Long working hours have been proven to damage employees’ physical and mental health and reduce social innovation performance and health costs. Particularly, the intelligent society, represented by the application of new technologies such as big data, the Internet of things, and artificial intelligence, is remolding the industrial landscapes. This kind of intelligent empowerment brings scientific decision-making and organizations' continuous upgrading and profoundly impacts the working environment and employees' workplace experience by requesting higher quantity and quality of employees' working hours.
On the one hand, the construction of an intelligent society blurs the boundary between the organization and the employees, which prolongs individuals’ working hours through the invasion of the work into life, thus leading to negative work experiences, such as work-life conflict, and job burnout. Furthermore, the application of intelligent technology transfers works offline to online, affecting employees' perception of positive psychological resources, such as organizational ownership and support. On the other hand, the rhythm of high-speed competition and consumption constantly stimulates employees to extend working hours to gain a competitive advantage, learn new skills, or obtain remuneration.
Why work overtime? What will an intelligent society bring to employees’ work intentions? The main purpose of this research topic is to explore the psychological mechanism of long working hours from the perspective of an intelligent society. We are particularly interested in studies that focus on work behavior related (but not limited) to the following:
1. Motivation of employees' long working hours.
2. Employees’ attitudes toward long working hours
3. Influence of boundary characteristics of work and life on employees' psychological resources
4. Consequences of overtime work brought by intelligent society on employees' work performance and mental health
5. Changes in interpersonal relationships brought by intelligent society
Long working hours have been proven to damage employees’ physical and mental health and reduce social innovation performance and health costs. Particularly, the intelligent society, represented by the application of new technologies such as big data, the Internet of things, and artificial intelligence, is remolding the industrial landscapes. This kind of intelligent empowerment brings scientific decision-making and organizations' continuous upgrading and profoundly impacts the working environment and employees' workplace experience by requesting higher quantity and quality of employees' working hours.
On the one hand, the construction of an intelligent society blurs the boundary between the organization and the employees, which prolongs individuals’ working hours through the invasion of the work into life, thus leading to negative work experiences, such as work-life conflict, and job burnout. Furthermore, the application of intelligent technology transfers works offline to online, affecting employees' perception of positive psychological resources, such as organizational ownership and support. On the other hand, the rhythm of high-speed competition and consumption constantly stimulates employees to extend working hours to gain a competitive advantage, learn new skills, or obtain remuneration.
Why work overtime? What will an intelligent society bring to employees’ work intentions? The main purpose of this research topic is to explore the psychological mechanism of long working hours from the perspective of an intelligent society. We are particularly interested in studies that focus on work behavior related (but not limited) to the following:
1. Motivation of employees' long working hours.
2. Employees’ attitudes toward long working hours
3. Influence of boundary characteristics of work and life on employees' psychological resources
4. Consequences of overtime work brought by intelligent society on employees' work performance and mental health
5. Changes in interpersonal relationships brought by intelligent society
