Employee–supervisor political skill congruence and work outcomes: The mediating role of leader–member exchange quality

This study aims to investigate the effect of employee–supervisor political skill congruence on the quality of leader–member exchange (LMX), which in turn influences employees' job satisfaction and turnover intention. For this purpose, two survey studies were conducted. The first study examined the relationship between employee–supervisor political skill congruence and LMX using multi-source data collected from 287 employee–supervisor dyads. The second study examined the indirect effect of congruence in political skill on work outcomes through LMX by using time-lagged multi-source data collected from 142 employee–supervisor dyads. The findings indicate that compared with incongruence, congruence in political skill is associated with higher employee-rated LMX. Moreover, among dyads with congruent political skills, congruence at high levels of political skill is associated with higher employee-rated LMX compared with congruence at low levels of political skill. Moreover, in case of incongruency, low employee–high supervisor political skill combination was related to higher supervisor-rated LMX compared with high employee–low supervisor political skill combination. Lastly, employee–supervisor political skill congruency indirectly influences job satisfaction and turnover intention through employee-rated LMX. This research significantly contributes to the political skill literature by examining potential consequences of employee–supervisor congruence in political skill in the workplace.     

Perceptual Categorization: Connectionist Modelling and Decision Rules

Although it is currently popular to model human associative learning using connectionist networks, the mechanism by which their output activations are converted to probabilities of response has received relatively little attention. Several possible models of this decision process are considered here, including a simple ratio rule, a simple difference rule, their exponential versions, and a winner-take-all network. Two categorization experiments that attempt to dissociate these models are reported. Analogues of the experiments were presented to a single-layer, feed-forward, delta-rule network. Only the exponential ratio rule and the winner-take-all architecture, acting on the networks' output activations that corresponded to responses available on test, were capable of fully predicting the mean response results. In addition, unlike the exponential ratio rule, the winner-take-all model has the potential to predict latencies. Further studies will be required to determine whether latencies produced under more stringent conditions conform to the model's predictions.