Advanced Journal of Management, Humanity and Social Science

Abstract Background: Generative artificial intelligence (GenAI) can support explanation and feedback, but unrestricted answers may encourage cognitive offloading, weak source evaluation, and diminished learner authorship. This study developed and content-validated NEXUS, which restricts GenAI to Socratic coaching, and examined preliminary effectiveness for learning agency, intrinsic motivation, and critical-thinking disposition among male upper-secondary students in Qazvin, Iran. Methods: Phase I combined needs mapping in 463 students, co-design, cognitive interviews, and two-round Delphi validation by 15 experts. Phase II randomized 12 classes (106 students; six clusters per arm) to ten weekly NEXUS sessions or a dose- and technology-matched active control. Three-month follow-up was primary. Mixed-model estimates were paired with CR2 inference, CR3 sensitivity analysis, restricted wild-cluster bootstrap-t intervals, and exact within-pair randomization tests. Model-based Hedges g used total class-plus-student variance. Results: The 55-element manual achieved S-CVI/Ave = 0.91; universal agreement was 0.31, and Fleiss kappa was 0.66 for relevance and 0.61 for necessity. Follow-up completion was 89.6%. Adjusted follow-up differences were 0.44 for agentic engagement (95% CI 0.10 to 0.78; Holm-adjusted p = 0.042; g = 0.43), 0.31 for intrinsic motivation (95% CI -0.04 to 0.66; adjusted p = 0.086; g = 0.30), and 6.1 for critical-thinking disposition (95% CI 0.6 to 11.6; adjusted p = 0.078; g = 0.38). The exact global multivariate randomization test was p = 0.031. Fidelity averaged 86.8%; minor AI-output and participant-burden events occurred, but no serious related event was observed. Conclusion: NEXUS showed credible content validity and a promising joint signal, strongest for agentic engagement. With only 12 clusters, incomplete blinding, and no prospective registration, independent replication is required.

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 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 Leadership remains a cornerstone of organizational success, particularly within multinational corporations (MNCs) that operate in diverse and complex environments. Effective leadership styles and strategies are crucial for enhancing employee motivation and improving organizational productivity. This paper explores various leadership theories, including transformational, transactional, servant, and situational leadership, to examine their applicability in motivating employees within MNCs. Additionally, the paper highlights the role of cross-cultural leadership, communication, emotional intelligence, and strategic human resource management in driving organizational outcomes. Through a comparative analysis of previous empirical studies, the paper underscores that no single leadership style is universally effective. Instead, adaptable, culturally sensitive, and employee-centered leadership approaches yield sustainable improvements in motivation, innovation, and productivity. The discussion also considers the challenges of globalization, digital transformation, and remote working, offering practical strategies for leaders in MNCs to build resilient, motivated, and high-performing teams.The integration of diverse markets, cultures, and technological systems has heightened the need for leaders who can adapt to rapid changes while motivating employees across geographies. Leadership, once understood merely as a positional authority or the ability to direct teams, has evolved into a multidimensional construct encompassing vision, strategy, communication, and the capacity to inspire. Leadership styles and strategies have direct implications for employee motivation, which in turn, influences organizational productivity and competitive advantage.

Abstract In the digital age, social media platforms have emerged as powerful spaces where youth not only interact but also experiment with and construct their identities. This article critically examines the influence of platforms such as Instagram, Tik Tok, Snapchat, and X (formerly Twitter) on youth identity development and explores how these evolving identity practices impact broader social cohesion. Youth today navigate complex networks of digital performance, where identity is shaped by peer feedback, algorithmically curated content, and global cultural flows. While these platforms offer avenues for self-expression, empowerment, and group belonging, they also foster echo chambers, comparison anxiety, identity polarization, and performative behaviors. Furthermore, the role of influencers, viral trends, and platform-specific aesthetics reinforce norms that often privilege superficiality over authenticity. It also investigates the political implications of identity radicalization and ideological polarization that emerge from algorithmic filtering and targeted content delivery. Through case studies from the United States, Iran, Germany, and Nigeria, the article provides empirical grounding to illustrate both the risks and potentials of youth digital engagement. A comparative lens between Global North and Global South contexts highlights the nuances of digital identity formation across sociocultural environments. Finally, the article calls for a multidimensional policy response involving education, media literacy, platform design, and civic engagement initiatives to ensure that social media becomes a tool for inclusive identity development and enhanced social cohesion. The findings underscore the urgent need to understand and address the sociopsychological and political ramifications of digital identity in the lives of young people today.

