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Gamification and Predictive Analytics for the Next Generation of Workers
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- Author / Creator
- Jalaja Shanmugalingam
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In this era of a new industrial revolution known as Industry 4, it is important for a company to determine ways to satisfy employees’ needs and companies’ needs simultaneously. This is the key to keep employees focused, engaged, motivated, and involved with their jobs. It would help companies stay competitive, as well as recruit and retain talent. The future of employee motivation is to take advantage of gamification elements using machine learning and a statistical model that have dominated social media and gaming applications. The implementation of psychological theories in the study of gamification has played an important role in our digital lives as multiple social media and gaming apps compete to harness user engagement to stay popular and relevant. A review of psychological theories that induce extrinsic and intrinsic motivations in the workplace, as well as the current applications of game elements in a non-gamified environment, are included in this research. Following that, a modified gamified model is developed in this research that uses real time data, Weibull statistical distribution, a K-means clustering algorithm, and machine learning along with a reward system that would help increase skill development and retention along with employee satisfaction.
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- Graduation date
- Fall 2019
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- Type of Item
- Thesis
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- Degree
- Master of Science
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- License
- Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.