Location-based services (LBS) are increasingly combined with new forms of mobile and ubiquitous based computing such as music players, cameras, email and internet access, and thousands of other mobile applications (a.k.a., “apps”). LBS features present both new and interesting benefits as well as new forms of privacy risk. Recent headlines have brought attention to the enormous privacy information available to mobile application developers and providers such as Apple and Google. As risks and benefits increase in LBS apps, it is unknown how users tradeoff between these converged risks and benefits — particularly in the market for mobile apps. This paper uses a unique theoretical model based on privacy calculus and network theory to empirically examine the effects of the risk/benefits tradeoff on the adoption of new and emerging forms of LBS apps. Through two experiments involving 1588 mobile application users, we examine how institutional privacy assurances — including app quality and network size — influence users' perceptions of location privacy risk and app benefits, in turn, affects their adoption intentions and willingness-to-pay. This research contributes to theory by demonstrating how network size affects not only perceived benefits, but also the perceived risks of IS in the absence of perfect information. Concerning practice, we provide evidence that (1) LBS privacy risk is of great concern to consumers, (2) that privacy assurance is particularly important when an app’s network size is low or if its quality cannot be verified, and (3) and improved standards for institutional privacy assurance at the app level could provide greater value/profit to consumers/providers.