Call for Papers
Transforming Business Management through Machine Learning and its Applications
Machine learning is the branch of artificial intelligence widely used in business applications. The dramatic progress made in the last few decades has enabled machine learning to be a disruptive technique across various industries focusing on data analytics applications. It extracts meaningful insights from the raw data and helps in data-intensive complex decision-making processes. Presently, machine learning technologies enhance business scalability and improve business operations in companies across industries. They acquired tremendous research attention due to the potential of business intelligence and analytics. Some of the critical factors, such as growing business data volume, affordable data storage facilities, cheaper and faster computational processing, and easy data availability, have made machine learning an important part of the business management process. If implemented in the right way, machine learning techniques can efficiently predict complex business behaviours and solve uncertain and difficult problems.
The most important benefits of implementing machine learning techniques for business management include predictive maintenance, customer lifetime value prediction, spam detection, eliminating manual data entry, product recommendation, medical diagnosis, image recommendation, improved cyber security, and improved customer satisfaction. This special issue aims to investigate the technical aspects of business analytics and extract appropriate knowledge to drive innovation and efficiency of the business processes. Research on technical aspects of machine learning will solve major business management problems and improve efficiency and productivity. Regardless of the kind of machine learning paradigm we select, the prime objective of machine learning algorithms and big data analytics is to adapt to the new data efficiently and make recommendations and suggestions based on the thousands of analytics and computation measures. It provides less expensive and more powerful business intelligence solutions for business processes. It effectively identifies patterns and makes interventions without any human interventions. The accuracy and efficiency of business data analytics can be improved with the proper implementation of machine learning techniques. Also, it enables businesses to stay competitive in ever-changing market demands. It provides a greater understanding of the overall business and the user requirements.
This special issue aims to investigate the ways in which machine learning technology and its application can revolutionize business management. We welcome researchers and practitioners working in this discipline to present their novel and unpublished research findings.
LIST OF TOPICS OF INTEREST INCLUDE THE FOLLOWING: -
- Trends in machine learning for emerging business market
- Importance of machine learning in complex business process management
- Machine learning and big data analytics in business management
- Business data analytics with machine learning and IoT
- Role of industrial IoT and machine learning in business management
- Improving business performance with machine learning
- Data mining and machine learning for business operation management
- Machine learning for understanding the consumer needs
- Decision making in business process management with machine learning algorithms
- Machine learning and artificial intelligence for business process automation
- Increasing user experience and customer satisfaction with machine learning
Dr.Anbarasan M
Professor,
Department of Computer Science and Engineering,
Chennai Institute of Technology,
Anna University, Tamil Nadu, India
Official Email: anbarasanm@citchennai.net
Google Scholar: https://scholar.google.co.in/citations?user=dNTBlNsAAAAJ&hl=en
Official Page: https://www.citchennai.edu.in/departments/ug-courses/computer-science-engineering/faculty/
Dr.Gabriel Ayodeji Ogunmola
Associate Professor,
School of Business Studies,
Sharda University,
Andijan, Uzbekistan.
Official Email: Gabriel.ogunmola@shardauniversity.uz
Google Scholar: https://scholar.google.com/citations?user=V2Nb_zgAAAAJ&hl=en
Official Page: https://www.shardauniversity.uz/faculty/globalfacultydetails/dr-gabriel-ayodeji-ogunmola
Dr. Anand M
Assistant Professor,
Department of Computer Science and Engineering,
School of Computing,
SRM Institute of Science and Technology,
Kattankulathur, India
Official Email: anandm4@srmist.edu.in
Official Page: https://www.srmist.edu.in/faculty/dr-m-anand-2/
Dr. Imran Shafique Ansari
Assistant Professor,
James Watt School of Engineering,
University of Glasgow,
Glasgow G12 8QQ, UK
Official Email: imran.ansari@glasgow.ac.uk
Google Scholar: https://scholar.google.com/citations?user=vxTEQZYAAAAJ&hl=en
Official Page: https://www.gla.ac.uk/schools/engineering/staff/imranansari/
TENTATIVE TIMELINE FOR SUBMISSION: -
Submissions due: - 25th January 2024
Preliminary notification: - 10th May 2024
Revisions due: - 25th August 2024
Final notification: - 05th November 2024
Please submit your paper by choosing the special issue title in the Editorial Manager.
https://www2.cloud.editorialmanager.com/ijitm/default2.aspx?pg=login.asp&username=