An ERP Selection Combination Model under Uncertainty: A Grey-BSCAHP-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.

Keywords:

Enterprise Resource Planning (ERP) selection , Three-parameter interval grey numbers , AHP , Shannon Entropy , Threeparameter grey interval incidence degree