Performance Comparison of Industry Clusters: Canonical Correlation Analysis vs Data Envelopment Analysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24310%2F23%3A00011506" target="_blank" >RIV/46747885:24310/23:00011506 - isvavai.cz</a>

Výsledek na webu

<a href="https://mme2023.vse.cz/mme_2023_proceedings.pdf" target="_blank" >https://mme2023.vse.cz/mme_2023_proceedings.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Performance Comparison of Industry Clusters: Canonical Correlation Analysis vs Data Envelopment Analysis

Popis výsledku v původním jazyce

The paper evaluates the performance of companies in two industries - automotive and textile in 2019 and 2020 concerning their membership in a cluster organisation. The surveyed firms in both sectors were divided into three groups. The first group included member companies of the cluster organisation. Their performance is expected to be higher than the other two groups due to their direct involvement in cluster activities. The second group includes companies operating in the cluster’s region. In this case, it can be assumed that these firms could benefit from the positive externalities of the existing cluster organisation. Their performance could thus be better than that of the third group of companies operating in other regions already too far from the cluster. Two alternative methods, Data Envelopment Window Analysis and Canonical Correlation Analysis, were used to assess the performance of the companies. Both tools can handle more inputs and outputs, but they work differently. This paper compares the results obtained using both methods and discusses their advantages and disadvantages.

Název v anglickém jazyce

Performance Comparison of Industry Clusters: Canonical Correlation Analysis vs Data Envelopment Analysis

Popis výsledku anglicky

The paper evaluates the performance of companies in two industries - automotive and textile in 2019 and 2020 concerning their membership in a cluster organisation. The surveyed firms in both sectors were divided into three groups. The first group included member companies of the cluster organisation. Their performance is expected to be higher than the other two groups due to their direct involvement in cluster activities. The second group includes companies operating in the cluster’s region. In this case, it can be assumed that these firms could benefit from the positive externalities of the existing cluster organisation. Their performance could thus be better than that of the third group of companies operating in other regions already too far from the cluster. Two alternative methods, Data Envelopment Window Analysis and Canonical Correlation Analysis, were used to assess the performance of the companies. Both tools can handle more inputs and outputs, but they work differently. This paper compares the results obtained using both methods and discusses their advantages and disadvantages.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

50401 - Sociology

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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