Multi-agent reinforcement learning for chiller system prediction and energy-saving optimization in semiconductor manufacturing DOI
Chia‐Yen Lee, Yao-Wen Li,

Chih-Chun Chang

и другие.

International Journal of Production Economics, Год журнала: 2024, Номер 280, С. 109488 - 109488

Опубликована: Дек. 9, 2024

Язык: Английский

Digital transformation and green total factor productivity in the semiconductor industry: The role of supply chain integration and economic policy uncertainty DOI
Lan Gao, Ruting Huang

International Journal of Production Economics, Год журнала: 2024, Номер 274, С. 109313 - 109313

Опубликована: Июнь 15, 2024

Язык: Английский

Процитировано

12

The value of corporate digital transformation: evidence from bond pricing DOI
Kangqi Jiang, Xin Xie,

Yu Xiao

и другие.

China Finance Review International, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 22, 2024

Purpose The main purpose of this study is to examine the effect corporate digital transformation on bond credit spreads. Additionally, it also explores two potential channels, information asymmetry and default risk, through which can influence Design/methodology/approach We use issuance data Chinese listed companies over period 2008–2020. Corporate these measured with textual analysis management discussion part annual reports. employ a panel regression model estimate Findings find robust evidence that higher experience lower further observe spread reduction for firms are smaller, non-state-owned, have ratings less analyst coverage. reduces spreads by reducing between investors enhanced mechanisms lowering risk strengthening operating efficiency. Originality/value To best our knowledge, first attempt understand impact Our findings help firms’ worthiness access capital.

Язык: Английский

Процитировано

5

Twin transition in industrial organizations: Conceptualization, implementation framework, and research agenda DOI Creative Commons
Sabrina Tabares, Vinit Parida, Koteshwar Chirumalla

и другие.

Technological Forecasting and Social Change, Год журнала: 2025, Номер 213, С. 123995 - 123995

Опубликована: Фев. 3, 2025

Язык: Английский

Процитировано

0

Digital Transformation and Carbon Emission Reduction: The Moderating Effect of External Pressure and Support DOI

Shaozhen Han,

Hanfeng Zhang,

Hui Li

и другие.

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 145108 - 145108

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Can digitalization promote cities' low-carbon development: Insights from local and neighboring regions DOI Creative Commons

Weijian Du,

Yuhuan Fan, Nini Yuan

и другие.

Energy Strategy Reviews, Год журнала: 2025, Номер 58, С. 101680 - 101680

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Environmental and social performance relationships to firm efficiency: Evidence from the semiconductor industry DOI
Lihua Sun, Chunguang Bai, Joseph Sarkis

и другие.

International Journal of Production Economics, Год журнала: 2024, Номер unknown, С. 109410 - 109410

Опубликована: Сен. 1, 2024

Язык: Английский

Процитировано

1

Open Innovation Over the Regional and National Boundaries in the Semiconductor Industry: The Effects of Digital Transformation and Decoupling of the Global Value Chain DOI
JinHyo Joseph Yun, Xiaofei Zhao, Heungju Ahn

и другие.

Science Technology and Society, Год журнала: 2024, Номер unknown

Опубликована: Дек. 27, 2024

Decoupling of the global value chains in semiconductor industry under digital transformation has not been adequately investigated, although it is a popular topic with emerging technological rivalry globally. This study empirically examines following research question to contribute limited research. How do firms’ collaborations across regional and national boundaries moderate effects open innovation on performance after decoupling chain? analyses patents which had registered at United States Patent Trademark Office (USPTO) Korean Intellectual Property (KIPO) during 2004 2020 representative terms before transformation. Findings are as follows: First, motivates enterprises’ collaboration over boundaries. Second, chain negatively moderates Therefore, by reconstructing industry, negative moderating industry’s could be diminished. In addition, constructing cluster South Korea, benefits increased.

Язык: Английский

Процитировано

1

Multi-agent reinforcement learning for chiller system prediction and energy-saving optimization in semiconductor manufacturing DOI
Chia‐Yen Lee, Yao-Wen Li,

Chih-Chun Chang

и другие.

International Journal of Production Economics, Год журнала: 2024, Номер 280, С. 109488 - 109488

Опубликована: Дек. 9, 2024

Язык: Английский

Процитировано

0