications sourced from Web of Science and Scopus. Using advanced semantic embedding and network analysis, we identify seven major research communities at the intersection of digital innovation, circular economy, and smart urban infrastructure. Through PageRank-based influence mapping, we highlight key contributions that shape each thematic cluster—ranging from AI-powered waste classification to blockchain-enabled traceability and IoT-driven logistics. Our results reveal a dynamic and interdisciplinary research landscape where waste valorisation is not only a sustainability imperative but also a driver of urban economic renewal. This study offers both a conceptual map and a methodological framework for understanding how cities can embed intelligence, efficiency, and circularity into waste systems as part of a broader transition to regenerative, data-informed urban economies.

Abstract: In light of the Sustainable Development Goals, businesses are progressively integrating environmental, social, and governance (ESG) factors in their investment planning. Scholars, investors, and politicians frequently examine climate variability risk (CVR) impact on enterprise worth (EW), how certain investing techniques mitigate this impact. In order to investigate these patterns, we quantify the impact of CVR on EW by analyzing data from 1720 US-listed companies throughout 2005 to 2020. To accomplish our goal, we apply GMM approach to consider the regression estimations. The following are our primary findings: Initially, CVR has a substantial detrimental impact on EW. However, enterprise worth is positively and considerably impacted by ESG investments. Similarly, the link between CVR and EW moderated in part by ESG investments. We verify that our estimations hold up well under different methodological conditions. Finally, this study presents a novel viewpoint on risk management with important policy ramification for US managers, investors, and regulators. We contend that US corporations need to use firms ESG investing as a key strategic driver.

Abstract: As technology rapidly evolves and global priorities shift toward sustainability, organizations are revisiting their human resource strategies to align with the United Nations’ Sustainable Development Goals (SDGs). This study examines the strategic integration of Artificial Intelligence (AI) into Sustainable Human Resource Management (S-HRM), focusing on its role in building resilient, future-oriented workforces. Drawing on primary data collected from HR professionals across diverse sectors, the research explores how AI tools—including predictive analytics, machine learning, and intelligent automation—can enhance eco-friendly recruitment, performance evaluation, and employee well-being. The study identifies key drivers and obstacles influencing the adoption of AI in sustainable HRM and presents a conceptual model for AI-enabled HR practices that promote environmental, social, and economic sustainability. Emphasizing ethical implementation, collaborative learning, and data-driven decision-making, the model supports long-term organizational adaptability and resilience. The paper contributes to both academic discourse and practical HR leadership by offering actionable insights for integrating AI into HR strategies that uphold sustainability values. Ultimately, this research provides a strategic roadmap for leveraging AI not just as a technological enhancement but as a catalyst for enduring, human-centered organizational development in a rapidly changing business landscape.

Abstract: This study examines the strategic complexity of decision-making inside live e-commerce supply chains, especially in relation to the impact of Netflix-style entertainment marketing. As live commerce integrates digital retail with immersive experiences, businesses must optimize pricing, quality, and marketing strategies in real time. This study constructs a game-theoretic framework to analyze interactions between manufacturers and online celebrity retailers (OCRs), examining centralized, manufacturer-led, and retailer-led scenarios. We present engagement-driven marketing as a strategic variable and incorporate consumer regret and switching costs into the demand function. To illustrate practical trade-offs in strategy, we incorporate a Multi-Criteria Decision-Making (MCDM) layer with AHP-TOPSIS, assessing profit, consumer surplus, engagement score, and channel efficiency. The experiment results indicate that Netflix-style marketing markedly increases demand and profit in retailer-led frameworks, whereas centralized tactics enhance overall channel performance. The TOPSIS analysis prioritizes high-effort, high-engagement methods, whereas the Stackelberg experiment underscores the influence of power dynamics on profit distribution. This study presents an innovative integrative decision-making methodology for enhancing live-streaming commerce tactics in data-driven and consumer-focused markets.

