LAPSE:2023.27628
Published Article
LAPSE:2023.27628
Performance Assessment of the Semiconductor Industry: Measured by DEA Environmental Assessment
Toshiyuki Sueyoshi, Youngbok Ryu
April 4, 2023
Abstract
This study measures the unified (i.e., operational and environmental) performance of semiconductor firms in the world by using Data Envelopment Analysis (DEA) environmental assessment. With its promising and expanding electronic applications, many industrial nations have supported the semiconductor industry under their strategic plans, and numerous firms are involved in the global value chain. Drawing on the proposed DEA-based environmental (sustainability) assessment, which uses two disposability criteria (i.e., natural and managerial), this study first compute the unified efficiency scores of semiconductor firms. Then, this study explores how corporate age, business model, and location influence the efficiency scores by employing Tobit regressions and t-tests. The empirical implications obtained from this research indicate that overall, the semiconductor firms look for their economic achievements but are not paying enough attention to environmental sustainability. Corporate age and business model are statistically related with their operational performance measures whereas corporate location is related with their environmental ones.
Keywords
corporate performance, data envelopment analysis, semiconductor industry
Suggested Citation
Sueyoshi T, Ryu Y. Performance Assessment of the Semiconductor Industry: Measured by DEA Environmental Assessment. (2023). LAPSE:2023.27628
Author Affiliations
Sueyoshi T: Department of Management, New Mexico Institute of Mining & Technology, 801 Leroy Place, Socorro, NM 87801, USA; Tokyo Institute of Technology, Tokyo Tech World Research Hub Initiative, School of Environment and Society, 3-6 Shibaura, Minato-ku, Tokyo 108-
Ryu Y: College of Professional Studies, Northeastern University, 360 Huntington Avenue, Boston, MA 02115, USA [ORCID]
Journal Name
Energies
Volume
13
Issue
22
Article Number
E5998
Year
2020
Publication Date
2020-11-17
ISSN
1996-1073
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Original Submission
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PII: en13225998, Publication Type: Journal Article
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LAPSE:2023.27628
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https://doi.org/10.3390/en13225998
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