“Trust in embedded settings” investigates the mechanisms through which social networks influence decisions in trust problems. People often find themselves in situations in which they have to decide whether or not they trust someone else. The question asked is to what extent people use the information they obtain from their network to make this decision. They can learn about the trustworthiness of their partner through experience of others or, in certain circumstances, they can trust just because they see others do so. Furthermore, social networks provide opportunities to sanction untrustworthy behavior. If trust is abused, people can spread this information and in this way damage the reputation of those who abused trust. The three mechanisms described above are called: learning, imitation and control. Hypotheses concerning these mechanisms are derived from a wide range of theories and tested using a unique combination of complementary research methods: two laboratory experiments, a vignette experiment and a longitudinal survey. The empirical results show that actors use the information available to them in embedded trust problems primarily to learn about the trustworthiness of their partner. However, if this information is insufficient or too complex, people can look at what others have done in similar situations and just do the same. In theory, social networks should also provide people with opportunities to sanction their partner, informing others about his or her behavior, if he or she is not trustworthy. However, the results of this research show that people generally do not take these sanctioning opportunities into account when making their trusting decisions.
|Qualification||Doctor of Philosophy|
|Publication status||Published - 2005|