AIMS AND SCOPE
The MAIT Journal of Science Technology seeks to serve as a scholarly platform for disseminating high-quality research and insights on cutting-edge technologies shaping modern engineering-driven businesses. With a particular focus on the transformative role of Artificial Intelligence (AI), the journal aims to highlight its impact on business, management, and decision-making processes.
Integrating AI-driven analytics and predictive modelling enables businesses to gain deeper insights into customer behaviour, market trends, and operational performance in an era where data-driven decisions significantly enhance productivity and cost efficiency. These capabilities empower organizations to tailor products and services, adapt to dynamic market conditions, and achieve agility in their strategies.
MAIT Journal of Science Technology encourages contributions that explore AI's potential in driving innovation, fostering operational efficiency, and generating vast datasets that serve as rich sources for research. The journal is committed to publishing high-quality scholarly work, including original research, reviews, surveys, case studies, technical notes, and short communications.
Through rigorous peer review and a dedication to academic excellence, MAIT Journal of Science Technology aspires to provide invaluable knowledge to academics, industry professionals, students, and innovators. This journal serves as a beacon for those striving to harness AI and other advanced technologies to gain a competitive advantage globally.
SCOPE
The MAIT Journal of Science Technology is an interdisciplinary, refereed journal dedicated to exploring the integration of advanced technologies and management strategies in engineering-driven domains. It focuses on the use of smart computing and decision-making frameworks to support business innovation and foster future growth.
The journal welcomes original, high-quality manuscripts, including research articles, case studies, and technical notes, in the following areas (but not limited to):
- AI in Business and Management
- AI and ethics in decision-making.
- AI-driven fraud detection and prevention.
- AI in financial modeling and investment analysis.
- AI in policy making for strategic markets.
- AI-enhanced cybersecurity for business protection.
- AI-enhanced data analytics for business intelligence.
- Explainable AI for regulatory compliance.
- Operational Excellence
- Predictive analytics for demand forecasting.
- Quality control and production optimization.
- Logistics and supply chain management with AI.
- Robotics and AI in manufacturing processes.
- Supply chain optimization with AI.
- Robotic process automation (RPA) in business processes.
- Customer and Market Insights
- Machine learning for customer segmentation and targeting.
- Recommendation systems for e-commerce.
- Sentiment analysis in financial markets.
- Natural language processing in chatbots for customer support.
- Decision Support and Bioinspired Systems
- Decision support systems for business intelligence.
- Knowledge-driven expert systems.
- Neural networks and algorithms for bioinspired systems.
The Journal contributes to bridging the gap between academia and industry by fostering a platform for innovative research and collaboration. The journal invites contributions that explore the practical and theoretical advancements of AI, innovative computing, and technology applications across diverse disciplines.
