Advanced Journal of Management, Humanity and Social Science

Abstract This study examines the impact of microfinance services on the financial sustainability and performance of medium-sized enterprises (SMEs) in Mazar-e-Sharif, Afghanistan, using data from 100 firms selected through systematic random sampling. The primary objective is to assess how microcredit access, savings services, and entrepreneurial development training affect return on assets (ROA) and financial sustainability (FS), while controlling for firm age and size. Data were collected via structured questionnaires administered to SME owners/managers, with reliability confirmed by Cronbach's alpha of 0.780 (N=100 items) and content validity established through review by 10 Afghan microfinance experts. Analysis employed descriptive statistics, Pearson correlation matrices, and multiple linear regression models following established SME research methodologies. The first regression model revealed that internal finance (β=0.012, t=10.78, p<0.001) and trade credit (β=0.008, t=7.23, p<0.001) significantly enhance ROA (R²=0.61, F=24.37, p<0.001), while non-institutional finance shows a negative effect (β=-0.130, p=0.017). The second model demonstrated strong positive impacts of microcredit (β=0.287, t=5.02, p<0.001), savings services (β=0.214, t=3.67, p=0.01), and entrepreneurial training (β=0.176, t=3.11, p=0.002) on financial sustainability (R²=0.65, Adj. R²=0.62, F=28.45, p<0.001), with larger/younger firms benefiting most. Nine of ten hypotheses were supported, underscoring microfinance's comprehensive role (financial + non-financial services) in fragile economies. Policy recommendations include government investment in energy infrastructure, transportation networks, and SME training programs to enhance competitiveness. These findings offer actionable insights for post-conflict development strategies.

Abstract Perfectionism has become a salient construct in understanding students’ psychological functioning within academic settings. Defined as the pursuit of excessively high standards accompanied by critical self-evaluation, perfectionism manifests in both adaptive and maladaptive forms. This paper explores the psychological correlates of perfectionism among students, highlighting its influence on mental health, motivation, coping strategies, and social relationships. Research indicates that while adaptive perfectionism may foster organization, persistence, and academic success, maladaptive perfectionism is closely linked to heightened anxiety, depression, low self-esteem, and academic burnout. Perfectionistic students often struggle with cognitive distortions, such as all-or-nothing thinking, and rely on maladaptive coping strategies like avoidance and rumination, which exacerbate stress. Additionally, perfectionism affects interpersonal dynamics, where fear of failure and excessive competitiveness can hinder collaborative learning and peer support. Cultural and parental expectations also reinforce perfectionistic tendencies, intensifying psychological vulnerability in highly competitive educational environments. Mechanisms such as achievement motivation, self-worth contingencies, and distorted cognitive appraisals help explain the varying outcomes of perfectionism. Interventions including cognitive-behavioral therapy, mindfulness, self-compassion training, and growth-mindset educational practices are proposed as effective strategies to mitigate the negative impacts of maladaptive perfectionism while preserving the motivational benefits of adaptive forms. Understanding the psychological correlates of perfectionism is critical for educators, counselors, and policymakers aiming to promote academic excellence without compromising students’ well-being. Ultimately, fostering balanced forms of perfectionism may enable students to strive for high achievement while maintaining resilience, self-acceptance, and positive mental health in their educational journey.

Abstract Financial transparency and auditing are critical mechanisms for improving the efficiency and integrity of municipal financial management. In recent decades, the role of local governments in providing public services has expanded, making effective oversight and accountability increasingly essential. This study explores how financial transparency and systematic auditing practices influence municipal performance, focusing on their capacity to reduce corruption and enhance operational efficiency. By conducting an analytical review of literature from various international contexts, this research highlights patterns and correlations between transparent financial reporting, rigorous auditing processes, and improved municipal outcomes. The findings indicate that municipalities that adopt comprehensive transparency policies, such as public disclosure of budgets, expenditures, and procurement processes, are more likely to demonstrate accountable governance and reduced incidences of financial mismanagement. Similarly, the implementation of independent and consistent auditing practices reinforces internal controls, deters fraudulent activities, and fosters public trust. The study also examines challenges, including political interference, resource constraints, and varying legal frameworks, which may hinder the effectiveness of transparency and auditing measures. By integrating empirical evidence and theoretical perspectives, this research underscores that the synergy of transparency and auditing not only enhances operational efficiency but also acts as a critical deterrent against corruption in municipal finance. The paper concludes with policy recommendations for municipal authorities to strengthen financial oversight mechanisms, improve reporting standards, and institutionalize audit practices, ultimately contributing to sustainable urban governance. These insights provide valuable guidance for policymakers, municipal administrators, and researchers interested in promoting accountable and efficient local government financial management.

Abstract The rapid evolution of artificial intelligence (AI) has transformed strategic decision-making processes in organizations, enabling faster insights, predictive analytics, and automation. However, the integration of AI systems also raises critical challenges concerning data governance, ethics, and regulatory compliance. Effective data governance ensures that data used in AI-driven decisions is accurate, secure, transparent, and aligned with corporate objectives. Ethical frameworks are essential to mitigate biases, prevent discrimination, and maintain trust among stakeholders. Moreover, the establishment of AI guidelines, including accountability, explainability, and fairness, plays a pivotal role in guiding organizations toward responsible innovation. This paper explores how robust data governance structures and ethical AI guidelines can enhance strategic decision-making and corporate integrity. It analyzes current models of governance frameworks, including ISO/IEC 38505 and OECD AI Principles, and their implications for business strategy. The discussion emphasizes that organizations adopting transparent and ethical data practices not only comply with regulations but also gain a competitive advantage through enhanced reputation and stakeholder confidence. Ultimately, the study concludes that integrating governance and ethics into AI decision systems is no longer optional—it is a strategic necessity for sustainable, fair, and accountable business practices in the era of intelligent automation.