Abstract Anxiety disorders are among the most common mental disorders worldwide that have an impact on the quality of life of individuals and society. These disorders manifest as excessive feelings and worries, unwanted physiological reactions, and behavioral changes, and can appear in some generalized anxiety disorders, social anxiety disorders, panic disorder, and obsessive-compulsive disorder. Comprehensive diagnosis of the causes of this disease is of great importance. Research has shown that biological, genetic, and neurobiological factors, psychological factors such as cognitive styles and stressful experiences, and environmental factors such as social pressures and traumatic events, play a key role in their development and exacerbation. The use of accurate indicators distinguishes anxiety disorders from other mental and physical disorders and makes the treatment process targeted. The treatment of anxiety disorders is based on two main pillars: drug treatment and psychotherapy. Selective serotonin reuptake inhibitors (SSRIs) and benzodiazepines, along with cognitive-behavioral techniques (CBT), acceptance and commitment therapy (ACT), and behavioral therapies, are treatment options to reduce and improve individual functioning. Studies show that a combination of medication and psychotherapy produces better results than either alone. Also, challenges such as treatment, resources, and stigma require practical and innovative solutions. Finally, future research is preliminary to understanding the biological and psychological mechanisms of mental disorders, developing new treatment methods, and using advanced technologies. Also, specialized treatment training, public education, and upgrading the health system infrastructure to provide comprehensive services and treatment are needed to address the growing burden of eating disorders in the world.

Abstract Neuromorphic is by no means a new concept. Like many other emerging technologies that are now gaining momentum, neuromorphic has been quietly developing for a long time, but it still needs more work to shine. Neuromorphic systems attempt to mimic the functioning of the human nervous system. This branch of engineering attempts to mimic the biological structure of sensory and information-processing neural systems. In other words, neuromorphic computing implements various aspects of neurobiological networks in the form of analog and digital signals in electronic circuits. Neuromorphic computing has its roots in computational systems that were developed in the late 1980s and were designed to model the functioning of animal nervous systems. Since then, neuromorphic computing has gained momentum, to the point where some of the biggest names in technology have produced neuromorphic hardware. For example, IBM’s TrueNorth chip, Intel’s Loihi chip, and the Pohoiki Beach neuromorphic system are currently in production. Neuromorphics can do all of this without consuming a lot of energy, rather than leaving AI tasks to energy-hungry and cooling-intensive cloud systems. For neuromorphics to have a significant impact, there will need to be a lot of changes in the technology world. For example, sensor technologies are not designed to work well with neuromorphic systems and need to be redesigned to extract data in a way that can be processed by neuromorphic chips.

Abstract Online behavioral addictions are an increasing psychosocial concern among university students, a group simultaneously navigating a sensitive period of identity formation and consolidation. This study takes a differentiated approach to problematic digital engagement by examining distinct online addiction profiles and their associations with self-identity outcomes. Using a cross-sectional mixed-methods design, survey data from university students (aged 18–25) were analyzed using correlation, regression, and group-difference tests, and were complemented by a small set of semi-structured interviews to contextualize students’ identity-related experiences. Overall, higher problematic online engagement was associated with weaker identity resources (including self-esteem, identity stability, self-regulation, and academic self-concept) and greater identity strain (including identity confusion and identity anxiety). Associations varied by behavior: social media overuse was linked with identity confusion, validation seeking with lower identity stability, smartphone dependency with weaker self-regulation, gaming addiction with lower academic self-concept, and FoMO with higher identity anxiety. Qualitative themes echoed these patterns, highlighting online-only confidence, persistent social comparison, and difficulty maintaining a coherent offline self. Taken together, the findings support a profile-based interpretation of online behavioral addictions and point to targeted, identity-supportive digital wellbeing interventions within university settings.