@ARTICLE{Guban_Miklos_Trends_2019, author={Guban, Miklos and Kasa, Richard and Takacs, David and Avornicului, Mihai}, volume={vol. 10}, number={No 2}, journal={Management and Production Engineering Review}, howpublished={online}, year={2019}, publisher={Production Engineering Committee of the Polish Academy of Sciences, Polish Association for Production Management}, abstract={The field of academic research on corporate sustainability management has gained significant sophistication since the economic growth has been associated with innovation. In this paper, we are to show our research project that aims to build an artificial intelligence-based neurofuzzy inference system to be able to approximate company’s innovation performance, thus the sustainability innovation potential. For this we used an empirical sample of Hungarian processing industry’s large companies and built an adaptive neuro fuzzy inference system.}, title={Trends of using artificial intelligence in measuring innovation potential}, URL={http://www.czasopisma.pan.pl/Content/113083/PDF/1-Guban.pdf}, doi={10.24425/mper.2019.129564}, keywords={process mapping, production logistics, process improvements, shipyard industry}, }