AHP-Based Micro and Small Enterprises' Cluster Identification

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86099411" target="_blank" >RIV/61989100:27240/13:86099411 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/13:86099411

Výsledek na webu

<a href="http://dx.doi.org/10.1109/SOCPAR.2013.7054132" target="_blank" >http://dx.doi.org/10.1109/SOCPAR.2013.7054132</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SOCPAR.2013.7054132" target="_blank" >10.1109/SOCPAR.2013.7054132</a>

Jazyk výsledku

angličtina

Název v původním jazyce

AHP-Based Micro and Small Enterprises' Cluster Identification

Popis výsledku v původním jazyce

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 an 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 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. (C) 2013 IEEE.

Název v anglickém jazyce

AHP-Based Micro and Small Enterprises' Cluster Identification

Popis výsledku anglicky

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 an 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 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. (C) 2013 IEEE.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2013 International Conference on Soft Computing and Pattern Recognition, SoCPaR 2013

ISBN

978-1-4799-3400-3

ISSN

—

e-ISSN

—

Počet stran výsledku

7

Strana od-do

225-231

Název nakladatele

IEEE

Místo vydání

New York

Místo konání akce

Hanoj

Datum konání akce

15. 12. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000380467000038