I am a social scientist working with data. My core research interest is pro-social behavior. I study its underlying motivations (e.g. reciprocity, moral emotions, self-, and social-image concerns) as well as its potential for improving market allocations. Crowdfunding, a recently emerged alternative funding channel for entrepreneurial activities, is a particular focus of mine. For my analysis I employ laboratory or field experiments as well as big data sets from online sources.
PhD in Economics, 2004
University of Bristol, UK
Diploma in Economics, 2000
University of Munich, Germany
Crowdinvesting emerged recently as an alternative way of funding for start-up projects. Our dataset consists of 16,666 investments made at Companisto, one of the largest crowdinvesting platforms in Europe. Using cluster analysis based on individual investment decisions, we find that crowdinvestors differ in their investment strategies and motivations. We can distinguish three types of crowdinvestors: Casual Investors, Crowd Enthusiasts, and Sophisticated Investors. The types also vary in their response to project quality signals, project-related information reducing the degree of uncertainty, and social influence by fellow investors. We conclude that crowdinvestors are anything but a homogeneous group. Instead, they are motivated by different factors and respond to different signals when making investment decisions.
A candidate explanation for the persistence of heterogeneous behavior in a sequential social dilemma played many times is the existence of heterogeneous preferences. Preferences-dependent conjectures about opponents’ behavior are an additional source of heterogeneity. By behaving differently, different preference types acquire different information. Thus, when observing only outcomes of own past interactions heterogeneous and possibly wrong conjectures about opponents’ strategies may endogenously arise and persist. In a Centipede game experiment played for forty rounds, we manipulate the type of ex post information and the method of play. We find that, when the game is played in its reduced normal form and subjects have only access to personal statistics, heterogeneity of behavior across preference types persists in the long run. In this case, behavior resembles a self-confirming equilibrium: selfish subjects take at earlier nodes due to an unjustified lack of trust. When subjects have also access to public statistics, heterogeneity disappears: selfish subjects tend to pass more often and play moves towards Bayes Nash equilibrium.
Motivated agents are characterized by increasing their effort, if their work generates not only a monetary return for them but also a benefit for a mission they support. While their motivation may stem from working for their preferred (i.e., the ‘right’ mission, it may also be the principal’s choice of the right mission (i.e., a mission preference match) that motivates them. We investigate experimentally to what extent these two motivations are driving the effect of a mission on agent effort. We find that agents mostly care about whether the principal shares their mission. It seems that the full potential of ‘motivation by mission’ is realized only when principals share as well as support the agents’ mission, stressing the importance of identity aspects in labor market settings.