A platform needs to have sufficient market potential, represented by the number of users who can join a platform. Platform openness affects the ease of actors joining the platform. Hence, in order to increase the chances of platform success, platforms want to maximize market potential and consequently also platform openness. This is problematic because architectural configurations with the highest market potential do not necessarily represent the most favourable configurations for societal values. Although there is anecdotal evidence of safety and privacy risks resulting in adjusted platform openness, there is little literature explaining the drivers and the process of adjusting due to risks posed to societal values. Hence, this thesis build an initial theory on the process of how digital platforms adjust their openness upon learning about risks for societal values. A case study was performed to pattern match theoretical concepts in a critical case. The study found that concepts of organizational legitimacy, double-loop learning and background theories may explain how a digital platform sponsor adjusts openness due to societal risks. In addition, empirical findings suggest that organizational maturity may affect platform openness. Nonetheless, it was inconclusively found whether societal risks cause a change in the value system of the platform. This research found that the identification of a societal risk may change the theories-in-use of a digital platform and subsequently affect platform openness.