Analysis of interactions of criteria and sub-criteria for the selection of supplier in the built-in-order supply chain environment

The supplier decision-making problem is complicated by several criteria and sub-criteria. The criteria and sub-criteria used may vary across different product categories and situations. The aim of this article is to analyse the interaction of criteria and sub-criteria that are used to select the supplier for the built-in-order supply chain environment in the original equipment manufacturing company. The paper aims to demonstrate how the model can help in solving such decisions in practice. This paper uses the Interpretive Structural Modeling (ISM) methodology to understand the interactions among the criteria, which influences the supplier selection. The effectiveness of the ISM model is illustrated using a case study taken in a company in the southern part of India.

[1]  Gary W. Dickson,et al.  AN ANALYSIS OF VENDOR SELECTION SYSTEMS AND DECISIONS , 1966 .

[2]  John N. Warfield,et al.  Toward Interpretation of Complex Structural Models , 1974, IEEE Trans. Syst. Man Cybern..

[3]  John N. Warfield,et al.  Developing Interconnection Matrices in Structural Modeling , 1974, IEEE Trans. Syst. Man Cybern..

[4]  D. W. Malone,et al.  An introduction to the application of interpretive structural modeling , 1975, Proceedings of the IEEE.

[5]  G. Stevens.  Integrating the Supply Chain , 1989 .

[6]  W. C. Benton,et al.  Vendor selection criteria and methods , 1991 .

[7]  Sushil,et al.  Scenario building: A critical study of energy conservation in the Indian cement industry , 1992 .

[8]  Sushil,et al.  The objectives of waste management in India: A futures inquiry , 1995 .

[9]  Jinlong Zhang,et al.  A supplier-selecting system using a neural network , 1997, 1997 IEEE International Conference on Intelligent Processing Systems (Cat. No.97TH8335).

[10]  Madeleine E. Pullman,et al.  AN ANALYSIS OF THE SUPPLIER SELECTION PROCESS , 1998 .

[11]  Fong-Yuen Ding,et al.  Using data envelopment analysis to compare suppliers for supplier selection and performance improvement , 2000 .

[12]  M. Braglia,et al.  Vendor Selection Using Principal Component Analysis , 2000 .

[13]  J. Current,et al.  An optimization approach to determining the number of vendors to employ , 2000 .

[14]  F. Veloso,et al.  Make-Buy Decisions in the Auto Industry: New Perspectives on the Role of the Supplier as an Innovator , 2001 .

[15]  V. M. Rao Tummala,et al.  An application of the AHP in vendor selection of a telecommunications system , 2001 .

[16]  Ashraf Labib,et al.  A Fuzzy Quality Function Deployment (FQFD) model for deriving optimum targets , 2001 .

[17]  J. Wisner,et al.  The determinants of service quality: issues for purchasing , 2002 .

[18]  Vinod Kumar,et al.  Enterprise resource planning systems adoption process: A survey of Canadian organizations , 2002 .

[19]  Felix T.S. Chan,et al.  Interactive selection model for supplier selection process: an analytical hierarchy process approach , 2003 .

[20]  R. Shankar,et al.  An interpretive structural modeling of knowledge management in engineering industries , 2003 .

[21]  Srinivas Talluri,et al.  Production , Manufacturing and Logistics Vendor evaluation with performance variability : A max – min approach , 2003 .

[22]  A. Cakravastia,et al.  Integrated model for supplier selection and negotiation in a make-to-order environment , 2004 .

[23]  R. Shankar,et al.  IT enablement of supply chains: modeling the enablers , 2004 .