This article brings together three current themes in organizational behavior: (1) a renewed interest in assessing person-situation interactional constructs, (2) the quantitative assessment of organizational culture, and (3) the application of “Q-sort,” or template-matching, approaches to assessing person-situation interactions. Using longitudinal data from accountants and M.B.A. students and cross-sectional data from employees of government agencies and public accounting firms, we developed and validated an instrument for assessing person-organization fit, the Organizational Culture Profile (OCP). Results suggest that the dimensionality of individual preferences for organizational cultures and the existence of these cultures are interpretable. Further, person-organization fit predicts job satisfaction and organizational commitment a year after fit was measured and actual turnover after two years. This evidence attests to the importance of understanding the fit between individuals' preferences and organiza...

Our hypotheses were that the influence of chief executive officers (CEOs) over boards of directors and the likelihood that the CEOs' compensation packages will reflect their preferences increase wi...

A study of the flow of information about organizational problems was conducted. We found that managers often avoided passing problems to formally designated problem solvers and used personal ties to forward information to problem solvers. The strength of ties between individuals had a weak effect on passing problems across professional boundaries.

A study of the flow of information about organizational problems was conducted. We found that managers often avoided passing problems to formally designated problem solvers and used personal ties to forward information to problem solvers. The strength of ties between individuals had a weak effect on passing problems across professional boundaries.

Theoretical models concerning technology-structure relationships typically are limited to one technology variable, one structure variable, and one contingency variable. This study draws on three decades of technology-structure research to develop and test more encompassing and potentially more valid models. Contrary to the most common explanations of mixed results on technology-structure relationships, the results of our meta-analytic theory testing indicate that the use of different definitions of technology and variation in organizational size generally do not affect these relationships. The results also indicate that two previously neglected contingency variables, professionalization and industrial sector, generally do not affect technology-structure relationships, but two methods variables, industrial sector heterogeneity and the size of the units of analysis, do affect them.