This study investigates the influence of perceived value and perceived risk on consumer intentions to purchase counterfeit luxury goods, drawing upon an integrated theoretical framework encompassing perceived value theory, risk perception theory, and consumer behavior models. Through a quantitative research design involving a structured survey and Structural Equation Modeling (SEM), the study examines the relationships among perceived value dimensions (functional, emotional, social, economic), perceived risk factors (financial, social, performance), consumer attitudes, and purchase intentions. The findings reveal that perceived value positively influences purchase intentions, with consumer attitudes acting as a critical mediating mechanism. Conversely, perceived risk negatively impacts purchase intentions, with this relationship also mediated by consumer attitudes. Furthermore, Bayesian Network analysis uncovers the indirect pathways through which perceived risk shapes purchase intentions via its influence on consumer attitudes. By integrating these theoretical frameworks and employing advanced analytical techniques, this study contributes to a comprehensive understanding of the complex decision-making processes underlying counterfeit luxury goods consumption. The findings provide valuable insights for policymakers, luxury brand managers, and consumer protection agencies in devising targeted strategies to address consumer perceptions of value and risk, ultimately mitigating the proliferation of counterfeit luxury goods.

The lack of attention from mining companies to the majority of areas still affected by mining activities can result in regional economic disparities and high levels of social violence. It is crucial to have policy strategies for mining contributions to rural development equity and social violence reduction through CSR assistance and other aid funds. This research employs the Multi-Criteria Decision Analysis method using the MULTIPOL analysis tool. Recommended action programs include the construction of schools, provision of scholarships, job openings, business capital, and infrastructure development, supported by strong regulations and law enforcement. Cracking down on illegal mining permits is essential to reduce environmental damage. Holistic and sustainable integration policies, alongside effective law enforcement, are necessary to achieve the goals of equitable development and social violence reduction. These steps should be reinforced with incentives for traditional/community leaders and increased police/military presence in villages within the next 2 years, particularly in zones 2 and 3 of the mining areas. Failure to implement these measures could escalate social violence, jeopardize security, and impede the operations of mining companies in Kolaka. The findings of this research support the priority of security and orderliness in development and underscore the importance of diverse research methods for mining area development policies.

Amidst an upsurge in the quantity of delinquent loans, the financial industry is experiencing a fundamental transformation in the approaches utilised for debt recovery. The debt collection process is presently undergoing automation and improvement through the utilisation of Artificial Intelligence (AI), an emergent technology that holds the potential to revolutionise this sector. By leveraging machine learning, natural language processing, and predictive analytics, automated debt recovery systems analyse vast quantities of data, generate forecasts regarding the likelihood of recovery, and streamline operational processes. Debt collection systems powered by AI are anticipated to be compliant, precise, and effective. On the other hand, conventional approaches are linked to increasing expenditures and inefficiencies in operations. These solutions facilitate efficient resource allocation, customised communication, and rapid data analysis, all while minimising the need for human intervention. Significant progress has been made in data analytics, predictive modelling, and decision-making through the application of artificial intelligence (AI) in debt recovery; this has the potential to revolutionize the financial sector’s approach to debt management. The findings of the research underscore the criticality of artificial intelligence (AI) in attaining efficacy and precision, in addition to the imperative of a data-centric framework to fundamentally reshape approaches to debt collection. In conclusion, artificial intelligence possesses the capacity to profoundly transform the existing approaches utilized in debt management, thereby guaranteeing financial institutions’ sustained profitability and efficacy. The application of machine learning methodologies, including predictive modelling and logistic regression, signifies the potential of the system.

Africa has been fighting against colonialism and Eurocentrism for a long time in an attempt to reverse the regime of oppression and socio-economic marginalization and exploitation, and take back control of its cultural identity and right to self-determination. This adventure requires the recognition and revitalisation of indigenous arts, culture, and law—all of which have been subjugated and ignored during colonial rule. Ironically, the situation has not improved much by the dominating presence of post-independent neo-colonial structures and perpetuated Eurocentric phenomenon that have been ingrained into the socio-cultural and economic fabrics of the African state. This research explores the critical need for integrating science on African indigenous arts, culture, and legal systems, as a way of globalizing as well as revitalizing these elements, towards the ultimate emancipation of the continent from the vestiges of colonialism and Eurocentricism. Relying on the postcolonial, and indigenous knowledge systems theoretical frameworks, the study engages the ethnographic, collaborative and interdisciplinary research approaches, subjecting data obtained to thematic analysis. Underscoring the profound interconnectedness of science, indigenous arts, and cultural heritage, the study argues that combining scientific methods with indigenous African epistemology provides a powerful framework for advancing Africa’s true independence from the protracted legacies of colonialism and Eurocentrism. The research concludes that a holistic integration of these elements therefore, is indispensable for fostering a decolonized and inclusive approach to knowledge production, self-determination and sustainable development, against the background of the rich insights and sustainable practices embedded within the African cultural traditions. Ultimately, the research recommends that embracing and integrating science on indigenous epistemologies can propel Africa towards an emancipated, truly independent, and culturally affirming future, transcending the enduring legacies of colonialism and Eurocentrism.

