Because of the climate crisis the world is facing, all sectors must move towards a more sustainable future. In the Netherlands, the industry sector emits large amounts of CO2 because of the heavy reliance on fossil-fuels and large electricity demand. The Paris agreement and the Green Deal forces the industry sector to rapidly transition towards more sustainable practices, which can be achieved if the correct synergies are established. The multi-actor nature and the technical and operational dependencies that industrial clusters have, makes optimal decision-making extremely important in working towards that net zero future. Innovations that re- duce the emissions are limited, but they exist and provide (intermediary) solutions to adhere with the imposed regulations. Furthermore, the industrial clusters are subject to numerous different factors that influences the behaviour of actors within the cluster. The issue faced is to understand how the transition of an industrial cluster is influenced by exogenous factors and how actors in such an integrated environment should invest, while keeping in mind that both the industrial clusters and the individual actors have to remain profitable and have differing investment behaviour. Current studies fall short in identifying, analysing and understanding how multi-actors in an institutional en- vironment relate to the technical options and the exogenous factors engaging with that system in an industrial setting. Identifying an optimal investment trajectory that such an industrial cluster should follow to adhere with the regulations whilst staying profitable with a multi-actor configuration requires different integrated methods and other tools. This thesis will address that problem through the following main research question: What is the effect of multiple exogenous factors on the optimal investment trajectories of indus- trial clusters in the Netherlands with multiple investment options? This question has been answered through exploratory research combined with a modelling approach. The first step in the exploratory research required attaining insights in what the current state of is multi-actor invest- ments. This in combination with looking at how they are structured contractually has been the main foundation for the literature review. A case study analysis has been conducted of an industrial cluster located in Geleen, called Chemelot. This allowed for analysing decarbonizing investment options and looking at what exogenous factors influence the industrial cluster. The investment options attempt to move Chemelot away from fossil-fuels as energy source and move towards lower emitting sources such as electricity. The information gathered served as an input to put together a methodology which captured the exogenous factors, interactions in the industrial cluster and the sustainable investment options in an optimization model. Using this, the optimization model was constructed using Linny-R, a Mixed Integer Linear Programming op- timization software developed by Dr. P.W.G. Bots. The model produced quantifiable results as well as serve as a proof of concept for the methodology that is presented to incorporate exogenous factors and sustainable investment options in the energy transition. The model also gives insights in what effect the exogenous factors have on the investment behaviour of actors within industrial clusters by showing cash flows, both individually and collectively and through an investment curve for the cluster. The economic performance is considered to be the leading metric in this research. Finally, using the results, the implications of implementing exogenous factors and sustainable investment options in an optimization model are discussed. The research outcomes show that CCS and electrification are favourable investments for Chemelot to remain profitable and cope with increasing prices of commodities and CO2. The model results has provided insights in the effect that exogenous factors have on the energy transition of an industrial cluster. More specifically, it showed that a cap on CO2 and increasing the price of CO2 emitted really accelerates the rate at which actors make investments in sustainable options. Added to that, increasing the price of other commodities such as natural gas and naphtha also forces actors to move away from those commodities and look for alternatives that provide the same product or energy without having to compensate the CO2 emissions related to them. Other factors such as limited infrastructure restrict industrial clusters in the amount of products they can produce and restrict them from innovating towards less emitting processes. Electrification of certain processes is possible, but increases the electricity demand with enormous amounts. With limited electricity infrastructure to provide those amounts, the innovation cannot be realized and therefore, halting the transition for an industrial cluster. The findings suggest that because of these exogenous factors, the actors will move towards electricity demanding innovations that do not make use of fossil-fuels and invest in CCS options. However, the methodology presented should be used as directing future research in looking at how industrial clusters should engage in the energy transition. The dependencies existing between actors in an industrial clusters and how different investments II may adjust these dependencies are identifiable using the methodology presented in this research. Ending with a general conclusion, the investment behaviour of industrial cluster changes because of multiple exogenous factors that influence the system. The increase in commodity prices combined with CO2 capping reg- ulations cause actors to invest more quickly into sustainable investment options to adhere with the regulations, but it also causes them to compromise their production levels in some scenarios to remain profitable. Actors downstream are dependent on the investments made by actors upstream since they rely on the output of those upstream actors to develop the final products that they sale. This combination generates valuable insights from a systems perspective but also from a multi-actor perspective.