Cryptoeconomics is an emerging research area in the field of blockchain technology aiming at understanding token design mechanisms intended to incentivize certain behaviors. Whereas several blockchain ecosystems have been emerging in recent years, little is known about incentive design in blockchain protocols other than Bitcoin. To address this gap, we use agent-based modeling (ABM) to simulate the effects of different token designs on usage in the context of prediction markets. We find that network tokens (i.e., tokens providing services within a system) provide the largest incentive for individuals to join and become long-term active users. Moreover, we find that investment tokens (i.e., tokens used to passively invest in the issuing entity) provide the smallest incentive compared to network tokens and cryptocurrencies (i.e., means of payment in a blockchain ecosystem). We advance the literature by testing the boundary conditions of different token designs for blockchain-based ecosystems using a novel ABM approach