Identifying and Evaluating Effective Factors in Green Supplier Selection using Association Rules Analysis

Nowadays companies measure suppliers on the basis of a variety of factors and criteria that affect the supplier's selection issue. This paper intended to identify the key effective criteria for selection of green suppliers through an efficient algorithm callediterative process mining or i-PM. Green data were collected first by reviewing the previous studies to identify various environmental criteria. Then, the suppliers were evaluated and ranked on the basis of those criteria. The score table derived for the green criteria was one of the inputs to the algorithm. Moreover, membership functions and minimum support values ​​were specified for each criterion as another input to the algorithm. The supplier ranking index was also obtained based on the score assigned to supplier's performance. Then, the hidden relationships between data were discovered and association rules were achieved and analyzed to identify the most important green criterion for selecting green suppliers.

Keywords:

Supplier selection , Association Rules Analysis , Iterative Process Mining Algorithm , fuzzy logic