Authors:
Nicola Costantino
;
Mariagrazia Dotoli
;
Marco Falagario
and
Fabio Sciancalepore
Affiliation:
Politecnico di Bari, Italy
Keyword(s):
Business Intelligence, Supplier Evaluation, Data Envelopment Analysis, Uncertainty, Monte Carlo Method.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Best Practices & Communities of Practice
;
Business Process Management
;
Communities of Practice
;
Computer-Supported Education
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Learning/Teaching Methodologies and Assessment
;
Society, e-Business and e-Government
;
Symbolic Systems
;
Web Information Systems and Technologies
Abstract:
The paper addresses one of the key objectives of the purchasing function of a supply chain, i.e., the optimal selection of suppliers. We present a novel methodology that integrates the well-known cross-efficiency evaluation called Data Envelopment Analysis (DEA) and the Monte Carlo approach, to manage supplier selection considering uncertainty in the supply process, e.g. evaluating potential suppliers. The model allows to distinguish among several suppliers, overcoming the limitation of the traditional DEA method of not distinguishing among efficient suppliers. Moreover, the technique is able to classify suppliers with uncertain performance. The method is applied to the selection of suppliers of a Southern Italy SME.