Analytics Predictive for HRM: Using Machine Learning to Improve Workforce Scheduling and Staff Engagement-Reference-Cited by-同舟云学术

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Analytics Predictive for HRM: Using Machine Learning to Improve Workforce Scheduling and Staff Engagement

Published:2024-03-22 Issue: Volume:7 Page:1-6
ISSN:
Container-title:2024 International Conference on Trends in Quantum Computing and Emerging Business Technologies
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Author:

Rajyalaxmi M.¹,Vijai C.²,Lourens Melanie³,Chatterjee Biswas Prasanta⁴,Jahnavi K. N.⁵,U Umesh⁶

Affiliation:

1. School of Business, SR University,Warangal,Telangana,India

2. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology,Department of Commerce and Business Administration,Chennai,India,62

3. Durban University of Technology,Deputy Dean Faculty of Management Sciences,South Africa

4. CDOE, Parul University,Vadodara

5. SIndhi Institute of Management,Bangalore

6. Amal College of Advanced Studies (Aided by Govt. of Kerala & Affiliated to University of Calicut) Myladi,Department of Commerce and Management Studies,Nilambur,Kerala,679329

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10543254/10545024/10545077.pdf?arnumber=10545077

Reference15 articles.

1. Workforce scheduling efficiency increasing: The case study company;INSWANG

2. Workforce scheduling: A new model incorporating human factors

3. Workforce Management and Scheduling Under Flexible Demand

4. Optimized Workforce Scheduling in Bus Transit Companies

5. Development of employee engagement measure: experiences from best companies to work for in India

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