Application of FUZZY-AHP for Industrial Cluster Identification

Abstract

Identifying industrial cluster has become a key strategic decision, during recent years. However, the nature of these decisions is usually uncertain and vague. From the existing methods, there is no single method which handles the uncertainty. This paper proposes a Fuzzy-AHP based industrial cluster identification model to solve the pitfalls with the exiting cluster identification methods. As a result, quantitative and qualitative factors including geographical proximity, sectorial concentration, market potential, support services, resource potential and potential entrepreneurs are found to be critical factors in cluster identification. In this paper, linguistic values are used to assess the ratings and weights of the factors. Then, AHP model based on fuzzy-sets theory will be proposed in dealing with the cluster selection problems. Finally, Ethiopian Tanning industries were taken to prove and validate the procedure of the proposed method. A sensitivity analysis is also performed to justify the results.