Abstract Sports injuries remain a major concern in both professional and recreational athletics, leading to significant physical, psychological, and economic consequences. Recent advances in biomechanics have provided a powerful framework for analyzing movement patterns, loading mechanisms, and tissue responses associated with sports-related injuries. This paper explores how biomechanical data analysis contributes to the understanding and prevention of sports injuries. Using motion capture systems, force plates, electromyography, and wearable sensors, researchers can quantify kinematic and kinetic variables that reveal underlying risk factors such as improper joint alignment, asymmetrical loading, or excessive repetitive forces. By integrating these biomechanical indicators with machine learning algorithms, predictive models can be developed to identify athletes at higher risk before injury occurs. The paper further reviews intervention strategies, including neuromuscular training, equipment design modifications, and individualized biomechanical feedback systems. Case studies from sports such as soccer, running, and basketball demonstrate how biomechanical insights have successfully reduced injury rates through targeted prevention programs. Ultimately, the synthesis of biomechanical data with modern computational tools represents a paradigm shift from reactive to proactive injury management. This approach not only enhances athletic performance but also promotes long-term musculoskeletal health. The findings underscore the need for interdisciplinary collaboration between biomechanists, sports scientists, medical professionals, and data analysts to create comprehensive injury-prevention ecosystems supported by empirical evidence.

Abstract Social anxiety is a type of anxiety that occurs when facing social situations and communicating with others. People who suffer from social anxiety experience intense fear and worry in social situations and feel unable to manage and control these situations. Cognitive behavioral therapy is an evidence-based treatment for anxiety disorders. Due to various barriers, many people face difficulties in accessing treatment. Therefore, researchers have investigated the possibility of using the Internet to deliver CBT. It is important to ensure that the decision to promote such a treatment is based on high-quality evidence. Exposure therapy is a technique designed to help people cope with their fears. Using this method, the person is gradually exposed to stimuli that provoke a fear response in them. These triggers can range from external stimuli such as objects or social situations to internal factors such as thoughts, mental images, or physical sensations related to the trauma. When people are anxious because of a fear, phobia, or a traumatic memory, they often avoid anything that reminds them of it. This avoidance provides temporary relief, but ultimately maintains and reinforces the fear and avoidance pattern. In fact, avoidance can make things worse. Exposure therapy enables people to face and experience feared stimuli by creating a safe environment. This leads to a reduction in fear and anxiety, minimizing avoidance of feared situations, and improving quality of life. The ultimate goal is to desensitize people to the point where they can face their fears without experiencing intense anxiety.

Abstract Artificial Intelligence (AI), as one of the most advanced technologies of the 21st century, has increasingly entered the world's judicial systems and has transformed judicial decision-making processes. With its ability to analyze large volumes of data, identify complex patterns, and predict outcomes, this technology enables the acceleration and increase of accuracy in the process of handling cases. In this regard, AI can help judges and lawyers make more accurate and objective decisions based on evidence and information, thereby promoting judicial justice. In addition, the use of intelligent systems in predicting the risk of committing a crime or returning to the criminal justice system greatly contributes to decisions related to conditional release or setting bail. Also, text analysis and behavioral pattern recognition tools in criminal and legal cases can reduce the possibility of human errors and unintentional biases. However, the use of AI in decriminalization also comes with significant challenges and concerns. The most important of these challenges is the issue of transparency and understandability of algorithms; because AI decisions may be ambiguous and uninterpretable for human users and even judges due to technical complexities. Also, the risk of algorithmic discrimination resulting from inappropriate training data or biases in the data can jeopardize judicial justice. Concerns related to privacy, data security, and liability in the event of errors are also important concerns. Ultimately, the impact of AI on judicial decision-making processes depends largely on how it is designed, monitored, and the legal and ethical frameworks governing its use.

Abstract Family law serves as a fundamental legal framework regulating relationships within families, including marriage, divorce, child custody, inheritance, and domestic obligations. This comparative study examines the divergent and convergent features of family law systems in Eastern and Western jurisdictions, highlighting the influence of cultural, religious, and social factors. Western legal systems, including common law and civil law traditions, emphasize individual autonomy, gender equality, and codified procedural safeguards. In contrast, Eastern systems, particularly those influenced by Islamic law and traditional Asian customs, prioritize family cohesion, social harmony, and religious or cultural norms. The study analyzes marriage and divorce regulations, child custody and protection mechanisms, inheritance rules, and contemporary reforms in both regions. It also addresses emerging trends such as recognition of same-sex marriages, assisted reproductive technologies, and cross-border legal issues. Comparative findings reveal key differences in the balance between individual rights and collective responsibilities, the role of religion in legal formulation, gender equality, and procedural approaches. Despite these differences, globalization and international human rights standards have prompted reforms in both regions, fostering convergence in areas such as child welfare, protection of vulnerable family members, and legal modernization. The study concludes that understanding the underlying social, religious, and cultural values of family law systems is essential for policymakers, legal scholars, and practitioners to promote effective, equitable, and culturally sensitive legal frameworks. Comparative analysis not only enhances cross-cultural legal understanding but also provides opportunities for harmonization, mutual learning, and informed reform in globalized contexts.