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Research on organizational climate has tended to focus on independent dimensions of climate rather than studying the total social context as configurations of multiple climate dimensions. The authors examined relationships between configurations of unit-level climate dimensions and organizational outcomes. Three profile characteristics represented climate configurations: (1) elevation, of the mean score across climate dimensions; (2) variability, or the extent to which scores across dimensions vary; and (3) shape, of the pattern of the dimensions. Across 2 studies (1,120 employees in 120 bank branches and 4,317 employees in 86 food distribution stores), results indicated that elevation was related to collective employee attitudes and service perceptions, while shape was related to customer satisfaction and financial performance. With respect to profile variability, results were mixed. The discussion focuses on future directions for taking a configural approach to organizational climate. Keywords: organizational climate, employee attitudes, customer satisfaction, financial performance, climate configurations

Much research has examined gender and age effects on compensation, concluding that a wage gap exists favoring men and negative stereotypes against older workers persist. Although the effect of an employee's gender or age has been widely studied, little work has examined the impact of the demographic characteristics of a focal employee's immediate referent groups (e.g., subordinates, peers, or supervisors) on pay. The effect of the gender and age composition of a focal manager's subordinates, peers, and supervisor on the manager's compensation levels was investigated in a sample of 2,178 managers across a wide range of organizations and functional areas. After controlling for a number of human capital variables, results indicated that not only does a wage gap favoring men exist, but also managerial pay is lower when managers' referent groups are largely female, when subordinates are outside the prime age group, and when peers and supervisors are younger.

Two studies tested whether method variance is present at multiple levels of analysis and whether methodological procedures can minimize its impact. In Study 1, 8,052 employees from 71 hotels completed measures of climate, work environment characteristics, and satisfaction. A comparison of correlations at the individual level, cross-level, cross-level split, aggregate level, and aggregate-split level of analysis revealed that response bias was present across multiple levels. Results suggest that samples should be split in half when cross-level and aggregate correlations are computed to ameliorate response bias problems that arise from individual-level method variance. In Study 2, results indicated that the temporal spacing of measures of climate and satisfaction influenced response bias. Implications and recommendations for future research are discussed.

Meta-analytic procedures allow for determining best estimates of the individual-level, the within-organization, and the organizational-level population correlations. In most validity generalization work, meta-analytic procedures have been used to provide best estimates of the within-organization correlation. However, in many other organizational domains, researchers often do not clearly specify which population parameter is of interest. Further, researchers often combine studies in which data were collected at different levels of analysis or with mixed (single- and multiple-organization) sampling schemes, making it difficult to interpret unambiguously the meta-analytic (mathematical expression not reproducible in ASCII). The authors focus on how to make appropriate inferences from meta-analytic studies by integrating a levels-of-analysis framework with meta-analytic techniques, highlighting how meta-analytic procedures can aid researchers in better understanding multilevel relationships among organizational constructs. The authors provide recommendations for clearer specifications of populations and levels issues in future meta-analytic studies.

Researchers are often interested in comparing correlations between variables at different levels of analysis (e.g., individual and organizational) to determine if the same relationship holds across the levels. A special situation emerges when correlations at higher levels are based on aggregated data. This article contains an analysis of the nature of the relationship between correlations based on individual-level data and correlations based on aggregated data from individuals. In particular, the conditions under which differences between individual correlations and correlations based on aggregates represent statistical artifacts or meaningful differences are explored. (Reprinted by permission of the publisher.)

Previous research has consistently shown little relationship between job satisfaction, job attitudes, and performance for individuals, but little work has investigated these relationships at the organizational level of analysis. This study investigated the relationship between employee satisfaction, other job-related attitudes (commitment, adjustment, and psychological stress), and organizational performance. Organizational performance data were collected for 298 schools; employee satisfaction and attitude data were collected from 13,808 teachers within these schools. Correlation and regression analyses supported the expected relationships between employee satisfaction/attitudes and organizational performance. Implications of these findings are discussed. (Reprinted by permission of the publisher.)

Many practitioners measure the halo effect, the tendency of some evaluators to generate higher correlations between performance factors than reality suggests, by taking an average standard deviation across performance dimensions. This, however, does not really produce a clearer picture of the real correlations. The past use of this measure may have affected published studies on halo effects. In the future, psychologists should use each rater's average observed intercorrelation among dimensions to assess the halo effect.