Supplier Selection in JIT Automotive Industry: A Multivariate Approach

Isti Surjandari
University of Indonesia, Indonesia

Sumarsono Sudarto
University of Indonesia, Indonesia

Santi Anggarini
University of Indonesia, Indonesia

In this globalization era, manufacturing industries have experienced many significant changes, indicated by highly-innovated and short-aged product emerging today. This condition has forced manufacturing industries to put more consideration to their core capability, thus consequently has made outsourcing activities become an important and strategic decision. A company’s efforts in achieving competitive benefits begin with managing its suppliers. In real conditions, selecting suppliers is not an easy thing to decide, yet it needs a correct strategic way in order to get potential suppliers. Furthermore in Just-In-Time (JIT) manufacturer, supplier selection is an important strategic issue for the company, because it is a long-term investment and success key to the JIT philosophy implementation. The objective of this paper is to design a framework for supplier selection in JIT manufacturing based on multivariate approach. This paper is based on a study in the largest JIT automotive manufacturer in Indonesia. The design begins by applying factor analysis to settle attributes used in the supplier selection process. Afterward, a conjoint analysis is used to find out the company’s preferences of its suppliers through the assessment of profiles, which are the combinations of attributes and levels used in the selection process. Selecting potential supplier can be established using Multidimensional Scaling (MDS) method. This method would specify company’s preferences visually in a multidimensional space, and in the end it would set the Euclidean distance for each supplier compared to the ideal point. Eventually, this perception map would help the company in choosing suppliers which are located within their ideal point.

Download Full Paper

This paper has been downloaded 1868 times since published. The persistent DOI of this paper is DOI:10.31387/oscm070042.