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Mature economies which are driven mainly by small and medium sized enterprises (SMEs) are increasingly becoming dependent on material imports. Global material consumption is ever increasing, mainly driven by population increases. Decoupling of material consumption from economic growth is one of the greatest challenges of the 21st century. Within this paper available methods for the assessment of material efficiency on different economic scales are investigated and those detected that are particulary suitable for the use in SMEs. Recommendations for further improvements of the selected tools and an outlook concerning planned research activities in the field of material efficiency in enterprises, supply chains and circular economy aspects are given.
The increased availability of data gives rise to the use of machine learning methods for purposes like forecasting or quality control in operations management. Practitioners who want to employ these methods are faced with the task of choosing from a large number of available methods. We give an overview of classification methods and available implementations and present considerations for choosing appropriate methods.