Trait and/or situation for evasive knowledge hiding? Multiple versus mixed-motives perspective of trait competitiveness and prosocial motivation in low- and high-trust work relationships

ABSTRACT

Evasive knowledge hiding (EKH) is a behavioural phenomenon with important personal and organizational implications, whose intraindividual motivational antecedents and situational contingencies are still not sufficiently clarified. In this paper, we integrate mixed-motives and trait-activation theory to address EKH in low- and high-trust work relationships. The focus is on complex interactions of trait competitiveness and prosocial motivation while responding to a knowledge-seeking request by a (dis)trusted colleague. Our findings based on three mixed-methods studies (two factorial survey field studies and one quasi-experimental student-based study) provide general evidence of the overwhelmingly positive effect of trait competitiveness (i.e., pro-self motives) on EKH across situations. Additionally, we found that if competitive individuals are also prosocially motivated, their “paradoxical personality” will manifest in less EKH behaviour, especially if situational trust cue is positive. Implications for research and practice are discussed.

KEYWORDS:

• evasive knowledge hiding
• trait competitiveness
• prosocial motivation
• trust
• mixed motives
• trait-activation theory

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. KH is a construct broadly understood as antonym of knowledge sharing (i.e., knowledge collection and donation) yet, these constructs have different motivational antecedents. For instance, lack of sharing does not necessary represent hiding. However, KH is much closer to knowledge withholding and knowledge hoarding. While withholding knowledge represents an umbrella term that likewise differs from non-sharing, an important distinction between hiding and hoarding as respective subtypes is that the latter is less intentional, that is, knowledge holder conceals his or her unrequested knowledge.

2. Situation strength is a degree to which the situation induces one to behave a certain way, despite personal tendencies (Tett & Guterman, 2000).

3. We used aggregated variables to calculate descriptives for latent variables.

4. Models 2 and 5 also included prosocial motivation and selected control variables.

5. Because we had missing data in our dataset, we adopted the full information maximum likelihood (FIML) approach in Mplus 8.0.

6. For example, we gave student A specific information about relevant qualifications (e.g., education level and skills) that the candidate would need to get this job. On the other hand, we gave student B specific information about the company and description of the job (e.g., in which sector the company operates, its ongoing projects) the individual is applying to.

7. Alternative models did not have theoretical backing to begin with, yet were tested if potentially more parsimonious models exhibited better fit; i.e., with prosocial motivation and trait competitiveness items loaded on the same factor [low- (χ2/df = 316.46/65; RMSEA .14; CFI .75) and high-trust EKH targets (χ2/df = 352.66/65; RMSEA .15; CFI .72) within the focal university; as well as for low- (χ2/df = 324,40/65; RMSEA .14; CFI .76) and high-trust EKH targets (χ2/df = 323.06/65; RMSEA .14; CFI .74) outside the focal university]; with KH and prosocial motivation items loaded on the same factor [low- (χ2/df = 520.67/65; RMSEA .18; CFI .58) and high-trust EKH targets (χ2/df = 450.55 /65; RMSEA .17; CFI .61) within the focal university; as well as for low- (χ2/df = 419.41/65; RMSEA .16; CFI .64) and high-trust EKH targets (χ2/df = 459.76/65; RMSEA .17; CFI .60) outside the focal university]; with trait competitiveness and KH items loaded on to the same factor [low- (χ2/df = 261.98/65; RMSEA .12; CFI .81) and high-trust EKH targets (χ2/df = 238.99/65; RMSEA .11; CFI .83) within the focal university; as well as for low- (χ2/df = 260.83/65; RMSEA .12; CFI .80) and high-trust EKH targets (χ2/df = 282.34/65; RMSEA .13; CFI .78) outside the focal university]. All exhibited significantly (p < .01) poorer fit.

8. We report aggregated mean values for the latent variables.