Dr. Maryam Ashrafi
Dr. M. Mujiya Ulkhaq
Mequanint Birhan
Tsinukal Bezabih
Section Collection Information
Dear Colleagues,
We are pleased to invite you to contribute to the section “ Project and Quality Management” .
Project and Quality Management research plays a crucial role in driving organizational success and ensuring customer satisfaction. In today's fast-paced and competitive business landscape, effective project management practices are essential for delivering projects on time, within budget, and meeting stakeholder expectations. Quality management, on the other hand, is vital for enhancing product and service quality, improving customer satisfaction, and building a strong reputation in the market. By conducting research in the field of project and quality management, we can uncover innovative strategies, methodologies, and tools that enable organizations to achieve excellence in project execution and deliver superior quality products and services. This call for papers aims to foster knowledge sharing, collaboration, and the dissemination of valuable insights that will contribute to the advancement of project and quality management practices.
We invite researchers and practitioners to submit their original contributions to the Project and Quality Management section of our journal. This section aims to explore the latest advancements, challenges, and best practices in project management, as well as quality management in various industries and domains.
Scope and Topics:
1. Project Management:
AI-based algorithms for optimizing project schedules
Predictive modeling using machine learning techniques
Resource allocation and optimization using AI
Intelligent decision support systems for project planning
Predictive analytics for identifying project risks using AI
AI-based algorithms for risk assessment and mitigation
Natural Language Processing (NLP) for sentiment analysis in risk management
Agile project management methodologies and practices
AI-driven tools for real-time risk monitoring and reporting
Project planning, scheduling, and resource management
Risk assessment and mitigation strategies
Project governance and stakeholder management
Project success factors and performance measurement
2. Quality Management:
AI-driven techniques for automated quality inspection
Machine learning for real-time quality monitoring and defect detection
Intelligent predictive maintenance using AI algorithms
AI-based tools for quality data analysis and anomaly detection
Total Quality Management (TQM) principles and applications
Quality control and assurance techniques
Continuous improvement methodologies (e.g., Six Sigma, Lean)
Quality metrics and performance evaluation
Supplier quality management
We welcome research papers, case studies, literature reviews, and conceptual papers that contribute to the understanding and advancement of project and quality management. Submissions should demonstrate rigorous research methods, practical relevance, and a clear contribution to the field.
Join us in shaping the future of project and quality management by submitting your work for consideration.
We look forward to receiving your innovative ideas and insights!
Leading Section Editor:
Dr. Maryam Ashrafi
Section Editors:
Dr. M. Mujiya Ulkhaq
Mequanint Birhan
Tsinukal Bezabih