The most cost efficient automotive vendor with price uncertainty: A new DEA approach

Abstract

Vendor’s performance evaluation is an important subject which has strategic implications for managing an efficient company. However, there are many important criteria for prospering company. These criteria may contradict together. In other words, while a criterion is improved, the other may worsen. Indeed, similar to manufacturing manager in global market, purchasing manager who has significant practical implications deals with this issue. The vendor selection problem (VSP) is obviously affected by the complexity and uncertainty due to the lack of information associated with related business environment of countries in a global market. On the other hand, in the automotive industry which plays an important role in the worldwide market, these decisions will be exacerbated by increasing the outsourcing and opportunities. There are varieties of techniques, from simple weighted scoring methods to complex mathematical programming, for handling VSP.

In this study, we propose a new cost efficiency data envelopment analysis (CE–DEA) approach with price uncertainty for finding the most cost efficient unit. Potential uses are then illustrated with an application to automotive industry involving 73 vendors in Turkey.