This chapter analyzes the agent-based diffusion model introduced in the previous chapter, with a particular focus on how it produces varying diffusion outcomes. The model has two distinctive features: the incorporation of a network structure among potential adopters and a two-stage adoption decision process, which consists of pre-screening and final adoption decisions. These features result in diverse diffusion patterns depending on the network structure. The simulation results are examined using two approaches. First, diffusion trajectories are visualized to illustrate the impact of different conditions, such as network structure and agents’ behavioral parameters. Second, the diffusion outcomes are aggregated into an index, Net Present Value (NPV), and regression analyses are conducted to statistically evaluate the effects of simulation conditions.