Purpose: This study investigates the role of personality disorders in the context of counterproductive knowledge behavior. Design/methodology/approach: Data were collected through a survey administered to 120 full-time employees recruited from Amazon’s Mechanical Turk. Personality disorders were measured by means of the Millon Clinical Multiaxial Inventory-IV. Findings: Personality disorders play an important role in the context of counterproductive knowledge behavior: employees suffering from various personality disorders are likely to hide knowledge from their fellow coworkers and engage in knowledge sabotage. Of particular importance are dependent, narcissistic and sadistic personality disorders as well as schizophrenic and delusional severe clinical syndromes. There is a need for a paradigm shift in terms of how the research community should portray those who engage in counterproductive knowledge behavior, reconsidering the underlying assumption that all of them act deliberately, consciously and rationally. Unexpectedly, most personality disorders do not facilitate knowledge hoarding. Practical implications: Organizations should provide insurance coverage for the treatment of personality disorders, assist those seeking treatment, inform employees about the existence of personality disorders in the workplace and their impact on interemployee relationships, facilitate a stress-free work environment, remove social stigma that may be associated with personality disorders and, as a last resort, reassign workers suffering from extreme forms of personality disorders to tasks that require less interemployee interaction (instead of terminating them). Originality/value: To the best of the authors’ knowledge, this work represents one of the first attempts to empirically investigate the notion of personality disorders in the context of knowledge management.
Serenko, A. (2023). Personality disorders as a predictor of counterproductive knowledge behavior: the application of the Millon Clinical Multiaxial Inventory-IV. Journal of Knowledge Management, 27(8), 2249–2282. https://doi.org/10.1108/JKM-10-2021-0796