The bioethanol sector is an extremely complex set of actors, technologies and market structures, influenced simultaneously by dierent natural, economic, social and political processes. That is why it lends itself to the application of system dynamics modelling. In last five years a relatively high level of experience and knowledge has accumulated related to the application of computer-aided system modelling for the analysis and forecasting of the bioethanol sector. The goal of the current paper is to oer a systematic review of the application of system dynamics models in order to better understand the structure, conduct and performance of the bioethanol sector. Our method has been the preferred reporting items for systematic reviews and meta-analyses (PRISMA), based on English-language materials published between 2015 and 2020. The results highlight that system dynamic models have become more and more complex, but as a consequence of the improvement in information technology and statistical systems, as well as the increasing experience gained they oer an ecient tool for decision makers in the business and political spheres. In the future, the combination of traditional system dynamics modelling and agent-based models will oer new perspectives for the preparation of more sophisticated description and forecasting.

The bioethanol sector is an extremely complex set of actors, technologies and market

structures, influenced simultaneously by dierent natural, economic, social and political processes.

That is why it lends itself to the application of system dynamics modelling. In last five years a

relatively high level of experience and knowledge has accumulated related to the application of

computer-aided system modelling for the analysis and forecasting of the bioethanol sector. The goal of

the current paper is to oer a systematic review of the application of system dynamics models in order

to better understand the structure, conduct and performance of the bioethanol sector. Our method

has been the preferred reporting items for systematic reviews and meta-analyses (PRISMA), based on

English-language materials published between 2015 and 2020. The results highlight that system

dynamic models have become more and more complex, but as a consequence of the improvement in

information technology and statistical systems, as well as the increasing experience gained they oer

an ecient tool for decision makers in the business and political spheres. In the future, the combination

of traditional system dynamics modelling and agent-based models will oer new perspectives for the

preparation of more sophisticated description and forecasting.