An ERP Selection Combination Model under Uncertainty: A Grey-BSC-AHP-Entropy Model

An enterprise resource planning (erp) software can help organizations and firms in their activities like: production planning, purchase, human resource, finance, sales, inventory control and etc. selection of an erp is mentioned as a multi-criteria decision making (mcdm) problem. however, several mcdm-models are proposed to solve this, but many of them didn't consider uncertainty as an effective environmental factor. in this paper, a new model has designed which used three-parameter interval grey numbers concept that is derived from grey-theory. these numbers can help for reducing the uncertainty of data. besides, a combination model for weighting has planned by implementing ahp and entropy methods that are used in order to reduce uncertainty. and last, a decision making method (three-parameter grey interval incidence degree method) is used for ranking process. there is a case study at the end of this paper that shows how this model works..