Advanced Journal of Management, Humanity and Social Science

Abstract Anxiety disorders are among the most prevalent mental health conditions worldwide and are frequently maintained by maladaptive cognitive and emotional processes, particularly rumination and deficits in emotion regulation. Anxiety is a normal and adaptive emotional response to perceived threat; however, when excessive, persistent, and disproportionate, it becomes pathological and interferes with daily functioning. Anxiety disorders represent a major public health concern, contributing substantially to disability, reduced quality of life, and economic burden. Traditional cognitive-behavioral approaches have demonstrated efficacy in treating anxiety, yet a significant proportion of individuals continue to experience residual symptoms or relapse. This has motivated the exploration of alternative and complementary approaches that address deeper cognitive and emotional processes. Mindfulness-based interventions (MBIs) have gained increasing attention as effective psychological approaches for addressing these underlying mechanisms. This article provides a comprehensive evaluation of the effects of mindfulness-based interventions on reducing rumination and improving emotion regulation in individuals with anxiety. Drawing on theoretical models and empirical findings, the paper examines how mindfulness practices influence attentional control, metacognitive awareness, and emotional responding. Mechanisms of change, clinical implications, limitations of existing research, and directions for future studies are also discussed. Overall, the evidence suggests that MBIs play a significant role in alleviating anxiety symptoms by targeting rumination and fostering adaptive emotion regulation strategies.

Abstract The rise of algorithmic governance and data-driven decision-making represents a transformative shift in contemporary state administration, profoundly impacting democratic accountability. As governments increasingly integrate artificial intelligence (AI), machine learning, and big data analytics into policy formulation, public service delivery, and regulatory mechanisms, both opportunities and challenges emerge for traditional democratic practices. This study examines how algorithmic systems influence the three dimensions of democratic legitimacy: input, throughput, and output. Drawing on a comprehensive literature review and multi-dimensional analysis, five analytical frameworks are developed to explore the effects of algorithmic governance on citizen participation, procedural fairness, transparency, efficiency, and policy outcomes.

Findings indicate that algorithmic decision-making enhances operational efficiency, predictive capacity, and evidence-based policy interventions, enabling governments to respond more rapidly and effectively to complex societal challenges. Simultaneously, the reliance on automated systems introduces risks of bias, discrimination, opacity, and accountability gaps, which can undermine public trust and erode procedural and output legitimacy. Human-in-the-loop oversight, explainable AI (XAI), participatory design, algorithmic auditing, and multi-level governance emerge as critical strategies to reconcile technological efficiency with democratic norms.

The study highlights the dual character of algorithmic governance: while it offers substantial opportunities for efficiency and policy optimization, it necessitates deliberate institutional, ethical, and participatory safeguards to preserve democratic accountability. By integrating human judgment, transparency measures, ethical constraints, and citizen engagement into algorithmic systems, states can enhance legitimacy across all dimensions of governance. The research contributes to the growing discourse on digital-era public administration by providing a structured framework to assess both the transformative potential and normative implications of AI-driven governance, offering practical insights for policymakers seeking to balance innovation with democratic accountability in contemporary states.

Abstract This study examines the effect of financial risk management practices on the financial performance of steel milling companies operating in Afghanistan. Using a quantitative, explanatory research design, primary data were collected from 32 finance-related staff across five steel companies through a structured Likert-scale questionnaire, while secondary financial data were obtained from audited statements to compute return on assets (ROA). Descriptive statistics, Pearson correlation analysis, and multiple linear regression were employed to evaluate the relationships between financial performance and four dimensions of financial risk management: understanding of risk and risk management, risk identification, risk analysis and assessment, and risk monitoring. The findings reveal that all four dimensions exhibit positive and statistically significant effects on ROA, indicating that firms with stronger and more structured risk-management systems achieve higher profitability. The regression model explains 84.3% of the variation in financial performance, demonstrating substantial predictive power. While firm size and capital structure show positive but statistically insignificant effects, the results emphasize that managerial capability in applying risk-management practices outweighs structural firm characteristics in determining profitability. The study concludes that effective financial risk management is essential for enhancing financial performance in Afghanistan’s steel industry, which operates within a highly volatile and uncertain environment. Strengthening internal controls, broadening risk-identification processes, and improving monitoring systems are recommended to support long-term financial sustainability.

