A Study of Outsourcing Material Availability Decision-Making

Authors

  • Dr. Anil Kumar Verma Department of Operations Management Institute of Management Studies, New Delhi, India
  • Mr. Jonathan R. Lewis School of Business and Economics De La Salle University, Manila, Philippines

Keywords:

Outsourcing, logistics, materials handling, transaction cost economics, resource based, network-based, framework

Abstract

Effective supply chain design calls for robust analytical models and design tools. Previous works in this area are mostly Operation Research oriented without considering manufacturing aspects. Recently, researchers have begun to realize that the decision and integration effort in supply chain design should be driven by the manufactured product, specifically, product characteristics and product life cycle. In addition, decision-making processes should be guided by a comprehensive set of performance metrics. In this paper, we relate product characteristics to supply chain strategy and adopt supply chain operations reference (SCOR) model level I performance metrics as the decision criteria. An integrated analytic hierarchy process (AHP) and preemptive goal programming (PGP) based multi-criteria decision-making methodology is then developed to take into account both qualitative and quantitative factors in supplier selection. While the AHP process matches product characteristics with supplier characteristics (using supplier ratings derived from pairwise comparisons) to qualitatively determine supply chain strategy, PGP mathematically determines the optimal order quantity from the chosen suppliers. Since PGP uses AHP ratings as input, the variations of pairwise comparisons in AHP will influence the final order quantity. Therefore, users of this methodology should put greater emphasis on the AHP progress to ensure the accuracy of supplier ratings.

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Published

30-06-2024

How to Cite

Dr. Anil Kumar Verma, and Mr. Jonathan R. Lewis. “A Study of Outsourcing Material Availability Decision-Making”. The Sankalpa: International Journal of Management Decisions, vol. 10, no. 1, June 2024, pp. 1-6, https://thesankalpa.org/ijmd/article/view/30.

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Section

Original Articles