Abstract: Rivers State stands at a crossroads. Despite its immense oil wealth, too many of its young people are locked out of many of these opportunities, facing high unemployment, living amid environmental decline, and, for some, turning to dangerous informal economies like artisanal oil bunkering popularly known as “kpo-fire” just to survive. But all hope isn’t lost, there is a way forward.

Abstract: This study investigates the relationship between economic policy uncertainty (EPU) and corporate cash holdings, focusing on non-financial firms listed on the Johannesburg Stock Exchange (JSE). It aims to understand how South African firms adapt their financial strategies in response to EPU, addressing a gap in empirical research within developing economies. The study uses a sample of 184 non-financial firms listed on the JSE to examine the impact of EPU on corporate cash holdings, exploring the mediating role of capital expenditure and the moderating role of financial constraints. The findings reveal a positive relationship between EPU and corporate cash holdings, mediated by capital expenditure. The results further show that financial constraints do not significantly moderate this relationship. This supports the real options theory over the pre-cautionary savings theory in explaining the observed link between EPU and cash holdings. The study offers insights for corporate managers and policymakers on how firms in developing economies adjust their financial policies in response to heightened economic uncertainty, informing strategic decisions in uncertain policy environments. This research contributes to the limited literature on EPU in emerging markets by providing evidence from South Africa. It advances understanding of firm behaviour under uncertainty and supports theoretical perspectives that prioritize investment deferral options over precautionary motives in cash holding decisions.

Abstract: The effective mobilization of large-scale capital for climate action represents a critical and defining challenge for emerging market economies (EMEs). This paper presents a comprehensive case study analysis of the Dominican Republic's inaugural sovereign green bond, a USD 750 million issuance in June 2024, examining its structure and performance as a potential model for sustainable finance (Global Green Growth Institute, 2025; World Bank, 2025). The analysis finds that the issuance was highly successful, achieving a notable 15-basis-point pricing advantage, or "greenium," attributable to a robust pre-issuance governance framework and strong international investor confidence (World Bank, 2025). However, this initial success is offset by two challenges: a national climate finance gap exceeding USD 17.6 billion required to meet its Nationally Determined Contribution (NDC) targets, and the pervasive global risk of "greenwashing," which threatens to erode investor trust and erase pricing advantages (Dominican Republic, 2020; Hong Kong Monetary Authority, 2022). This paper argues that to transition from a successful single transaction to a scalable national strategy, EMEs must institutionalize credibility through radical, technology-enabled transparency. It proposes the development of a "Green Bond Impact Tracker," a national digital platform for transparent monitoring, reporting, and verification (MRV) of bond proceeds and their environmental impacts. This proposed solution is presented as a strategic instrument designed to institutionalize transparency, proactively mitigate greenwashing risk, and thereby secure and expand the nation's access to preferential climate financing while simultaneously fulfilling international climate reporting obligations under the Paris Agreement's Enhanced Transparency Framework (UNFCCC, n.d.-b).

Abstract: Cambodia, like countries along the historical Silk Road, stands to gain significant economic benefits from improving its logistics capabilities, international trade, and tourism. In today's globalized economy, the efficiency of logistics is a crucial driver for national economic growth and competitiveness. This analysis, inspired by studies on Silk Road nations, examines how strengthening Cambodia's logistics sector can foster economic development. In today's globalized world, regional connectivity initiatives, such as the broader "Belt and Road Initiative," which impacts Southeast Asia, present significant opportunities for countries like Cambodia to bolster their economies. Key drivers for Cambodia's integration into the global economy are effective logistics, robust international trade, and thriving tourism. This study's relevance lies in its methodological approach, which assesses the logistics factors influencing the economies of countries within these economic corridors. By analyzing international indices of logistics efficiency, trade conditions, and economic models, we can identify challenges and their underlying causes that affect Cambodia's economic development. Ultimately, this approach helps to pinpoint priority initiatives to overcome restrictions that currently impede logistics development and limit trade capacity in Cambodia.

