The main drivers for adopting product multiple lifecycles are to gain ecological and economic advantages. However, in most of the cases it is not straight forward to estimate the potential ecological and economic gain that may result from adopting product multiple lifecycles. Even though many researchers have concluded that product multiple lifecycles result in gain, there are examples which indicate that the gain is often marginal or even none in many cases. The purpose of this research is to develop system dynamics models that can assist decision makers in assessing and analysing the potential gain of product multiple lifecycles considering the dynamics of material scarcity. The foundation of the research presented in this paper is laid based on literature review. System dynamics principles have been used for modelling and simulations have been done on Stella iThink platform. The data used in the models have been extracted from different reports published by World Steel Association and U.S. Geological Survey. Some of the data have been assumed based on expert estimation. The data on iron ore reserves, iron and steel productions and consumptions have been used in the models. This research presents the first system dynamics model for decision making in product multiple lifecycles which takes into consideration the dynamics of material scarcity. Physical unavailability and price of material are the two main factors that would drive product multiple lifecycles approach and more sustainable decisions can be made if it is done by taking holistic system approach over longer time horizon. For an enterprise it is perhaps not attractive to conserve a particular type of material through product multiple lifecycles approach which is naturally abundant but extremely important if the material becomes critical. An enterprise could through engineering, proper business model and marketing may increase the share of multiple lifecycle products which eventually would help the enterprise to reduce its dependency on critical materials.