EconPapers    
Economics at your fingertips  
 

Meta-Frontier Analysis of Disclosing Sustainable Development Information: Evidence from China’s AI Industry

An-Chi Liu, Junyi Wang, Yiting Zhan, Chien-Jung Li and Yang Li
Additional contact information
An-Chi Liu: College of Business Administration, Fujian Business University, Fuzhou 350016, China
Junyi Wang: New Huadu Business School, Minjiang University, Fuzhou 350108, China
Yiting Zhan: New Huadu Business School, Minjiang University, Fuzhou 350108, China
Chien-Jung Li: Department of Finance, Tunghai University, Taichung 407224, Taiwan
Yang Li: Department of International Business, National Taiwan University, Taipei 10617, Taiwan

Energies, 2021, vol. 14, issue 19, 1-13

Abstract: China currently adopts voluntary principles to disclose sustainable development information, and so considerable numbers of listed companies have chosen not to disclose such information. Since disclosure and non-disclosure groups face different production opportunities, this research uses the meta-frontier framework to completely analyze sustainable development practices of China’s artificial intelligence (AI) industry. Empirical results show that the disclosure group outperforms the non-disclosure group in operating scales, efficiencies, and technologies, while the superior efficiency of state-owned enterprises (SOEs) comes entirely from the non-disclosure group. Hence, the government should mandate or actively encourage capable corporations, especially SOEs, to disclose sustainable development information, as doing so improves the overall sustainable development of society and also enhances these firms’ performance. Finally, the authority can formulate a nationwide disclosure policy regardless of the existing differences in regional development.

Keywords: disclosing sustainable development information; meta-frontier approach; AI industry; reputation effect; state-owned enterprises (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/19/6139/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/19/6139/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:19:p:6139-:d:643947

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6139-:d:643947