Applying artificial intelligence technique to predict knowledge hiding behavior
| dc.contributor.author | Abubakar A.M. | |
| dc.contributor.author | Behravesh E. | |
| dc.contributor.author | Rezapouraghdam H. | |
| dc.contributor.author | Yildiz S.B. | |
| dc.date.accessioned | 2025-04-10T11:07:05Z | |
| dc.date.available | 2025-04-10T11:07:05Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | Drawing on psychological ownership and social exchange theories, this study suggests theoretical arguments and empirical evidence for understanding employee reactions to distributive, procedural, and interactional (in)justice — three crucial bases of employees’ feelings of social self-worth. Utilizing field data and artificial intelligence technique, this paper reveals that distributive, procedural, and interactional (in)justice contribute to higher levels of knowledge hiding behavior among employees and that this impact is non-linear (asymmetric). By reuniting the discourses of organizational justice and knowledge management, this study indicates that feelings of psychological ownership of knowledge and the degree of social interaction are mechanisms that work with organizational (in)justice to influence knowledge hiding behavior. The current research may inform contemporary theories of business research and provide normative guidance for managers. © 2019 Elsevier Ltd | |
| dc.identifier.DOI-ID | 10.1016/j.ijinfomgt.2019.02.006 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.14701/47163 | |
| dc.publisher | Elsevier Ltd | |
| dc.title | Applying artificial intelligence technique to predict knowledge hiding behavior | |
| dc.type | Article |