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Application of FUZZY-AHP for Industrial Cluster Identification

  • Netsanet Jote
  • Daniel Kitaw
  • Jakub Štolfa
  • Svatopluk Štolfa
  • Václav Snášel
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 303)

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.

Keywords

Fuzzy-AHP Industrial cluster Cluster identification 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Netsanet Jote
    • 1
  • Daniel Kitaw
    • 1
  • Jakub Štolfa
    • 2
  • Svatopluk Štolfa
    • 2
  • Václav Snášel
    • 2
  1. 1.Addis Ababa Institute of Technology, School of Mechanical and Industrial EngineeringAddis AbabaEthiopia
  2. 2.Department of Computer ScienceVSB - Technical University of OstravaOstrava-PorubaCzech Republic

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