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435 research outputs found
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Environmental Risk Assessment of Textile Waste from Bio-Engineered Fibers in the Fashion Industry
No full textThe global fashion industry generates over 92 million tons of textile waste annually, a figure projected to increase significantly by 2030. Bio-engineered fibers, including bacterial cellulose, mycelium-based leather, and recombinant protein textiles emerge as sustainable alternatives to conventional fibers. Despite their promise, recent evidence suggests that these fibers may pose environmental risks at the end-of-life stage, such as incomplete biodegradation in landfills, microfiber shedding, and chemical leaching from dyes and coatings. The purpose of this study is to examine how these risks are represented through scientific literature, corporate sustainability reports, and policy frameworks, and to identify strategies for integrating risk management into sustainability-focused project planning. Guided by Environmental Risk Perception Theory and Framing Theory, the qualitative study employs document-based content analysis of sources drawn from scientific, industry, and regulatory domains. Coding and thematic analysis are supported by Python and R, with results synthesized into a risk assessment matrix aligned with the PMBOK. The study is limited to North America and Europe and focuses on post-consumer disposal rather than production or use-phase impacts. Findings are expected to provide project managers with practical tools for assessing risks, improving stakeholder communication, and aligning sustainability claims with real disposal outcomes. This research contributes to both academic understanding of environmental risk communication and practical applications for project management in sustainable innovation
Regulatory Reform for Agentic AI: Addressing Governance Challenges in Federal AI Adoption
No full textThe rapid advancement of artificial intelligence (AI), particularly agentic AI systems capable of autonomous decision-making, has exposed significant gaps in existing federal regulatory frameworks. This paper examines the regulatory barriers inhibiting AI innovation and adoption identified in the Office of Science and Technology Policy\u27s (OSTP) Request for Information (RFI) on regulatory reform. We analyze five categories of barriers—regulatory mismatches, structural incompatibility, lack of clarity, direct hindrance, and organizational factors—and propose a comprehensive governance framework integrating technical standards, risk management protocols, and policy recommendations. Drawing from extensive literature on AI governance tools and frameworks, we present actionable solutions for modernizing federal regulations to foster responsible AI innovation while maintaining public trust and safety
Understanding Community Engagement as a Tool for Equitable Project Outcomes: Lessons from Domino Park and Hudson Yards Public Square
Full text linkThis thesis explores the significance of community engagement in urban planning within the project management framework. In the face of intricate challenges in contemporary urban environments, adopting effective project management strategies prioritising the community voice has become crucial. This study inquires into the methods, barriers, and the scope of using community engagement as a tool for successful and fair project outcomes in urban environments. The aim of this thesis is to provide valuable insights and practical recommendations to practitioners in the fields of urban planning, project management, and urban policymaking. There is a growing recognition that inclusive and participatory processes are key to achieving successful project outcomes that are aligned with the needs of the communities being planned for. The significance of this research lies in its potential to highlight to practitioners the value and benefits of inclusive community engagement to enhance project outcomes, stakeholder relationships, and an overall improvement in the quality of urban projects. This thesis ultimately aims to uncover why project management should integrate more inclusive practices especially when it comes to developing urban spaces. It will do so by employing a case study analysis of two urban park developments in New York City, namely, Domino Park in Brooklyn, and Hudson Yards Public Square in Manhattan, to identify any difference in the approaches to community engagement and how it impacted the project outcomes and perceptions. A comprehensive exploration of the role of community engagement in urban planning projects positions this thesis to advance project management practices in creating more prosperous and thriving urban communities
Enhancing stakeholder engagement in project management through ai-driven predictive modeling
Full text linkThe ongoing difficulty in project management in achieving desired outcomes is frequently linked to the value gap that appears between program installation and execution, where stakeholders find it difficult to adjust actions to achieve desired outcomes. Adaptable tactics are required to overcome the challenges posed by a various of interests, decision-making procedures, and resource limitations in traditional stakeholder engagement approaches. This study aims to know the key factors that influence the acceptance of AI-driven forecasting in project management processes for stakeholder management, and how these characteristics help to overcome the drawbacks of conventional stakeholder engagement approaches. The paper investigates the revolutionary potential of AI-driven forecasting in closing the value gap through an extensive examination of the literature. By utilizing AI-driven predictive modeling and analyzing current literature, the research endeavors to offer practical solutions for enhancing project success and deepening our comprehension of stakeholder involvement. Stakeholders can enhance the dynamic field of project management by adopting AI technology, enabling them to address obstacles, optimize resource allocation, and promote collaborative interactions
Customized Agile Project Management for Scientific Computing: Addressing Challenges and Developing a Framework
Full text linkThis paper presents a novel Agile framework tailored for scientific computing projects. Identifying gaps in existing methodologies, the research emphasizes the need for adaptable solutions in this dynamic field. The proposed framework, characterized by flexibility and stakeholder engagement, addresses specific challenges posed by scientific computing endeavors. Through a comprehensive literature review, the paper highlights the limitations of generic Agile practices and positions the proposed framework as a valuable contribution. The study motivates further exploration into specialized Agile approaches, promising enhanced efficiency and success in scientific computing projects
Human-ai collaboration in project management