Abstract The purpose of this study was to present a model of factors affecting psychological operations of combat forces. To this end, the researchers referred to experts from the Iranian armed forces and collected data through in-depth interviews. Data obtained from fifteen interviews and relevant documents were coded and analyzed. The research employed a mixed-methods approach (qualitative and quantitative), and the DEMATEL technique was used to identify the levels of the model of factors affecting psychological operations of combat forces and to examine causal relationships among the criteria. This technique scores the intensity of relationships, examines feedback along with their importance, and accepts non-transitive relationships. The grouping of codes revealed twenty-nine components across five levels, including psychological operations training, virtual space management, societal psychological factors, psychological operations design, and the use of psychological operations tools.

Conclusion: According to the findings, the proposed model can serve as a foundation for success in the psychological preparation of combat forces. In military environments, psychological operations are considered an integral part of mission planning and design and are regarded as highly important. Accordingly, the model of factors affecting psychological operations of combat forces was extracted and validated, the research framework was developed, and its goodness of fit was confirmed.

Abstract Conflict of interest (COI) in contractual relationships represents a critical legal and ethical concern, impacting the validity, enforceability, and fairness of contracts. COI arises when a party’s personal, financial, or professional interests may improperly influence the performance of contractual obligations, leading to compromised decision-making and potential harm to the other party or the public. This paper provides a comprehensive legal analysis of COI in various contractual contexts, including commercial, corporate, and public sector agreements. Through a doctrinal and comparative approach, it examines how different legal systems define COI, regulate disclosure obligations, and impose remedies for breaches. Common law jurisdictions typically address COI through fiduciary duty principles, equitable remedies, and statutory regulations, whereas civil law systems emphasize good faith obligations, fairness, and statutory prohibitions against conflicts. The study also highlights the consequences of non-disclosure or misrepresentation, including contract voidability, rescission, damages, and restitution. Moreover, it explores preventive measures, such as contractual clauses, mandatory disclosure requirements, and judicial oversight, which are crucial in mitigating COI risks. By analyzing legislative frameworks, case law, and best practices, the paper demonstrates the importance of transparency and ethical conduct in maintaining contractual integrity. The findings underscore that effective management of COI not only safeguards the interests of contracting parties but also promotes trust, accountability, and efficient commercial interactions. Overall, this analysis contributes to a deeper understanding of the legal mechanisms governing COI and their practical implications for contractual practice, offering guidance for policymakers, legal practitioners, and organizations engaged in complex contractual arrangements.

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.

Abstract In today’s competitive landscape, where brands strive not only for visibility but also for emotional resonance, storytelling has emerged as a strategic pillar of experiential marketing. This study examines the role of artificial intelligence (AI) in advancing personalized brand storytelling and fostering emotional engagement, focusing on L’Oréal’s integration of ModiFace and SkinConsult AI as a case study. Grounded in theories of narrative transportation and experiential branding, the research proposes a conceptual framework that connects AI technologies with individualized storytelling, emotional immersion, and consumer response.

Using a qualitative, exploratory case study approach, the study analyzes secondary data drawn from L’Oréal’s digital campaigns, product platforms, and consumer feedback. A thematic content analysis demonstrates that AI operates not merely as a data-processing tool but as a narrative engine that enables brands to co-create meaning with consumers. Through ModiFace and SkinConsult AI, personalized product experiences are transformed into emotionally resonant narratives, positioning users as protagonists in their own beauty journeys.

Findings indicate that AI-driven storytelling enhances consumer engagement, strengthens brand trust, and fosters identity alignment, ultimately driving loyalty and word-of-mouth advocacy. Furthermore, the case illustrates how AI-enabled personalization contributes to sustainable marketing practices by minimizing product waste through virtual try-ons, broadening access to beauty experiences, and supporting profitable yet responsible growth.

