Research

The overarching theme of our research and teaching is sports governance. We thus explore incentive, monitoring, and enforcement systems in sports as a social, economic, and political phenomenon. In doing so, we aim to make scholarly contributions to positive sports development and balanced sports diversity. Our focus is on organizational and governance issues in the allocation of resources in sports among the state, the market, and the nonprofit third sector of so-called “organized sports,” comprising sports clubs and associations. In our empirical research, we address questions of sports organization, sports policy, and strategic sports management—ranging from recreational and grassroots sports to elite and professional sports.

A cross-cutting theme within the framework of sports governance is the management of sporting events. In the wake of the so-called “eventization” of society, sporting events are both a result and an instrument of sports development, and are also linked to economic and political interests. The management of sporting events poses a challenge for the sports system and increasingly requires academic expertise. Our research therefore focuses on the assessment and governance of the socioeconomic impacts of major sporting events.

Methods

Our research approach is based on fundamental theories of modern microeconomics (particularly institutional economics) and public finance. Our research designs focus on real-world market imperfections—which are characteristic of most sports markets—and which require appropriate regulatory and governance systems to enhance efficiency and ensure distributive justice in resource allocation. Depending on the specific subject of study within the field of sports, management, socio-economics, and political economy offer helpful analytical frameworks that also incorporate concepts from business administration and/or the social sciences. From these heterodox theoretical frameworks, we derive our problem-specific empirical models, which are econometrically tested using (sometimes large-scale) survey data or custom-compiled secondary data sets. Occasionally, we also use mixed-methods designs that combine expert interviews with quantitative analyses, or simulation models for forecasting studies (e.g., cost-benefit analyses or financial risk analyses).

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