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.

The initiation of tapering, sparked by heightened inflation in the United States, reverberates across global markets, with notable implications for Indonesia. This study delved into the nuanced impact of tapering on Sharia-compliant stocks in both Indonesia and Malaysia. The rationale behind selecting Sharia stocks for analysis lies in their composition, featuring companies boasting low debt-to-asset and equity ratios, thereby positing robust resilience in the face of the Federal Reserve’s implementation of tapering. Employing a time series dataset with a weekly sampling period spanning from January to September 2022, the analysis adopted the Error Correction Model (ECM) within a multiple regression framework to circumvent potential spurious regression pitfalls. The results of this study indicate that the impact of tapering off policy in Indonesia has a positive impact in the short term and long term, while in Malaysia it tends to be insignificant in the short term and has a positive impact from the US 10-year bond yield variable and a negative impact from US 1-Year Treasury Bills. This result is interesting because it differs from the general theory. The causal factors include the agility of the Indonesian central bank in maintaining the benchmark interest rate spread with the Fed, the economic stability of both countries, and the increasing trend of coal, with Indonesia being one of the largest producers of the commodity. Investors, in navigating these intricate dynamics, may find strategic insights derived from this research invaluable for shaping their investment decisions. while government policymakers may use them as a reference for shaping policies related to Sharia stock investments, including the incorporation of artificial intelligence.

This paper aims to investigate the determinants of performance for insurance companies in Tunisia from 2004 to 2017. Namely, we consider three dimensions of determinants; those related to firms’ microenvironment, macroenvironment and meso or industry environment. The performance of insurance companies is measured using three criteria: Return On Assets (ROA), Return On Equity (ROE), and Combined Ratio. The independent variables are categorized into three groups: microeconomic variables (Firm Size, Financial leverage, Capital management risk, Volume of capital, and Age of the firm), meso-economic variables (Concentration ratio and Insurance Sector Size), and macroeconomic variables (Inflation, Unemployment, and Population Growth). The General Least Squares (GLS) regression technique is employed for the analysis. The study reveals that the financial performance of Tunisian insurance companies is positively influenced by firm size, capital amount, and risk capital management. On the other hand, it is negatively influenced by leverage level, industry size, concentration index, inflation, and unemployment. In terms of technical performance, the capital amount of the firm, industry size, age of the firm, and population growth have a positive impact. However, firm size, leverage, concentration index, and risk capital management negatively affect technical performance. This paper contributes to the existing literature by examining the determinants of performance specifically for insurance companies in Tunisia. Besides the classical proxies of performance, this paper has the originality of using the technical performance which is the most suitable for the case of Insurance companies.

The research is focused on the evolution of the enterprises, in the field of specialized professional services, medium-period, enterprises that implemented projects financed within Regional Operational Program (ROP) during the 2007–2013 financial programming period. The analysis of the economic performance of the micro-enterprises corresponds to general objectives, but there can be outlined connections between these performances and other economic indicators that were not considered or followed through the financing program. The study case is focused on the development of micro-enterprises in the services area, in the Central Region, Romania (one of the eight development regions in Romania). The scientific approach for this article was based on a regressive statistical analysis. The analysis included the economic parameters for the enterprises selected, comparing the economic efficiency of these enterprises, during implementation with the economic efficiency after the implementation of the projects, during medium periods, including the sustainability period. The purpose of the research was to analyse the economic efficiency of the selected micro-enterprises, after finalizing the projects’ implementation. The authors intend to point out the need for a managerial instrument based on the economic efficiency of companies that are benefiting from non-reimbursable funds. This instrument should be taken into consideration in planning regional development at the national level, regarding the conditions and results expected. Although the authors used regressive statistical analysis the purpose was to prove that there is a need for additional managerial instruments when the financial allocations are being designed at the regional level. This study follows the interest of the authors in proving that the efficiency of non-reimbursable funds should be analysed distinctively on the activity sectors.

The convergence of multifaceted global challenges encompassing the rise of populism, Brexit, the climate crisis, the COVID-19 pandemic, and the Russian invasion of Ukraine has catalyzed a profound reassessment of international trade policies. This article critically examines the intricate linkages between these challenges and their profound implications for the contemporary international trading system. Traditionally, globalization debates in the 1990s underscored the social and environmental dimensions of trade, yet the current landscape reveals an undeniable entwining of societal implications with trade policies. This article delves into the interconnectedness of these global challenges with trade, evaluating how each phenomenon influences and reshapes policy discourse. In particular, the rise of populism and its attendant protectionist sentiments have engendered a reevaluation of trade relationships and multilateral agreements. The seismic geopolitical event of Brexit has disrupted regional trade dynamics, signaling a paradigm shift in established trade blocs. Simultaneously, the imperatives of addressing the escalating climate crisis have spotlighted the necessity for trade policies to align with environmental sustainability goals. The COVID-19 pandemic, acting as a disruptor on a global scale, has accentuated vulnerabilities within supply chains, emphasizing the need for resilience and adaptability in trade frameworks. Additionally, the Russian invasion of Ukraine has introduced geopolitical tensions that further complicate the trade-policy landscape. By critically evaluating these intersecting challenges, this article delineates the evolving nature of trade policies and their inextricable relationship with societal and geopolitical realities. It underscores the imperative for a holistic approach in policy formulation that integrates social, environmental, and geopolitical considerations, acknowledging the integral role of trade policies in addressing contemporary global challenges.