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Conjoint Analysis based Predictive Analytics to study the employee attitude towards virtual and digital work practices in IoT work environments

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dc.contributor.author Nagpal, Gaurav
dc.contributor.author Nagpal, Ankita
dc.contributor.author Jasti, Naga Vamsi Krishna
dc.date.accessioned 2023-05-17T10:59:09Z
dc.date.available 2023-05-17T10:59:09Z
dc.date.issued 2023-02
dc.identifier.uri https://ieeexplore.ieee.org/abstract/document/10100481
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/10901
dc.description.abstract Covid-19 has been one of the most disruptive pandemics to date. Among the other aspects of disruption, it also disrupted the way people work in organizations. Many of the organizations surrendered their offices for good. However, there are many ill effects of these unconventional work practices also. This research study aims to explore the perception of the employees towards the adoption of Virtual and flexible work practices. The study uses a conjoint analysis approach on different possible Work Practice Profiles, that specify the nature of work (Virtual, offline, or hybrid), nature of work schedule (flexible, or fixed), nature of ownership (individual, or team), and length of working hours (8.5 hours, or 9.5 hours or 10.5 hours). The study finds that the number of working hours is the most important criterion for the employees followed by mode of work, responsibility, and work schedule. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Management en_US
dc.subject Virtual work en_US
dc.subject Flexible work en_US
dc.subject Working hours en_US
dc.subject Work-life balance en_US
dc.subject Work practice profiles en_US
dc.title Conjoint Analysis based Predictive Analytics to study the employee attitude towards virtual and digital work practices in IoT work environments en_US
dc.type Article en_US


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