Social networks are currently gaining increasing impact especially in the light of the ongoing growth of web-based services like facebook.com. A central challenge for the social network analysis is the identification of key persons within a social network. In this context, the article aims at presenting the current state of research on centrality measures for social networks. In view of highly variable findings about the quality of various centrality measures, we also illustrate the tremendous importance of a reflected utilization of existing centrality measures. For this purpose, the paper analyzes five common centrality measures on the basis of three simple requirements for the behavior of centrality measures.

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In the last years, customer centricity has turned out to be a promising paradigm for maximizing corporate value by increasing value contributions from customers. In this context, the discipline of revenue management provides plenty of methods to optimize (predominantly short-term) cash-inflows from customers. However, the paradigm of a value-oriented management requires the integration of perspectives from revenue management and customer relationship management: When controlling scarce, inflexible capacity, the effects of the acceptance or denial of a customer request on the value of a customer for the enterprise have to be considered. Hence, this paper proposes a model for a customer lifetime valueoriented capacity control by allocating scarce resources to products for different customer segments combining methods from both revenue management and customer relationship management -termed CR²M. The model presented in this paper at the same time allows a transparent calculation of opportunity costs caused by a short-term oriented control mechanism. In order to illustrate the applicability of the model, a company of the semiconductor industry serves as example.

In light of the growing relevance of customeroriented business strategies IT investments in the field of Customer Relationship Management have increased considerably. However, firms often could not realize sufficient returns on these IT investments. One major reason for this failure seems to be the lack of appropriate approaches to determine the economic impact of such investments ex ante. Therefore, we develop an economic model to determine the optimal level of Customer Relationship Management IT investments. Using this approach, firms can evaluate, to what extent investments in Customer Relationship Management IT are reasonable. One major result is that in most cases the "all or nothing strategy" pursued by many firms does not lead to the optimal level of investments. To illustrate the practical utility and applicability of the approach, we provide a real world example of a German financial services provider.