The evaluation of productive efficiency using a fuzzy mathematical programming approach: the case of the newspaper preprint insertion process

In order to compute relative efficiency performance, numerous mathematical programming formulations usually labeled collectively as data envelopment analysis (DEA) have been proposed in the literature. These formulations assume that data can be precisely collected with respect to the resources used and the outputs produced, i.e., that the production plans are known precisely. Unfortunately, in a number of applications, measurement inaccuracies are more than prevalent. It is the primary objective of this paper to illustrate in detail the implementation of a fuzzy set-based methodology that can be used to accommodate the measurement inaccuracies associated with production plans. This approach suggests that production plans can be treated as fuzzy, i.e., that fuzzy inputs and outputs vary between risk-free and impossible bounds. These bounds represent the production extremes for each fuzzy input and output within the constraints of the underlying production technology. The approach is illustrated by analyzing the technical efficiency performance of a newspaper preprint insertion manufacturing process. It is shown that the approach identifies production plans that are very sensitive or completely insensitive to the variation of the degree of fuzziness and in turn have unique operating characteristics which when analyzed can define efficiency improvement strategies.