This research enriches marketing scholarship by reframing AI as a storytelling partner and introducing a model that integrates emotion, experience, technology, and sustainability within contemporary brand communication.

Abstract Generative Artificial Intelligence (Generative AI) has rapidly emerged as a transformative force within media organizations, reshaping how content is created, managed, distributed, and monetized. This article examines the applications of Generative AI in three critical domains of media management: content management, creative processes, and intellectual property (IP) governance. In content management, Generative AI enables automation of tasks such as content tagging, summarization, localization, and personalization, significantly improving efficiency and scalability while reducing operational costs. Algorithms capable of generating metadata and optimizing content workflows allow media organizations to respond more rapidly to audience demands across digital platforms. From a creativity perspective, Generative AI functions as a collaborative tool rather than a replacement for human creators. Technologies such as large language models, image generators, and audio synthesis systems support journalists, editors, and designers by assisting in idea generation, drafting, visualization, and prototyping. This human–AI co-creation model expands creative possibilities, accelerates production cycles, and lowers barriers to experimentation. However, it also raises questions about originality, authorship, and the cultural value of media products. The article further explores the complex implications of Generative AI for intellectual property. AI-generated or AI-assisted content challenges existing copyright frameworks, particularly regarding ownership, authorship, and liability. Media organizations must navigate risks related to training data transparency, potential infringement, and the protection of proprietary content. The study argues that effective governance strategies—combining legal compliance, ethical guidelines, and organizational policies—are essential for sustainable adoption. Overall, Generative AI represents both an opportunity and a strategic challenge for media organizations, requiring a balanced approach that integrates technological innovation with creative integrity and robust IP management.

Abstract A municipality is a public non-governmental institution that has also become responsible before the law due to the powers and duties entrusted to it by law; Therefore, the legal duties that municipalities undertake in line with their duties will have the ability to apply the law or judicial action. The civil liability of municipalities is subject to the rules that are defined for other persons, but the omission of actions by municipalities is specifically related to the type of organized activity of this non-governmental institution. This research was conducted in a theoretical manner and with a descriptive-analytical method. The research data collection method was library-based and was compiled by referring to documents; books and articles. The results of the research showed that the liability of municipalities is subject to Article 11 of the Civil Liability Law; However, determining the type and estimating the amount of damage, as well as the role of each organizational level of this institution against omission of action, has not been properly specified and is not subject to a reliable procedure. This issue becomes more complicated when multiple contractors cooperating with the municipality also join the scope of civil liability of municipalities. Ultimately, it seems that the municipality is immune from damages resulting from the exercise of its sovereignty and is exempt from paying damages. Other lawyers believe that in addition to the aspect of exercising sovereignty, the necessity of omission of action must be proven to the judge, otherwise, they will not be exempt from applying the law and compensating for damages simply by exercising sovereignty.

Abstract The integration of agile methodologies into digital transformation initiatives within public sector organizations represents a critical yet challenging endeavor in contemporary governance. This article examines the paradoxical relationship between Agile principles—emphasizing flexibility, iterative delivery, and self-organizing teams—and the inherently bureaucratic nature of public administration, characterized by hierarchical structures, rigid procurement frameworks, and risk-averse cultures. Through a systematic synthesis of empirical studies published between 2014 and 2025, this research identifies four primary categories of implementation challenges: institutional and regulatory barriers, procurement and contractual misalignments, cultural and resistance factors, and resource and capability constraints. The findings reveal that while agile adoption can significantly enhance transparency, responsiveness, and citizen-centered service delivery, successful implementation requires fundamental adaptations rather than wholesale methodological transplantation. A multidimensional framework proposed, integrating legal-procedural adaptations, hybrid governance models, tailored procurement mechanisms, cultural transformation strategies, and iterative implementation roadmaps. This research contributes to both public administration theory and digital government practice by providing evidence-based guidance for navigating the inherent tensions between agility and accountability in democratic governance contexts.