Search Results (4,173)

The rise in illicit financial activities across the South Africa–Zimbabwe corridor, with an estimated annual loss of $3.1 billion demands advanced AI solutions to augment traditional detection methods. This study introduces FALCON, a groundbreaking hybrid transformer–GNN model that integrates temporal transaction analysis (TimeGAN) and graph-based entity mapping (GraphSAGE) to detect illicit financial flows with unprecedented precision. By leveraging data from South Africa’s FIC, Zimbabwe’s RBZ, and SWIFT, FALCON achieved 98.7%, surpassing Random Forest (72.1%) and human auditors (64.5%), while reducing false positives to 1.2% (AUC-ROC: 0.992). Tested on 1.8 million transactions, including falsified CTRs, STRs, and Ethereum blockchain data, FALCON uncovered $450 million laundered by 23 shell companies with a cross-border detection precision of 94%, directly mitigating illicit financial flows in Southern Africa. For regulators, FALCON met FAFT standards, yielding 92% court admissibility, and its GDPR-compliant design (ε = 1.2 differential privacy) met stringent legal standards. Deployed on AWS Graviton3, FALCON processed 2 million transactions/second at $0.002 per 1000 transactions, demonstrating real-time scalability, making it cost-effective for financial institutions in emerging markets. As the first AI framework tailored for Southern Africa’s financial ecosystems, FALCON sets a new benchmark for ethical AML solutions in emerging economies with immediate applicability to CBDC supervision. The transparent validation of publicly available data underscores its potential to transform global financial crime detection. Full article

“The Internet of Things” is a relatively new idea that refers to objects that can connect to the Internet and exchange data. The Internet of Things (IoT) enables novel interactions between objects and people by interconnecting billions of devices. While there are many IoT-related products, challenges pertaining to their effective implementation, particularly the lack of knowledge and confidence about security, must be addressed. To provide IoT-based enterprises with a platform for efficiency and sustainability, this study aims to identify the critical elements that influence the growth of a successful company integrated with an IoT system. This study proposes a decision support tool that evaluates the influential features of IoT using the Pythagorean Fuzzy and Interval Grey approaches within the Analytical Hierarchy Process (AHP). This study demonstrates that security, value, and connectivity are more critical than telepresence and intelligence indicators. When both strategies are used, market demand and information privacy become significant indicators. Applying the Pythagorean Fuzzy approach enables the identification of sensor networks, authorization, market demand, and data management in terms of importance. The application of the Interval Grey approach underscores the importance of data management, particularly in sensor networks. The indicators that were finally ranked are compared to obtain a good coefficient of agreement. These findings offer practical insights for promoting sustainability in enterprise operations by optimizing IoT infrastructure and decision-making processes. Full article

To remain competitive in the decarbonization process of the economy worldwide, energy companies must preserve their market value to attract new investors and remain resilient throughout the transition to net zero. This article examines the market value of US energy companies during the period 2012–2024 in relation to their power generation mix. Panel regression analyses reveal that Tobin’s q and price-to-book ratios increase significantly for solar and wind power, while they experience moderate increases for natural gas power. In contrast, Tobin’s q and price-to-book ratios decline for nuclear and coal power. Furthermore, accounting-based profitability, measured by the return on assets (ROA), does not show significant variation with any type of power generation. The findings suggest that market investors prefer solar, wind, and natural gas power generation, thereby attributing greater value (that is, demanding lower risk compensation) to green companies compared to traditional ones. These insights provide guidance to executives, investors, and policy makers on how the power generation mix can influence strategic decisions in the energy sector. Full article

The green renovation of existing residential buildings is a key way for the construction industry to achieve sustainable development and the dual carbon goals of China, which makes it urgent to make collaborative decisions among multiple stakeholders. However, because of divergent interests and risk perceptions among governments, energy service companies (ESCOs), and owners, the implementation of green renovation is hindered by numerous obstacles. In this study, we integrated prospect theory and evolutionary game theory by incorporating core prospect-theory parameters such as loss aversion and perceived value sensitivity, and developed a psychologically informed tripartite evolutionary game model. The objective was to provide a theoretical foundation and analytical framework for collaborative governance among stakeholders. Numerical simulations were conducted to validate the model’s effectiveness and explore how government regulation intensity, subsidy policies, market competition, and individual psychological factors influence the system’s evolutionary dynamics. The findings indicate that (1) government regulation and subsidy policies play central guiding roles in the early stages of green renovation, but the effectiveness has clear limitations; (2) ESCOs are most sensitive to policy incentives and market competition, and moderately increasing their risk costs can effectively deter opportunistic behavior associated with low-quality renovation; (3) owners’ willingness to participate is primarily influenced by expected returns and perceived renovation risks, while economic incentives alone have limited impact; and (4) the evolutionary outcomes are highly sensitive to parameters from prospect theory, The system’s evolutionary outcomes are highly sensitive to prospect theory parameters. High levels of loss aversion (λ) and loss sensitivity (β) tend to drive the system into a suboptimal equilibrium characterized by insufficient demand, while high gain sensitivity (α) serves as a key driving force for the system’s evolution toward the ideal equilibrium. This study offers theoretical support for optimizing green renovation policies for existing residential buildings in China and provides practical recommendations for improving market competition mechanisms, thereby promoting the healthy development of the green renovation market. Full article

