FuzzyAHP-Based Micro and Small Enterprises’ Cluster Identification

Authors

  • Netsanet Jote
  • Birhanu Beshah
  • Daniel Kitaw
  • Ajith Abraham

Keywords:

Fuzzy-AHP, MSEs cluster, Cluster identification

Abstract

Micro and Small Enterprises (MSEs) cluster is a group of small firms operating in a defined geographic location, producing similar products or services, cooperating and competing with one another, learning from each other to solve internal problems, setting common strategies to overcome external challenges, and reaching distance markets through developed networks. During recent years, identifying MSEs cluster has become a key strategic decision. However, the nature of these decisions is usually complex and involves conflicting criteria. The aim of this paper is to develop a Fuzzy AHP-based MSEs cluster identification model. 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, a case study was taken to prove and validate the procedure of the proposed method. A sensitivity analysis is also performed to justify the results

Downloads

Download data is not yet available.

Downloads

Published

2014-10-01

How to Cite

Netsanet Jote, Birhanu Beshah, Daniel Kitaw, & Ajith Abraham. (2014). FuzzyAHP-Based Micro and Small Enterprises’ Cluster Identification. Journal of Network and Innovative Computing, 2, 6. Retrieved from https://cspub-jnic.org/index.php/jnic/article/view/79

Issue

Vol. 2 (2014)

Section

Original Article

License

You are free to:

  1. Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
  2. Adapt — remix, transform, and build upon the material for any purpose, even commercially.
  3. The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

  1. Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  2. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Notices:

You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .

No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.