Reciprocal Relationships between Leader–Member Exchange (LMX) and Job Satisfaction: A Cross‐Lagged Analysis

While previous research has mainly emphasised the importance of leader–member exchange (LMX) to job satisfaction, there is a lack of research on reciprocal relationships between job satisfaction and LMX. In this study, we not only suggest that good LMX increases job satisfaction, but that job satisfaction can also enhance high‐quality supervisor–employee relationships. A full cross‐lagged panel analysis was used to test reciprocal relationships between LMX and job satisfaction. Employees (N= 279) of a large information technology company filled out questionnaires at two times, with a time lag of 3 months. In line with our predictions, findings revealed a positive relationship between LMX and job satisfaction both at Time 1 and Time 2. Moreover, LMX at Time 1 predicted the increase of job satisfaction at Time 2, and job satisfaction at Time 1 predicted the increase of LMX at Time 2. The results demonstrate the need to consider reciprocal relationships between job satisfaction and LMX when explaining employees' workplace outcomes. Our findings are discussed in terms of positive psychology theory.     

Hierarchical classes: Model and data analysis

A discrete, categorical model and a corresponding data-analysis method are presented for two-way two-mode (objects × attributes) data arrays with 0, 1 entries. The model contains the following two basic components: a set-theoretical formulation of the relations among objects and attributes; a Boolean decomposition of the matrix. The set-theoretical formulation defines a subset of the possible decompositions as consistent with it. A general method for graphically representing the set-theoretical decomposition is described. The data-analysis algorithm, dubbed HICLAS, aims at recovering the underlying structure in a data matrix by minimizing the discrepancies between the data and the recovered structure. HICLAS is evaluated with a simulation study and two empirical applications.This research was supported in part by a grant from the Belgian NSF (NFWO) to Paul De Boeck and in part by NSF Grant BNS-83-01027 to Seymour Rosenberg. We thank Iven Van Mechelen for clarifying several aspects of the Boolean algebraic formulation of the model and Phipps Arabie for his comments on an earlier draft.     

Understanding the central processing limit in consistent-mapping visual search tasks

Effects of load (i.e., the number of stimuli in the display) have been observed in multiple-frame studies using a consistent mapping of stimuli to responses (e.g., Fisher, 1982, 1984). In a series of four experiments, it is shown that these effects are not the consequence of differences across the high- and low-load conditions in either decision noise or peripheral masking. Additionally, it is shown that of two modes of limited capacity (a limited-channel and divided-capacity model) considered as possible explanations of load effects in tasks where subjects are required to locate a target, only one--the limited-channel model--is consistent with the results from all three location tasks. Finally, it is argued that the limited-channel model predicts not only the behavior observed in the four consistent-mapping experiments reported in this article but also the behavior observed in several related consistent-mapping tasks (Kleiss & Lane, 1986; Shiffrin & Gardner, 1972).