CEO succession and the CEO’s commitment to the status quo

Chief executive officer (CEO) commitment to the status quo (CSQ) is expected to play an important role in any firm’s strategic adaptation. CSQ is used often as an explanation for strategic change occurring after CEO succession: new CEOs are expected to reveal a lower CSQ than established CEOs. Although widely accepted in the literature, this relationship remains imputed but unobserved. We address this research gap and analyze whether new CEOs reveal lower CSQ than established CEOs. By analyzing the letters to the shareholders of German HDAX firms, we find empirical support for our hypothesis of a lower CSQ of newly appointed CEOs compared to established CEOs. However, our detailed analyses provide a differentiated picture. We find support for a lower CSQ of successors after a forced CEO turnover compared to successors after a voluntary turnover, which indicates an influence of the mandate for change on the CEO’s CSQ. However, against the widespread assumption, we do not find support for a lower CSQ of outside successors compared to inside successors, which calls for deeper analyses of the insiderness of new CEOs. Further, our supplementary analyses propose a revised tenure effect: the widely assumed relationship of an increase in CSQ when CEO tenure increases might be driven mainly by the event of CEO succession and may not universally and continuously increase over time, pointing to a “window of opportunity” to initiate strategic change shortly after the succession event. By analyzing the relationship between CEO succession and CEO CSQ, our results contribute to the CSQ literature and provide fruitful impulses for the CEO succession literature

Patterns of Subject Mix in Higher Education Institutions : A First Empirical Analysis Using the AQUAMETH Database

Teaching and research are organised differently between subject domains: attempts to construct typologies of higher education institutions, however, often do not include quantitative indicators concerning subject mix which would allow systematic comparisons of large numbers of higher education institutions among different countries, as the availability of data for such indicators is limited. In this paper, we present an exploratory approach for the construction of such indicators. The database constructed in the AQUAMETH project, which includes also data disaggregated at the disciplinary level, is explored with the aim of understanding patterns of subject mix. For six European countries, an exploratory and descriptive analysis of staff composition divided in four large domains (medical sciences, engineering and technology, natural sciences and social sciences and humanities) is performed, which leads to a classification distinguishing between specialist and generalist institutions. Among the latter, a further distinction is made based on the presence or absence of a medical department. Preliminary exploration of this classification and its comparison with other indicators show the influence of long term dynamics on the subject mix of individual higher education institutions, but also underline disciplinary differences, for example regarding student to staff ratios, as well as national patterns, for example regarding the number of PhD degrees per 100 undergraduate students. Despite its many limitations, this exploratory approach allows defining a classification of higher education institutions that accounts for a large share of differences between the analysed higher education institutions