Name
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-08156-4_32 | PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INNOVATIONS IN BIO-INSPIRED COMPUTING AND APPLICATIONS (IBICA 2014) |
Keywords | Field | DocType |
Fuzzy-AHP,Industrial cluster,Cluster identification | Critical factors,Market potential,Computer science,Operations research,Analytic hierarchy process,Fuzzy ahp | Conference |
Volume | ISSN | Citations |
303 | 2194-5357 | 0 |
PageRank | References | Authors |
0.34 | 8 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Netsanet Jote | 1 | 0 | 0.68 |
| Daniel Kitaw | 2 | 12 | 1.96 |
| Jakub Štolfa | 3 | 13 | 10.23 |
| Svatopluk Štolfa | 4 | 25 | 13.96 |
| Václav Snasel | 5 | 1261 | 210.53 |