In this regard the key factor determining the success of the mining industry is the cost of electricity. By understanding the risks associated with crypto mining industry. The method is based on systemic literature review and bibliometric analysis exploring keyword “bitcoin mining”. This review paper studies 50 papers for the period of 2019–2023. The results propose recommendations for crypto miners. Currently, the results confirm that bitcoin mainly depends on the consumption of inexpensive electricity. Consequently, the bitcoin network predominantly uses energy in regions where it is abundant and cannot be stored or exported. Most miners rely on electricity generated from hydroelectric power plants, geysers and geothermal sources, which are not easy to transport or store. Bitcoin will continue to look for such cost-effective and underutilized energy sources, as mining in urban areas or industrial centers will remain financially unviable. If the price of bitcoin stabilizes and a sufficient number of miners enter the market, it is quite possible that in the near future we may witness a fivefold increase in their energy consumption.

Art studies and activities for older adults have received significantly less attention as a result of prohibitively expensive materials that are unfit for commercial use, and research utilizing digital technology to investigate artistic activities for older adults is extremely limited. The purpose of this article is to analyze and review recent research in these fields to summarize the current trends. The literature review comprised 108 articles from databases that included Scopus, ScienceDirect, and Google Scholar. The papers were subjected to a thorough examination by the VOSviewer program and researchers, who utilized content analysis to classify them into four themes: 1) inclusive design; 2) accessibility; 3) digital art therapy and 4) digital technology environments. Further investigation and development are necessary to propose a novel approach to instructing senior-level art utilizing cutting-edge technologies, which could be enhanced by the findings of this review article.

This study investigates the influence of government expenditure on the economic growth of the ASEAN-5 countries from 2000 to 2021. The study employs the Pooled Mean Group (PMG) ARDL model and robust least squares method. The importance of the current study lies in its analysis of the short and long-run impact of government expenditure on economic growth in ASEAN-5. The empirical findings demonstrate a positive relationship between government expenditure and economic growth in the long run. These results align with the Keynesian perspective, asserting that government expenditure stimulates economic growth. The study also confirms one-way causality from government expenditure to economic growth, supporting the Keynesian hypothesis. These insights hold significance for policymakers in the ASEAN-5, highlighting the necessity for policies promoting the effective allocation of productive government expenditure. Moreover, it is important to enhance systems that promote economic growth and efficiently allocated economic resources toward productive expenditures while also maintaining effective governance over such expenditures.

Firms, recognizing their Corporate Social Responsibility (CSR), are becoming catalysts for societal change by integrating Environmental, Social and Governance (ESG) criteria into their activities. The fashion industry exemplifies this effort, with an increasing number of companies embracing sustainability and ethical practices. In this context, our purpose is to provide a clear and comprehensive picture of the link between sustainability and business performance in the fashion industry. This work presents a Multivariate Regression Analysis, scrutinizing both external perspectives through stock prices and internal perspectives via profitability indices. Our aim is to discern the intricate relationship between sustainability practices and financial performance within the fashion industry, aligning ESG criteria with long-term economic success. Our regression analysis reveals a significant positive correlation between ESG scores and stock prices, indicating investor recognition of ESG performance as a crucial investment criterion. However, when focusing internally on profitability, the ESG score does not exhibit statistical significance, suggesting a yet-to-be-established connection between ESG policies and corporate profitability. This study underscores the evolving role of companies as sustainability promoters, emphasizing the crucial role of ESG performance in shaping investor perceptions. Nevertheless, it also highlights the need for further exploration into the intricate relationship between sustainable policies and corporate profitability. As businesses increasingly embrace sustainability, in fact, it could become paramount for informed decision-making and fostering ethical societal and environmental progress.