A long‐standing debate has focused on the extent to which different levels of analysis shape firm performance. The strategic group level has been largely excluded from this inquiry, despite evidence that group membership matters. In this study, we use hierarchical linear modeling to simultaneously estimate firm‐, strategic group‐, and industry‐level influences on short‐term and long‐term measures of performance. We assess the three levels' explanatory power using a sample of 1,165 firms in 12 industries with data from a 7‐year period. To enhance comparability to previous research, we also estimate the effects using the variance components and ANOVA methods relied on in past studies. To assess the robustness of strategic group effects, we examine both deductively and inductively defined groups. We found that all three levels are significantly associated with performance. The firm effect is the strongest, while the strategic group effect rivals and for some measures outweighs the industry effect. We also found that the levels have varying effects in relation to different performance measures, suggesting more complex relationships than depicted in previous studies. Copyright © 2007 John Wiley & Sons, Ltd.

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DICTION is a computer-aided content analysis program grounded in a number of theoretical bases in linguistic research. DICTION has a number of attractive features that could be used to analyze unique elements of language in narrative texts germane to strategic management research. The authors apply the DICTION software to a sample of mission statements from 408 Association to Advance Collegiate Schools of Business colleges of business with a focus on gaining insights concerning how DICTION can be used in strategic management research utilizing content analysis. They find significant differences in word usage in mission statements based on organizational characteristics, including business school performance. They conclude with suggestions for future research.

The authors empirically examine differences between automatic and controlled processing by executives in an increasingly dynamic industry. The results suggest that cognitive inertia affects judgments in both modes, but the effect is stronger with automatic processing. Specifically, the authors conducted two studies examining executives' cognitive maps of competitive positioning. First, they explored differences in ways strategists categorize competitors in a cross-sectional field study conducted during a period of significant environmental upheaval. They found that managers relied on cognitive maps that reflected obsolete industry boundaries rather than configurations representative of the deregulated marketplace. Hence, managers must be mindful to incorporate new information proactively from many sources and to actively discard old, automatic maps in order to develop reliable maps for changing environments. In a second study, managerial competitive schemas of competitive positioning were compared longitudinally across three research projects conducted in the financial intermediary industry. An eight-year time frame provided a unique opportunity to explore the content of mental models in an industry undergoing an accelerating rate of change. The longitudinal results indicate that change creates diversity of thought across managers in the same environment. Managers at competing firms are therefore apt to view competition quite differently in turbulent environments. Implications of the study findings for strategic decision making, consensus and conflict, and organizational learning and executive succession in turbulent environments are discussed. Issues are identified that warrant further research.

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Both business commentators and scholarly researchers have acknowledged the key role that top management teams (TMTs) play in reversing the fortunes of failing firms. Nonetheless, relatively few empirical studies have investigated the importance of TMTs in turnaround situations. To encourage such studies, we draw upon the multiple theories employed in TMT research as a guide to review studies that have examined how TMTs formulate and implement turnaround strategies. Based on this review, we highlight TMT topics that have received limited attention in the turnaround literature and, thus, represent opportunities for future research. We conclude by discussing methodological issues that should be considered when examining a TMT's role in a turnaround situation.

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