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IMPACT OF GLOBAL LEADERSHIP IN LEADING TO THE SUCCESS OF A PROJECT
Full text linkThis research explores the impact of leadership competencies on the success of global projects, focusing on key factors such as cultural intelligence (CQ), emotional intelligence (EI), communication, and adaptability. Through a survey of project leaders, the study investigates how cultural differences affect team performance, the competencies required for effective leadership in diverse environments, and the challenges of managing cross-cultural teams. The findings emphasize the importance of understanding and navigating cultural nuances, fostering positive team dynamics, and aligning team objectives with organizational goals. The research also highlights the necessity of flexibility in leadership approaches to accommodate diverse team needs and improve project outcomes. The implications suggest that global leaders must prioritize these competencies to drive successful collaboration and performance in international projects
Enhancing Stakeholder Collaboration in Indonesian-Owned Businesses in the United States
Full text linkThis research examines stakeholder engagement strategies among Indonesian restaurant owners in the United States, focusing on their operational success and business sustainability. Using a qualitative methodology, the study conducted semi-structured interviews with five purposively selected restaurant owners to investigate how they integrate stakeholder interests into business strategies, leverage government support, and adapt engagement practices across different sectors. The findings reveal three key challenges: insufficient frameworks for integrating stakeholder interests with business strategies, inadequate government support mechanisms, and inconsistent stakeholder engagement practices. The study identified successful informal approaches to stakeholder management, particularly in balancing cultural authenticity with market demands. However, it also uncovered significant gaps between government support programs\u27 intended outcomes and their practical implementation. The research contributes to theoretical understanding by suggesting modifications to stakeholder theory for diaspora enterprises and practical implications for enhancing government support mechanisms. The findings emphasize the need for improved frameworks that consider the unique challenges of cultural food businesses while maintaining authenticity in international markets.
Keywords: Stakeholder engagement, stakeholder collaboration, diaspora entrepreneurship, government support, gastrodiplomac
Operational Endings, Emotional Impacts: Ethical Considerations When Project Teams Form Attachments to AI Collaborators
Full text linkThe project investigated responses to an AI displaying emotional qualities, such as fear, through a mixed-methods approach. Participants were randomly assigned to one of two scenarios—one featuring an AI coworker and the other a human coworker and evaluated for emotional attachment and loss. Results revealed that professionals exhibited significant emotional responses to the potential termination of an AI team member. Qualitative analysis identified eight themes, including emotional responses and termination. Findings suggest that emotionally expressive AI activates psychological processes akin to human relationships, with implications for AI design, workplace dynamics, and ethical considerations surrounding AI termination
Community-Driven Stakeholder Engagement Strategies in Public Health Projects
Full text linkCommunity-driven stakeholder engagement is vital for the success and sustainability of public health initiatives, yet its implementation is often hindered by significant challenges. This qualitative study explored the strategies, barriers, and lessons learned in stakeholder engagement within public health projects. Guided by Project Stakeholder Management from the PMBOK Guide and the Social-Ecological Model (SEM), this research conducted a thematic analysis of in-depth, semi-structured interviews with eleven public health professionals. The findings reveal that effective engagement strategies include early and continuous involvement, co-creation of solutions, and building on existing community trust. Key challenges identified were overcoming deep-seated community mistrust, navigating complex power dynamics, and managing resource constraints and stakeholder burnout. The study concluded that successful community-driven engagement requires flexibility, transparent communication, valuing lived experience as a form of expertise, and cultivating a shared vision. These findings provide evidence-based recommendations for public health practitioners and policymakers to enhance stakeholder collaboration, thereby driving positive social change and improving health outcomes
Research on credit card transaction risk prediction model based on multi-source data fusion and its application