This study investigates the predictive performance of financial indicators in forecasting stock prices within the automotive sector using an adaptive neuro-fuzzy inference system (ANFIS). In light of the growing complexity of global financial markets and the increasing demand for automated, data-driven forecasting models, this research aims to identify those financial ratios that most accurately reflect price dynamics in this specific industry. The model incorporates four widely used financial indicators, return on assets (ROA), return on equity (ROE), earnings per share (EPS), and profit margin (PM), as inputs. The analysis is based on real financial and market data from automotive companies, and model performance was assessed using RMSE, nRMSE, and confidence intervals. The results indicate that the full model, including all four indicators, achieved the highest accuracy and prediction stability, while the exclusion of ROA or ROE significantly deteriorated model performance. These findings challenge the weak-form efficiency hypothesis and underscore the relevance of firm-level fundamentals in stock price formation. This study’s sector-specific approach highlights the importance of tailoring predictive models to industry characteristics, offering implications for both financial modeling and investment strategies. Future research directions include expanding the indicator set, increasing the sample size, and testing the model across additional industry domains. Full article

Although cemented carbides have been manufactured by the powder metallurgy (P/M) technology for over a century now, systematic developmental efforts are still underway. In the present study, tool life improvements in metal grooving applications are the key objective. Four PVD-coated cemented carbides compositions, dedicated to groove steel, stainless steel, cast iron, and aluminium alloys, have been newly designed, along with their manufacturing conditions. Physical, mechanical and chemical characteristics—such as sintered density, modulus of elasticity, hardness, fracture toughness, WC grain size, and the chemical composition of the substrate material, as well as the chemical composition, microhardness, structure, and thickness of the coatings—have been studied. A series of grooving tests have also been conducted to assess whether modifications to the thus far marketed tool materials, tool geometries, and coatings can improve cutting performance. In order to compare the laboratory and application properties of the investigated materials with currently produced by reputable companies, commercial inserts have also been tested. The experimental results obtained indicate that the newly developed grooving inserts exhibit excellent microstructural characteristics, high hardness, fracture toughness, and wear resistance and that they show slightly longer tool life compared to the commercial ones. Full article

Environmental protection has become one of the key challenges of our time. This has led to an increase in pro-environmental activities in the field of cosmetics and household chemicals, where manufacturers are increasingly trying to meet the expectations of consumers who are aware of the potential risks associated with the production of cosmetics and household chemistry products. This is one of the most important challenges of today’s industry, given that some of the raw materials still commonly used, such as surfactants, may be toxic to aquatic organisms. Many companies are choosing to use natural raw materials that have satisfactory performance properties but are also environmentally friendly. In addition, modern products are also characterized by reduced consumption of water, resources, and energy in production processes. These measures reduce the carbon footprint and reduce the amount of plastic packaging required. In the present study, seven formulations of environmentally friendly car shampoo concentrates were developed, based entirely on mixtures of bio-based surfactants. The developed formulations were tested for application on the car body surface, allowing the selection of the two best products. For these selected formulations, an in-depth physicochemical analysis was carried out, including pH, density, and viscosity measurements. Comparison of the results with commercial products available on the market was also performed. Additionally, using the multiple light scattering method, the foamability and foam stability were determined for the car shampoos developed. The results obtained indicate the very high application potential of the products under study, which combine high performance and environmental concerns. Full article

