As an important part of the sharing economy, the usage of car sharing increases world widely with the help of developments in the technology. Especially after COVID-19 the demand for private car ownership and car sharing systems increased tremendously. Therefore, its market share attracts new investors and causes existing service providers to enlarge their service area. In this article, a novel multi-objective location-dependent two-stage stochastic optimization model is proposed to determine the most appropriate locations for car sharing system and allocate the demand to these locations. The model is applied to determine the best locations among 15 candidates, and three objectives are considered, which are the minimization of total cost that comprises locating costs minus income from satisfying the demand, minimization of CO$_2$ emission occurs by the usage of car sharing system's cars and minimization of average unsatisfied demand. Both location-independent and location-dependent demands are taken into account. The proposed model delivers a more precise decision process framework for problems include stochasticity and multiobjectivity, and it easily can be implemented to any region, providing region sensitive parameters.