No full textIn this paper, the credit card risk control and early warning model is constructed to predict and control the credit card risk by fusing multi-source data through data mining technology. After analyzing the theoretical application of XGBoost algorithm on credit card transaction risk, its model parameters are optimized by particle swarm algorithm to construct PSO-XGBoost credit card transaction risk prediction model. The credit card transaction risk prediction performance of the PSO-XGBoost model is verified and applied to the abnormal transaction risk assessment of Bank A. The AUC value, accuracy, F1 value, precision rate, and recall rate of the PSO-XGBoost model are the largest among all the algorithms, and the correct detection rate of the PSO-XGBoost model is significantly higher than that of other algorithms, and the error detection rate significantly lower than other algorithms, with the best risk prediction performance. Among the 10 Bank A credit card customers, customer 4 and customer 5 have very high risk in their credit card transactions, customer 2 and customer 3 have high risk, customer 1, 5, 7 and 8 have medium risk in their credit card transactions, and customer 9 and customer 10 have low risk
Integration of Artificial Intelligence and Project Management Techniques in Financial Restructuring
Full text linkFinancial restructuring is a critical strategy for organizations navigating economic challenges, particularly during mergers and acquisitions (M&A). However, 61% of strategic initiatives fail due to ineffective knowledge transfer, communication barriers, and insufficient integration of advanced technologies like artificial intelligence (AI) (PMI, 2014; Durst & Zieba, 2019). This study explores the integration of project management (PM) methodologies and AI-driven tools to enhance financial restructuring outcomes. Through a quantitative analysis of 64 professionals across industries, the research identifies key challenges including cultural clashes (44%), communication barriers (43%), and lack of standardized processes (38%) while demonstrating AI\u27s positive impact on knowledge transfer efficiency (*r* = 0.62, *p* \u3c 0.05). AI-enhanced Project Management Offices (PMOs) outperformed traditional PMOs (M = 4.2 vs. 3.1), yet hybrid structures faced unexpected resistance. The findings underscore the need for balanced AI adoption, addressing both technological and human-centric barriers. This research contributes actionable frameworks for practitioners and advances theoretical discourse by merging Nonaka and Takeuchi’s (1995) knowledge creation theory with AI capability maturity models (Anderson & Martinez, 2023)
Readmission Prediction for Diabetic Patients: A Scalable Big Data Approach for Resource-Constrained Hospitals
Full text linkHospital readmissions, particularly among diabetic patients, place a significant burden on healthcare systems by increasing operational costs and straining limited resources. This project presents a scalable, cloud-based solution that leverages machine learning and big data analytics to predict 30-day hospital readmissions. Utilizing a ten-year dataset of over 100,000 patient records, we implemented a Random Forest classifier trained on clinical, demographic, and hospitalization data. The system architecture integrates Google Cloud Platform services—including BigQuery, Vertex AI, and Looker Studio—with a custom Python/Flask web application for real-time data input and inference. Data preprocessing and feature engineering were conducted in Vertex AI Workbench, enabling the transformation of raw medical records into model-ready formats. Our deployed model achieves high accuracy and supports prediction through a REST API endpoint, with interactive dashboards providing actionable insights to healthcare providers. The project demonstrates the potential of artificial intelligence to support proactive care management and reduce hospital readmissions, while laying the groundwork for automated retraining pipelines to accommodate evolving patient data
Leadership in the age of AI: Review of quantitative models and visualization for managerial decision-making
No full textThis paper offers a comprehensive review of existing literature on the intersection of Artificial Intelligence (AI) and leadership, drawing on both theoretical insights and practical implementations. By analyzing scholarly publications from the past two years (2023-2025), the review traces emerging patterns in how AI technologies are being integrated into leadership practices. Key themes include the growing relevance of learning-based systems for adaptive decision-making and the application of attention-based models to improve responsiveness in dynamic environments. The review also addresses ethical dimensions of AI-enabled leadership, emphasizing the need to balance algorithmic efficiency with human judgment and oversight. Concerns