The sharing economy (SE) has rapidly expanded to become a key component of the global economy. However, as SE platforms evolve, a growing disconnect may exist between the value propositions companies emphasize and the values consumers actually perceive. Do the value frames communicated by SE companies align with those perceived as important by consumers, and how does this alignment differ across cultural contexts such as South Korea and the U.S.? Drawing on two complementary studies, we examine value alignment between SE companies and consumers in South Korea and the U.S. Study 1 employs content analysis of marketing messages from 246 SE platforms across five sectors, identifying the core value propositions emphasized. Study 2 applied structural topic modeling (STM) to consumer reviews from major SE platforms in both countries, focusing on three sectors: accommodation, service exchanges, and second-hand transactions. The findings reveal that SE companies in both countries primarily emphasize functional and economic values, with U.S. companies placing greater additional emphasis on emotional and social values than their South Korean counterparts. Similarly, consumers in both countries value functional, emotional, and economic aspects, showing general alignment with company marketing communications. However, South Korean consumers tended to emphasize functional and economic values more, while U.S. consumers were relatively more oriented toward emotional and social values. Notably, sustainability, widely regarded as a core principle of the SE, was not strongly emphasized by either companies or consumers. These findings contribute to the theoretical understanding of value dynamics in the SE and offer practical implications for developing culturally informed and value-driven marketing strategies. Full article

This study investigates the influence of corporate governance on reducing financial statement fraud (FSF) in Jordanian service and industrial companies listed on the Amman Stock Exchange from 2018 to 2022. To achieve this, the study employed the Beneish M-score model to assess the likelihood of FSF and logistic regression to examine the influence of corporate governance structure on fraud mitigation. The study identified 13 independent variables, including board size, board director’s independence, board director’s compensation, non-duality of CEO and chairman positions, board diversity, audit committee size, audit committee accounting background, number of annual audit committee meetings, external audit fees, board family business, the presence of women on the board of directors, firm size, and market listing on FSF. The study included 74 companies from both sectors—33 from the industrial sector and 41 from the service sector. Primary data was collected from financial statements and other information published in annual reports between 2018 and 2022. The results of the study revealed a total of 295 cases of fraud during the examined period. Out of the 59 companies analyzed, 21.4% demonstrated a low probability of fraud, while the remaining 78.6% (232 observations) showed a high probability of fraud. The results indicate that the following corporate governance factors significantly impact the mitigation of financial statement fraud (FSF): independent board directors, board diversity, audit committee accounting backgrounds, the number of audit committee meetings, family business involvement on the board, and firm characteristics. The study provides several recommendations, highlighting the importance for companies to diversify their boards of directors by incorporating different perspectives and experiences. Full article

This paper explores the intervening role in SEP performance of corporate environmental, cultural, and ethnic activities (ECEAs) and diversity, equity, inclusion, and social initiatives (DEISIs) on blockchain adoption (BCA) strategy, particularly useful in the Western Balkans (WB), which demands transparency due to extended fraud and ethnic complexities. In this domain, a question has been raised: In BCA strategies, is there any correlation between SEP performance and ECEAs and DEISIs in a mediating role? A serial mediation model was tested on a dataset of 630 WB and EU companies, and the research conceptual model was validated by CFA (Confirmation Factor Analysis), and the SEM (Structural Equation Model) fit was assessed. We found a statistically sound (significant, positive) correlation between BCA and ESG success performance, especially in the innovation and integrity ESG performance success indicators, when DEISIs mediate. The findings confirmed the influence of technology, and environmental, cultural, ethnic, and social factors on BCA strategy. The findings revealed some important issues of BCA that are of worth to WB companies’ managers to address BCA for better performance. This study adds to the literature on corporate blockchain transformation, especially for organizations seeking investment opportunities in new international markets to diversify their assets and skill pool. Furthermore, it contributes to a deeper understanding of how DEI initiatives impact the correlation between business transformation and socioeconomic performance, which is referred to as the “social impact”. Full article

The logistics industry faces challenges from evolving consumer expectations, technological advances, sustainability demands, and market disruptions. Logistics collaboration is in theory perceived as one of the most promising solutions to solve these issues, but here are still a lot of challenges that needs to be better understood and addressed. While vertical collaboration among supply chain actors is well advanced, horizontal collaboration among competing service providers remains under-explored. This study developed a novel methodology based on the COM-B behaviour-change framework to better understand the main challenges, opportunities, capabilities and drivers that would motivate competing companies to exploit the potential of horizontal logistics collaboration. A survey was designed and conducted among 71 logistics service providers in Slovenia, chosen for its fragmented market and low willingness to collaborate. Statistical analysis reveals cost reduction (M = 4.21/5) and improved vehicle utilization (M = 4.29/5) as the primary motivators. On the other hand, maintaining company reputation (M = 4.64/5), fair resource sharing (M = 4.20/5), and transparency of logistics processes (M = 4.17/5) all persist as key enabling conditions. These findings underscore the pivotal role of behavioural drivers and suggest strategies that combine economic incentives with targeted trust-building measures. Future research should employ experimental designs in diverse national contexts and integrate vertical–horizontal approaches to validate causal pathways and advance theory. Full article

