Cognitive diversity has been shown to positively affect team performance, especially in the early stages of strategic planning. We report on a process that explicitly identifies cognitive factions; sub-groups of individuals with diverse views and beliefs within a top management team (TMT). Our group-driven causal mapping process provides greater clarity to understanding the underlying belief structures of the cognitive factions through the adoption of givens-means-ends (GME) and casual path analysis. We achieve this clarity by having members of the TMT define and agree on the strategic factors before they construct their individual cause maps. Through this process, based on the relationships shared among the team members, we can readily merge individual cause maps into cognitive faction maps. By employing GME and casual path analysis to the cognitive faction maps, we can surface the differences in beliefs among the different cognitive factions within the TMT. We demonstrate our process using a 13-person TMT from an information technology services firm. The cause maps of the cognitive factions directly represent some of the issues and assumptions that need to be discussed and debated among the members of the TMT, thus increasing the potential for cognitive faction beliefs to enhance decision-making. We also find that cognitive factions relate to task roles of the team members, providing further evidence that different beliefs develop in different areas of the organization.
Empirical tests have produced mixed support for a membership-performance link in strategic groups, perhaps due to incomplete treatment of industry forces. We argue that strategic group concept is more useful for explaining performance differences among firms in some industries (where conditions favour conformity in firm conduct) than others. Using three industry structure constructs as criteria, 47 four-digit SIC industries are classified into 'conforming' or 'non-conforming' industry samples. Firms are then clustered into strategic groups in a separate treatment for each sample. Performance differences among groups are tested under conforming and non-conforming industry conditions. Tests confirm membership effects on ROA and ROE are significantly stronger in 'conforming' industries, where stronger regression relationships between conduct variables and performance also obtain.
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