The number of connected products with intelligent functionalities being introduced to the market increases steadily. These smart products are perceived to possess a significant economic potential and their intelligence offers decision makers various new opportunities for product differentiation, the realization of new business models or the development of new products. From a marketing perspective, the emergence of smart products is also accompanied by new challenges, such as new barriers of adoption or the widely unknown willingness to pay for product intelligence. As a research focus, the chair of marketing addresses these new challenges of smart products.
Researchers have shown that the image of a brand is the most important driver of brand equity. As a multidimensional attitude construct, it is formed and developed by different branding activities. Due to this, measuring brand images is more difficult than measuring other effects of marketing activities (e.g., the increase or decrease of sales). At the same time, it is highly important for successful brand management. Against this background, our current research focuses on different approaches for measuring brand images. Furthermore, we investigate both the influence and the effects of branding activities (e.g., brand extensions, brand alliances) on brand images.
The individual buying behavior can be investigated both in qualitative and in quantitative respect. As a qualitatively oriented discipline, buying behavior research tries to obtain insights of how human beings are affected by their own personality as well as their social and economic environment regarding their buying and consumption behavior, and how they react to these impacts. As a quantitatively oriented discipline, and by applying suitable mathematical models, it contributes to the explanation and prediction of individual buying behavior. Thus it provides valuable hints for developing well-founded marketing strategies. The main interest of the research group is quantitative modeling of buying behavior.
Quantitative marketing research has experienced a considerable momentum in recent years and its fundamental relevance is hardly disputed today. The associated continuous advancement of already existing as well as the development of new methods, with a special focus on their applicability to real marketing problems, is a permanent challenge to marketing science. Members of our research group are currently concerned with the application and advancement of machine learning methods for data analysis, with the systematic treatment of missing values in marketing research, as well as the analysis of point-of-sale scanner data by means of data mining techniques. Further current fields of research concern the techniques for environmental scanning as well as for computer-based preference measurement.