Abstract: While previous research has examined the role of team resources on team resilience from a resource-based perspective, the underlying mechanisms of team resilience emergence from a process perspective remain insufficiently discussed. Grounded in the context of VUCA era and team stress appraisal theory, we explore the mechanism through which team job insecurity influences team resilience and the contextual effects of team task characteristics. Through a three-wave questionnaire conducted with 464 employees from 96 teams, we found that team job insecurity was positively related to team challenge appraisal, which in turn positively related to team resilience. Meanwhile, team job insecurity was positively related to team hindrance appraisal, which in turn negatively related to team resilience. Furthermore, ream task interdependence reinforced the positive effect of team job insecurity on team resilience via challenge appraisal while weakened the negative effect of team job insecurity on team resilience via hindrance appraisal. Both theoretical and practical contributions were discussed.

Abstract: The application of artificial intelligence (AI) in small and medium-sized enterprises (SMEs) in Latin America, highlighting its potential to optimize processes and improve resilience in an uncertain business environment. Using a systematic review of fourteen studies published between 2020 and 2025 and the PRISMA protocol, significant barriers such as lack of technological infrastructure, shortage of specialized talent, and budget constraints were identified. Despite these challenges, AI adoption is advancing, allowing companies to automate processes and perform predictive analytics to make more informed decisions. The discussion emphasizes the need for clear regulatory frameworks to address ethical issues, such as data privacy. In conclusion, although there are significant obstacles, the responsible adoption of AI can significantly improve business performance in the region, provided that public policies are implemented that foster inclusive and sustainable technological development.

Abstract: This study investigates the critical capabilities and integration mechanisms that enable organizations to achieve substantive sustainability transformations. Using a mixed-methods approach combining survey data (n=234), in-depth interviews (n=42), and comparative case studies (n=6), the research identifies how organizations effectively navigate sustainability paradoxes while developing integration practices that embed sustainability throughout organizational systems. Statistical analysis reveals strong relationships between paradox navigation capabilities and transformation outcomes (β=0.31, p<0.01), with integration practices emerging as the strongest predictor of sustainability success (β=0.42, p<0.01). Qualitative findings illuminate four essential integration mechanisms—governance integration, strategic integration, operational integration, and performance integration—and their temporal development. The research contributes to sustainability science by advancing theory on paradoxical tensions in transformation processes, demonstrating how organizations can transcend the gap between sustainability rhetoric and substantive action through both structural integration and power-conscious approaches. By identifying contextual contingencies across sectors and organizational types, the study challenges universal prescriptions for sustainability transformation, offering instead a nuanced framework for creating organizational conditions conducive to context-specific transformation toward more sustainable futures.

Abstract: This study examines the application of Complex Adaptive Systems (CAS) theory to organizational resilience through a mixed-methods approach combining quantitative analysis of 42 organizations across four industries with qualitative case studies. Results indicate that organizations demonstrating higher implementation of CAS principles showed significantly greater resilience during market disruptions (p < 0.01) and higher innovation metrics (p < 0.05). Four key principles emerged as particularly impactful: conceptualizing organizations as living systems, developing self-maintenance capabilities, establishing deep foundations for resilience, and implementing effective feedback mechanisms. The findings contribute to both complexity science and organizational theory by empirically validating CAS principles in organizational contexts, identifying specific mechanisms through which these principles enhance resilience, and providing a practical framework for implementation. This research advances our understanding of organizational adaptation by integrating CAS theory with established organizational frameworks, offering evidence-based strategies for enhancing resilience in volatile environments.

