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Measurement and Management of Chief Executive Reputation


Richard Rinkenburger

Whereas the importance of CEO reputation has increased over the last years, only very little scientific research has been conducted. This thesis addresses the vagueness of past conceptualizations by providing a well-founded theoretical background, the development of a reliable and valid measurement model of CEO reputation as well as the validation of identified relations to its antecedents and consequences. An empirical online study was conducted among students of the university in Munich to validate the CEO reputation model. Using PLS path modeling, the analysis provides evidence for the impact of CEO reputation on several outcome variables (e.g., corporate reputation) and confirms different influences of the identified antecedents on CEO reputation. Thereby, practitioners can get valuable implications for the management of chief executives’ reputations.


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- latent variable in a reflective measurement model - latent variable in a formative measurement model x - vector of the manifest indicators x - weighting vector of the manifest indicators x in the reflective mode x - weighting vector of the manifest indicators x in the formative mode , - path coefficients - vector of the error terms of the manifest indicators x - error term of the latent variable rij - correlation coefficient between variable i and variable j

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