Use of fuzzy AHP for evaluating the benefits of information‐sharing decisions in a supply chain

The purpose of this paper is to provide a good insight into the use of fuzzy Analytical Hierarchy Process (fuzzy AHP) approach that is a multi‐criteria decision‐making methodology in evaluating the benefits of information‐sharing decision problems.

In this study, the integration of AHP with the fuzzy synthetic extent analysis method (fuzzy AHP) is proposed in evaluating the benefits of information‐sharing decision problems as a framework to guide managers.

Findings demonstrate that the customer requirement and operational information alternatives are the preferred key decisions, which all supply chain partners might agree to share with one another. Further, it can also be concluded that the planning and financial information alternatives have almost the same importance.

Fuzzy AHP is a highly complex methodology and requires more numerical calculations in assessing composite priorities than the traditional AHP and hence it increases the effort. In addition, fuzzy methodology could be extended with the other multi‐criteria decision‐making (MCDM) methods such as Analytical Network Process (ANP), TOPSIS, ELECTRE and DEA techniques in solving such a problem.

There is a lack of research in the literature to deal directly with the uncertainty of human judgements in evaluating the benefits of various information‐sharing decisions in a supply chain. Therefore, fuzzy AHP is an appropriate methodology to select the various types of information and has the ability to be used as a decision‐making analysis tool since it handles uncertain and imprecise data. In addition, the paper is especially of interest to managers as they make decisions on which types of information they should share with their supply chain partners.