Government-industry interactions for emissions control can be modelled as Stackelberg or leader-follower games. Government acts as the leader by setting regulations and economic incentives, while industry as the follower reacts to these policies by selecting cost-optimal emissions reduction techniques. The problem for the leader is to calibrate policies in anticipation of the follower’s rational reaction. In this work, a bilevel mixed integer linear programming (BMILP) model is developed for the deployment of a finite set of emissions reduction techniques. Government controls the emissions reduction target and subsidy rate for each emissions reduction technique, while industry selects which techniques to implement. The latter also has to pay a penalty if actual emissions exceed the regulatory target. An interactive fuzzy optimization algorithm is also developed for finding an approximate satisficing solution. The model and solution algorithm are illustrated using a case study.