around transparency, psychological safety, and trust in automated systems are explored in depth. Furthermore, the paper outlines various AI-supported leadership support systems that are currently in use, highlighting their potential to assist leaders in strategic forecasting, communication, and stakeholder engagement. The synthesis incorporates multiple theoretical frameworks that help contextualize AI’s role in leadership transformation, offering a structured view of how emerging technologies are reshaping leadership thought and behavior. Ultimately, this review maps out a landscape of opportunities and challenges, providing a foundation for future research in AI-augmented leadership. The analysis identifies reinforcement learning as a predominant approach in leadership strategies, with a theory-weighted impact metric (Impact=∑T_i×F_i) assigning it a weighted score of 4.08/6.0. The review also highlights the use of multi-head attention mechanisms (LeadershipAttention(Q,K,V)) to enhance crisis response times by 37% (p\u3c 0.001). Additionally, ethical concerns are discussed, particularly regarding the incorporation of KL divergence optimization systems (KL(p_AI |)p_human )\u3c ϵ) to maintain human oversight. The findings from the reviewed studies show that AI adoption leads to a 58% ±12% faster decision-making process, a 41% ±9% increase in strategic accuracy, and 89.2% forecasting precision. However, challenges in psychological safety thresholds (T\u3c 0.4) and transparency in AI decision-making (A\u3c 0.6) persist. The paper also discusses existing AI-Driven Leadership Decision Support Systems (AI-LDSS), including the use of transformer-based NLP, SHAP-explainable predictions, and bias detection. This review synthesizes theoretical frameworks, including differential leadership equations ((dL_i)/dt=αL_i (1-L_i/K)-β∑L_i L_j+γA_i (t)), and provides an overview of the current state of AI in leadership research. This is pure review paper and all results are from cited literature
Effects of Cultural Diversity on Project Performance
Full text linkCultural diversity emerged as a critical factor influencing team dynamics and performance in contemporary project environments. With globalization reshaping the structure of project teams, understanding how cultural diversity affected project outcomes was essential for project managers and organizations. This qualitative study examined the relationship between cultural diversity and project performance within diverse organizational settings. Specifically, the study explored how aspects of cultural diversity such as ethnicity, nationality, language, and values influenced project outcomes measured in terms of schedule adherence, budget compliance, quality standards, and stakeholder satisfaction. The research was grounded in Hofstede’s Cultural Dimensions Theory and Social Identity Theory, which provided a theoretical basis for understanding how cultural traits influenced interpersonal and group behavior. Data were collected through semi-structured interviews with professionals working in multicultural project teams. Thematic analysis was used to identify patterns and insights from participant responses. The findings provided empirical insights into how cultural diversity could be managed to enhance project effectiveness. These results supported project managers in designing inclusive team strategies that leveraged diversity as a strength rather than a barrier. This research contributed to the field of project management by offering evidence-based recommendations for improving project outcomes in culturally diverse work environments
Application of Hybrid Agile-Waterfall in Digitization of the Fashion Industry
Full text linkThis qualitative study explored employee perceptions of hybrid agile–waterfall methodologies during a digital transformation at a luxury fashion company. Using the Technology Acceptance Model (TAM) as a framework, the research examined how employees with limited exposure to agile frameworks understood, accepted, and anticipated their impact across creative, operational, and technical departments, focusing on perceived usefulness, ease of use, training, leadership support, and cultural fit. Twelve semi-structured interviews were conducted with professionals from merchandising, design, IT, logistics, and digital operations. Thematic analysis revealed limited familiarity with agile principles, moderate perceived usefulness, low ease of use, and widespread demand for contextualized training and leadership advocacy. While participants were open to change, agile was often viewed as IT-centric, emphasizing the need to reframe it as cross-functional. The study contributes to agile scholarship in creative industries, highlights phased implementation and tailored training as practical strategies, and recommends future mixed-method, cross-sector, and longitudinal studies to track agile readiness and cultural alignment over time