Abstract: Investors study forecasting models for future stock values to make assertive decisions, as each trend movement offers different investment opportunities. The forecasting models described in this research are well suited to provide a realistic view of the future behaviour of stock prices. The autoregressive integrated moving average (ARIMA) model is one of the most relevant linear models for time series forecasting. Recurrent neural networks (RNN) are a class of neural networks that allow using previous outputs as inputs, while having hidden states and capturing the robust and non-linear relationships of the sequence. This paper proposes a hybrid methodology that takes advantage of the strengths of RNNs, linear and ARIMA models in value forecasting problems. Real datasets of Nvidia Corporation (NVDA) stock price on NASDAQ were used to analyse the forecasting accuracy of the proposed model. The main objective is to compare the performance of the combined model compared to each of them separately when it comes to stock price forecasting. By hybridising these models, the methodology is able to correctly predict the NVDA share price. The root mean square error (RMSE), mean absolute percentage error (MAPE) and mean absolute error (MAE) metrics were used to assess accuracy while coefficient of determination (R²) was used to measure goodness of fit.

Abstract: This research examines the influence of innovative leadership and an entrepreneurial mindset on building sustainable business development. Based on five business leadership case studies, the study aims to assess the degree to which innovative leadership, an entrepreneurial mindset, and a certain business leadership style account for organizational sustainability. The central hypothesis is that this combination is essential for sustained organizational progress. Using a purposive sampling approach, five cases across different industries and geographical locations were selected to provide insights and address the research question. The findings clarify the characteristics of innovative leadership, entrepreneurial mindset, and five different leadership styles. The results indicate that a proper fit between the leadership style adopted and the dominant innovative leadership and entrepreneurial mindset can enable the establishment of a unique organizational identity, fostering differentiation and continuous growth.

Abstract: Sustainable aviation fuel (SAF) has demonstrated promising potential in reducing carbon emissions within the aviation industry. Several initiatives have been started to increase the use of SAF in the industry. However, the technology needed for its development requires important insights to guide policymakers and investors. Industry 4.0 is a potential platform that can provide the most technologically sophisticated technologies. This study aims to review the existing literature and identify similar studies and case studies that can assist in advancing SAF supply chains and production processes utilizing technologies offered by Industry 4.0, ultimately helping the SAF Grand Challenge achieve its sustainability goals. This research's findings will benefit practitioners, policymakers, investors, government entities, and other stakeholders in the aviation sector by identifying appropriate methods and technology to enhance SAF production and advance the mission.

Abstract: Recognizing unexplored retail prospects requires an expert understanding of spatial and demographic dynamics. This study introduces an integrated geospatial framework for retail opportunity mapping in Germany, integrating multi-criteria suitability modeling with spatial autocorrelation analysis and Geographically Weighted Regression (GWR). Using high-resolution demographic and retail data, we demonstrate pronounced spatial variation in the influence of key drivers: for example, the local effect of population density on retail suitability peaks in the Hamburg metropolitan region (notably in Norderstedt and Ahrensburg), while point-of-interest clustering is most influential near Rotenburg (Wümme) in Lower Saxony. These findings highlight the regional variability of retail market determinants as revealed by GWR. The gap analysis discovered 40 "white spot" grid cells throughout rural and urban areas that exhibit extraordinarily high anticipated suitability yet lack any retail infrastructure. These priority locations are geographically diverse, including well-populated municipalities in areas such as the districts of Esslingen and Göppingen (Baden-Württemberg), northeastern Brandenburg, and southern Bavaria. The spatial logic of these “white spots” is robust across alternative model specifications and externally validated by independent studies that document substantial retail supply gaps even in thriving communities. These insights not only benefit retailers seeking to enter underserved markets but also provide urban planners with actionable data to balance service provision and enhance infrastructure in high-demand areas, optimizing both commercial and community outcomes. By pinpointing both established retail hotspots and emerging underserved markets, this approach provides important information for retai lers and urban planners alike, and advances the science of data-driven site selection in geomarketing.

