A framework is developed to parametrically evaluate networks under user equilibrium route guidance (UERG) and system optimal route guidance (SORG), assuming that the unguided traffic is in stochastic user equilibrium. The framework can determine in what condition an advanced traveler information system performs well and which route guidance state performs better as the market penetration of guidance systems increases. Unlike other studies that assumed a fixed number of compliant drivers, this study explicitly considers compliance rate as an endogenous variable in a general parametric nonlinear programming framework. Under endogenously determined compliance rate, SORG may result in a higher total system cost than UERG because of a lower compliance rate, even though SORG aims to minimize total system cost. In contrast, even though UERG is generally preferable because of higher acceptance, it may result in increased total system cost under certain conditions. A simple network is used to illustrate the application of the framework and show that the performance of route guidance is highly dependent on the level of unguided drivers' familiarity with the network. A significant part of the framework is the scheme to find "sustainable" compliance rates under assumed compliance function.