Description
This book brings insight to the HR management system and offers data-centric approaches and AI-enabled applications for the design and implementation strategies used for workforce development and management.
Designing Workforce Management Systems for Industry 4.0: Data-Centric and AI-Enabled Approaches focuses on the mechanisms of proposing solutions along with architectural concepts, design principles, smart solutions, and intelligent predictions with visualization simulation. Data visualization for the metrics of management systems and robotic process automation applications and tools are also offered.
This book is also useful as a reference for those involved in AI-enabled applications, data analytics, data visualization, as well as systems engineering and systems designing.
Table of Contents
1. Workforce Management System: Concepts, Definitions, Principles, and Implementation.
Snehal Maheshkar, Babasaheb Jadhav, Alex Khang
2. Industry Revolution 4.0: Workforce Competency Models and Designs.
Alex Khang, Babasaheb Jadhav, Sphurti Birajdar
3. AI Powered Workforce Management in Industry 4.0 Era.
Lokpriya Gaikwad, Alex Khang
4. AI-based Competency Model and Design in the Workforce Development System.
Parin Somani, Shashi Kant Gupta, Chandra Kumar Dixit, Anchal Pathak
5. Data: An Anchor for Decision Making to Build the Future Workforce Management System.
Samiksha Shukla, Aerica Rishiraj, Yash Lucas
6. Data Mining Processes and Decision-Making Models in Personnel Management System.
Shashi Kant Gupta, Alex Khang, Parin Somani, Chandra Kumar Dixit, Anchal Pathak
7. Data-driven Application of Human Capital Management Databases, Big Data, and Data Mining.
Alex Khang, Shashi Kant Gupta, Chandra Kumar Dixit, Parin Somani
8. ata-centric Predictive Modelling of Turnover Rate and New Hire in Workforce Management System.
Chandra Kumar Dixit, Parin Somani, Shashi Kant Gupta, Anchal Pathak
9. Impact of Artificial Intelligence (AI) on Talent Management (TM): A Futuristic Overview.
Arpita Nayak, Ipseeta Satpathy, B.C.M. Patnaik, Sukanta Kumar Baral, Alex Khang
10. Data-driven Artificial intelligence (AI) Models in the Workforce Development Planning.
Pallavi Jain, Vandana Tripathi, Ravisankar Malladi, Alex Khang
11. Prediction of Employee’s Performance Using Machine Learning (ML) Techniques.
Anchal Pathak, Chandra Kumar Dixit, Parin Somani, Shashi Kant Gupta
12. AI-enabled Approaches and Models for Designing Workforce through Training Systems for Physically Challenged People.
Babasaheb Jadhav, Ashish Kulkarni, Pooja Kulkarni
13. Relevance Analytics of Work Motivation and Job Satisfaction in the era of Industry 4.0.
Mohammad Qais Rezvani, Hayri Uygun, Rashmi Gujrati, Shivangi Singh, Nirmala Chaudhary
14. A Bibliometric Analysis on Application of Artificial Intelligence (AI) in Workforce Management.
Durga Prasad Singh Samanta, B.C.M. Patnaik, Ipseeta Satpathy, Liji Panda
15. Leveraging Employee Data to Optimize Overall Performance - Using Workforce Analytics.
Saravanakrishnan V, Ginu George, Anson K. Joy, Anusha B
16. Robotic Process Automation (RPA) Applications and Tools for Workforce Management System.
Sathya V, Jayashree K, Malathi S
17. Exploring the Concept of Managing Women Employees Work Life Balance in Information Technology Company.
Jansi Rani T, Krishan Priya V
18. Challenges Faced by Marketers in Developing and Managing Contents in Workforce Development System.
Ashwini Y. Sonawane, Alex Khang
19. Linkages between Critical Success Factors and Factors of Workforce Performance in Remanufacturing Industry.
Lalit K. Toke, Amol D. Lokhande, Vishal S. Fegade
20. A Study on the Impact of the Industry 4.0 on the Employees Performance in Banking Sector.
Pooja Aggarwal, Alex Khang
