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435 research outputs found
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The Role of 15-Minute Cities in Promoting Sustainable Urban Development: A Stakeholder-Centered Project Management Approach
No full textThe 15-minute city is an innovative urban planning approach that aims to enhance sustainability, accessibility, and quality of life by placing essential services within a 15-minute walk or cycle radius. Despite its popularity globally, the majority of projects fail to realize their objective due to ineffective stakeholder engagement, competing priorities, and inadequate communication throughout the project procedure. This study addresses the urgent problem of limited stakeholder involvement in 15-minute city planning and implementation. The purpose of the study is to determine challenges of stakeholder engagement and develop a stakeholder-centric approach rooted in project management best practices. Guided by the Stakeholder Performance Domain of the PMBOK Guide, the study takes a qualitative case study methodology, employing semi-structured interviews, document analysis, and thematic coding in examining how residents, planners, and policymakers communicate and negotiate their conflicting agendas. Salient findings are that episodic consultation, incongruent goals, and a lack of continuous communication undermine project success
Evaluating the Effectiveness of Automation and Robotics in Reducing Delays in On-Site Construction Activities
No full textConstruction delays cause substantial cost overruns and in most cases strained stakeholder relationships in the industry. This study acknowledges the problem that while automation and robotics are touted as solutions, their quantifiable effectiveness in reducing onsite delays remains unclear. The purpose of this research is to evaluate how these technologies reduce construction delays caused by labor shortages, workflow inefficiencies, and coordination issues. Guided by Workflow Optimization Theory and the Technology Acceptance Model, the study employs a qualitative method design. Qualitative data from stakeholder interviews will explore adoption barriers and perceptual impacts on team coordination. Analysis will involve statistical comparison of time efficiency and thematic analysis of interview records. This research is important for providing empirical evidence to help construction firms make informed investment decisions in automation technologies
Institutional Constraints and the AI Automation Gap: A Case Study of Proposal Evaluation in Federal ICT Procurement at U.S. Customs and Border Protection
Full text linkThis research investigates the institutional constraints shaping the adoption of AI-assisted proposal evaluation in federal ICT procurement, using U.S. Customs and Border Protection (CBP) as a case study. Although AI tools are increasingly used by contractors to generate proposals, their integration into government evaluation processes remain limited. Using institutional theory as an analytical framework, this study examines how regulative rules, normative expectations, and cognitive assumptions jointly reinforce a risk-averse procurement culture that inhibits automation. Through a mixed-methods approach—comprising policy analysis, procurement data from FPDS and USAspending.gov, and an elite interview with a CBP contracting officer—the research identifies key barriers to AI adoption. Regulative constraints such as FAR or HSAM mandated procedural defensibility foster institutional rigidity. Normative constraints such as preferences for manual processes and legacy contract types discourage experimentation. Cognitive constraints reveal a limited organizational readiness for AI and skepticism toward AI-generated outputs. While recent judicial rulings and strategic plans signal openings for reform, institutional inertia persists. The study concludes that targeted pilot programs, evidence-based business cases, and internal capability-building are some steps that could align AI potential with federal procurement realities
THE ROLE OF FINANCIAL MANAGEMENT IN PROJECT SUCCESS: BUDGETING, FORECASTING, AND COST CONTROL
Full text linkFinancial management is essential for the success of projects, where budgeting, forecasting, and cost control are pivotal in reducing financial risks. This research investigates the efficacy of financial management practices across various sectors, pinpointing challenges including budget overruns, stakeholder pressures, and unforeseen costs. Utilizing qualitative research methods and analyzing survey data gathered via Qualtrics, the study reveals the effects of financial limitations, delays in approvals, and the use of digital financial tools on project outcomes.
The results indicate that insufficient budget allocation and poor forecasting practices are significant factors leading to project failures. Conversely, the implementation of financial technologies, including enterprise resource planning (ERP) systems and predictive analytics, improves the quality of financial decision-making. Additionally, the engagement of stakeholders was identified as a vital element that affects financial priorities and the allocation of resources. The research also delves into strategies for risk mitigation, highlighting the importance of contingency planning and flexible financial management.
