Analysing Trends and Patterns in Employee Engagement Through AI
Produktdetaljer
Om bidragsyterne
Soumi Majumder is a research scholar of the Department of Business and Accounting in Lincoln University College, Malaysia. She is an assistant professor at Future Business School, Future Institute of Engineering and Management, Kolkata, India. Previously, she was associated with Sister Nivedita University, Techno India College of Technology, NSHM College of Management and Technology, J D Birla Institute of Science and Commerce, West Bengal State Labor Institute, Siliguri, DAITM and many more B Schools. She is an associate researcher at the Universidad Internacional de La Rioja, Logroño, La Rioja, Spain She is having 8 years of experience in academia and 2 years of industrial experience. She has 3 authored books from Springer Nature, 1 authored book from Taylor and Francis publisher, 1 authored book from Emerald publisher and 2 edited books and more than 25 research papers in national, and international conferences and journals in the area of quality work-life, decent work-life, work-life balance, stress management, employee engagement, job satisfaction, leadership, training, learning, knowledge management, people management, safety management, entrepreneurship etc. She has 1 patent and 3 copyrights from the Government of India for her research work. She acts as a reviewer in international journals. Furthermore, she is a member of the AIMA, ACM, IS, SDIWC, and NIPM.
Bitan Misra is currently working as an Assistant Professor, in Dept. of CSE, Techno International New Town, Kolkata, India. She received her B. Tech and M. Tech dual degree in Electronics and Telecommunication Engineering from KIIT University, Bhubaneswar, India in 2018. She received her Ph.D. in 2022 from National Institute of Technology, Durgapur, India. She received a Gold Medal during her UG for securing the highest CGPA in the university. She has published many research papers in various international journals and conferences. Her main research interests include optimization techniques, deep learning, evolutionary algorithms and soft computing techniques. She has worked as a reviewer in several national and international journals and conferences.
This book explores the concept of employee engagement, which is crucial for a company's success, as it is closely linked to job satisfaction and employee morale. Engaged workers tend to be more productive, efficient, and committed to the values and objectives of the company. Artificial intelligence plays a significant role in HR analytics, particularly in automating tedious tasks like data collection and organization from multiple sources. AI-driven employee engagement software can analyze employee feedback, surveys, and social media posts to capture the overall sentiment of the workforce. This allows HR teams to gain insights into employee experiences and perceptions, uncover areas for improvement, and address any issues that require attention. By leveraging past data and employing machine learning algorithms, AI enables HR professionals to predict turnover rates, forecast employee engagement levels, and identify potential flight risks.
Introduction.- Importance of measuring employee engagement trends in organisations.- Employee engagement challenges.- Significance of Employee Engagement Levels in the Workplace.- Employee Engagement Models.- Artificial intelligence in employee engagement and retention.- Leveraging AI for Employee Engagement.- AI-powered analytics uncover hidden patterns in employee engagement data.- Predictive analytics: Anticipating future engagement trends with AI.- Ethical Considerations and Future Directions of AI in Employee Engagement.
This book explores the concept of employee engagement, which is crucial for a company's success, as it is closely linked to job satisfaction and employee morale. Engaged workers tend to be more productive, efficient, and committed to the values and objectives of the company. Artificial intelligence plays a significant role in HR analytics, particularly in automating tedious tasks like data collection and organization from multiple sources. AI-driven employee engagement software can analyze employee feedback, surveys, and social media posts to capture the overall sentiment of the workforce. This allows HR teams to gain insights into employee experiences and perceptions, uncover areas for improvement, and address any issues that require attention. By leveraging past data and employing machine learning algorithms, AI enables HR professionals to predict turnover rates, forecast employee engagement levels, and identify potential flight risks.
Produktdetaljer
Om bidragsyterne
Soumi Majumder is a research scholar of the Department of Business and Accounting in Lincoln University College, Malaysia. She is an assistant professor at Future Business School, Future Institute of Engineering and Management, Kolkata, India. Previously, she was associated with Sister Nivedita University, Techno India College of Technology, NSHM College of Management and Technology, J D Birla Institute of Science and Commerce, West Bengal State Labor Institute, Siliguri, DAITM and many more B Schools. She is an associate researcher at the Universidad Internacional de La Rioja, Logroño, La Rioja, Spain She is having 8 years of experience in academia and 2 years of industrial experience. She has 3 authored books from Springer Nature, 1 authored book from Taylor and Francis publisher, 1 authored book from Emerald publisher and 2 edited books and more than 25 research papers in national, and international conferences and journals in the area of quality work-life, decent work-life, work-life balance, stress management, employee engagement, job satisfaction, leadership, training, learning, knowledge management, people management, safety management, entrepreneurship etc. She has 1 patent and 3 copyrights from the Government of India for her research work. She acts as a reviewer in international journals. Furthermore, she is a member of the AIMA, ACM, IS, SDIWC, and NIPM.
Bitan Misra is currently working as an Assistant Professor, in Dept. of CSE, Techno International New Town, Kolkata, India. She received her B. Tech and M. Tech dual degree in Electronics and Telecommunication Engineering from KIIT University, Bhubaneswar, India in 2018. She received her Ph.D. in 2022 from National Institute of Technology, Durgapur, India. She received a Gold Medal during her UG for securing the highest CGPA in the university. She has published many research papers in various international journals and conferences. Her main research interests include optimization techniques, deep learning, evolutionary algorithms and soft computing techniques. She has worked as a reviewer in several national and international journals and conferences.