| Title |
Feature Based Statistical Model of Employee Productivity with Real Time Checked Data |
| ID_Doc |
70576 |
| Authors |
Shanmugalingam, J; Lario, D; Ma, YS |
| Title |
Feature Based Statistical Model of Employee Productivity with Real Time Checked Data |
| Year |
2021 |
| Published |
|
| DOI |
10.1109/IEEM50564.2021.9672783 |
| Abstract |
The COVID-19 pandemic has led to a decentralization of the workforce in many industries. Due to the stay-at-home orders to control the spread of the virus, many are working from home. Even though modern technological advancements have helped some companies adapt to this new norm, many others are still scrambling to find the best way to remotely manage employees and accommodate their needs. Our research shows that the current challenges organizations face in managing their human capital are like the ones they face due to workplace demographic changes. This study focuses on analyzing those challenges and how human competency can be unlocked and developed to encourage sustainable autonomous working in an office, at home, or during frequent traveling. This study investigates the challenges faced by both organizations and employees, and presents a new business model that helps with the sustainable use of human resources and improves employee efficiency. |
| Author Keywords |
Sustainable autonomous work; Weibull distribution; PERT; Statistical performance modeling; real-time efficiency data; Manpower management |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000821855600179 |
| WoS Category |
Engineering, Industrial; Operations Research & Management Science |
| Research Area |
Engineering; Operations Research & Management Science |
| PDF |
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