Concave effect of financial flexibility on semiconductor industry performance: quantile regression approach
To survive increasingly uncertain and competitive markets, technology and capitalintensive semiconductor companies need to be more agile, responsive and flexible than ever before. This study investigates the impact financial flexibility on firm performance within Taiwan’s semiconductor industry and...
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Format: | Article |
Language: | English |
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Vilnius Gediminas Technical University
2022-05-01
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Series: | Technological and Economic Development of Economy |
Subjects: | |
Online Access: | https://btp.vgtu.lt/index.php/TEDE/article/view/16622 |
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author | Bao-Guang Chang Kun-Shan Wu |
author_facet | Bao-Guang Chang Kun-Shan Wu |
author_sort | Bao-Guang Chang |
collection | DOAJ |
description |
To survive increasingly uncertain and competitive markets, technology and capitalintensive semiconductor companies need to be more agile, responsive and flexible than ever before. This study investigates the impact financial flexibility on firm performance within Taiwan’s semiconductor industry and whether the impact on FP differs depending on the semiconductor industry characteristics. Using quantile regression analysis, data from semiconductor companies listed on the Taiwan Stock Exchange during the COVID-19 shock was investigated. The results evidence an inverted U-shaped relationship between FF and FP in the lower and median return on equity quantiles of the semiconductor industry. For the asset heavy business model companies, FF has a concave impact on FP for IC-design and IC-manufacturing companies but not the semiconductor companies. For the asset light business model companies, FF has a concave impact on FP in the lower and median quantiles for semiconductor companies, in the upper quantiles for IC-design companies and in all except the 90th quantile for IC-manufacturing companies. The results of this research significantly contribute to extant literature as with such specific knowledge regarding the impact of FF on FP, managers are able to make decisions based on a firm’s individual FF-FP relationship and identify the most lucrative business trajectory.
First published online 19 May 2022
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first_indexed | 2024-12-12T03:34:26Z |
format | Article |
id | doaj.art-65d702555b3b466a91a15961222cc2c3 |
institution | Directory Open Access Journal |
issn | 2029-4913 2029-4921 |
language | English |
last_indexed | 2024-12-12T03:34:26Z |
publishDate | 2022-05-01 |
publisher | Vilnius Gediminas Technical University |
record_format | Article |
series | Technological and Economic Development of Economy |
spelling | doaj.art-65d702555b3b466a91a15961222cc2c32022-12-22T00:39:50ZengVilnius Gediminas Technical UniversityTechnological and Economic Development of Economy2029-49132029-49212022-05-0110.3846/tede.2022.16622Concave effect of financial flexibility on semiconductor industry performance: quantile regression approachBao-Guang Chang0Kun-Shan Wu1Department of Accounting, Tamkang University, New Taipei City 251301, TaiwanDepartment of Business Administration, Tamkang University, New Taipei City 251301, Taiwan To survive increasingly uncertain and competitive markets, technology and capitalintensive semiconductor companies need to be more agile, responsive and flexible than ever before. This study investigates the impact financial flexibility on firm performance within Taiwan’s semiconductor industry and whether the impact on FP differs depending on the semiconductor industry characteristics. Using quantile regression analysis, data from semiconductor companies listed on the Taiwan Stock Exchange during the COVID-19 shock was investigated. The results evidence an inverted U-shaped relationship between FF and FP in the lower and median return on equity quantiles of the semiconductor industry. For the asset heavy business model companies, FF has a concave impact on FP for IC-design and IC-manufacturing companies but not the semiconductor companies. For the asset light business model companies, FF has a concave impact on FP in the lower and median quantiles for semiconductor companies, in the upper quantiles for IC-design companies and in all except the 90th quantile for IC-manufacturing companies. The results of this research significantly contribute to extant literature as with such specific knowledge regarding the impact of FF on FP, managers are able to make decisions based on a firm’s individual FF-FP relationship and identify the most lucrative business trajectory. First published online 19 May 2022 https://btp.vgtu.lt/index.php/TEDE/article/view/16622financial flexibilityfirm performancereturn on equitysemiconductor industryquantile regressionCOVID-19 |
spellingShingle | Bao-Guang Chang Kun-Shan Wu Concave effect of financial flexibility on semiconductor industry performance: quantile regression approach Technological and Economic Development of Economy financial flexibility firm performance return on equity semiconductor industry quantile regression COVID-19 |
title | Concave effect of financial flexibility on semiconductor industry performance: quantile regression approach |
title_full | Concave effect of financial flexibility on semiconductor industry performance: quantile regression approach |
title_fullStr | Concave effect of financial flexibility on semiconductor industry performance: quantile regression approach |
title_full_unstemmed | Concave effect of financial flexibility on semiconductor industry performance: quantile regression approach |
title_short | Concave effect of financial flexibility on semiconductor industry performance: quantile regression approach |
title_sort | concave effect of financial flexibility on semiconductor industry performance quantile regression approach |
topic | financial flexibility firm performance return on equity semiconductor industry quantile regression COVID-19 |
url | https://btp.vgtu.lt/index.php/TEDE/article/view/16622 |
work_keys_str_mv | AT baoguangchang concaveeffectoffinancialflexibilityonsemiconductorindustryperformancequantileregressionapproach AT kunshanwu concaveeffectoffinancialflexibilityonsemiconductorindustryperformancequantileregressionapproach |