Full text linkThe integration of Artificial Intelligence (AI) into project management has emerged as a transformative trend, promising enhanced efficiency and strategic capabilities. This study explores the dynamics of human-AI collaboration in project management, focusing on factors that influence effective implementation, the impact of AI on project outcomes, and the challenges encountered in AI adoption. Utilizing a qualitative approach, data were collected from project management professionals across various industries, revealing that trust and transparency are crucial for successful collaboration. The findings indicate that AI positively impacts project efficiency and cost-effectiveness by automating routine tasks and optimizing resource allocation. However, challenges such as resistance to change, data privacy concerns, and lack of understanding pose significant barriers. The study integrates Socio-Technical Systems Theory (STS) to frame the discussion, highlighting the importance of ethical AI practices and the need for seamless integration into existing processes. These insights contribute to the broader discourse on AI integration in project management, offering practical implications for enhancing human-AI collaboration. Future research should explore cross-industry AI adoption, longitudinal impacts, and strategies to further optimize the human-AI collaboration dynamic
Problem Of Rolling Over Of The Stories In Agile IT Projects
Full text linkAgile teams had the problem of rolling over of the stories in the IT projects. The spillover of the stories was happening despite of already having the commitment from the skillful team to finish the work in a Sprint. The reason of inefficiency was lack of Agile best practices like communication, collaboration, trust, teamwork, and self-organization in the Agile teams. Even though the team was skillful, the configuration was not proper. T-shaped team members have generic skill as well as diverse skill set. The T-shaped team members were lacking in the Agile teams and that’s why the spillover was happening. In this study, first the Agile best practices like communication, collaboration, trust, teamwork, and self-organization shown by the T-shaped team member were discussed. It was found that the Agile best practices enhance the efficiency of the teams. Later, the theoretical framework which support the hypothesis that the T-shaped employees embrace the Agile best practices were analyzed. The theoretical framework discussed here were Agile team dynamics, T-shaped skill theory, Cross-functional team theory, Competency-based framework, and Knowledge sharing and social capital theory. All these theoretical frameworks supported the hypothesis that the T-shaped skilled team could help in reducing the occurrence of rolling over of the stories. The chronological and thematic organization were done for the literature review. The thematic organization was done on the variables of study like communication, collaboration, teamwork, trust, self-organization, adaptability, lifelong learning, and knowledge sharing. T-shaped team members demonstrated all the qualities mentioned as the variable of study in the thematic organization of the literature review. The Qualitative research design was used in this study and thematic analysis was done on Qualtrics survey open-ended questions responses. Based on the responses of the survey questions, the reason for rolling over of the stories were improper sprint planning, not considering the retrospective feedback, immaturity in the team, and roadblocks like technical complexity, scope change etc. The survey responses also suggested that the reason for rolling over of the stories could be avoided if the team followed the Agile best practices. As per the survey responses, the T-shaped team members follow the Agile best practices. The overall efficiency was excellent in case of T-shaped team members. The T-shaped team members were good in meeting the project deadlines. Thus, it was concluded that the T-shaped team members can help in reducing the rolling over of the stories. There were some limitations with the T-shaped team members like the T-shaped team members could not become experts in the long run. The limitations with the T-shaped team members led into the future research opportunities
Project Management and Jira with Agile Scrum Methodology
Full text linkIn an era characterized by rapid technological advancement and increasing project complexity, effective project management has become paramount for organizational success. This study investigates the effectiveness of Jira software, a prominent tool within Agile and Scrum frameworks, in optimizing project management processes. Despite its widespread adoption, many organizations struggle to fully leverage Jira\u27s capabilities, often leading to project delays and miscommunication. This research aims to address the critical gap in literature regarding Jira\u27s application and effectiveness by systematically evaluating its impact on project management efficiency and team collaboration.
Utilizing a quantitative approach, the study surveyed 50 project managers and team members across various industries actively using Jira. The findings reveal a substantial 25% increase in project completion rates and a strong positive correlation (r = 0.65) between user satisfaction and project success. However, significant challenges were identified, including the complexity of Jira\u27s interface and the necessity for comprehensive training, which can hinder effective utilization.
These results underscore the importance of user experience and training in maximizing Jira\u27s benefits. The study provides actionable recommendations for organizations, emphasizing the need for robust training programs and a supportive culture to mitigate barriers to effective usage. By contributing valuable insights into the interplay between technology and project management practices, this research informs better implementation strategies for organizations seeking to enhance their project outcomes through Jira. Future research directions are proposed, including longitudinal studies and comparative analyses of project management tools, to further enrich the understanding of Agile methodologies in diverse contexts
Contrast and compare the cyber hacking laws between the United States, Russian federation, and the people\u27s Republic of China
Full text linkCyber hacking is a growing threat in the modern world. As the world becomes more digital, the threat of cybercrime continues to grow. Cyberattacks can lead to stolen personal information, financial losses and damage to critical information. The increase in the digital transformation of companies has also led to an increase in cyber security concerns. With cybercriminals using increasingly advanced methods to gain access and take advantage of sensitive information. As a result, governments around the world have developed measures, laws, and regulations to address cybercrime and protect against cyberattacks. The United States, Russian Federation, and the People’s Republic of China are among the countries with the most developed cyber hacking laws
Exploring the impact of artificial intelligence on project management across the manufacturing, technology, and construction industries
Full text linkThis study explores the impact of Artificial Intelligence (AI) on project management across the manufacturing, technology, and construction industries. The research focuses on understanding the benefits, challenges, and long-term implications of AI utilization in these sectors. Key findings indicate that 46% of participants use AI mainly for task automation and enhancing functions like brainstorming and communication, which significantly boosts efficiency and team productivity. Despite these benefits, the research identifies several obstacles, including high initial costs, inadequate training, technical issues, and unclear regulatory guidelines. The study addresses four main questions, revealing that AI not only enhances project management processes but also requires ongoing learning and adaptation of professional skills to overcome barriers to its adoption