This study examines the complex relationship between environmental, social, and governance (ESG) and financial performance in the automotive industry, with a particular focus on how financial constraints shape this relationship. Using a global data set for the period 2008 to 2023 and employing a range of panel data techniques, including those addressing endogeneity concerns, we find that higher ESG scores positively affect financial performance. Specifically, a one-point rise in ESG score corresponds to an estimated 1–1.7% increase in the market-to-book ratio, with the effect reaching approximately 1.6% for firms facing financial constraints. These findings highlight the economic significance of ESG engagement, particularly for resource-constrained companies. The novelty of this study is that it focuses on the automotive sector, an industry with limited ESG-specific research, and that it makes a theoretical contribution by linking ESG performance outcomes to financial constraints, an angle largely overlooked in prior research. The findings offer critical policy insights, emphasizing the strategic importance of ESG initiatives for value creation under varying financial conditions. Full article

Managing finances in a supply chain today is not as straightforward as it once was. The world is constantly shifting—markets fluctuate, risks emerge unexpectedly—and companies are continually trying to stay one step ahead. In all this, financial resilience has become more than just a strategy. It is a survival skill. In our research, we examined how newer technologies (such as blockchain and the Internet of Things) can make a difference. The idea was not to reinvent the wheel but to see if these tools could actually make financing more transparent, reduce some of the friction, and maybe even help companies breathe a little easier when it comes to liquidity. We employed two optimization methods (Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO)) to achieve a balanced outcome. The goal was lower financing costs, better liquidity, and stronger resilience. Blockchain did not just record transactions—it seemed to build trust. Meanwhile, the Internet of Things (IoT) provided companies with a clearer picture of what is happening in real-time, making financial outcomes a bit less of a guessing game. However, it gives financial managers a better chance at planning and not getting caught off guard when the economy takes a turn. Full article

To ensure stability and transparency in the European logistics sector, in May 2017, the European Commission presented several proposals to change the regulation of the market—in particular, market access, driving and rest periods, and business trips. In the development of this package, several unfavourable decisions were made that go against Lithuanian transport companies, which will have a significant impact on the companies’ finances, as the frequent return of trucks will lead to additional fuel costs and is also in contradiction with the concept of green logistics. Thus, it is essential to study the Mobility Package’s pros and cons and compare researchers’ views. Accordingly, the subject of this article is the impact of the Mobility Package on Lithuanian logistics companies. This article employs various methods, including an analysis of the scientific literature and legislation, statistical data analysis, PEST analysis, and qualitative research based on expert interviews. The results allow us to identify that the content of the Mobility Package is driven by the goal of ensuring equivalent working conditions throughout the EU, which in this case is the most important object of the legal changes. Also, based on the results obtained, it can be stated that Lithuanian logistics companies that want to remain in the market have several solutions they can employ to achieve that goal, and to support their efforts, a competitiveness improvement model for Lithuanian logistics companies has been developed. Full article

This study evaluates the competitiveness and sustainable development prospects of French-speaking African countries by constructing a comprehensive framework integrating the TOPSIS method and adaptive LASSO algorithm. Using multivariate data from sources such as the World Bank, 30 indicators covering core, basic, and auxiliary competitiveness were selected to quantitatively analyze the competitiveness of 26 French-speaking African countries. Results show that their comprehensive competitiveness exhibits spatial patterns of “high in the north and south, low in the east and west” and “high in coastal areas, low in inland areas”. Algeria, Morocco, and six other countries demonstrate high competitiveness, while Central African countries generally show low competitiveness. The adaptive LASSO algorithm identifies three key influencing factors, including the proportion of R&D expenditure to GDP, high-tech exports, and total reserves, as well as five secondary key factors, including the number of patent applications and total number of domestic listed companies, revealing that scientific and technological investment, financial strength, and innovation transformation capabilities are core constraints. Based on these findings, sustainable development strategies are proposed, such as strengthening scientific and technological research and development and innovation transformation, optimizing financial reserves and capital markets, and promoting China–Africa collaborative cooperation, providing decision-making references for competitiveness improvement and regional cooperation of French-speaking African countries under the background of the “Belt and Road Initiative”. Full article