Seit Jahrzehnten weist die Forschung unermüdlich auf die Vorteile transformationaler Führung hin. Statt über einen Austausch von Leistung und Gegenleistung oder über Belohnung und Bestrafung zu motivieren, rückt die Führungskraft dabei ein erstrebenswertes, grösseres Ziel ins Zentrum ihrer Bemühungen. Über die operativen Aufgaben hinaus vermittelt sie so ein Sinnangebot, das die Emotionen anspricht, die Arbeit im besten Sinne transformiert und mit einer umfassenderen Idee verbindet. Wissenschaftler haben die positive Wirkung dieses Führungsstils für Leistung und Zufriedenheit von Mitarbeitern inzwischen in vielen Untersuchungen nachgewiesen.
Doch so einfach ist die Sache nicht.
In this paper, we analyze whether structured PhD programs operate at optimal size and whether there are differences between different disciplinary fields. Theoretically, we postulate that the relation between the size of a PhD program and program performance is hump shaped. For our empirical analysis, we use hand-collected data on 86 Research Training Groups (RTGs) funded by the German Research Foundation (DFG). As performance indicators, we use (a) the number of completed PhDs and (b) the number of publications by RTG students (PhD students and postdoctoral researchers). Applying DEA with constant and variable returns to scale, we find that the optimal team size varies between 10 and 16 RTG students in the humanities and social sciences. In contrast, our empirical analysis does not uncover a systematic relation between size and performance for RTGs in the natural and life sciences.
Firms generate new knowledge that leads to innovations by recombining existing knowledge sources. A successful recombination depends on the availability of a knowledge stock (human capital pool) and the flow of knowledge within the firm (induced by HRM systems). While human resource theory expects complementarities between human capital pools and HRM systems, it does not explicitly address how knowledge exchange may be guaranteed or fostered. Moreover, empirical approaches neglect the complexity of such complementarities. In this study we develop a model that integrates a firm's knowledge stock and flow into a knowledge creation (KC) system comprising four ideal types. This system explains the occurrence of superior incremental innovation performance. We empirically analyze the KC system by applying fuzzy set qualitative comparative analysis (fsQCA) and identify configurations concurring with our ideal types. The results show that the use of human capital and HRM practices depends on firm size and industry dynamism.
