Chunhong Guo
Biographic Data
| ID | 4682843 |
|---|---|
| NAME | Chunhong Guo |
| GIVEN NAMES | Chunhong |
| FAMILY NAME | Guo |
| SIGNATURE | GUO C |
| AFFILIATIONS | University of Science and Technology Liaoning |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
The double-edged sword effects of algorithmic opacity
Algorithmic opacity is mainly regarded as a disruptive feature. Although the literature suggests that algorithmic opacity improves efficiency, we need a thorough understanding of the contexts in which algorithmic opacity enhances efficiency and the behavioral responses that employees will have. The purpose of this study is to address this research gap. We construct structural equation models using data from 421 full-time employees interacting wit…
Algorithmic opacity and employees’ knowledge hiding
We explored the effects of algorithmic opacity on employees’ playing dumb and evasive hiding rather than rationalized hiding. We examined the mediating role of job insecurity and the moderating role of employee-AI collaboration. Participants were 421 full-time employees (female = 46.32%, junior employees = 31.83%) from a variety of organizations and industries that interact with AI. Employees filled out data on algorithm opacity, job insecurity, …
No prominent works on this page.
The double-edged sword effects of algorithmic opacity
Algorithmic opacity is mainly regarded as a disruptive feature. Although the literature suggests that algorithmic opacity improves efficiency, we need a thorough understanding of the contexts in which algorithmic opacity enhances efficiency and the behavioral responses that employees will have. The purpose of this study is to address this research gap. We construct structural equation models using data from 421 full-time employees interacting wit…
Algorithmic opacity and employees’ knowledge hiding
We explored the effects of algorithmic opacity on employees’ playing dumb and evasive hiding rather than rationalized hiding. We examined the mediating role of job insecurity and the moderating role of employee-AI collaboration. Participants were 421 full-time employees (female = 46.32%, junior employees = 31.83%) from a variety of organizations and industries that interact with AI. Employees filled out data on algorithm opacity, job insecurity, …
AI and HR Technologies (1 work) · AI in Service Interactions (1 work) · Applied Psychology (1 work) · Behavioral Health and Interventions (1 work) · Ethics and Social Impacts of AI (1 work) · Job insecurity (1 work) · Moderation (1 work) · Motivation and Self-Concept in Sports (1 work) · Psychology (1 work) · Social Psychology (1 work)