Abstract: Agroforestry represents a land use system that integrates woody perennial plants, agricultural crops, and livestock to foster beneficial ecological and economic interactions for the production of food, fibre, and livestock. A well-managed agroforestry system yields numerous advantages and enhances livelihoods and income generation. These systems are tailored to specific areas and climates, making it essential to develop agroforestry practices that are relevant to local conditions and take into account the biophysical and socio-economic contexts on an individual basis. South Africa, recognized as a semi-arid nation, is particularly susceptible to water stress, especially drought. Additionally, agri-silviculture refers to a system that combines and integrates crops and trees within the same landscape. The current study aimed to assess the status of agri-silviculture practices concerning socio-economic factors and community perceptions. The primary objectives included: (1) Identifying and describing the socio-economic characteristics of selected agri-silviculture community growers, and (2) Evaluating the perception status of these growers. A purposive sampling method was employed to select 90 community growers involved in agri-silviculture (specifically Groundnuts and Eucalyptus Trees). Both quantitative and qualitative research designs were utilized, incorporating a questionnaire written in English, stakeholder discussions, and field observations as part of the data collection process. The socio-economic and perception data were coded, captured, and analysed using the Statistical Package for Social Science (SPSS). Moreover, it is crucial to acknowledge and address the primary perceptions and factors that affect the competitiveness of communities engaged in agri-silviculture practices, as these are vital for adoption and encompass both economic and sociological dimensions. The agri-silviculture community growers also noted that they relocated from their villages to the Mondi Group plantation in pursuit of its favourable climate, including rainfall. Therefore, it is recommended that the agri-silviculture practice be intensified throughout South Africa, as it contributes significantly to food security, market access, and sustainable livelihoods.

Abstract: The study aimed to investigate the factors influencing the effectiveness of internal audit in the public sectors of Lemi Kura Sub City. A mixed-methods approach was employed, combining quantitative data from a structured survey questionnaire and qualitative data from in-depth interviews. The target population consisted of senior managers and internal auditors, and a census approach was utilized, encompassing the entire population of 131 individuals. The study was utilized both primary and secondary sources. The findings reveal significant and positive relationships between several factors and internal audit effectiveness. Top management support, IA independence, audit committee involvement, internal auditors' competency, and audit quality demonstrate a strong positive correlation with internal audit effectiveness. However, the analysis indicates that the organizational setting has a positive but insignificant relationship with internal audit effectiveness. The study also shown that internal audit practitioners face significant challenges, including resource constraints, lack of management support, difficulties in maintaining independence and objectivity, organizational dynamics, and regulatory changes, emphasizing the need to address these challenges to enhance internal audit effectiveness and improve risk management and compliance processes. According to the study finding the recommendations was made include measures to improve top management support, strengthen IA independence, address organizational setting issues, and enhance the role of audit committees. The findings and recommendations can guide senior management, and internal auditors in enhancing internal audit practices and ultimately improving overall organizational performance and accountability in the public sectors of Lemi Kura Sub City, Addis Ababa.

Abstract: Purpose: This study aims to empirically examine the determinants of non-performing loans (NPLs) in selected private commercial banks in Ethiopia, focusing on both bank-specific and macroeconomic factors. Design/Methodology/Approach: The research adopts an explanatory design with a quantitative approach, analyzing panel data from twelve private commercial banks over a period of ten years (2012–2021). The data was processed using E-Views 10 software, employing descriptive statistics, correlation matrices, and multiple linear regression with both fixed and random effects models. Findings: The results indicate that exchange rates have a positive and statistically significant impact on NPLs. In contrast, income diversification, capital adequacy, loan growth rate, and loan-to-asset ratio show negative and significant effects on NPLs. Research Limitations/Implications: The study is limited to private commercial banks, thereby excluding public banks and non-bank financial institutions. Additionally, the reliance on secondary data may overlook qualitative factors that influence NPLs. Future research could broaden the sample size and incorporate primary data for deeper insights. Originality/Value: This study contributes to the literature by providing context-specific insights into the determinants of NPLs in Ethiopia's banking sector, addressing gaps in existing research. Its findings offer actionable recommendations for policymakers and bank managers to mitigate NPL risks, ultimately enhancing financial stability in emerging economies.