This study adds to the existing body of knowledge in project management by offering valuable perspectives on the enhancement of financial strategies, the promotion of sustainability, and the improvement of project efficiency. It emphasizes the importance for organizations to adopt emerging technologies and data-centric methodologies to bolster financial planning processes. Furthermore, the research identifies potential avenues for future inquiry, especially in the application of artificial intelligence (AI) for real-time financial oversight and decision-making. The findings of this research have implications that reach beyond individual projects, influencing financial management practices across the industry, and providing significant guidance for project managers, financial analysts, and policymakers aiming to enhance financial performance and project results
Scalable Mental Health Analysis Using Big Data: A Demographic and Geographic Study of Depressive Symptoms
Full text linkThis project explores the application of Big Data technologies for large-scale mental health analysis, focusing on the prevalence of depressive disorder symptoms across diverse demographic and geographic subgroups. Utilizing Apache Spark on Google Cloud Dataproc, the system efficiently processed millions of survey records stored in Hadoop Distributed File System (HDFS). Through comprehensive data preprocessing, aggregation, and visualization, the analysis revealed critical trends and disparities in mental health outcomes related to age, race, education level, gender, and state. Seasonal variations and subgroup-specific confidence intervals were also examined to identify high-risk populations and areas of measurement uncertainty. The results offer actionable insights for public health decision-makers, supporting targeted interventions and equitable resource allocation. This work demonstrates the potential of scalable data processing frameworks to inform data-driven mental health strategies and highlights the integration of computational tools in addressing public health challenges
Scalable and Adaptive Agile Framework for Semiconductor Foundry: Advanced Packaging and Heterogeneous Integration Perspective
Full text linkThis research addressed the critical requirement for a scalable and adaptive agile framework specifically designed for the unique demands of semiconductor foundries specializing in advanced packaging and heterogeneous integration (HI). The semiconductor industry was encountering growing pressure to innovate and respond quickly to rapidly evolving demands, yet traditional manufacturing processes often struggled to adapt. Existing agile frameworks, mainly developed for the software industry, lacked the necessary adaptations to address the complexities of semiconductor manufacturing, including extended lead times, high capital investment, rigorous quality requirements, and the integration of various technologies. This research gap hindered the ability of semiconductor foundries to optimize their operations and maintain competitiveness. This study utilized a qualitative method, interviewing professionals from semiconductor foundries actively involved in advanced packaging and HI. Through thematic analysis of interview data, this research sought to identify crucial patterns and gain deeper understandings of the factors influencing agile transformation. The primary goal was to develop a tailored agile framework that addressed the particular requirements of advanced packaging and HI, enabling real-time visibility, flexibility, and responsiveness in managing complex workflows. The outcome of this research included improved manufacturing efficiency, enhanced innovation capabilities, and accelerated deployment of next-generation semiconductor technologies. The developed framework would offer actionable guidance for semiconductor foundries seeking to implement agile principles, contributing to the advancement of the semiconductor industry
The Influence of Emotional Intelligence on Project Leadership Effectiveness
Full text linkEffective leadership was necessary to enable the completion of modern projects due to their increasing complexity. An important component of leadership success was emotional intelligence (EI), which was defined by self-awareness, self-regulation, motivation, empathy, and social skills. This study examined how emotional intelligence affected project leadership effectiveness and how it might have improved project delivery results. The study adopted a qualitative approach and concentrated on detailed information obtained from project managers across a range of industries. Stakeholder communication, team motivation, conflict resolution, and project success rates were examples of leadership performance indicators that were examined in this study in connection to emotional intelligence components. Project managers with high EI were more equipped to manage challenging interpersonal circumstances, which improved team satisfaction and project performance, according to the qualitative research. The significance of integrating emotional intelligence development into leadership training programs for project managers was underscored by these findings. According to the study’s findings, improving emotional intelligence was essential to becoming a successful leader and maximizing project completion
The Role of Artificial Intelligence in Transforming Project Management in the Fashion
Full text linkThe quick adaptation of artificial intelligence (AI) is driving a significant revolution in the fashion. The use of AI in project management is still somewhat unexplored, despite its widespread adaptation in design, retail, and marketing. The impact of AI on project management procedures in the fashion industry is examined in this study, with a focus on striking a balance between operational effectiveness and creative freedom. The study is based on the Technology Acceptance Model (TAM), Industry 4.0, and Project Management Theory, which collectively offer a multi-theoretical perspective for comprehending the adoption and effects of AI. Examining fashion expert’s perspectives and experiences with the use of AI techniques like digital twins, predictive analytics, and generative design is the aim of this qualitative study. Four Major topics emerged from the thematic analysis: the role of AI in sustainability planning, the conflict between technical and creative teams, ethical worries about algorithmic opacity, and AI as a collaborative partner. This study adds to the limited knowledge on AI in fashion project management and provides useful advice for business executives looking to incorporate AI technologies without sacrificing originality. The study emphasizes AI’s ability to support sustainable practices, encourage innovation, and enhance operations in a typically manual industry.
This investigation emphasizes how crucial it is to match human values with technology innovation to maintain the fashion industry’s effectiveness and creative vibrancy in a time of digital revolution
Agile and Lean Integration Effects in Financial Services Organizations
Full text linkThe financial services industry, predominantly in large investment banks, faces mounting pressure to improve operational efficiency, simplify communication channel, and meet rigorous regulatory requirements in a constantly changing market environment. This research assesses the incorporation of Agile and Lean practices within the financial services sector, particularly concentrating on their effect on front-office functions, such as sales and investment banking, and control operations like risk and compliance. The study investigates how Agile and Lean processes foster innovation, decrease inefficiencies, and promote partnership between front-office teams and control functions. By examining case studies from leading organizations such as Goldman Sachs, JP Morgan, and Citi, the study underlines the challenges and opportunities of embracing these tactics in an extremely regulated setting. The conclusions contribute to a increasing body of knowledge on cultivating organizational efficiency, agility, and regulatory compliance through Agile and Lean methods, resulting in an wholistic framework for financial institutions to retain competitiveness in fast-changing market surroundings
Rethinking Schedule Quality Risk Assessment
No full textCritical Path Method schedule reliability is dependent on exhibition of specific qualities. Failure to exhibit these qualities (i.e., schedule defects) increases project risk exposure. Although current schedule quality assessment methods provide diagnostic remediation insights, they do not provide a meaningful singular assessment value that characterizes the nature and magnitude of schedule quality risk nor do they enable parity when comparing schedule quality across multiple schedules of disparate size (e.g., number of tasks) or complexity (e.g., number of concurrent paths, degree of merge bias). This study employed a design science research approach to address current schedule quality assessment practice dilemmas through proposition of a new methodological artifact for evaluating schedule quality risk